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| Meta Title | Comparison of diagnostic accuracy of rapid antigen tests for COVID-19 compared to the viral genetic test in adults: a systematic review and meta-analysis - PMC |
| Meta Description | The objective of this review was to determine the diagnostic accuracy of the currently available and upcoming point-of-care rapid antigen tests (RATs) used in primary care settings relative to the viral genetic real-time reverse transcriptase ... |
| Meta Canonical | null |
| Boilerpipe Text | Abstract
Objective:
The objective of this review was to determine the diagnostic accuracy of the currently available and upcoming point-of-care rapid antigen tests (RATs) used in primary care settings relative to the viral genetic real-time reverse transcriptase polymerase chain reaction (RT-PCR) test as a reference for diagnosing COVID-19/SARS-CoV-2 in adults.
Introduction:
Accurate COVID-19 point-of-care diagnostic tests are required for real-time identification of SARS-CoV-2 infection in individuals. Real-time RT-PCR is the accepted gold standard for diagnostic testing, requiring technical expertise and expensive equipment that are unavailable in most primary care locations. RATs are immunoassays that detect the presence of a specific viral protein, which implies a current infection with SARS-CoV-2. RATs are qualitative or semi-quantitative diagnostics that lack thresholds that provide a result within a short time frame, typically within the hour following sample collection. In this systematic review, we synthesized the current evidence regarding the accuracy of RATs for detecting SARS-CoV-2 compared with RT-PCR.
Inclusion criteria:
Studies that included nonpregnant adults (18 years or older) with suspected SARS-CoV-2 infection, regardless of symptomology or disease severity, were included. The index test was any available SARS-CoV-2 point-of-care RAT. The reference test was any commercially distributed RT-PCRâbased test that detects the RNA genome of SARS-CoV-2 and has been validated by an independent third party. Custom or in-house RT-PCR tests were also considered, with appropriate validation documentation. The diagnosis of interest was COVID-19 disease and SARS-CoV-2 infection. This review considered cross-sectional and cohort studies that examined the diagnostic accuracy of COVID-19/SARS-CoV-2 infection where the participants had both index and reference tests performed.
Methods:
The keywords and index terms contained in relevant articles were used to develop a full search strategy for PubMed and adapted for Embase, Scopus, Qinsight, and the WHO COVID-19 databases. Studies published from November 2019 to July 12, 2022, were included, as SARS-CoV-2 emerged in late 2019 and is the cause of a continuing pandemic. Studies that met the inclusion criteria were critically appraised using QUADAS-2. Using a customized tool, data were extracted from included studies and were verified prior to analysis. The pooled sensitivity, specificity, positive predictive, and negative predictive values were calculated and presented with 95% CIs. When heterogeneity was observed, outlier analysis was conducted, and the results were generated by removing outliers.
Results:
Meta-analysis was performed on 91 studies of 581 full-text articles retrieved that provided true-positive, true-negative, false-positive, and false-negative values. RATs can identify individuals who have COVID-19 with high reliability (positive predictive value 97.7%; negative predictive value 95.2%) when considering overall performance. However, the lower level of sensitivity (67.1%) suggests that negative test results likely need to be retested through an additional method.
Conclusions:
Most reported RAT brands had only a few studies comparing their performance with RT-PCR. Overall, a positive RAT result is an excellent predictor of a positive diagnosis of COVID-19. We recommend that Rocheâs SARS-CoV-2 Rapid Antigen Test and Abbottâs BinaxNOW tests be used in primary care settings, with the understanding that negative results need to be confirmed through RT-PCR. We recommend adherence to the STARD guidelines when reporting on diagnostic data.
Review registration:
PROSPERO CRD42020224250
Keywords:
COVID19, point of care, rapid antigen tests, respiratory infection, SARS-CoV-2
Summary of Findings
Test accuracy of STANDARD Q COVID-19 Antigen test from SD Biosensor for COVID-19 or SARS-CoV-2 infection in symptomatic adults
Sensitivity
0.782 (95% CI: 0.587 to 0.900)
Specificity
0.984 (95% CI: 0.949 to 0.995)
Prevalences
0.5%
5%
10%
Outcome
â of studies (â of patients)
Study design
Factors that may decrease certainty of evidence
Effect per 1000 patients tested
Test accuracy certainty of evidence
Risk of bias
Indirectness
Inconsistency
Imprecision
Publication bias
Pre-test probability of 0.5% (95% CI)
Pre-test probability of 5% (95% CI)
Pre-test probability of 10% (95% CI)
True positives
4 studies (3179 patients)
cross-sectional (cohort type accuracy study)
not serious
not serious
very serious
a
not serious
none
4 (3 to 5)
39 (29 to 45)
78 (59 to 90)
â¨â¨âŻâŻ Low
False negatives
1 (0 to 2)
11 (5 to 21)
22 (10 to 41)
True negatives
4 studies (3179 patients)
cross-sectional (cohort type accuracy study)
not serious
not serious
serious
a
not serious
none
979 (944 to 990)
935 (902 to 945)
886 (854 to 896)
â¨â¨â¨âŻ Moderate
False positives
16 (5 to 51)
15 (5 to 48)
14 (4 to 46)
Explanations:
a. High heterogeneity across studies.
Test accuracy of PanBio by Abbott for COVID-19 or SARS-CoV-2 infection in symptomatic adults
Sensitivity
0.780 (95% CI: 0.610 to 0.889)
Specificity
0.999 (95% CI: 0.993 to 1.000)
Prevalences
0.5%
5%
10%
Outcome
â of studies (â of patients)
Study design
Factors that may decrease certainty of evidence
Effect per 1000 patients tested
Test accuracy certainty of evidence
Risk of bias
Indirectness
Inconsistency
Imprecision
Publication bias
Pre-test probability of 0.5% (95% CI)
Pre-test probability of 5% (95% CI)
Pre-test probability of 10% (95% CI)
True positives
2 studies (1324 patients)
cross-sectional (cohort type accuracy study)
not serious
not serious
very serious
a
not serious
none
4 (3 to 4)
39 (31 to 44)
78 (61 to 89)
â¨â¨âŻâŻ Low
False negatives
1 (1 to 2)
11 (6 to 19)
22 (11 to 39)
True negatives
2 studies (1324 patients)
cross-sectional (cohort type accuracy study)
not serious
not serious
not serious
not serious
none
994 (988 to 995)
949 (943 to 950)
899 (894 to 900)
â¨â¨â¨â¨ High
False positives
1 (0 to 7)
1 (0 to 7)
1 (0 to 6)
Explanations:
a. High heterogeneity across studies.
Test accuracy of Roche SARS-CoV-2 Rapid Antigen Test for COVID-19 or SARS-CoV-2 infection in symptomatic adults
Sensitivity
0.812 (95% CI: 0.762 to 0.855)
Specificity
0.996 (95% CI: 0.974 to 0.999)
Prevalences
0.5%
5%
10%
Outcome
â of studies (â of patients)
Study design
Factors that may decrease certainty of evidence
Effect per 1000 patients tested
Test accuracy certainty of evidence
Risk of bias
Indirectness
Inconsistency
Imprecision
Publication bias
Pre-test probability of 0.5% (95% CI)
Pre-test probability of 5% (95% CI)
Pre-test probability of 10% (95% CI)
True positives
2 studies (874 patients)
cross-sectional (cohort type accuracy study)
not serious
not serious
not serious
not serious
none
4 (4 to 4)
41 (38 to 43)
81 (76 to 86)
â¨â¨â¨â¨ High
False negatives
1 (1 to 1)
9 (7 to 12)
19 (14 to 24)
True negatives
2 studies (874 patients)
cross-sectional (cohort type accuracy study)
not serious
not serious
not serious
not serious
none
991 (969 to 994)
946 (925 to 949)
896 (877 to 899)
â¨â¨â¨â¨ High
False positives
4 (1 to 26)
4 (1 to 25)
4 (1 to 23)
Test accuracy of BinaxNOW by Abbott for COVID-19 or SARS-CoV-2 infection in symptomatic adults
Sensitivity
0.867 (95% CI: 0.797 to 0.919)
Specificity
0.988 (95% CI: 0.974 to 0.996)
Prevalences
0.5%
5%
10%
Outcome
â of studies (â of patients)
Study design
Factors that may decrease certainty of evidence
Effect per 1000 patients tested
Test accuracy certainty of evidence
Risk of bias
Indirectness
Inconsistency
Imprecision
Publication bias
Pre-test probability of 0.5% (95% CI)
Pre-test probability of 5% (95% CI)
Pre-test probability of 10% (95% CI)
True positives
1 study 642 patients
cross-sectional (cohort type accuracy study)
not serious
not serious
not serious
not serious
none
4 (4 to 5)
43 (40 to 46)
87 (80 to 92)
â¨â¨â¨â¨ High
False negatives
1 (0 to 1)
7 (4 to 10)
13 (8 to 20)
True negatives
1 study 642 patients
cross-sectional (cohort type accuracy study)
not serious
not serious
not serious
not serious
none
983 (969 to 991)
939 (925 to 946)
889 (877 to 896)
â¨â¨â¨â¨ High
False positives
12 (4 to 26)
11 (4 to 25)
11 (4 to 23)
Introduction
According to the World Health Organization, as of August 2024, there were more than 775 million confirmed cases of COVID-19 caused by the virus SARS-CoV-2 and more than 7 million deaths.
1
In addition to recently updated vaccines, testing and accurate diagnosis of SARS-CoV-2 has been a key tool in fighting the pandemic.
2
Based on the current statistics of new cases
1
showing that the virus remains in circulation within human and animal populations,
3
accurate diagnostic testing is required to prevent future outbreaks that can lead to additional loss of life.
Accurate COVID-19 point-of-care (POC) diagnostic tests are required for real-time identification of SARS-CoV-2 infections in individuals. Early and accurate identification of potential cases leads to better control of virus transmission and early treatment interventions for individuals at high risk of severe disease. At this point, asymptomatic screening for SARS-CoV-2 infection has fallen out of fashion, with most public locations not requiring tests as part of day-to-day life. However, symptomatic individuals who present at primary care locations need to be diagnosed quickly and reliably. Real-time reverse transcriptase PCR (qRT-PCR or RT-PCR) is the accepted gold standard for diagnostic testing
4
and is available in many health care settings. However, RT-PCR requires technical expertise and expensive equipment that are not available in most primary care locations. Additionally, samples are required to be collected at the POC and sent to off-site laboratories for testing. The time delay between visiting the primary care provider and receiving results can increase transmission and delay appropriate treatment. For SARS-CoV-2 infections, RT-PCR detects viral RNA but is unable to discriminate between transmissible and replicating viruses and RNA remaining after the infection has been contained by the immune system.
5
Primary care providers should have access to reliable POC rapid antigen tests (RATs) for COVID-19, similar to those that are available for many other infectious diseases. Evaluation of the accuracy of POC diagnostic tests is needed to utilize these tests with confidence.
6
Rapid antigen tests are immunoassays that detect the presence of a specific viral protein, glycan, or nucleic acid, which implies a current infection with SARS-CoV-2. RATs are useful for identifying infectious viruses as they detect viral proteins, which are cleared before the remaining viral RNA.
5
The accuracy of these tests compared with the gold standard RT-PCR appears to vary depending on the manufacturer. However, many studies have reported disparate accuracy results compared with manufacturersâ reported results.
7
â
12
In this systematic review, we synthesized the current evidence regarding RAT accuracy for the detection of SARS-CoV-2, and considered the overall performance of these techniques compared with the gold standard RT-PCR.
A search of PROSPERO, DARE (Database of Abstracts of Reviews of Effects), PubMed, the Cochrane Database of Systematic Reviews, JBI Registration of Systematic Review Titles, and
JBI Evidence Synthesis
was conducted in November 2020. We identified 1 review in PROSPERO
13
and 2 systematic reviews in the Cochrane Database of Systematic Reviews,
14
,
15
each of which became available after our title registration in PROSPERO and the JBI Registration of Systematic Review Titles in June 2020. The PROSPERO review examined peer-reviewed publications for tests commercially available before August 15, 2020.
13
Our systematic review included additional sources for tests, including gray literature available from the manufacturers, and included search results from tests not yet commercially available. The literature searches of the 2 Cochrane reviews ended in May 2020
14
,
15
and were updated in July 2022, with a search that ended in March 2021.
16
In the time since then, significant amounts of research and numbers of tests have become available, warranting an additional review. With the rapidly changing environment around COVID-19, our review adds to those published with a longer, more recent timeline. Additionally, our question is of a more general nature of POC diagnostic accuracy for primary care settings anywhere in the world. Our review has important implications for health care providers caring for patients in both resource-rich and resource-poor regions.
We framed our review question using the population index test reference test diagnosis (PIRD) mnemonic, which is commonly used for diagnostic reviews.
17
The objective of this systematic review was to synthesize the best available evidence related to the diagnostic accuracy of the available POC RATs (index test) relative to a certified medical laboratory viral genetic RT-PCR test (reference test) for the diagnosis of COVID-19/SARS-CoV-2 in adults 18 years and older. The rationale for combining both test types in this systematic review was to provide a comprehensive comparison of RT-PCR with the POC RATs. As the COVID-19 pandemic continues to rapidly evolve, the highest diagnostic accuracy, lowest cost, and quickest results are important considerations for monitoring and managing disease spread in a primary care setting. The aim of this study was to identify the rapid diagnostic tests that fit this requirement.
Review question
What is the diagnostic accuracy of the currently available and upcoming POC RATs used in primary care settings relative to the viral genetic RT-PCR test as a reference for the diagnosis of COVID-19/SARS-CoV-2 in adults?
Inclusion criteria
Participants
The review examined studies that included nonpregnant adults (18 years and older) with suspected SARS-CoV-2 infection, regardless of symptomology or disease severity. Persons of any ethnicity or race in any geographic location were considered. Studies that included data from pregnant women or children within the study population that could be separated from the overall study data were included in the review. We excluded studies that only contained tests that could not be used in primary care settings, such as those that required larger equipment or specialized expertise. The setting of the study was recorded but not used as an exclusion criterion. Any non-primary care setting was initially an exclusion criterion,
18
but upon further discussion, the criterion was adjusted to focus on the RAT used rather than the setting in which the RAT was used.
Index test
The index tests investigated in this review were any currently available or pre-market POC SARS-CoV-2 RATs. RATs are qualitative or semi-quantitative diagnostics that provide a result within a short time frame, typically within the hour following sample collection.
19
Tests could use any easily obtained bodily fluid or sample, including saliva, mucus, blood, urine, breath, or feces. Most of the studies considered used nasopharyngeal, nasal, or oropharyngeal swab specimens. RATs include a variety of techniques, such as chromogenic-based or fluorescence-based detection and lateral flow-based detection, but as a common denominator, all detect viral antigens from presently infected fluids and cells.
19
Tests that detect immunoglobulin against SARS-CoV-2 were excluded from this review, as antibodies develop upon resolution of SARS-CoV-2 infection or from vaccination and, therefore, are not used in the POC setting for diagnosing acute infection.
6
Reference test
The reference test was commercially distributed RT-PCRâbased tests that detect the RNA genome of SARS-CoV-2 and have been validated by an independent third party. Additionally, custom or in-house RT-PCR tests were considered with appropriate validation documentation. For example, Japanâs National Institute of Infectious Disease method was accepted as a validated RT-PCR test.
20
These tests must be performed in certified laboratories where personnel have been trained to perform RT-PCR assays.
Diagnosis of interest
The diagnoses of interest were COVID-19 disease and SARS-CoV-2 infection.
Types of studies
This review considered any English-language or English-translated cross-sectional or cohort study that examined the diagnostic accuracy (sensitivity and specificity, positive predictive value, negative predictive value) of COVID-19/SARS-CoV-2 infection where the participants had both index and reference tests performed. Case-control studies were excluded due to high risk of bias (see âAssessment of methodological qualityâ). Meta-analysis was performed on studies that provided true-positive (TP), true-negative (TN), false-positive (FP), and false-negative (FN) values. Studies published from November 2019 to July 12, 2022, were included, as SARS-CoV-2 emerged in late 2019 and is the cause of a continuing pandemic.
Methods
This systematic review was conducted in accordance with JBI methodology for systematic reviews of diagnostic test accuracy
17
and follows our published protocol,
18
with exceptions noted throughout.
Search strategy
The search strategies for all databases aimed to locate published and unpublished studies, including preprints. An initial limited search of several sources was undertaken to identify articles, review other search strategies, and search for published articles on the topic. These initial sources were PubMed, PROSPERO,
JBI Evidence Synthesis
, Cochrane Database of Systematic Reviews, DARE, and the Cochrane Central Register of Controlled Trials. The text words contained in the titles and abstracts of relevant articles and the articlesâ index terms were used to develop a full search strategy for PubMed. We adopted the Canadian Agency for Drugs and Technologies (CADTH) COVID-19 search string developed for PubMed.
21
Once a draft was fully developed, the PubMed search strategy was peer-reviewed by a medical librarian following the Peer Review of Electronic Search Strategy (PRESS) Guideline Statement.
22
After that initial pilot search, the search strategy was further edited and finalized for review. The search strategy, including all identified keywords and index terms, was adapted for each included information source.
The full search of MEDLINE (PubMed), Embase, Scopus, Qinsight (Quertle), and the World Health Organization (WHO) COVID-19 database was undertaken in July 2021 and updated on July 12, 2022 (with the exception of Qinsight, which was no longer available). See
Appendix I
for the full search strategy. Scopus, Qinsight, and WHO COVID-19 include gray literature.
Study selection
Following the search, all identified citations were collated and uploaded into EndNote v.X9.3.3. The EndNote edition was later upgraded to EndNote 20.5 (Clarivate Analytics, PA, USA). All duplicates were removed using a method developed and detailed by Bramer
et al
.
23
Titles and abstracts were screened first by 2 independent reviewers of the research team (EH, GM, BH, SS, SR, TH, CK, SF, AD, JK, AA, KD, TE, MD, AS) against the inclusion criteria using Google Sheets. Potentially relevant studies were retrieved in full, and their citation details were imported into a Google Sheet. The full texts of selected citations were assessed in detail against the inclusion criteria by at least 2 reviewers from the team independently (EH, GM, BH, SS, SR, TH, CK, SF, AD, JK, AA, KD, TE, MD, AS). Conflicts were resolved at the completion of each stage by a third reviewer (AS, AA, KD, TE). Reasons for the exclusion of full-text studies that did not meet the inclusion criteria were recorded and are provided in Supplemental Digital Content 1,
http://links.lww.com/SRX/A55
. The results of the search and screening are presented in a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram
24
(Figure
1
).
Figure 1.
Search results and study selection and inclusion process
24
Assessment of methodological quality
Selected studies were critically appraised by at least 2 reviewers from the team independently (EH, GM, BH, SS, SR, TH, CK, SF, AD, JK, AA, KD, TE, MD, AS) for risk of bias using the standardized critical appraisal instrument from the QUADAS-2.
25
QUADAS-2 provides a series of yes/no questions to appraise studies. At a minimum, we required the following questions to be answered âyesâ for a study to be included in the systematic review: #2: Was a case-control design avoided? #3: Did the study avoid inappropriate exclusions? #6: Is the reference standard likely to correctly classify the target condition? #8: Was there an appropriate interval between the index test and reference standard?
Studies that answered ânoâ or âunclearâ to any of these 4 QUADAS-2 questions were excluded. Disagreements were resolved through discussion or with an additional reviewer. The decision to exclude was based on the consensus of the 2 independent reviewers and, if needed, an additional reviewer (EH, GM, BH, SS, SR, TH, CK, SF, AD, JK, AA, KD, TE, MD, AS). Studies were excluded from data extraction if specificity and sensitivity were not presented or the data could not be used to calculate specificity and sensitivity. We did not exclude any studies due to low statistical power.
Data extraction
We performed a pilot data extraction of 52 studies to determine the effectiveness of our initial data extraction tool. Based on the challenges of combining the extracted data from the pilot data extraction, a new custom data extraction tool was developed, building on the initial tool. The custom data extraction tool was modified from the original protocol to better separate and standardize the data during extraction. See
Appendix II
for the updated data extraction tool. We identified specific portions of the data extraction tool to be standardized prior to data extraction, including the setting, sample, reference test, and index test. For these, we used drop downs for the data extractors to select from, including an âotherâ option that allowed the entering of data items not found in the initial pilot extraction. The extracted data were reviewed and verified prior to analysis. The final standardization of data was performed by 2 individuals (SK-C, AS) to ensure inter-extractor reliability.
For each study, we identified the primary (dominant) strain of SARS-CoV-2 circulating in the study country during the study time frame using CoVariants.org.
26
When specific dates or specific country-level data were not available, variants were estimated by the time frame of initial study submission and dominant strains in neighboring countries. Subgroup analyses were identified after pilot data extraction but prior to overall data extraction, and were used to refine the data extraction tool. The authors of studies missing key relevant information (such as TN, FN, TP, and FP) were contacted for additional information. If no reply was received on the first attempt, we attempted to contact the authors a second time. No additional information or data were retrieved from this effort.
Data synthesis
Papers that reported the TP, FP, TN, and FN were pooled in statistical meta-analysis using the R statistical software (R Foundation for Statistical Computing, Vienna, Austria) packages meta
27
and dmetar.
28
Due to our custom data extraction tool, we were unable to utilize the JBI System for the Unified Management, Assessment and Review of Information (JBI SUMARI; JBI, Adelaide, Australia) software as initially planned.
18
Studies that did not include these 4 values were excluded from meta-analysis. As we expected this information to be included in all published studies, these criteria were not stated in our inclusion/exclusion criteria in the original protocol.
18
However, without these data, the combined accuracy data could not be accurately calculated. As an
a priori
decision, we only included RATs that were reported in at least 5 studies for the meta-analysis due to the minimum number of groups needed to fully benefit from the random-effects model in dmetar.
28
The pooled sensitivity, specificity, positive predictive, and negative predictive values were calculated assuming a random-effects model and presented with 95% CIs. The positive predictive and negative predictive values were calculated using the formulas TP/(TP+FP) and TN/(FN+TN) when not presented in the papers. Forest plots for the sensitivity and specificity were generated using the R package meta.
27
Potential subgroups that were proposed in our protocol included index tests used, symptomatic vs asymptomatic, and cycle threshold (Ct) values. Where statistical pooling was not possible, the findings were presented in narrative format, including tables and figures.
Heterogeneity was assessed using the
I
2
value. When heterogeneity above 90% was observed, outlier analysis was conducted to identify studies contributing to overall heterogeneity. The R package dmetar was used to identify outliers based on their contribution to heterogeneity and the pooled value of the measurement.
28
This package examines the 95% CI of each study compared with the pooled 95% CI. When a study was removed, the data set was reanalyzed for heterogeneity. The results shown were generated by removing outliers. The code and the data used for data synthesis can be found at
https://github.com/skoshyc/covid_systematic_review_2023
.
Assessing certainty in the evidence
The Summary of Findings were created using GRADEPro GDT software (McMaster University, ON, Canada).
29
The GRADE approach for grading the certainty of evidence for diagnostic test accuracy was used.
30
The following outcomes are included in the Summary of Findings: the review question; the index test names and types; the reference tests used; the population; the estimates of true negatives, true positives, false negatives, and false positives; the absolute difference between the index and reference tests for these values per 1000 patients; the sample size; the number of studies contained within the sample set; the GRADE (Grading of Recommendations Assessment, Development and Evaluation) quality of evidence for each finding; and any comments associated with the finding.
Deviations from and clarifications to protocol
Title and abstract screening, full-text screening, critical appraisal, data extraction, and data synthesis were completed as described in our protocol
18
with the following exceptions.
Software and procedure flow
All steps were performed using Google Sheets set up specifically for our review. The full-text screening was adjusted to use a drop-down selection of prioritized reasons for exclusion. Reviewers selected the highest priority exclusion reason for excluded studies (Table
1
). For critical appraisal, we used a drop-down setup for each question and the decision for inclusion or exclusion. The exclusions from the critical appraisal process were prioritized by question number from the JBI critical appraisal tool for diagnostic accuracy reviews.
25
We piloted and adjusted our data extraction tool using a subset of studies. This step was not specified in our published protocol.
18
We were not able to use JBI SUMARI due to our customized data extraction tool. We utilized R software with custom code instead. Rather than assessing heterogeneity visually as originally planned, we used the
I
2
value. For the meta-analysis, we included only RATs reported in at least 5 studies.
Table 1.
Prioritized exclusion criteria for studies, as selected by reviewers during full-text screening
1
Not RAT compared to RT-PCR
2
Results took more than 4 hours to determine after test was initiated
3
Diagnostic accuracy was not provided
4
Children were included in the analysis
5
Pregnant individuals were included in the analysis
6
Studies were dated prior to the emergence of COVID-19
7
Study examined antibodies against COVID-19, not COVID-19 antigens
8
Test is incompatible with a standard primary care setting
9
Study is a review without primary data
10
Study is in a foreign language and not available in English
11
Duplicate article
RAT, rapid antigen test; RT-PCR, reverse transcriptase polymerase chain reaction.
Inclusion and exclusion criteria
We adjusted our inclusion/exclusion criteria to clarify several points. First, our protocol stated that we would exclude studies performed in non-primary care settings.
18
We included studies from non-primary care settings if the RAT being used could also be easily used in primary care settings. Instead, RATs that could not be performed in a primary care setting were excluded. Next, our protocol stated that the reference test considered was commercially available RT-PCR tests and that any RT-PCR test would be considered.
18
We considered and included studies where the reference test was a validated custom or in-house RT-PCR test. Third, we clarified that cross-sectional and cohort studies would be considered, but case-control studies were excluded for poor methodological quality.
Results
Study inclusion
A total of 3122 citations were identified from searches of databases and gray literature. After duplicates were removed through EndNote, 1204 records were screened for inclusion by title and abstract using JBI SUMARI (pilot search only) and Google Sheets. We examined the full text of 580 studies for inclusion based on our described criteria and excluded 319 (see Supplemental Digital Content 1,
http://links.lww.com/SRX/A55
. The most common reason for study exclusion was the inclusion of individuals younger than 18 years within the data set (n = 102). After removing studies based on our exclusion criteria, we critically appraised 261 studies. The primary reason for excluding studies after critical appraisal was the use of a case-control study design (n = 107 out of 118 excluded studies; see Supplemental Digital Content 2,
http://links.lww.com/SRX/A56
. After critical appraisal, we extracted data from 143 articles.
7
,
8
,
11
,
31
â
170
From these articles, data from 91 studies were used for overall and subgroup analyses based on the data synthesis methods. See the full search results and study selection and inclusion process in Figure
1
.
Methodological quality
The extracted studies had high certainty of evidence based on the GRADE analysis.
30
Given that we restricted our review to cross-sectional and cohort designs, all of the included studies began at âhighâ quality.
The majority of the studies had a low risk of bias based on the QUADAS-2 tool (Figure
2
[summary of risk of bias assessment] and Supplemental Digital Content 3,
http://links.lww.com/SRX/A57
[individual study analysis]). While most papers stated that the reference test was performed at a different site or through a central public health laboratory, a few papers (16.0%) did not clearly indicate whether the reference test was interpreted without knowledge of the index test result (Q#7). All studies used a validated RT-PCR as their reference test, but some papers (15.3%) used multiple RT-PCR kits (Q#9). About 1 in 5 papers (20.8%) did not include all participants in their analysis (Q#10). The reasons cited for these exclusions were a lost sample or inconclusive/invalid results on either the index or reference test.
Figure 2.
Summary of risk of bias assessment of included studies. The percentage of included studies where the answer to each question from the QUADAS-2 tool25 was âyesâ (green, no stripes), ânoâ (red, diagonal stripes), or ânot clearâ (yellow, vertical stripes) are shown. Questions that required a âyesâ answer for the study to be included in the data extraction are not shown (#2, #3, #6, and #8).
The indirectness, publication bias, and impreciseness of the included studies represented minor or no concerns regarding the quality of evidence. The largest driver of the quality of evidence decrease was the high heterogeneity found across studies. This is discussed further in the review findings section.
Characteristics of included studies
The studies included in our data extraction consisted of retrospective and prospective cohort studies and cross-sectional studies. In general, most studies collected a single subject sample that was used for the index and reference tests, or 2 samples were collected consecutively at the same encounter. On occasion, 2 samples were taken from different anatomical locations from the same subject (eg, a nasopharyngeal sample for RT-PCR and an anterior nares sample for RAT). Most studies used a design where the RAT was performed on-site with the participant, and the RT-PCR sample was stored cold and transferred to a central laboratory location. For some studies, the laboratory was on-site, such as a clinical laboratory associated with the hospital performing the study. However, many studies used central public health laboratories within their local health districts to perform the RT-PCR. A benefit of using a clinical laboratory instead of utilizing their own laboratory staff to run the RT-PCRs is that the clinical laboratory technicians are blinded to the RAT results because they are not involved in the study.
Where possible, we validated the reported sensitivity and specificity numbers in each study using the TP, FP, TN, and FN values. Not every study provided these numbers, so some reported sensitivity and specificity calculations could not be verified. The key findings of each paper are summarized in
Appendix III
.
The studies included in our meta-analysis were performed in a variety of settings (Table
2
). The breadth of study locations demonstrates the generalizability of RATs across different levels of health care and the ease of use of these POC tests. While we focused on determining best practices for primary care settings, these findings are applicable to a wide range of health care locations.
Table 2.
Reported settings of included studies
Location
# of studies performed
COVID-19 testing site/screening location
52
Hospital - inpatient
38
Emergency department/room
26
College/university campus (medical center/hospital)
25
Hospital - outpatient
15
Primary care location
15
Not described/unclear
8
Long-term care facility (nursing home, rehab centers)
5
Public area (not a designated screening location)
5
College/university campus (non-medical)
4
Urgent care location
1
The studies were conducted in 44 countries across 6 continents starting in March 2020 through our search date in July 2022 (Figure
3
A). We generated heatmaps showing the locations of dominant variants based on the countries of the studies (Figure
3
B-D). Studies from the Beta and Gamma waves were less common (not shown). We had few studies completed during the dominance of the Omicron variants due to the dates of our searches (not shown).
Figure 3.
Maps of study locations. The heatmaps show the geography of the studies included in this review, illustrating the global nature of COVID-19 rapid antigen tests. (A) The number of included studies from each country is shown by heatmap. (BâD) The number of included studies from each country with data collected during the dominance of the Ancestral (B), Alpha (C), and Delta (D) strains of SARS-CoV-2 are shown by heatmap. Gray indicates that no included studies came from that country.
The included studies resulted in a total participant number of 212,874. There were 139 papers that either specified the number of participants, the number of samples, or both (Figure
4
). The number of participants or samples ranged from 42 to 18,457, with a median of 635 participants. Overall, the studies included in the meta-analysis all shared the general design of testing subjectsâ samples collected at the same time with both RAT and RT-PCR.
Figure 4.
Numbers of participants/samples per included study. Studies were grouped by the number of participants. The number of studies for each group is shown.
The studies included in the analysis listed 50 commercially available RATs, whereas 3 studies described novel tests that were not yet commercially available (
Appendix IV
). Tests reported in fewer than 5 studies were excluded from the meta-analysis, as described in the methods.
28
The reported diagnostic accuracy data for all studies can be found in
Appendix III
. Most studies reported using nasopharyngeal swabs to acquire the test sample (Table
3
). Many studies reported using multiple sample sites in their analysis. However, few studies compared the accuracy of the tests from multiple sample sites.
Table 3.
Sample types collected for COVID-19 testing, as reported in included studies
Sample type
# of studies
Nasopharyngeal swabs
128
Oropharyngeal swabs/throat swabs
41
Nasal swabs
37
Other
8
Saliva
7
Blood
2
Bronchoalveolar lavage/bronchial sample
1
We did not restrict the use of reference tests to a specific manufacturer or target. The studies used a variety of RT-PCR tests as their reference test. All reference tests were either commercially available RT-PCRs or in-house primers based on national or international public health organization recommendations. Many studies used multiple reference tests due to the availability of the tests over the course of their studies. The most commonly reported reference test was the Roche cobas systems, with 30 studies reporting its use. Other common reference tests were Allplex assays by Seegene (23 studies), TaqPath assays by ThermoFisher (18 studies), and Xpert Xpress/GeneXpert assays by Cepheid (19 studies ). Seventeen studies reported a custom or in-house PCR assay based on published primers, and 15 studies did not report a specific RT-PCR assay.
Review findings
We compared the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for each index test across the published studies. A total of 91 studies were used for synthesis, as those studies provided the TP, FP, TN, and FN values.
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For the analysis of the index test, we considered the entries from the paper that specified the overall accuracy of the test across their entire study population.
We only included index tests examined in at least 5 studies for the pooled sensitivity, specificity, PPV, and NPV, which are shown in the forest plots. The tests meeting this criterion were STANDARD Q COVID-19 Ag Test (SD Biosensor; 27 studies), PanBio COVID-19 Ag Rapid Test Device (Abbott; 14 studies), SARS-CoV-2 Rapid Antigen Test (Roche Diagnostics; 11), and BinaxNOW COVID-19 Antigen (Abbott; 10 studies). All tests that were considered are listed in
Appendix IV
.
We considered the studies that were outliers in the pooled analysis. An outlier was defined as described in the methods. On removing the outliers, we observed that overall heterogeneity reduced considerably.
Sensitivity
The maximum sensitivity reported was 100%, which included the Flowflex COVID-19 Antigen test (ACON Labs) and STANDARD Q COVID-19 Ag Test (SD Biosensor;
Appendix IV
). The heterogeneity of the data set was high when we considered the included studies,
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as indicated by an
I
2
value of 94.6% (95% CI 93.6â95.4%). The pooled sensitivity of these data was 67.0% (95% CI 62.6â71.1%). Each testâs pooled sensitivity is shown in Table
4
.
Table 4.
Pooled sensitivity of index tests (point-of-care SARS-CoV-2 rapid antigen tests), with outliers (as identified based on their contribution to heterogeneity)
Test name
# of studies
Pooled sensitivity
95% CI
I
2
STANDARD Q COVID-19 Ag (SD Biosensor)
27
66.0%
59.2-72.2%
95.3%
PanBio (Abbott)
13
70.2%
61.0-78.0%
92.7%
Roche SARS-CoV-2 Rapid Antigen Test (Roche)
11
69.3%
61.2-76.4%
83.1%
BinaxNOW (Abbott)
10
62.3%
49.4-73.6%
94.2%
On removing the outliers, the pooled sensitivity was 66.7% (95% CI 63.4â69.8%), with an
I
2
value of 70.4%.
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The updated test subgroup results are shown in Table
5
. The individual sensitivities reported for the 4 tests included in the pooled analysis are shown in Figure
5
(outliers removed). The high heterogeneity is still present in the large discrepancies in reported sensitivities and 95% CIs.
Table 5.
Pooled sensitivity of index tests (point-of-care SARS-CoV-2 rapid antigen tests), without outliers (as identified based on their contribution to heterogeneity)
Test name
# of studies
Pooled sensitivity
95% CI
I
2
STANDARD Q COVID-19 Ag (SD Biosensor)
15
65.4%
61.1-69.4%
70.0%
PanBio (Abbott)
6
71.0%
64.6-76.6%
73.8%
Roche SARS-CoV-2 Rapid Antigen Test (Roche)
7
68.5%
60.3-75.7%
73.3%
BinaxNOW (Abbott)
2
54.7%
46.0-63.1%
0.0%
Figure 5.
Diagnostic accuracy of COVID-19/SARS-CoV-2 infectionâsensitivity forest plot for the overall cohort. The forest plot shows the sensitivities and 95% CIs reported for the STANARD Q COVID-19 Ag Test (SD Biosensor), PanBio (Abbott), Roche SARS-CoV-2 Rapid Antigen Test (Roche), and BinaxNOW (Abbott) index tests (point-of-care SARS-CoV-2 rapid antigen tests) after outlier studies were removed. Pooled sensitivity and heterogeneity value (I2) for each index test are shown at the bottom of each test section. The pooled sensitivity and 95% CI of all reported tests on the forest plot are shown at the bottom. The vertical line at 0.671 represents the pooled sensitivity value for all shown tests. Boxes represent the reported sensitivity, and solid horizontal lines represent the 95% CI reported by each study.
Specificity
The maximum specificity recorded was 100%, and there were 27 index tests that had this value (
Appendix IV
). As in the case of the sensitivity, the heterogeneity of the data set when we consider the included studies was high, as indicated by an
I
2
value of 93.7% (95% CI 92.5â94.6%). The pooled specificity of these data was 99.6% (95% CI 99.3â99.8%).
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,
169
Each testâs pooled specificity is shown in Table
6
.
Table 6.
Pooled specificity of index tests (point-of-care SARS-CoV-2 rapid antigen tests), with outliers (as identified based on their contribution to heterogeneity)
Test name
# of studies
Pooled specificity
95% CI
I
2
STANDARD Q COVID-19 Ag (SD Biosensor)
27
99.2%
98.4-99.6%
95.0%
PanBio (Abbott)
13
99.9%
99.6-100%
62.9%
Roche SARS-CoV-2 Rapid Antigen Test (Roche)
11
99.8%
98.9%-100%
93.8%
BinaxNOW (Abbott)
10
99.8%
99.5-99.9%
87.8%
On removing the outliers, the pooled specificity was 99.8% (95% CI 99.7â99.9%), with an
I
2
value of 40.4%.
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The updated test subgroup results are shown in Table
7
. The individual specificities reported for the 4 tests included in the pooled analysis are shown in Figure
6
(outliers removed). The high heterogeneity is still present in the large discrepancies in reported specificities and 95% CIs.
Table 7.
Pooled specificity of index tests (point-of-care SARS-CoV-2 rapid antigen tests), without outliers (as identified based on their contribution to heterogeneity)
Test name
# of studies
Pooled specificity
95% CI
I
2
STANDARD Q COVID-19 Ag (SD Biosensor)
16
99.6%
99.4-99.7%
46.7%
PanBio (Abbott)
10
99.9%
99.8-100.0%
0.0%
Roche SARS-CoV-2 Rapid Antigen Test (Roche)
7
99.9%
99.5-100.0%
0.0%
BinaxNOW (Abbott)
6
99.9%
99.7-100.0%
16.0%
Figure 6.
Diagnostic accuracy of COVID-19/SARS-CoV-2 infectionâspecificity forest plot for the overall cohort. The forest plot shows the specificities and 95% CIs reported for the STANARD Q COVID-19 Ag Test (SD Biosensor), PanBio (Abbott), Roche SARS-CoV-2 Rapid Antigen Test (Roche), and BinaxNOW (Abbott) index tests after outlier studies were removed. Pooled specificity and heterogeneity value (I2) for each index test are shown at the bottom of each test section. The pooled specificity and 95% CI of all reported tests on the forest plot are shown at the bottom. The vertical line at 0.996 represents the pooled specificity value for all shown tests. Boxes represent the reported specificity, and solid horizontal lines represent the 95% CI reported by each study.
Positive predictive value
The maximum recorded PPV was 100%, and there were 21 index tests that reported this value in at least 1 study (
Appendix IV
). To obtain the pooled PPV, we assumed the formula PPV = TP/(TP + FP), as most papers stated it this way. After removing outliers, as with sensitivity and specificity, we obtained a pooled PPV value of 97.7% (95% CI 96.8â98.4%) and
I
2
value of 0.0% (95% CI 0.0â34.8%).
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,
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The forest plot for the PPVs is shown in Figure
7
. Each testâs pooled PPV is shown in Table
8
.
Figure 7.
Diagnostic accuracy of COVID-19/SARS-CoV-2 infectionâpositive predictive values forest plot. The forest plot shows the positive predictive values (PPVs) and 95% CIs reported for the STANDARD Q (SD Biosensor), PanBio (Abbott), Roche SARS-CoV-2 Rapid Antigen Test (Roche), and BinaxNOW (Abbott) index tests after outlier studies were removed. Pooled PPV and heterogeneity value (I2) for each index test is shown at the bottom of each test section. The pooled PPV and 95% CI of all reported tests on the forest plot are shown at the bottom. The vertical line at 0.962 represents the pooled PPV for all shown tests. Boxes represent the reported PPV, and solid horizontal lines represent the 95% CI reported by each study. Some studies reported multiple sites and are included as an individual row for each site.
Table 8.
Pooled positive predictive values of index tests (point-of-care SARS-CoV-2 rapid antigen tests), without outliers (as identified based on their contribution to heterogeneity)
Test name
# of studies
Pooled PPV
95% CI
I
2
STANDARD Q COVID-19 Ag (SD Biosensor)
18
96.3%
94.8-97.4%
24.1%
PanBio (Abbott)
12
98.9%
97.4-99.5%
0.0%
Roche SARS-CoV-2 Rapid Antigen Test (Roche)
8
98.6%
94.4-99.6%
0.0%
BinaxNOW (Abbott)
6
97.3%
92.3-99.1%
0.0%
PPV, positive predictive value.
Negative predictive value
The maximum value was 100%, and included the Flowflex COVID-19 Antigen test (ACON Labs) and STANDARD Q COVID-19 Ag Test (SD Biosensor). To obtain the pooled NPV, we assumed the formula NPV = TN/(TN + FN), as most papers stated it this way. After removing outliers, as with sensitivity and specificity, we obtained a pooled NPV value of 95.2% (95% CI 94.3â95.9%) and
I
2
value of 81.7% (95% CI 73.3â87.5%; see Table
9
and Figure
8
).
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,
154
,
168
The BinaxNOW (Abbott) subgroup of papers was excluded, as they all contributed substantially to the heterogeneity.
Table 9.
Pooled negative predictive values of index tests (point-of-care SARS-CoV-2 rapid antigen tests), without outliers (as identified based on their contribution to heterogeneity)
Test name
# of studies
Pooled NPV
95% CI
I
2
STANDARD Q COVID-19 Ag (SD Biosensor)
15
95.3%
94.0-96.2%
84.1%
PanBio (Abbott)
4
95.1%
92.9-96.6%
87.2%
Roche SARS-CoV-2 Rapid Antigen Test (Roche)
3
94.9%
94.0-95.7%
39.3%
NPV, negative predictive value.
Figure 8.
Diagnostic accuracy of COVID-19/SARS-CoV-2 infectionânegative predictive value forest plot. The forest plot shows the negative predictive value (NPV) and 95% CIs reported for the STANDARD Q (SD Biosensor), PanBio (Abbott), Roche SARS-CoV-2 Rapid Antigen Test (Roche), and BinaxNOW (Abbott) index tests after outlier studies were removed. Pooled NPV and heterogeneity value (I2) for each index test is shown at the bottom of each test section. The pooled NPV and 95% CI of all reported tests on the forest plot are shown at the bottom. The vertical line at 0.949 represents the pooled NPV for all shown tests. Boxes represent the reported value, and solid horizontal lines represent the 95% CI reported by each study. Some studies reported multiple sites and are included as an individual row for each site.
Symptomatic test subgroup
The protocols for testing and screening have changed over the course of the pandemic, and now widespread testing is uncommon. Symptom presentation has now replaced screening tests for most locations and businesses. Taking this into consideration, we performed an additional analysis of studies that reported subgroups of symptomatic and asymptomatic individuals. The symptomatic subgroup diagnostic accuracy may be the most relevant cohort for primary care settings, as most asymptomatic individuals will not present to their primary care providers to be screened for COVID-19.
We found differences in the accuracy of the index tests in subjects who were symptomatic or asymptomatic. There were 9 studies that examined symptomatic
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and 11 studies that examined asymptomatic
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subgroups, and provided the values used to calculate accuracy values (TP, FP, TN, and FN). If there was only 1 study in the group,
I
2
was reported as âNA.â As with the overall analysis of the studies, there was high heterogeneity between the studies. Due to fewer studies reporting these subgroups, we did not have enough studies to remove outliers from these analyses. The symptomatic subgroups showed higher overall levels of sensitivity compared to the overall group (Table
10
and Figure
9
A). Specificity was slightly lower in the symptomatic subgroup than in the overall group (Table
10
and Figure
9
B). The symptomatic subgroup also had a slightly lower PPV and NPV (Table
11
) compared with the overall group (Figure
10
).
Table 10.
Sensitivity and specificity of index tests (point-of-care SARS-CoV-2 rapid antigen tests) in the symptomatic subgroup
Test name
# of studies
Sensitivity (95% CI)
I
2
Specificity (95% CI)
I
2
STANDARD Q COVID-19 Ag (SD Biosensor)
4
78.2% (58.7â90.0%)
96.1%
98.4% (94.9â99.5%)
74.9%
PanBio (Abbott)
2
78.0% (61.0â88.9%)
90.7%
99.9% (99.3â100%)
0.0%
Roche SARS-CoV-2 Rapid Antigen Test (Roche)
2
81.2% (76.2â85.5%)
0.0%
99.6% (97.4â99.9%)
0.0%
BinaxNOW (Abbott)
1
86.7% (79.7â91.9%)
NA
98.8% (97.4â99.6%)
NA
NA, not applicable.
Figure 9.
Diagnostic accuracy of COVID-19/SARS-CoV-2 infectionâsensitivity and specificity forest plots for symptomatic subgroup. Forest plot shows the sensitivities (A) and specificities (B) and 95% CIs reported for the symptomatic subgroup for the STANDARD Q (SD Biosensor), PanBio (Abbott), Roche SARS-CoV-2 Rapid Antigen Test (Roche), and BinaxNOW (Abbott) index tests after outlier studies were removed. Pooled values and heterogeneity value (I2) for each index test are shown at the bottom of each test section. The pooled values and 95% CI of all reported tests on each forest plot are shown at the bottom. The vertical lines at 0.804 (sensitivity) and 0.994 (specificity) represent the pooled values for all shown tests. Boxes represent the reported sensitivity and specificity, and solid horizontal lines represent the 95% CI reported by each study.
Table 11.
Positive and negative predictive values of index tests (point-of-care SARS-CoV-2 rapid antigen tests) in the symptomatic subgroup
Test name
# of studies
Pooled PPV (95% CI)
I
2
Pooled NPV (95% CI)
I
2
STANDARD Q COVID-19 Ag (SD Biosensor)
4
92.1% (85.9-95.6%)
63.2%
94.7% (89.0-97.5%)
93.8%
PanBio (Abbott)
2
99.5% (96.3-99.9%)
0.0%
95.5% (86.1-98.6%)
96.5%
Roche SARS-CoV-2 Rapid Antigen Test (Roche)
2
98.7% (95.9-99.6%)
0.0%
93.7% (85.0-97.5%)
92.4%
BinaxNOW (Abbott)
1
95.1% (89.7-98.2%)
NA
96.5% (94.6-97.9%)
NA
NA, not applicable; NPV, negative predictive value; PPV, positive predictive value.
Figure 10.
Diagnostic accuracy of COVID-19/SARS-CoV-2 infectionâpositive predictive value and negative predictive value forest plots for symptomatic subgroup. Forest plot shows the positive (A) and negative (B) predictive values (PPV/NPV) and 95% CIs reported for the symptomatic subgroups of the STANDARD Q (SD Biosensor), PanBio (Abbott), Roche SARS-CoV-2 Rapid Antigen Test (Roche), and BinaxNOW (Abbott) index tests after outlier studies were removed. Pooled values and heterogeneity values (I2) for each index test are shown at the bottom of each test section. The pooled values and 95% CI of all reported tests on the forest plot are shown at the bottom. The vertical lines at 0.971 (PPV) and 0.950 (NPV) represent the pooled values for all shown tests. Boxes represent the reported values, and solid horizontal lines represent the 95% CI reported by each study.
Asymptomatic test subgroup
Asymptomatic test performance is relevant in any screening situation. The asymptomatic samples resulted in overall lower sensitivity in the RATs (Table
12
and Figure
11
A), although specificity remained high (Table
12
and Figure
11
B).
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,
166
The PPV was lower in the asymptomatic group compared with the symptomatic and overall groups. However, the NPV remained similar between the 3 groups. Additional information about the PPV and NPV for this subgroup can be found in Table
13
and Figure
12
.
Table 12.
Sensitivity and specificity of index tests (point-of-care SARS-CoV-2 rapid antigen tests) in the asymptomatic subgroup
Test name
# of studies
Sensitivity (95% CI)
I
2
Specificity (95% CI)
I
2
STANDARD Q COVID-19 Ag (SD Biosensor)
5
43.8% (30.4-58.2%)
86.3%
99.6% (99.4-99.7%)
0.0%
PanBio (Abbott)
3
57.7% (29.1-81.9%)
78.5%
100.0% (0.0-100.0%)
0.0%
Roche SARS-CoV-2 Rapid Antigen Test (Roche)
1
58.8% (44.2-72.4%)
NA
100.0% (99.1-100.0%)
NA
BinaxNOW (Abbott)
2
70.8% (62.9-77.7%)
0.0%
99.8% (99.5-99.9%)
72.8%
NA, not applicable.
Figure 11.
Diagnostic accuracy of COVID-19/SARS-CoV-2 infectionâsensitivity and specificity forest plots for asymptomatic subgroup. Forest plot shows the sensitivities (A) and specificities (B) and 95% CIs reported for the asymptomatic subgroup for the STANDARD Q (SD Biosensor), PanBio (Abbott), Roche SARS-CoV-2 Rapid Antigen Test (Roche), and BinaxNOW (Abbott) index tests after outlier studies were removed. Pooled values and heterogeneity value (I2) for each index test are shown at the bottom of each test section. The pooled values and 95% CI of all reported tests on each forest plot are shown at the bottom. The vertical lines at 0.537 (sensitivity) and 0.998 (specificity) represent the pooled values for all shown tests. Boxes represent the reported sensitivity and specificity, and solid horizontal lines represent the 95% CI reported by each study.
Table 13.
Positive and negative predictive values of index tests (point-of-care SARS-CoV-2 rapid antigen tests) in the asymptomatic subgroup
Test name
# of studies
PPV (95% CI)
I
2
NPV (95% CI)
I
2
STANDARD Q COVID-19 Ag (SD Biosensor)
5
80.4% (72.2-86.7%)
36.4%
97.7% (95.1-98.9%)
97.2%
PanBio (Abbott)
3
100.0% (0.0-100.0%)
0.0%
99.1% (93.0-99.9%)
97.4%
Roche SARS-CoV-2 Rapid Antigen Test (Roche)
1
100.0% (88.4-100.0%)
NA
95.2% (92.7-97.0%)
NA
BinaxNOW (Abbott)
2
90.3% (83.3-94.5%)
0.0%
99.1% (97.7-99.7%)
95.0%
NA, not applicable; NPV, negative predictive value; PPV, positive predictive value.
Figure 12.
Diagnostic accuracy of COVID-19/SARS-CoV-2 infectionâpositive predictive value and negative predictive value forest plots for asymptomatic subgroup. Forest plot shows the positive (A) and negative (B) predictive values (PPV/NPV) and 95% CIs reported for the asymptomatic subgroups of the STANDARD Q (SD Biosensor), PanBio (Abbott), Roche SARS-CoV-2 Rapid Antigen Test (Roche), and BinaxNOW (Abbott) index tests after outlier studies were removed. Pooled values and heterogeneity values (I2) for each index test are shown at the bottom of each test section. The pooled values and 95% CI of all reported tests on the forest plot are shown at the bottom. The vertical lines at 0.904 (PPV) and 0.983 (NPV) represent the pooled values for all shown tests. Boxes represent the reported values, and solid horizontal lines represent the 95% CI reported by each study.
Summary of Findings
Based on our meta-analysis, Rocheâs SARS-CoV-2 Rapid Antigen Test and Abbottâs BinaxNOW tests meet the WHOâs recommendation of minimum diagnostic accuracy for symptomatic individuals (⼠80% sensitivity and ⼠97% specificity)
171
and can be reliably used in primary care settings (see the Summary of Findings). Other tests may also meet this standard, but we did not find sufficient studies for other tests. In the Summary of Findings, the effect per 1000 patients tested and certainty of evidence for test accuracy are shown for symptomatic adults using STANDARD Q, PanBio, Roche, and BinaxNOW.
Overall, RATs can identify individuals who have COVID-19 with high reliability when considering overall performance. However, the lower levels of sensitivity suggest that negative tests likely need to be retested through an additional method, such as RT-PCR or repeat testing over several days, when COVID-19 is suspected. Positive tests are highly likely to correctly diagnose SARS-CoV-2 infections, and based on our analyses, we recommend treating those patients as having a COVID-19 diagnosis. These results are likely driven by the symptomatic subject data, as subgroup analysis found higher reliability in symptomatic individuals than in asymptomatic individuals.
Considering only symptomatic individuals, RATs have a higher performance in correctly identifying negative cases, with similar reliability for detecting cases through a positive result. However, a sensitivity of 80% means that 1 in 5 people with a negative RAT have a false-negative result. Thus, negative COVID-19 RAT results in symptomatic patients should be interpreted with caution. As the symptomatic analysis of BinaxNOW included a single study and the same analysis of Rocheâs test had only 2 studies, more studies are needed to confirm these findings.
Discussion
Rapid antigen tests are an important tool in infectious disease control. RATs are less expensive, require less expertise, and are better indicators of infectious virus than the gold standard diagnostic of RT-PCR.
5
RATs have limitations in their performance, including large discrepancies in diagnostic accuracy depending on the situation in which they are used.
Discrepancies across studies and with manufacturer reported results
Of significant concern is the discrepancy between the manufacturerâs listed diagnostic accuracy and the accuracy found in this analysis. Based on the published accuracies on the manufacturersâ websites, the manufacturers overestimate the accuracy of their tests.
172
â
175
Our meta-analysis found the pooled sensitivity of the SD Biosensor STANDARD Q test to be 66.1%, while the manufacturerâs website lists the sensitivity as 85.0%.
175
For the Abbott tests, the pooled sensitivity from our analysis was 71.0% and 54.7% for PanBio and BinaxNOW tests, respectively. The product pages from the Abbott website list the sensitivities as 91.1% for PanBio and 84.6% for BinaxNOW.
172
,
173
Roche specifies that their listed sensitivity is for Ct values < 30 and reports a specificity of 95.5%
174
compared with our overall pooled sensitivity of 68.5%. These discrepancies can increase the errors in medical practice by falsely increasing the confidence providers have in the various RATs. The differences in accuracy between the collected studies, our meta-analysis, and the manufacturerâs reported values are likely driven by the same factors that may have contributed to the high heterogeneity in our results.
Potential sources of heterogeneity
We found high heterogeneity across the studies included in our data extraction and meta-analysis. Potential sources of heterogeneity could include the prevalence of the virus during each studyâs data collection phase, the access to various manufacturersâ RATs, and the skill level at which the sample was taken.
176
,
177
Additionally, the level of infection within each subject will vary greatly depending on their previous immunity, the day post-exposure, or the day post-symptom compared to when the RAT was performed.
Gold standard is RT-PCR but the threshold for a positive result varies by manufacturer and kit. While all reference tests were performed by qualified individuals based on reporting in the studies, the conditions in which the tests were performed are not reflective of ideal conditions. The number of samples that needed processing at a single time, as well as the general increased sense of urgency felt by public health employees, may have resulted in heterogeneity across the reference samples, which would increase heterogeneity across the sensitivity and specificity.
Variants that alter the test epitope can change the accuracy of the RATs. The accuracy of the RATs decreased as the variants mutated further from the Ancestral strain.
178
A recent study of RATs intended for Delta and Omicron variant detection found no differences in sensitivity,
179
while other studies have found a decrease in sensitivity between these 2 variants.
178
However, the tests in our review were developed and intended for use with the Ancestral strain. We examined the time frame and dominant variants of our studies to address this question. Further work is needed to have a better understanding of how changes in SARS-CoV-2 proteins affect RAT sensitivity. As novel variants emerge with distinct proteins (epitopes), the accuracy of the RATs will need to be reassessed.
Clinical significance of symptomatic and asymptomatic testing
The relevance of asymptomatic testing is lower than in symptomatic individuals because asymptomatic individuals are unlikely to present in a primary care setting. The individuals most likely to present in our target setting of primary care are those who are symptomatic. However, asymptomatic testing may continue in some contexts, such as during outbreaks, prior to certain elective procedures, or as part of ongoing surveillance and epidemiological efforts. The lower accuracy in the RATs in the asymptomatic context could lead to additional viral spread because of a false-negative result. Given the reduced accuracy, health care providers should interpret a negative result with caution and follow-up with RT-PCR testing for cases with a high suspicion of infection. The likelihood of a negative result from a RAT to be a true negative is dependent on disease prevalence in the patientâs community. Health care practitioners in areas with high disease prevalence (10%) at the time of testing should assume that a negative result is positive 2.4% of the time. These situations make the overall test performance, and subgroup analyses of symptomatic and asymptomatic individuals, relevant across multiple health care settings.
Other systematic reviews of diagnostic accuracy have also noted similar sensitivity for symptomatic and asymptomatic cohorts.
180
,
181
These studies associated viral load as measured by RT-PCR Ct value with the positivity of the RATs.
180
,
181
The lower the Ct value, the more likely a RAT would detect the presence of viral protein.
180
,
181
Conflicting studies have reported similar and disparate Ct values in asymptomatic compared with symptomatic individuals (reviewed in Puhach
et al
.
5
). Asymptomatic individuals are considered to be major sources of transmission due to behavior changes when an individual develops symptoms.
182
Additional studies are needed to understand the connection between detectable viral protein via RATs, Ct values determined by RT-PCR, and transmission as measured by cell culture assays, because the clear difference in RAT performance between symptomatic and asymptomatic subjects does not align with the comparative Ct values
5
and cell culture positivity
182
previously reported.
Limitations of this review
One limitation of the review was that, due to author language proficiencies, the search strategies were limited to studies published in English. Records not available in English were not included in the review.
Heterogeneity can be studied and addressed in multiple ways, including outlier analysis and removal. The underlying source of heterogeneity is not immediately detectable in the data found within the studies and this could be investigated further. The high heterogeneity was an unexpected result. Revisions of this systematic review and meta-analysis could use a more stringent approach to reduce heterogeneity or better identify its sources through a different data extraction tool. Further, with additional collected data, more nuanced subgroup analyses could be performed.
Tied to symptom presentation, viral load has also been shown to impact RAT accuracy, with higher Ct values (lower viral loads) associated with decreased test accuracy.
180
,
181
Our review did not examine the subgroups of Ct values, which is a limitation of our review. A challenge with subdividing the collected data from the included studies is that the studies that reported values for various Ct values divided their data in different ways. The lack of consistent division makes grouping for meta-analysis challenging. Further, the Ct values across different reference tests may not be comparable. Each kit, primer set, and polymerase used to complete an RT-PCR reference test may vary in their specificity and sensitivity.
183
The Ct values that are reported are dependent on reference test reagent efficiency as well as the sampleâs viral RNA load.
183
Further work needs to be done to be able to accurately compare the Ct values to RAT performance or to viral load.
Sample type also has an impact on test accuracy. The most common sample types were nasopharyngeal swabs. These swabs are uncomfortable for patients and require a trained health care professional for administration, limiting their use in wider settings. Nasal swabs and oropharyngeal swabs were present in about one-third of the studies each, and saliva samples were present in the selected studies. We did not analyze sample type within our meta-analysis due to a low number of studies identifying the sample location used specifically for the RAT compared with the RT-PCR tests. This is a limitation of our review. Other reviews have examined some of these sample types and found that anterior nares (nasal) swabs and nasopharyngeal swabs have similar sensitivities.
181
Saliva samples were noted to be of lower diagnostic accuracy than swabs.
181
Nasal swabs are a popular collection method and are found in many at-home and POC tests. These are easy to collect by anyone and have minimal associated discomfort, making them ideal for primary care settings. A potential future analysis on RAT accuracy could be performed to analyze the impact of nasal swab vs nasopharyngeal sample collection. These data may be more readily available as more studies are published regarding sample collections. The studies included in this analysis were primarily nasopharyngeal and most did not compare accuracy across sample types.
Given our experience with this systematic review and meta-analysis, it is clear that there are more parameters that would provide insight into the use of RATs in primary care settings that were not captured by our data extraction tool. These include potential sources of heterogeneity listed above, such as timing of RAT compared with symptom onset, and variations in sample collection methods.
Conclusions
We found high heterogeneity across studies examining the same RATs, leading to an overall decrease in the quality of evidence presented here. Many tests have only a few studies comparing their performance to RT-PCR. Future diagnostic accuracy studies need to adhere to the STARD guidelines
184
to provide the best evidence to build recommendations on. Studies without diagnostic accuracy numbers (2 Ă 2 tables) were excluded from the meta-analysis, resulting in a limitation to our review. Overall, RATs are excellent at predicting when a positive result means a positive diagnosis of COVID-19. However, these tests have reduced capacity to allow a negative result to rule out COVID-19 as a diagnosis. Misidentifying SARS-CoV-2 infection for other respiratory viral infections can lead to potential viral spread among vulnerable patients and health care workers. Further, it can delay appropriate treatment in cases with high risk of complications. In the primary care setting, false-negative results should be considered for further testing via RT-PCR or repeat RATs over several days
185
when there is high suspicion of COVID-19, such as loss of taste or smell as a presenting symptom. Overall negative likelihood ratio is dependent on local prevalence, and health care practitioners should take into account their current community status when determining the best course of action for a negative RAT result.
Recommendations for practice
Based on our findings, we recommend that Rocheâs SARS-CoV-2 Rapid Antigen Test and Abbottâs BinaxNOW tests be used in primary care settings, with the understanding that negative results need to be confirmed through RT-PCR or repeated testing over several days when COVID-19 is highly suspected. These tests are widely available, relatively inexpensive, and have good reliability.
Recommendations for research
The primary recommendation for research is to adhere to the STARD guidelines when reporting on diagnostic data.
184
If all studies had adhered to these guidelines, that would have allowed significantly more information to be gleaned from the studies selected. The key components of these guidelines that would have greatly improved our meta-analysis are the inclusion of the STARD diagram or the cross-tabulation (also known as a contingency table or a 2 Ă 2 table).
184
We only included studies that reported the TP, FP, TN, and FN values (91/143 studies) in our meta-analysis. We further recommend that any subgroup analysis performed also include these components. Using the STARD guidelines improves generalizability of reported data,
184
whereas failing to adhere to these guidelines limits the usefulness of the published data in developing evidence-based practice recommendations.
As new variants emerge, new testing will be needed using high-quality, rigorous methods in populations of vulnerable subjects. As rapid testing will likely remain the first line diagnostic for primary and secondary care environments, and consecutive testing using RATs or RT-PCR will be used as confirmation of a negative diagnosis, identifying the most sensitive and specific tests will remain critically important.
Author contributions
GM, BH and SS: These authors contributed equally to this work. SR and TH: These authors contributed equally to this work. AD and JK: These authors contributed equally to this work. KD and TE: These authors contributed equally to this work. MDeA and AE, LS: These authors contributed equally to this work.
Acknowledgments
Linsey Bui for assistance with screening steps and Cheryl Vanier for discussions and critique.
Funding
This work was supported by internal research support from Touro University Nevada and the Federal Work-Study program. The funder had no role in the content development.
Supplementary Material
Appendix I: Search strategy
The search strategy identified key terms in the question and searched terms related to COVID-19, rapid antigens, and sensitivity and specificity. The COVID-19 searches for PubMed, Embase, and Scopus were modified versions from CADTH COVID-19 literature searching strings (documented on
https://covid.cadth.ca/literature-searching-tools/cadth-covid-19-search-strings/#covid-19-medline
). The search was initially run on July 11, 2021, and rerun on July 12, 2022. All databases were rerun, with the exception of Qinsight, which was no longer available from Quertle as of April 2022.
MEDLINE (PubMed) Search conducted July 11, 2021 Search reran July 12, 2022 Filters: English language; publication date October 31, 2019 to present
Search number
Query
Results retrieved
#1
(((âantigen sâ[All Fields] OR âantigeneâ[All Fields] OR âantigenesâ[All Fields] OR âantigenicâ[All Fields] OR âantigenicallyâ[All Fields] OR âantigenicitiesâ[All Fields] OR âantigenicityâ[All Fields] OR âantigenizedâ[All Fields] OR âantigensâ[MeSH Terms] OR âantigensâ[All Fields] OR âantigenâ[All Fields]) AND (âbasedâ[All Fields] OR âbasingâ[All Fields]) AND (âRapidâ[All Fields] OR ârapiditiesâ[All Fields] OR ârapidityâ[All Fields] OR ârapidnessâ[All Fields]) AND (âdetectâ[All Fields] OR âdetectabilitiesâ[All Fields] OR âdetectabilityâ[All Fields] OR âdetectableâ[All Fields] OR âdetectablesâ[All Fields] OR âdetectablyâ[All Fields] OR âdetectedâ[All Fields] OR âdetectibleâ[All Fields] OR âdetectingâ[All Fields] OR âdetectionâ[All Fields] OR âdetectionsâ[All Fields] OR âdetectsâ[All Fields]) AND (âresearch designâ[MeSH Terms] OR (âresearchâ[All Fields] AND âdesignâ[All Fields]) OR âresearch designâ[All Fields] OR âtest*â[All Fields])) OR ((âantigensâ[MeSH Terms] OR âantigenâ[Text Word]) AND âtestâ[Title/Abstract]) OR âRADâ[Title/Abstract] OR ârapid antigen detectionâ[Title/Abstract] OR âRapid antigen assayâ[Title/Abstract] OR âRapid antigen detection testâ[Title/Abstract] OR âRADTâ[Title/Abstract] OR âRAgTâ[Title/Abstract] OR âVATâ[All Fields] OR âviral antigen test*â[Title/Abstract] OR ((âantigens/analysisâ[MeSH Terms] OR âantigens/geneticsâ[MeSH Terms] OR âantigens/immunologyâ[MeSH Terms] OR âantigens/isolation and purificationâ[MeSH Terms] OR âantigens/ultrastructureâ[MeSH Terms] OR âantigens/virologyâ[MeSH Terms] OR (âantigensâ[MeSH Terms] OR âantigenâ[Text Word])) AND âtestâ[Title/Abstract]) OR (âRapidâ[All Fields] AND âpoint of careâ[All Fields] AND (âantigen sâ[All Fields] OR âantigeneâ[All Fields] OR âantigenesâ[All Fields] OR âantigenicâ[All Fields] OR âantigenicallyâ[All Fields] OR âantigenicitiesâ[All Fields] OR âantigenicityâ[All Fields] OR âantigenizedâ[All Fields] OR âantigensâ[MeSH Terms] OR âantigensâ[All Fields] OR âantigenâ[All Fields]))) AND 2019/10/31:2021/12/31[Date - Publication]
#2
(((âcoronavirusâ[MeSH Terms:noexp] OR âbetacoronavirusâ[MeSH Terms:noexp] OR âCoronavirus Infectionsâ[MeSH Terms:noexp]) AND (âDisease Outbreaksâ[MeSH Terms:noexp] OR âepidemicsâ[MeSH Terms:noexp] OR âpandemicsâ[MeSH Terms])) OR âCOVID-19 testingâ[MeSH Terms] OR âCOVID-19 drug treatmentâ[Supplementary Concept] OR âCOVID-19 serotherapyâ[Supplementary Concept] OR âCOVID-19 vaccinesâ[MeSH Terms] OR âspike protein sars cov 2â[Supplementary Concept] OR âCOVID-19â[Supplementary Concept] OR âSARS-CoV-2â[MeSH Terms] OR ânCoVâ[Title/Abstract] OR ânCoVâ[Transliterated Title] OR â2019nCoVâ[Title/Abstract] OR â2019nCoVâ[Transliterated Title] OR âcovid19*â[Title/Abstract] OR âcovid19*â[Transliterated Title] OR âCOVIDâ[Title/Abstract] OR âCOVIDâ[Transliterated Title] OR âSARS-CoV-2â[Title/Abstract] OR âSARS-CoV-2â[Transliterated Title] OR âSARSCOV-2â[Title/Abstract] OR âSARSCOV2â[Title/Abstract] OR âSARSCOV2â[Transliterated Title] OR âSevere Acute Respiratory Syndrome Coronavirus 2â[Title/Abstract] OR ((âsevere acute respiratory syndromeâ[Title/Abstract] OR âsevere acute respiratory syndromeâ[Transliterated Title]) AND âcorona virus 2â[Title/Abstract]) OR ânew coronavirusâ[Title/Abstract] OR (ânewâ[Transliterated Title] AND âcoronavirusâ[Transliterated Title]) OR ânovel coronavirusâ[Title/Abstract] OR ânovel coronavirusâ[Transliterated Title] OR ânovel corona virusâ[Title/Abstract] OR (ânovelâ[Transliterated Title] AND âcorona virusâ[Transliterated Title]) OR ânovel CoVâ[Title/Abstract] OR (ânovelâ[Transliterated Title] AND âCoVâ[Transliterated Title]) OR ânovel HCoVâ[Title/Abstract] OR (ânovelâ[Transliterated Title] AND âHCoVâ[Transliterated Title]) OR ((â19â[Title/Abstract] OR â19â[Transliterated Title] OR â2019â[Title/Abstract] OR â2019â[Transliterated Title] OR âWuhanâ[Title/Abstract] OR âWuhanâ[Transliterated Title] OR âHubeiâ[Title/Abstract] OR âHubeiâ[Transliterated Title]) AND (âcoronavirus*â[Title/Abstract] OR âcoronavirus*â[Transliterated Title] OR âcorona virus*â[Title/Abstract] OR âcorona virus*â[Transliterated Title] OR âCoVâ[Title/Abstract] OR âCoVâ[Transliterated Title] OR âHCoVâ[Title/Abstract] OR âHCoVâ[Transliterated Title])) OR ((âcoronavirus*â[Title/Abstract] OR âcoronavirus*â[Transliterated Title] OR âcorona virus*â[Title/Abstract] OR âcorona virus*â[Transliterated Title] OR âbetacoronavirus*â[Title/Abstract]) AND (âoutbreak*â[Title/Abstract] OR âoutbreak*â[Transliterated Title] OR âepidemic*â[Title/Abstract] OR âepidemic*â[Transliterated Title] OR âpandemic*â[Title/Abstract] OR âpandemic*â[Transliterated Title] OR âcrisisâ[Title/Abstract] OR âcrisisâ[Transliterated Title])) OR ((âWuhanâ[Title/Abstract] OR âWuhanâ[Transliterated Title] OR âHubeiâ[Title/Abstract] OR âHubeiâ[Transliterated Title]) AND (âpneumoniaâ[Title/Abstract] OR âpneumoniaâ[Transliterated Title]))) AND 2019/10/31:2021/12/31[Date - Publication]
#3
âpredictive value of testsâ[MeSH Terms] OR âpredictive value of testsâ[All Fields] OR âSensitivity and Specificityâ[MeSH Terms] OR âSensitivity and Specificityâ[All Fields]
#4
#1 AND #2 AND #3
239
Reran search July 12, 2022
373
Qinsight (Quertle) Search conducted July 11, 2021
Search number
Query
Results retrieved
#1
covid
#2
rapid antigen test
#3
sensitivity and specificity
#4
#1 AND #2 AND #3
204
Embase Search conducted on July 11, 2021 Search reran on July 12, 2022 Filters: English language; publication date October 31, 2019 to present
Search number
Query
Results retrieved
#1
((âsars-related coronavirusâ/exp OR âcoronavirinaeâ/exp OR âbetacoronavirusâ/exp OR âcoronavirus infectionâ/exp) AND (âepidemicâ/exp OR âpandemicâ/exp)) OR (âsevere acute respiratory syndrome coronavirus 2â/exp OR âsars coronavirus 2 test kitâ/exp OR âsars-cov-2 OR (clinical isolate wuhan/wiv04/2019)â/exp OR âcoronavirus disease 2019â/exp) OR ((ncov* OR 2019ncov OR 19ncov OR covid19* OR covid OR âsars cov 2â OR âsarscov 2â OR âsars cov2â OR sarscov2 OR severe) AND (acute AND respiratory AND syndrome AND coronavirus AND 2 OR severe) OR (acute AND respiratory AND syndrome AND corona AND virus AND 2)) OR (new OR novel OR â19â OR â2019â OR wuhan OR hubei OR china OR chinese) AND (coronavirus* OR corona) AND (virus* OR betacoronavirus* OR cov OR hcov) OR (coronavirus* OR corona) AND (virus* OR betacoronavirus*) AND (pandemic* OR epidemic* OR outbreak* OR crisis) OR (wuhan OR hubei) NEAR/5 pneumonia
#2
rapid antigen testâ/exp OR ârapid antigen detection testâ/exp OR (rapid AND antigen AND test)
#3
(âpredictive valueâ/exp OR âsensitivity and specificityâ/exp) OR (âpredictive valueâ OR âsensitivity and specificityâ)
#4
#1 AND #2 AND #3
212
Reran search July 12, 2022
410
WHO Covid-19 Database
https://search.bvsalud.org/global-literature-on-novel-coronavirus-2019-ncov/
Search conducted July 11, 2021 Search reran on July 12, 2022
Search number
Query
Results retrieved
#1
tw:(rapid antigen test)
#2
tw:(predictive value)
#3
tw:(sensitivity and specificity)
#4
la:(âenâ)
#5
#1 AND (#2 OR #3) AND #4
627
Reran search July 12, 2022
702
Scopus Search conducted July 11, 2021 Search reran on July 12, 2022 Filters English Language; Publication year greater than 2018
Search number
Query
Results retrieved
#1
( TITLE-ABS-KEY ( {coronavirus} OR {betacoronavirus} OR {coronavirus infections} ) AND TITLE-ABS-KEY ( {disease outbreaks} OR {epidemics} OR {pandemics} ) OR TITLE-ABS-KEY ( ( ncov* ) OR {2019nvoc} OR {19ncov} OR {covid19*} OR
15
OR {sars-cov-2} OR {severe acute respiratory syndrome coronavirus 2} OR {severe Acute Respiratory Syndrome Corona Virus 2} ) OR TITLE-ABS-KEY ( ( new 2/3 coronavirus* ) OR ( new W/3 betacoronavirus* ) OR ( new W/3 cov ) OR ( new W/3 hcov ) OR ( novel W/3 coronavirus* ) ) OR TITLE-ABS-KEY ( ( corona AND virus* W/3 epidemic* ) OR ( corona AND virus* W/3 outbreak* ) OR ( corona AND virus* W/3 crisis ) OR ( betacoronavirus* W/3 pandemic* ) ) OR TITLE-ABS-KEY ( ( corona AND virus* W/3 epidemic* ) OR ( corona AND virus* W/3 outbreak* ) OR ( corona AND virus* W/3 crisis ) OR ( betacoronavirus* W/3 pandemic* ) OR ( betacoronavirus* W/3 epidemic* ) OR ( betacoronavirus* W/3 outbreak* ) OR ( betacoronavirus* W/3 crisis ) ) ) AND PUBYEAR > 2018
#2
( TITLE-ABS-KEY ( {rapid antigen test} OR ârapid antigen test*â ) OR TITLE-ABS-KEY ( ârapidâ AND âantigenâ AND âtestâ ) ) AND PUBYEAR > 2018
#3
( TITLE-ABS-KEY ( {predictive value} OR {sensitivity and specificity} ) AND TITLE-ABS-KEY ( âpredictive valueâ OR âsensitivity and specificityâ ) ) AND PUBYEAR > 2018
#4
#1 AND #2 AND #3
176
Reran search July 12, 2022
462
Appendix II: Data extraction instrument
Field name
Entry type
Data extractor
Free-text
Data validated by
Free-text
Article #
Free-text
Article first author
Free-text
Article title
Free-text
Month, year
Free-text
DOI/PMID/other identifier
Free-text
Country
Free-text
Setting/context
Drop-down
âPrimary care location
âHospital â inpatient
âCOVID-19 testing site/screening location
âUrgent care location
âEmergency dept/room
âPublic area (not a designated screening location)
âCollege/university campus (non-medical)
âLong-term care facility (nursing home, rehab centers)
âNot described/unclear
âHospital â outpatient
âCollege/university campus (medical center/hospital)
Year/time frame for data collection
Free-text
Participant characteristics (age range, gender breakdown, rural/urban, etc)
Free-text
Number of participants
Free-text
Sample type
Drop-down
âNasopharyngeal swabs (NP)
âBlood (Bld)
âBronchoalveolar lavage (BAL)/bronchial sample
âNasal swabs (NS)
âOropharyngeal swabs (OP)
âOther
âSaliva (Sal)
âThroat swabs (TS)
Sample type if other
Free-text
Reference test description
Drop-down
âAbbott RealTime SARS-CoV-2 (Abbott)
âAlinity m SARS-CoV-2 AMP (Abbott)
âAllplex assays (Seegene)
âARGENE SARS-CoV-2 R-Gene (Biomerieux)
âBD Max (Becton-Dickinson)
âBGI 2019-nCoV Real-time Fluorescent RT-PCR kit (BGI Genomics)
âBiofire
âCDC 2019-nCoV Real-Time RT-PCR Diagnostic Panel
âCobas Kits/Systems (Roche)
âCOVID-19 Multiplex RT-PCR kit (DIANA Biotech)
âCOVID-19 Real-time PCR kit (HBRT-COVID-19) (Chaozhou Hybribio Biochemistry Ltd., China)
âCovidsure Multiplex RT-PCR kit (Trivitron Healthcare Labsystems Diagnostics)
âCRSP SARS-CoV-2 (Clinical Research Sequencing Platform, Harvard/MIT)
âCustom/In-house SARS-2 primers
âDAAN Gene RT-PCR COVID-19 (DaAnGene)
âFTD SARS-CoV-2 Assay (Fast Track Diagnostics, Luxembourg)
âGENECUBE (Toyobo Co., Ltd.)
âGeneFinder COVID-19 Plus RealAmp Kit (Osang Healthcare Co., Ltd)
âGenesig Real-time PCR Coronavirus assay/Z-Path-COVID-19-CE (Primerdesign)
âGenomeCoV19 Detection kit (ABM)
âIDT SARS-CoV-2 (2019-nCoV) multiplex CDC qPCR probe Assay (Integrated DNA Technologies)
âJapanese National Institute of Infectious Diseases (NIID)
âLabTurbo AIO COVID-19 RNA Testing Kit
âLightMix SarbecoV (TIB Microbiol)
âLuna Universal Probe One-Step RT-PCR for Detection of COVID-19 (SignaGen Labs)
âMeril COVID-19 One-Step RT-PCR Kit
âMutaPLEX Coronavirus Real-time-RT-PCR kit (Immundiagnostik AG)
âNeuMoDx SARS-CoV-2 Assay (Qiagen)
âNovel Coronavirus (2019-nCoV) Real Time Multiplex RT-PCR kit (Liferiver)
âPanther Fusion or Aptima SARS-CoV-2 assay (Hologic)
âPCR Biosystems
âPerkinElmer SARS-CoV-2 Real-time RT-PCR Assay
âReal-Q 2019-nCoV Detection Kit (Biosewoom)
âREALQUALITY RQ-SARS-CoV-2 kit (AB Analitica)
âRealStar SARS-CoV-2 RT-PCR kit (Altona)
âRIDAGENE SARS-CoV-2 (R-Bio-pharm)
âSansure Biotech COVID-19 Nucleic Acid Test kit
âShimadzu Ampdirect 2019 novel coronavirus detection kit
âSimplexa (DiaSorin)
âSpecific Test Not Described
âStandard M nCoV Real-Time Detection Kit (SD Biosenor)
âTakara Bio SARS-CoV-2 direct detection RT-qPCR kit
âTaqPath COVID-19 Combo kit (Applied Biosystems/ThermoFisher)
âVIASURE (CerTest)
âVitassay (Vitassay)
âXpert Xpress SARS-CoV-2/GeneXpert (Cepheid)
Reference test if other
Free-text
Reference test comments (if any)
Free-text
Index test description
Drop-down
âSTANDARD Q COVID-19 Ag Test
âPanBio COVID-19 Ag Rapid Test Device
âSARS-CoV-2 Rapid Antigen Test
âBinaxNOW COVID-19 Antigen
âRapid Test Ag 2019-nCov
âSARS-CoV-2 Ag
âCustom/Novel/In-house
âCOVISTIX (COVIDMARK) Covid 19 Antigen Rapid Test Device
âAMP Rapid Test SARS-CoV-2 Ag
âBD Veritor COVID-19 Rapid Antigen Test
âCerTest SARS-CoV-2
âEspline SARS-CoV-2
âSARS-CoV-2 Antigen Rapid Test
âHUMASIS COVID-19 Ag Test
âMologic Covid-19 Rapid Antigen Test
âBIOCREDIT COVID-19 Ag
âRida Quick SARS-CoV-2 Antigen Test
âSTANDARD F COVID-19 Ag FIA
âRapidTesta SARS-CoV-2
âFluorecare SARS-CoV-2 Spike Protein Test kit (Colloidal Gold)
âCLINITEST Rapid COVID-19 Antigen Test
âImmupass VivaDiag
âCOVID-VIRO COVID-19 Ag Rapid Test
âFlowflex COVID-19 Antigen test
âCOVID-19 Antigen Rapid Test
âAlltest COVID-19 ART Antigen Rapid Test
âCOVID-19 Antigen Rapid Test
âCOVID-19 RAT kit
âNowCheck COVID-19 Ag test
âNovel Corona Virus (SARS-CoV-2) Ag Rapid Test kit
âCovid-19 AG BSS
âHelix i-SARS-CoV-2 Ag Rapid Test
âCOVID-19 Ag K-SeT
âLiaison SARS-CoV-2 Ag
âCOVID-19 Antigen Detection
âCOVID-19 Ag ECO Teste
âInflammacheck CoronaCheck
âGenBody COVAG025
âGENEDIA W COVID-19 Ag Test
âRapid COVID-19 Antigen Test
âInnova SARS-CoV-2 Antigen Rapid test
âAccucare PathoCatch Covid-19 Ag Detection Kit
âOrient Gene Rapid Covid-19 (Antigen) Self-Test
âGeneFinder COVID-19 Ag Plus Rapid Test
âGreen Spring SARS-CoV-2 Antigen Rapid Test Kit (Colloidal Gold)
âSevere Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Antigen Detection Kit (Colloidal Gold-Based)
â2019-nCoV Antigen Test
Index test if other
Free-text
Index test comments (if any)
Free-text
Subgroups (if any; include overall)
Free-text
True positive (TP)
Free-text
False positive (FP)
Free-text
True negative (TN)
Free-text
False negative (FN)
Free-text
Sensitivity (TP/[TP+FN])
Free-text
Sensitivity 95% CI (low, high)
Free-text
Specificity (TN/[TN+FP])
Free-text
Specificity 95% CI (low, high)
Free-text
Positive predictive value PPV (TP/[TP+FP])
Free-text
Negative predictive values NPV (TN/[FN+TN])
Free-text
Description of main results (include adverse events from tests)
Free-text
Exclusion reasons (if any)
Free-text
Notes
Free-text
Need to contact authors? Put contact info here
Free-text
Appendix III: Characteristics of included studies
Author, year
Article title
Index test description
Sensitivity (TP/[TP+FN])
Sensitivity 95% CI (low, high)
Specificity (TN/[TN+FP])
Specificity 95% CI (low, high)
Abdelrazik,
et al.
31
Mar 2021
Potential use of antigen-based rapid test for SARS-CoV-2 in respiratory specimens in low-resource settings in Egypt for symptomatic patients and high-risk contacts
RapiGen (BioCredit)
43.1
Abusrewil,
et al.
32
Dec 2021
Time scale performance of rapid antigen testing for SARS-CoV-2: evaluation of ten rapid antigen assays
PanBio (Abbott)
76.92
46.19, 94.96
100
Flowflex COVID-19 Antigen test (ACON Labs)
100
78.20, 100
100
AMP Rapid Test SARS-CoV-2 Ag (AMP Diagnostics)
85.71
42.13, 99.64
100
COVID-19 Antigen Rapid Test (Assut Europe)
71.43
29.04, 96.33
100
Novel Corona Virus (SARS-CoV-2) Ag Rapid Test kit (Bioperfectus)
80
44.39, 94.78
100
CerTest SARS-CoV-2 (Certest Biotech)
62.5
24.49, 91.48
100
Espline SARS-CoV-2 (Fujirebio)
80
44.39, 97.48
100
Fluorecare (Colloidal Gold/Fluorescent) SARS-CoV-2 Spike Protein Test kit (Shenzen Microprofit)
91.67
61.52, 99.79
100
Orient Gene Rapid Covid-19 (Antigen) Self-Test (Orient Gene)
50
18.71, 81.29
100
RapiGen (BioCredit)
62.5
35.4, 84.80
100
Afzal,
et al.
33
Sep 2021
Diagnostic accuracy of PANBIO COVID-19 rapid antigen method for screening in emergency cases
PanBio (Abbott)
90.47
Â
100
Akashi,
et al.
34
Feb 2022
A prospective clinical evaluation of the diagnostic accuracy of the SARS-CoV-2 rapid antigen test using anterior nasal samples
Roche SARS-CoV-2 Rapid Antigen Test (Roche)
72.7
63.4, 80.8
100
99.5, 100
Al-Alawi,
et al.
35
Jan 2021
Evaluation of four rapid antigen tests for detection of SARS-CoV-2 virus
STANDARD Q COVID-19 Ag (SD Biosensor)
65.8
48.65, 80.37
100
87.66, 100
PCL COVID19 Ag Rapid FIA Antigen Test (PCL)
69.8
55.66, 81.66
94.1
80.32, 99.28
RapiGen (BioCredit)
64
49.19, 77.08
100
86.28, 100
Sofia SARS Rapid Antigen FIA/Sofia 2 (Quidel)
64.3
50.36, 76.64
100
84.56, 100
Aleem,
et al.
36
Jan 2022
Diagnostic accuracy of STANDARD Q COVID-19 antigen detection kit in comparison with RT-PCR assay using nasopharyngeal samples in India
STANDARD Q COVID-19 Ag (SD Biosensor)
54.43
42.83, 65.69
99.24
97.79, 99.84
Alghounaim,
et al.
37
Dec 2021
The performance of two rapid antigen tests during population-level screening for SARS-CoV-2 infection
Liaison
43.3
30.6, 56.8
99.9
99.3, 100
STANDARD Q COVID-19 Ag (SD Biosensor)
30.6
19.6, 43.7
98.8
97.8, 99.4
Allan-Blitz,
et al.
38
Sep 2021
A real-world comparison of SARS-CoV-2 rapid antigen testing versus PCR testing in Florida
BinaxNOW (Abbott) - all sample types PCR
49.2
47.4, 50.9
98.8
98.6, 98.9
BinaxNOW (Abbott) - Anterior Nares PCR
47.5
39.1, 56.1
100
99.3, 100
BinaxNOW (Abbott) - Nasopharyngeal Fluid PCR
46.1
37.3, 55.1
99.7
98.9, 100
BinaxNOW (Abbott) - Oral Fluid PCR
49.37
47.5, 51.2
98.7
98.5, 98.8
Amer,
et al.
39
Oct 2021
Diagnostic performance of rapid antigen test for COVID-19 and the effect of viral load, sampling time, subject's clinical and laboratory parameters on test accuracy (preprint)
STANDARD Q COVID-19 Ag (SD Biosensor)
78.2
67, 86
64.2
38, 83
Anastasiou,
et al.
40
Apr 2021
Fast detection of SARS-CoV-2 RNA directly from respiratory samples using a loop-mediated isothermal amplification (LAMP) test
Custom/Novel/In-house
68.8
57.3, 78.4
100
90.6, 100
Avgoulea,
et al.
41
Apr 2022
Field evaluation of the new rapid NG-Test(ÂŽ) SARS-CoV-2 Ag for diagnosis of COVID-19 in the emergency department of an academic referral hospital
Custom/Novel/In-house - NP sample
81
73, 87
99
95, 100
Custom/Novel/In-house - OP sample
51
42, 59
100
96, 100
Babu,
et al.
42
Jul 2021
The burden of active infection and anti-SARS-CoV-2 IgG antibodies in the general population: Results from a statewide sentinel-based population survey in Karnataka, India
STANDARD Q COVID-19 Ag (SD Biosensor)
Not reported
Bachman,
et al.
43
Aug 2021
Clinical validation of an open-access SARS-CoV-2 antigen detection lateral flow assay, compared to commercially available assays
Custom/Novel/In-house - PCR collected by NP
69
60, 78
97
88, 100
BinaxNOW (Abbott) - PCR collected by NP
82
73, 88
100
94, 100
Sofia SARS Rapid Antigen FIA/Sofia 2 (Quidel) - PCR collected by NP
74
64, 82
98
91, 100
Custom/Novel/In-house - PCR collected by NS
83
74, 90
97
91, 100
BinaxNOW (Abbott) - PCR collected by NS
91
84, 96
94
85, 98
Sofia SARS Rapid Antigen FIA/Sofia 2 (Quidel) - PCR collected by NS
86
77, 92
96
89, 99
Basso,
et al.
44
Feb 2021
Salivary SARS-CoV-2 antigen rapid detection: a prospective cohort study
Espline SARS-CoV-2 (Fujirebio)
48
Â
100
Blairon,
et al.
45
Aug 2020
Implementation of rapid SARS-CoV-2 antigenic testing in a laboratory without access to molecular methods: experiences of a general hospital
Respi-Strip (Coris BioConcept)
30
16.7, 47.9
100
Bond,
et al.
46
May 2022
Utility of SARS-CoV-2 rapid antigen testing for patient triage in the emergency department: a clinical implementation study in Melbourne, Australia
PanBio (Abbott)
75.5
69.9, 80.4
100
99.8, 100
Borro,
et al.
47
Apr 2022
SARS-CoV-2 transmission control measures in the emergency department: the role of rapid antigenic testing in asymptomatic subjects
Green Spring "SARS-CoV-2 Antigen Rapid Test Kit (Colloidal Gold)" - standard protocol
79.8
Â
100
Green Spring "SARS-CoV-2 Antigen Rapid Test Kit (Colloidal Gold)" - UTM modified protocol
70.7
Â
100
Green Spring "SARS-CoV-2 Antigen Rapid Test Kit (Colloidal Gold)" - UTM modified protocol
43.9
Â
100
Boum,
et al.
48
May 2021
Performance and operational feasibility of antigen and antibody rapid diagnostic tests for COVID-19 in symptomatic and asymptomatic patients in Cameroon: a clinical, prospective, diagnostic accuracy study
STANDARD Q COVID-19 Ag (SD Biosensor)
58.4
53.0, 64.8
93.2
88.0, 97.0
Bulilete,
et al.
49
Feb 2021
Panbio⢠rapid antigen test for SARS-CoV-2 has acceptable accuracy in symptomatic patients in primary health care
PanBio (Abbott)
71.4
63.1, 78.7
99.8
99.4, 99.9
Burdino,
et al.
50
Oct 2021
SARS-CoV-2 microfluidic antigen point-of-care testing in emergency room patients during COVID-19 pandemic
SARS-CoV-2 Ag (LumiraDx)
90.1
86.2, 93.1
99.4
98.6, 99.8
Bwogi,
et al.
7
May 2022
Field evaluation of the performance of seven antigen rapid diagnostic tests for the diagnosis of SARs-CoV-2 virus infection in Uganda
Immupass VivaDiag (VivaChek Biotech)
30.2
18.0, 46.1
94.1
90.1, 96.6
MEDsan SARS-CoV-2 Antigne Rapid Test
13
8.1, 20.3
100
96.9, 100
Novegent COVID-19 Antigen Rapid Test Kit (Colloidal gold)
46
36.3, 56.0
89.9
83.3, 94.1
PanBio (Abbott)
49.4
38.7, 60.1
100
96.4, 100
PCL COVID19 Ag Rapid FIA Antigen Test (PCL)
37.6
28.2, 48.1
89.9
80.8, 94.9
RapiGen (BioCredit)
27.4
20.5, 35.6
98.2
93.1, 99.6
Respi-Strip (Coris BioConcept)
19.4
11.5, 30.9
99.2
94.5, 99.9
Caruana,
et al.
51
Apr 2021
Implementing SARS-CoV-2 rapid antigen testing in the emergency ward of a Swiss university hospital: the INCREASE Study
PanBio (Abbott)
41.2
Â
99.5
BD Veritor COVID-19 Rapid Antigen Test (Becton-Dickinson)
41.2
Â
99.7
Exdia (Precision Biosensor)
48.3
Â
99.5
STANDARD Q COVID-19 Ag (SD Biosensor)
41.2
Â
99.7
Caruana,
et al.
52
May 2021
The dark side of SARS-CoV-2 rapid antigen testing: screening asymptomatic patients
STANDARD Q COVID-19 Ag (SD Biosensor)
28.6
Â
98.2
Cassuto,
et al.
53
Jul 2021
Evaluation of a SARS-CoV-2 antigen-detecting rapid diagnostic test as a self-test: diagnostic performance and usability
COVIDâVIRO nasal swab test
96.88
83.78, 99.92
100
98.19, 100.00
Cattelan,
et al.
8
Mar 2022
Rapid antigen test LumiraDx(TM) vs real time polymerase chain reaction for the diagnosis of SARS-CoV-2 infection: a retrospective cohort study
SARS-CoV-2 Ag (LumiraDx)
76.3
70.8, 81.8
94.4
88.3, 100
Cento,
et al.
54
May 2021
Frontline screening for SARS-CoV-2 infection at emergency department admission by third generation rapid antigen test: can we spare RT-qPCR?
SARS-CoV-2 Ag (LumiraDx)
85.6
82, 89
97.05
96, 98
Cerutti,
et al.
55
Nov 2020
Urgent need of rapid tests for SARS CoV-2 antigen detection: evaluation of the SD-Biosensor antigen test for SARS-CoV-2
STANDARD Q COVID-19 Ag (SD Biosensor)
70.6
Â
100
Chaimayo,
et al.
56
Nov 2020
Rapid SARS-CoV-2 antigen detection assay in comparison with real-time RT-PCR assay for laboratory diagnosis of COVID-19 in Thailand
STANDARD Q COVID-19 Ag (SD Biosensor)
98.33
91.06, 99.6
98.73
97.06, 99.59
Cheng,
et al.
57
May 2022
Evaluation of a rapid antigen test for the diagnosis of SARS-CoV-2 during the COVID-19 pandemic
Enimmune Speedy COVID-19 AG Rapid Test - Heping
69.1
68.8, 69.5
99.1
99.1, 99.1
PanBio (Abbott) - RenAi
62
61.6, 62.3
99.9
99.9, 99.9
VTRUST COVID-19 Antigen Rapid Test (Taidoc Technology Corporation) - YangMing
78.6
78.2, 78.9
98.2
98.2, 98.3
VTRUST COVID-19 Antigen Rapid Test (Taidoc Technology Corporation) - Zhongxiao
60.5
60.1, 60.8
99.1
99.0, 99.1
Enimmune Speedy COVID-19 AG Rapid Test - Zhongxing
64.6
64.3, 64.8
98.3
98.3, 98.3
Choudhary,
et al.
58
Apr 2022
Validation of rapid SARS-CoV-2 antigen detection test as a screening tool for detection of Covid-19 infection at district hospital in northern India
Standard Q COVID-19 Ag (SD Biosensor)
55.04
46.43, 63.35
99.2
98.15, 99.66
Cottone,
et al.
59
May 2022
Pitfalls of SARS-CoV-2 antigen testing at emergency department
Roche SARS-CoV-2 Rapid Antigen Test (Roche)
45.5
35.6, 55.8
98.1
96.1, 99.2
Cubas-Atienzar,
et al.
60
May 2021
Accuracy of the Mologic COVID-19 rapid antigen test: a prospective multi-centre analytical and clinical evaluation
Mologic Covid-19 Rapid Antigen Test (Mologic Ltd. United Kingdom) - Northumberland
86
76.9, 92.6
97.5
93.8, 99.3
Mologic Covid-19 Rapid Antigen Test (Mologic Ltd. United Kingdom) - Yorkshire
84.6
54.6, 98.1
100
91.2, 100
Dierks,
et al.
61
May 2021
Diagnosing SARS-CoV-2 with antigen testing, transcription-mediated amplification and real-time PCR
SARS-CoV-2 Ag (LumiraDx)
45.45
20.22, 73.26
99.54
98.17, 99.88
NADAL COVID-19 Antigen Rapid Test (New Art Laboratories/nal von minden)
14.29
1.94, 58.35
76.44
70.16, 81.74
Escribano,
et al.
62
Feb 2022
Different performance of three point-of-care SARS-CoV-2 antigen detection devices in symptomatic patients and close asymptomatic contacts: a real-life study
PanBio (Abbott) - Close Asymptomatic Contacts
33.3
11.8, 61.6
Â
SGTI-Flex - Close Asymptomatic Contacts
84.6
54.5, 98.1
Â
NovaGen - Close Asymptomatic Contacts
55.5
30.7, 78.4
Â
PanBio (Abbott)-COVID-19 Suspected Cases
71.1
55.6, 83.6
Â
SGTI-Flex - COVID-19 Suspected Cases
68.8
55.7, 80
Â
NovaGen - COVID-19 Suspected Cases
84.6
72.0, 93.1
Â
EscrivĂĄ,
et al.
63
Aug 2021
The effectiveness of rapid antigen test-based for SARS-CoV-2 detection in nursing homes in Valencia, Spain
PanBio (Abbott)
85
90, 99
100
100, 100
FaĂco-Filho,
et al.
64
Mar 2022
Evaluation of the Panbio⢠COVID-19 Ag rapid test at an emergency room in a hospital in São Paulo, Brazil
PanBio (Abbott)
Not reported
Â
Â
Farfour,
et al.
65
Mar 2021
The Panbio COVID-19 Ag rapid test: which performances are for COVID-19 diagnosis?
PanBio (Abbott)
Not reported
Â
Â
Fernandez-Montero,
et al.
66
Jul 2021
Validation of a rapid antigen test as a screening tool for SARS-CoV-2 infection in asymptomatic populations. Sensitivity, specificity and predictive values
Roche SARS-CoV-2 Rapid Antigen Test (Roche)
71.43
56.74, 83.42
99.68
99.37, 99.86
FertĂŠ,
et al.
67
Jun 2021
Accuracy of COVID-19 rapid antigenic tests compared to RT-PCR in a student population: the StudyCov study
PanBio (Abbott)
63.5
49.0, 76.4
100
99.4, 100
Fitoussi,
et al.
68
Oct 2021
Analytical performance of the point-of-care BIOSYNEX COVID-19 Ag BSS for the detection of SARSâCoVâ2 nucleocapsid protein in nasopharyngeal swabs: a prospective field evaluation during the COVID-19 third wave in France
BIOSYNEX Ag-RDT
81.80
79.2, 84.1
99.60
98.9, 99.8
Ford,
et al.
69
Sep 2021
Antigen test performance among children and adults at a SARS-CoV-2 community testing site
BinaxNOW (Abbott) - Exposed
79.80
Â
99.70
BinaxNOW (Abbott)
80.80
Â
99.90
Freire,
et al.
11
Jun 2022
Performance differences among commercially available antigen rapid tests for COVID-19 in Brazil
PanBio (Abbott) - NP Swab
60.00
45.9, 73.0
100
69.2, 100
PanBio (Abbott) - NS Swab
58.20
44.1, 71.4
100
69.2, 100%
COVID-19 Ag ECO Teste (Eco Diagnostica)
42.90
30.5, 56.0
83.30
58.6, 96.4
STANDARD Q COVID-19 Ag (SD Biosensor)
53.00
40.3, 65.4
86.70
59.5, 98.3
CORIS Bioconcept1 Ag-RDT (Nanosens)
9.80
3.7, 20.2
100
78.2, 100
CELLER WONDFO SARSCOV2 Ag-RDT
47.20
33.3, 61.4
100
69.2, 100
NowCheck COVID-19 Ag test (Bionote)
60
45.9, 73.0
100
66.4, 100
Ag-RDT COVID-19 (Acro Biotech)
81.10
68.0, 90.6
84.60
54.5, 98.1
Galliez,
et al.
70
Jun 2022
Evaluation of the Panbio COVID-19 antigen rapid diagnostic test in subjects infected with omicron using different specimens
PanBio (Abbott) - NS Swab
89
82.4, 93.3
100
94.4, 100
PanBio (Abbott) - Oral Specimen
12.6
7.9, 19.5
100
94.4, 100
Garcia-Cardenas,
et al.
71
Sep 2021
Analytical performances of the COVISTIX and Panbio antigen rapid tests for SARS-CoV-2 detection in an unselected population (all comers)
PanBio (Abbott)
62%
58, 64
99
99, 100
COVISTIX Covid 19 Antigen Rapid Test Device
81
76, 85
96
94, 98
Garcia-Cardenas,
et al.
72
May 2022
Analytical performances of the COVISTIX⢠antigen rapid test for SARS-CoV-2 detection in an unselected population (all-comers)
COVISTIX Covid 19 Antigen Rapid Test Device
81
75.0, 85.0
96
94.0, 98.0
COVISTIX Covid 19 Antigen Rapid Test Device
93
88, 98
98
97, 99
GarcĂa-FernĂĄndez,
et al.
73
Mar 2022
Evaluation of the rapid antigen detection test STANDARD F COVID-19 Ag FIA for diagnosing SARS-CoV-2: experience from an emergency department
STANDARD F COVID-19 Ag FIA (SD Biosensor Inc.)
84
76.1, 89.7
99.6
98.5, 99.9
GarcĂa-FiĂąana,
et al.
74
Jul 2021
Performance of the Innova SARS-CoV-2 antigen rapid lateral flow test in the Liverpool asymptomatic testing pilot: population based cohort study
Innova (recalled 06/2021)
40
28.5, 52.4
99.9
99.8, 99.99
Goga,
et al.
75
Mar 2022
Utility of COVID-19 point-of-care antigen tests in low-middle income settings
RapiGen (BioCredit)
34.8
26.1, 44.2
97.6
93.9, 99.3
STANDARD Q COVID-19 Ag (SD Biosensor)
49.1
43.3, 55.0
95.7
93.5, 97.3
SARS-CoV-2 Ag (LumiraDx)
63.8
55.9, 71.2
97
95.5, 98.3
GonzĂĄlez-Fiallo,
et al.
76
Apr 2022
Evaluation of SARS-CoV-2 rapid antigen tests in use on the Isle of Youth, Cuba
STANDARD Q COVID-19 Ag (SD Biosensor)
75.30%
66.0, 84.6
96.10
94.5, 97.6
Gupta,
et al.
77
Feb 2021
Rapid chromatographic immunoassay-based evaluation of COVID-19: a cross-sectional, diagnostic test accuracy study & its implications for COVID-19 management in India
STANDARD Q COVID-19 Ag (SD Biosensor)
81.8
71.3, 89.6
99.6
97.8, 99.9
Harris,
et al.
78
May 2021
SARS-CoV-2 rapid antigen testing of symptomatic and asymptomatic individuals on the University of Arizona campus
Sofia SARS Rapid Antigen FIA/Sofia 2 (Quidel)
91.4
Â
100
Holzner,
et al.
79
Apr 2021
SARS-CoV-2 rapid antigen test: fast-safe or dangerous? An analysis in the emergency department of an university hospital
STANDARD Q COVID-19 Ag (SD Biosensor)
68.8
66.84, 70.73
99.56
99.3, 99.82
Homza,
et al.
80
Apr 2021
Five antigen tests for SARS-CoV-2: virus viability matters
Ecotest (Assure Tech)
75.7
66.5, 83.5
96.7
93.3, 98.7
Immupass VivaDiag (VivaChek Biotech)
41.8
31.5, 52.6
96
92.0, 98.4
ND Covid (NDFOS)
70.1
58.6, 80
56.1
46.5, 65.4
SARS-CoV-2 Antigen Rapid Test (JoysBio)
57.8
46.9, 68.1
98.5
94.8, 99.8
STANDARD Q COVID-19 Ag (SD Biosensor)
61.9
45.6, 76.4
99
94.4, 100
HĂśrber,
et al.
81
Jun 2022
Evaluation of a laboratory-based high-throughput SARS-CoV-2 antigen assay
CoV2Ag assay (Siemens Healthineers, Eschborn, Germany)
88.50
83.7, 91.9
99.50
97.4, 99.9
Ifko,
et al.
82
Jul 2021
Diagnostic validation of two SARS-CoV-2 immunochromatographic tests in Slovenian and Croatian hospitals
NADAL COVID-19 Antigen Rapid Test (New Art Laboratories/nal von minden)
84.61
54.55, 98.08
100
90.75, 100
NADAL COVID-19 Antigen Rapid Test (New Art Laboratories/nal von minden)
86.96
66.41, 97.23
88.24
80.35, 93.77
Igloi,
et al.
83
May 2021
Clinical evaluation of Roche SD Biosensor rapid antigen test for SARS-CoV-2 in municipal health service testing site, the Netherlands
STANDARD Q COVID-19 Ag (SD Biosensor)
84.9
79.1, 89.4
99.5
98.7, 99.8
Jakobsen,
et al.
84
Jun 2021
Accuracy and cost description of rapid antigen test compared with reverse transcriptase-polymerase chain reaction for SARS-CoV-2 detection
STANDARD Q COVID-19 Ag (SD Biosensor)
69.7
Â
99.5
Jakobsen,
et al.
85
Feb 2022
Accuracy of anterior nasal swab rapid antigen tests compared with RT-PCR for massive SARS-CoV-2 screening in low prevalence population
STANDARD Q COVID-19 Ag (SD Biosensor)
48.5
Â
100
Jeewandara,
et al.
86
Mar 2022
Sensitivity and specificity of two WHO approved SARS-CoV2 antigen assays in detecting patients with SARS-CoV2 infection
STANDARD Q COVID-19 Ag (SD Biosensor)
36.24
33.1, 39.5
97.6
97, 98
PanBio (Abbott)
52.6
46.7, 58.5
99.6
99.2, 99.8
Jegerlehner,
et al.
87
Jul 2021
Diagnostic accuracy of a SARS-CoV-2 rapid antigen test in real-life clinical settings
STANDARD Q COVID-19 Ag (SD Biosensor)
65.3
56.8, 73.1
99.9
99.5, 100
PCL COVID19 Ag Rapid FIA Antigen Test (PCL)
30.2
18.3, 44.3
98.1
96.0, 99.3
Jegerlehner,
et al.
88
Jun 2022
Diagnostic accuracy of SARS-CoV-2 saliva antigen testing in a real-life clinical setting
PCL COVID19 Ag Rapid FIA Antigen Test (PCL)
30.2
18.3, 44.3
98.1
96.0, 99.3
Jirungda,
et al.
89
May 2022
Clinical performance of the STANDARD F COVID-19 AG FIA for the detection of SARS-COV-2 infection
STANDARD F COVID-19 Ag FIA (SD Biosensor Inc.)
98.8
Â
89.7
Kahn,
et al.
90
Aug 2021
Performance of antigen testing for diagnosis of COVID-19: a direct comparison of a lateral flow device to nucleic acid amplification based tests
STANDARD F COVID-19 Ag FIA (SD Biosensor Inc.)
59.4
Â
99
Kessler,
et al.
91
Mar 2022
Identification of contagious SARS-CoV-2 infected individuals by Roche's Rapid Antigen Test
Roche SARS-CoV-2 Rapid Antigen Test (Roche)- Central Lab
Â
Â
Â
Kim,
et al.
92
Apr 2021
Development and clinical evaluation of an immunochromatography-based rapid antigen test (GenBody⢠COVAG025) for COVID-19 diagnosis
GenBody COVAG025 (GenBody)
Not reported
Â
Â
GenBody COVAG025 (GenBody) - Prospective
94
87.4, 97.77
100
96.38, 100
GenBody COVAG025 (GenBody) - Retrospective
90
73.47, 97.89
98
92.96, 99.76
King,
et al.
93
Sep 2021
Validation of the Panbio⢠COVID-19 Antigen Rapid Test (Abbott) to screen for SARS-CoV-2 infection in Sint Maarten: a diagnostic accuracy study
PanBio (Abbott)
84
76.2, 90.1
99.9
99.6, 100
Kiyasu,
et al.
94
Jul 2021
Prospective analytical performance evaluation of the QuickNaviâ˘-COVID19 Ag for asymptomatic individuals
QuickNavi-COVID19 Ag
80.3
73.9, 85.7
100
99.7, 100
Klajmon,
et al.
95
Dec 2021
Comparison of antigen tests and qPCR in rapid diagnostics of infections caused by SARS-CoV-2 virus
Humasis COVID-19 Ag Test kit (Humasis Co., Ltd.)
91.49
79.62, 97.63
97.9
93.99, 99.57
Klein,
et al.
96
May 2021
Head-to-head performance comparison of self-collected nasal versus professional-collected nasopharyngeal swab for a WHO-listed SARS-CoV-2 antigen-detecting rapid diagnostic test
PanBio (Abbott) - NMT
84.4
71.2, 92.3
99.2
97.1, 99.8
PanBio (Abbott) - NP Swab
88.9
76.5, 95.5
99.2
97.1, 99.8
Kohmer,
et al.
97
Jan 2021
The comparative clinical performance of four SARS-CoV-2 rapid antigen tests and their correlation to infectivity in vitro
SARS-CoV-2 Ag (LumiraDx)
50
38.1, 61.9
100
86.8, 100
NADAL COVID-19 Antigen Rapid Test (New Art Laboratories/nal von minden)
24.3
15.1, 35.7
100
86.8, 100
Rida Quick SARS-CoV-2 (R-Biopharm)
39.2
28, 51.2
96.2
80.4, 99.9
Roche SARS-CoV-2 Rapid Antigen Test (Roche)
43.2
37.8, 55.3
100
86.8, 100
Korenkov,
et al.
98
Aug 2021
Evaluation of a rapid antigen test to detect SARS-CoV-2 infection and identify potentially infectious individuals
STANDARD Q COVID-19 Ag (SD Biosensor)
100
88.3, 100
71.91
61.82, 80.20
Korenkov,
et al.
99
May 2021
Assessment of SARS-CoV-2 infectivity by a rapid antigen detection test
STANDARD Q COVID-19 Ag (SD Biosensor)
42.86
Â
Â
99.89
KrĂźger,
et al.
100
Aug 2021
Evaluation of accuracy, exclusivity, limit-of-detection and ease-of-use of LumiraDxâ˘: an antigen-detecting point-of-care device for SARS-CoV-2
SARS-CoV-2 Ag (LumiraDx) - Berlin
80.2
70.3, 87.5
99.5
97.1, 100
SARS-CoV-2 Ag (LumiraDx) - Heidelberg
84.6
7.9, 91.4
99.3
97.9, 99.7
SARS-CoV-2 Ag (LumiraDx)
82.2
75.2, 87.5
99.3
97.9, 99.7
KrĂźger,
et al.
101
Dec 2021
Accuracy and ease-of-use of seven point-of-care SARS-CoV-2 antigen-detecting tests: A multi-centre clinical evaluation
Fluorecare (Colloidal Gold/Fluorescent) SARS-CoV-2 Spike Protein Test kit (Shenzen Microprofit) - Germany
66.7
41.7, 84.8
93.1
91.0, 94.8
RapiGen (BioCredit) - Brazil
74.4
65.8, 81.4
98.9
97.2, 99.6
STANDARD F COVID-19 Ag FIA (SD Biosensor Inc.) - Brazil
77.5
69.2, 84.1
97.9
95.7, 99
NowCheck COVID-19 Ag test (Bionote) - Brazil
89.2
81.7, 93.9
97.3
94.8, 98.6
RapiGen (BioCredit) - Germany
52
33.5, 70
100
99.7, 100
STANDARD Q COVID-19 Ag (SD Biosensor) - Germany
76.2
68.0, 82.8
99.3
98.8, 99.6
Espline SARS-CoV-2 (Fujirebio) - Germany
79.5
71.1, 85.9
100
99.4, 100
Mologic Covid-19 Rapid Antigen Test (Mologic Ltd. United Kingdom) - Germany
90.1
85.1, 93.6
100
99.2, 100
STANDARD F COVID-19 Ag FIA (SD Biosensor Inc.)
75.5
68.2, 81.5
97.2
96.0, 98.1
STANDARD Q COVID-19 Ag (SD Biosensor)
81.9
76.4, 86.3
99
98.5, 99.4
RapiGen (BioCredit)
70.4
62.4, 77.3
99.7
99.3, 99.9
KrĂźger,
et al.
102
Dec 2022
A multi-center clinical diagnostic accuracy study of Surestatus - an affordable, WHO emergency-use-listed, rapid, point-of-care, antigen-detecting diagnostic test for SARS-CoV-2 (preprint)
SureStatus
82.4
76.6, 87.1
98.5
97.4, 99.1
KrĂźger,
et al.
103
May 2021
The Abbott PanBio WHO emergency use listed, rapid, antigen-detecting point-of-care diagnostic test for SARS-CoV-2-Evaluation of the accuracy and ease-of-use
PanBio (Abbott)
86.8
79.0, 92.0
99.9
99.4, 100
Kurihara,
et al.
104
Jul 2021
The evaluation of a novel digital immunochromatographic assay with silver amplification to detect SARS-CoV-2
Custom/Novel/In-house
74.7
64.0, 83.6
99.8
99.5, 100
PanBio (Abbott)
Not reported
Â
Â
Roche SARS-CoV-2 Rapid Antigen Test (Roche)
Not reported
Â
Â
Espline SARS-CoV-2 (Fujirebio)
Not reported
Â
Â
Kweon,
et al.
105
May 2022
Positivity of rapid antigen testing for SARS-CoV-2 with serial followed-up nasopharyngeal swabs in hospitalized patients due to COVID-19
STANDARD Q COVID-19 Ag (SD Biosensor) - E gene
43.9
37.7, 50.3
Â
QuickNavi-COVID19 Ag
Not reported
Â
Â
STANDARD Q COVID-19 Ag (SD Biosensor) RdRp gene
43.9
37.7, 50.3
Â
Kyritsi,
et al.
106
Aug 2021
Rapid Test Ag 2019-nCoV (PROGNOSIS, BIOTECH, Larissa, Greece); performance evaluation in hospital setting with real time RT-PCR
Rapid Test Ag 2019-nCov (PROGNOSIS, BIOTECH, Greece)
85.5
79.1, 90.5
99.8
98.8, 100
Rapid Test Ag 2019-nCoV (PROGNOSIS, BIOTECH, Larissa, Greece); performance evaluation in hospital setting with real time RT-PCR
Rapid Test Ag 2019-nCov (PROGNOSIS, BIOTECH, Greece): 1 part/thousand prevalence
85.5
79.1, 90.5
99.8
98.8, 100
Rapid Test Ag 2019-nCoV (PROGNOSIS, BIOTECH, Larissa, Greece); performance evaluation in hospital setting with real time RT-PCR
Rapid Test Ag 2019-nCov (PROGNOSIS, BIOTECH, Greece): 1 percent prevalence
85.5
79.1, 90.5
99.8
98.8, 100
Rapid Test Ag 2019-nCoV (PROGNOSIS, BIOTECH, Larissa, Greece); performance evaluation in hospital setting with real time RT-PCR
Rapid Test Ag 2019-nCov (PROGNOSIS, BIOTECH, Greece): 5 percent prevalence
85.5
79.1, 90.5
99.8
98.8, 100
Landaverde,
et al.
107
Mar 2022
Comparison of BinaxNOW TM and SARS-CoV-2 qRT-PCR detection of the omicron variant from matched anterior nares swabs (preprint)
BinaxNOW (Abbott)
53.9
Â
100
Layer,
et al.
108
Feb 2022
SARS-CoV-2 screening strategies for returning international travellers: evaluation of a rapid antigen test approach
Roche SARS-CoV-2 Rapid Antigen Test (Roche)
59
Â
100
LeGoff,
et al.
109
Oct 2021
Evaluation of a saliva molecular point of care for the detection of SARS-CoV-2 in ambulatory care
EasyCov (SkillCell-Alcen, France)
34
26, 44
97
96, 98
STANDARD Q COVID-19 Ag (SD Biosensor)
85
77, 91
99
98, 99
Leixner,
et al.
110
Jul 2021
Evaluation of the AMP SARS-CoV-2 rapid antigen test in a hospital setting
AMP Rapid Test SARS-CoV-2 Ag (AMP Diagnostics)
69.15
58.8, 78.3
99.66
98.1, 100
Linares,
et al.
111
Oct 2020
Panbio antigen rapid test is reliable to diagnose SARS-CoV-2 infection in the first 7 days after the onset of symptoms
PanBio (Abbott)
73.3
62.2, 83.8
100
Lindner,
et al.
112
Apr 2021a
Head-to-head comparison of SARS-CoV-2 antigen-detecting rapid test with self-collected nasal swab versus professional-collected nasopharyngeal swab
STANDARD Q COVID-19 Ag (SD Biosensor)-NMT
74.4
58.9, 85.4
99.2
97.1, 99.8
STANDARD Q COVID-19 Ag (SD Biosensor)-NP
79.5
64.5, 89.2
99.6
97.8, 100
Lindner,
et al.
113
Apr 2021b
Head-to-head comparison of SARS-CoV-2 antigen-detecting rapid test with professional-collected nasal versus nasopharyngeal swab
STANDARD Q COVID-19 Ag (SD Biosensor)-NMT
80.5
66.0, 89.8
98.6
94.9, 99.6
STANDARD Q COVID-19 Ag (SD Biosensor)-NP
73.2
58.1, 84.3
99.3
96.0, 100
Lindner,
et al.
114
May 2021
Diagnostic accuracy and feasibility of patient self-testing with a SARS-CoV-2 antigen-detecting rapid test
STANDARD Q COVID-19 Ag (SD Biosensor)-Professional
85
70.9, 92.9
99.1
94.8, 99.5
STANDARD Q COVID-19 Ag (SD Biosensor)-Self testing
82.5
68.1, 91.3
100
96.5, 100
Mandal,
et al.
115
May 2022
Diagnostic performance of SARS-CoV-2 rapid antigen test in relation to RT-PCR CqValue
Espline SARS-CoV-2 (Fujirebio)
63.60%
54.7, 71.9
97.90
93.6, 99.6
Mane,
et al.
116
May 2022
Diagnostic performance of oral swab specimen for SARS-CoV-2 detection with rapid point-of-care lateral flow antigen test
PathoCatch (Accucare)
Not reported
Â
Â
PathoCatch (Accucare) - oral swabs
Not reported
Â
Â
Maniscalco,
et al.
117
Aug 2021
A rapid antigen detection test to diagnose SARS-CoV-2 infection using exhaled breath condensate by a modified Inflammacheck(ÂŽ) device
Inflammacheck (Exhalation Technology LTD)
92.3
64.0, 99.8
98.9
94.1, 100.0
MasiĂĄ,
et al.
118
Jan 2021
Nasopharyngeal Panbio COVID-19 antigen performed at point-of-care has a high sensitivity in symptomatic and asymptomatic patients with higher risk for transmission and older age
PanBio (Abbott)
68.1
Â
100
Mizrahi,
et al.
119
Nov 2021
The Coris BioConcept COVID 19 Ag Respi-Strip, a field experience feedback
Respi-Strip (Coris BioConcept) - Coris-Ag: 30-min reading (n = 294)
45.2
Â
100
Respi-Strip (Coris BioConcept) - Period 1 (n = 158)
59.3
Â
100
Respi-Strip (Coris BioConcept) - Period 2 (n = 136)
20
Â
100
Møller,
et al.
120
Jan 2022
Diagnostic performance, user acceptability, and safety of unsupervised SARS-CoV-2 rapid antigen-detecting tests performed at home
SARS-CoV-2 Antigen Rapid Test (Hangzhou Immuno Biotech Co Ltd, China).
62.1
50.1, 72.9
100
98.9, 100
COVID-19 Antigen Detection Kit (DNA Diagnostic A/S, Denmark)
65.7
49.2, 79.2
100
99, 100
PanBio (Abbott)
Not estimable
Â
100
95.6, 100
Nagura-Ikeda,
et al.
121
Aug 2020
Clinical evaluation of self-collected saliva by quantitative reverse transcription-PCR (RT-qPCR), direct RT-qPCR, reverse transcriptionâloop-mediated isothermal amplification, and a rapid antigen test to diagnose COVID-19
Espline SARS-CoV-2 (Fujirebio)
11.7
Nikolai,
et al.
122
Aug 2021
Anterior nasal versus nasal mid-turbinate sampling for a SARS-CoV-2 antigen-detecting rapid test: does localisation or professional collection matter?
STANDARD Q COVID-19 Ag (SD Biosensor) - Prof.-sampling: All (N =36), Prof AN
86.1
71.3, 93.9
100
95.7, 100
STANDARD Q COVID-19 Ag (SD Biosensor) - Self-sampling: All (N=34), Prof. NP
91.2
77, 97
100
94.2, 100
STANDARD Q COVID-19 Ag (SD Biosensor) - Self-sampling: All (N=34), Self NMT
91.2
77.0, 97
98.4
91.4, 99.9
NĂłra,
et al.
123
Feb 2022
Evaluating the field performance of multiple SARS-Cov-2 antigen rapid tests using nasopharyngeal swab samples
PanBio (Abbott)
Not reported
Â
Â
CoV2Ag assay (Siemens Healthineers, Eschborn, Germany)
Not reported
Â
Â
GenBody COVAG025 (GenBody)
Not reported
Â
Â
GENEDIA W COVID-19 Ag Test (Green Cross Medical Science Corp.)
Not reported
Â
Â
Humasis COVID-19 Ag Test kit (Humasis Co., Ltd.)
Not reported
Â
Â
Immupass VivaDiag (VivaChek Biotech)
Not reported
Â
Â
Helix i-SARS-CoV-2 Ag Rapid Test (Cellex Biotech Co.)
Not reported
Â
Â
Roche SARS-CoV-2 Rapid Antigen Test (Roche)
Not reported
Â
Â
Rapid COVID-19 Antigen Test (Healgen Scientific)
Not reported
Â
Â
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Antigen Detection Kit (Colloidal Gold-Based) Nanjing Vazyme Medical Technology Co
Not reported
Â
Â
Okoye,
et al.
124
Feb 2022
Diagnostic accuracy of a rapid diagnostic test for the early detection of COVID-19
BinaxNOW (Abbott)
91.84
80.40, 97.73
99.95
99.81, 99.99
Onsongo,
et al.
125
Feb 2022
Performance of a rapid antigen test for SARS-CoV-2 in Kenya
NowCheck COVID-19 Ag test (Bionote)
Not reported
Â
Â
Osmanodja,
et al.
126
May 2021
Accuracy of a novel sars-cov-2 antigen-detecting rapid diagnostic test from standardized self-collected anterior nasal swabs
Custom/Novel/In-house
88.6
78.7, 94.9
99.7
98.2, 100
Paap,
et al.
127
Jun 2022
Clinical evaluation of single-swab sampling for rapid COVID-19 detection in outbreak settings in Dutch nursing homes
Roche SARS-CoV-2 Rapid Antigen Test (Roche)
50.9
Â
89
Pandey,
et al.
128
Aug 2021
Comparison of the rapid antigen testing method with RT-qPCR for the diagnosis of COVID-19
STANDARD Q COVID-19 Ag (SD Biosensor)
53.6
39.7, 67.0
97.3
94.6, 98.9
Park,
et al.
129
Feb 2022
Analysis of the efficacy of universal screening of coronavirus disease with antigen-detecting rapid diagnostic tests at point-or-care settings and sharing the experience of admission protocolâa pilot study
STANDARD Q COVID-19 Ag (SD Biosensor)
68.3
Â
99.5
Peacock,
et al.
130
Jan 2022
Utility of COVID-19 antigen testing in the emergency department
BinaxNOW (Abbott)
76.9
69.9, 82.9
98.6
97.2, 99.4
PeĂąa,
et al.
131
Apr 2021
Performance of SARS-CoV-2 rapid antigen test compared with real-time RT-PCR in asymptomatic individuals
STANDARD Q COVID-19 Ag (SD Biosensor)
69.86
58.56, 9.18
[typo in paper]
99.61
98.86, 99.87
PeĂąa-Rodriguez,
et al.
132
Feb 2021
Performance evaluation of a lateral flow assay for nasopharyngeal antigen detection for SARS-CoV-2 diagnosis
STANDARD Q COVID-19 Ag (SD Biosensor)
75.9
66.5, 83.8
100
98.6, 100
Peronace,
et al.
133
May 2022
Validation of GeneFinder COVID-19 Ag plus rapid test and its potential utility to slowing infection waves: a single-center laboratory evaluation study
GeneFinder COVID-19 Ag Plus Rapid Test
96.03
91.55, 98.53
99.78
98.77, 99.99
Pilarowski,
et al.
134
Jan 2021
Performance characteristics of a rapid SARS-CoV-2 antigen detection assay at a public plaza testing site in San Francisco
BinaxNOW (Abbott)
57.7
36.9, 76.6
100
99.6, 100
Pollock,
et al.
135
Apr 2021
Performance and implementation evaluation of the Abbott BinaxNOW Rapid Antigen Test in a high-throughput drive-through community testing site in Massachusetts
BinaxNOW (Abbott)
84.1
77.4, 89.4
99.6
99.1, 99.9
Poopalasingam,
et al.
136
Feb 2022
Determining the reliability of rapid SARS-CoV-2 antigen detection in fully vaccinated individuals
STANDARD Q COVID-19 Ag (SD Biosensor)
57.3
46.1, 67.9
99.7
98.8, 99.9
Prost,
et al.
137
Dec 2021
Evaluation of a rapid in vitro diagnostic test device for detection of SARS-CoV-2 antigen in nasal swabs
SARS-CoV-2 Antigen Rapid Test (Hangzhou Immuno Biotech Co Ltd, China).
97.3
94.2, 99.0
99.5
97.3, 100
Rahman,
et al.
138
Nov 2021
Clinical evaluation of SARS-CoV-2 antigen-based rapid diagnostic test kit for detection of COVID-19 cases in Bangladesh
STANDARD Q COVID-19 Ag (SD Biosensor)- Adults
85.76
81.25, 89.54
Â
Rana,
et al.
139
Sept 2021
Evaluation of the currently used antigen-based rapid diagnostic test for the detection of SARS CoV-2 virus in respiratory specimens
STANDARD Q COVID-19 Ag (SD Biosensor)
37.5
Â
99.79
Rastawicki,
et al.
140
Jan 2021
Evaluation of PCL rapid point of care antigen test for detection of SARS-CoV-2 in nasopharyngeal swabs
PCL COVID19 Ag Rapid FIA Antigen Test (PCL)
38.9
Â
83.3
Rohde,
et al.
142
Feb 2022
Diagnostic accuracy and feasibility of a rapid SARS-CoV-2 antigen test in general practice - a prospective multicenter validation and implementation study
Roche SARS-CoV-2 Rapid Antigen Test (Roche)
78.3
70.9, 84.6
99.5
99, 99.8
Salcedo,
et al.
143
Feb 2022
Comparative Evaluation of Rapid Isothermal Amplification and Antigen Assays for Screening Testing of SARS-CoV-2
Custom/Novel/In-house
Not reported
Â
Â
Salvagno,
et al.
144
Jan 2021
Clinical assessment of the Roche SARS-CoV-2 rapid antigen test
STANDARD Q COVID-19 Ag (SD Biosensor)
72.5
64.6, 79.5
99.4
96.8, 100
Salvagno,
et al.
145
May 2021
Real-world assessment of Fluorecare SARS-CoV-2 Spike Protein Test Kit
Fluorecare (Colloidal Gold/Fluorescent) SARS-CoV-2 Spike Protein Test kit (Shenzen Microprofit)
27.5
21.8, 33.7
99.2
95.5, 100
Savage,
et al.
146
Jun 2022
A prospective diagnostic evaluation of accuracy of self-taken and healthcare worker-taken swabs for rapid COVID-19 testing
Covios COVID-19 Antigen Rapid Dianostic test-Health-care worker taken swab
78.4
69.0, 87.8
98.9
97.3, 100.0
Covios COVID-19 Antigen Rapid Dianostic test-Self-taken swab
90.5
83.9, 97.2
99.4
98.3, 100.0
Schildgen,
et al.
147
Jan 2021
Limits and opportunities of SARS-CoV-2 antigen rapid tests: an experienced-based perspective
PanBio (Abbott)
50
35, 64
77.4
60, 89
RapiGen (BioCredit)
33.3
21, 48
87.1
71, 95
Roche SARS-CoV-2 Rapid Antigen Test (Roche)
88.1
75, 95
19.4
9, 36
Selvabai,
et al.
148
Apr 2022
Diagnostic Efficacy of COVID-19 Rapid Antigen Detection Card in Diagnosis of SARS-CoV-2
Athenese-DX COVID-19 RAT kit
74.19
Â
100
Shaw,
et al.
149
Jul 2021
Evaluation of the Abbott Panbio(TM) COVID-19 Ag rapid antigen test for the detection of SARS-CoV-2 in asymptomatic Canadians
PanBio (Abbott)
Not reported
Â
Â
Siddiqui,
et al.
150
Dec 2021
Implementation and Accuracy of BinaxNOW Rapid Antigen COVID-19 Test in Asymptomatic and Symptomatic Populations in a High-Volume Self-Referred Testing Site
BinaxNOW (Abbott)
81
75, 86
99.8
100.0, 100.0
Sitoe,
et al.
151
Feb 2022
Performance Evaluation of the STANDARD(TM) Q COVID-19 and Panbio(TM) COVID-19 Antigen Tests in Detecting SARS-CoV-2 during High Transmission Period in Mozambique
PanBio (Abbott)
41.3
34.6, 48.4
98.2
96.2, 99.3
STANDARD Q COVID-19 Ag (SD Biosensor)
45
39.9, 50.2
97.6
95.3, 99.0
SkvarÄ
152
Apr 2022
Clinical validation of two immunochromatographic SARS-CoV-2 antigen tests in near hospital facilities
Immupass VivaDiag (VivaChek Biotech)
90.6
84.94, 94.36
100
99.41, 100.0
Alltest Covid19 Ag test
94.37
89.20, 97.54
100
98.83, 100.0
Smith,
et al.
153
Jun 2021
Clinical Evaluation of Sofia Rapid Antigen Assay for Detection of Severe Acute Respiratory Syndrome Coronavirus 2 among Emergency Department to Hospital Admissions
Sofia SARS Rapid Antigen FIA/Sofia 2 (Quidel)
76.6
71, 82
99.7
99.0, 100
Soleimani,
et al.
141
May 2021
Rapid COVID-19 antigenic tests: usefulness of a modified method for diagnosis
PanBio (Abbott)
75
68.9, 80.4
Â
COVID19-Speed/Biospeedia COVID19 Antigen test (Biospeedia)
65.5
59.0, 71.6
100
Stohr,
et al.
154
May 2022
Self-testing for the detection of SARS-CoV-2 infection with rapid antigen tests for people with suspected COVID-19 in the community
BD Veritor COVID-19 Rapid Antigen Test (Becton-Dickinson)
49.1
41.7, 56.5
99.9
99.7, 100.0
Roche SARS-CoV-2 Rapid Antigen Test (Roche)
61.5
54.6, 68.3
99.7
99.4, 99.9
Surasi,
et al.
155
Nov 2021
Effectiveness of Abbott BinaxNOW rapid antigen test for detection of SARS-CoV-2 infections in outbreak among horse racetrack workers, California, USA
BinaxNOW (Abbott)
43.3
34.6, 52.4
100
99.4, 100.0
Suzuki,
et al.
156
May 2022
Analytical performance of rapid antigen tests for the detection of SARS-CoV-2 during widespread circulation of the Omicron variant
QuickNavi-COVID19 Ag
94.2
91.6, 96.3
99.5
98.7, 99.9
Suzuki,
et al.
157
Jan 2022
Diagnostic performance of a novel digital immunoassay (RapidTesta SARS-CoV-2): A prospective observational study with nasopharyngeal samples
RapidTesta SARS-CoV-2
71.6
59.9, 81.5
99.2
98.5, 99.7
RapidTesta SARS-CoV-2
78.4
67.3, 87.1
97.6
96.5, 98.5
Terpos,
et al.
158
May 2021
Clinical Application of a New SARS-CoV-2 Antigen Detection Kit (Colloidal Gold) in the Detection of COVID-19
Custom/Novel/In-house
Not reported
Â
Â
Thakur,
et al.
159
Nov 2021
Utility of Antigen-Based Rapid Diagnostic Test for Detection of SARS-CoV-2 Virus in Routine Hospital Settings
PathoCatch (Accucare)
34.5
24.5, 45.6
99.8
99.1, 100
Thell,
et al.
160
Nov 2021
Evaluation of a novel, rapid antigen detection test for the diagnosis of SARS-CoV-2
Roche SARS-CoV-2 Rapid Antigen Test (Roche)-Emergency Dept
77.9
70.0, 84.6
98.1
94.6, 99.6
Roche SARS-CoV-2 Rapid Antigen Test (Roche)-Primary Health Care
84.4
74.4, 91.7
100
97.8, 100.0
Thirion-Romero,
et al.
161
Oct 2021
Evaluation of Panbio rapid antigen test for SARS-CoV-2 in symptomatic patients and their contacts: a multicenter study
PanBio (Abbott)
54.2
51.2, 57.2
98.5
97.7, 99.2
Tonelotto,
et al.
162
Jan 2022
Efficacy of Fluorecare SARS-CoV-2 Spike Protein Test Kit for SARS-CoV-2 detection in nasopharyngeal samples of 121 individuals working in a manufacturing company
Fluorecare (Colloidal Gold/Fluorescent) SARS-CoV-2 Spike Protein Test kit (Shenzen Microprofit)
84.6
54.6, 98.1
100
98.6, 100.0
Toptan,
et al.
163
Feb 2021
Evaluation of a SARS-CoV-2 rapid antigen test: potential to help reduce community spread?
Rida Quick SARS-CoV-2 (R-Biopharm)-Berlin
77.6
Â
100
Rida Quick SARS-CoV-2 (R-Biopharm)-Frankfurt
50
Â
100
Trobajo-SanmartĂn,
et al.
164
Mar 2021
Evaluation of the rapid antigen test CerTest SARS-CoV-2 as an alternative COVID-19 diagnosis technique
CerTest SARS-CoV-2 (Certest Biotech)
78.75
67.89, 86.79
100
97.08, 99.94
Turcato,
et al.
165
Mar 2021
Clinical application of a rapid antigen test for the detection of SARS-CoV-2 infection in symptomatic and asymptomatic patients evaluated in the emergency department: a preliminary report
Standard Q COVID-19 Ag (SD Biosensor)
80.3
74.9, 85.4
99.1
98.6, 99.3
Turcato,
et al.
166
Jan 2022
Rapid antigen test to identify COVID-19 infected patients with and without symptoms admitted to the emergency department
Standard Q COVID-19 Ag (SD Biosensor)
82.9
81.0, 84.8
99.1
98.8, 99.3
Van der Moeren,
et al.
167
May 2021
Evaluation of the test accuracy of a SARS-CoV-2 rapid antigen test in symptomatic community dwelling individuals in the Netherlands
BD Veritor COVID-19 Rapid Antigen Test (Becton-Dickinson)
94.1
71.1, 100
100
98.9, 100
BD Veritor COVID-19 Rapid Antigen Test (Becton-Dickinson)-Visual
94.1
71.1, 100
100
98.9, 100
Van Honacker,
et al.
168
Aug 2021
Comparison of five SARS-CoV-2 rapid antigen tests in a hospital setting and performance of one antigen assay in routine practice. A useful tool to guide isolation precautions?
Standard Q COVID-19 Ag (SD Biosensor)
54.2
Â
99.7
von Ahnen,
et al.
169
Mar 2022
Evaluation of a rapid-antigen test for COVID-19 in an asymptomatic collective: a prospective study
Roche SARS-CoV-2 Rapid Antigen Test (Roche)
92.3
78.0, 100
100
100.0, 100.0
Wertenauer,
et al.
170
Mar 2022
Diagnostic performance of rapid antigen testing for SARS-CoV-2: the COVid-19 AntiGen (COVAG) study
PanBio (Abbott)
56.8
Â
99.9
Roche SARS-CoV-2 Rapid Antigen Test (Roche)
60.4
Â
99.7
Appendix IV: Rapid antigen tests from included studies
Name
Company
Study count
Reported 100% sensitivity in at least 1 study
Reported 100% specificity in at least 1 study
Reported 100% positive predictive value in at least 1 study
Reported 100% negative predictive value in at least 1 study
1
STANDARD Q COVID-19 Ag Test
SD Biosensor Inc.
28
X
X
X
X
2
PanBio COVID-19 Ag Rapid Test Device
Abbott
14
X
X
3
SARS-CoV-2 Rapid Antigen Test
Roche Diagnostics
11
X
X
4
BinaxNOW COVID-19 Antigen
Abbott
10
X
X
5
Rapid Test Ag 2019-nCov
ProGnosis Biotech
4
6
SARS-CoV-2 Ag
LumiraDx
3
X
7
Custom/Novel/In-house
N/A
3
8
COVISTIX (COVIDMARK) Covid 19 Antigen Rapid Test Device
Sorrento Therapeutics
3
9
AMP Rapid Test SARS-CoV-2 Ag
AMP Diagnostics
2
X
X
10
BD Veritor COVID-19 Rapid Antigen Test
Becton-Dickinson
2
X
X
11
CerTest SARS-CoV-2
Certest Biotec
2
X
X
12
Espline SARS-CoV-2
Fujirebio
2
X
X
13
SARS-CoV-2 Antigen Rapid Test
Hangzhou Immuno Biotech Co Ltd
2
X
14
HUMASIS COVID-19 Ag Test
Humasis Co., Ltd
2
15
Mologic Covid-19 Rapid Antigen Test
Mologic Ltd. United Kingdom
2
X
X
16
NADAL COVID-19 Ag Rapid Test
New Art Laboratories/nal von minden
2
X
X
17
Quick Navi-COVID 19 Ag
Otsuka Pharmaceutical Co., Ltd.
2
X
18
PCL COVID19 Ag Rapid FIA Antigen Test
PCL, Inc.
2
19
Sofia SARS Rapid Antigen FIA/Sofia 2
Quidel
2
X
X
20
BIOCREDIT COVID-19 Ag
RapiGen, Inc.
2
X
X
21
Rida Quick SARS-CoV-2 Antigen Test
R-Biopharm AG
2
X
X
22
STANDARD F COVID-19 Ag FIA
SD Biosensor Inc
2
23
RapidTesta SARS-CoV-2
Sekisui Medical Co., Ltd
2
24
Fluorecare SARS-CoV-2 Spike Protein Test kit (Colloidal Gold)
Shenzen Microprofit Biotech Co., Ltd.
2
X
X
25
CLINITEST Rapid COVID-19 Antigen Test
Siemens Healthineers
2
26
Immupass VivaDiag
VivaChek Biotech
2
X
27
COVID-VIRO COVID-19 Ag Rapid Test
AAZ
1
X
X
28
Flowflex COVID-19 Antigen test
ACON Labs
1
X
X
X
X
29
COVID-19 Antigen Rapid Test
Acro Biotech, Inc.
1
30
Alltest COVID-19 ART Antigen Rapid Test
ALLTEST
1
X
31
COVID-19 Antigen Rapid Test
Assut Europe
1
X
X
32
COVID-19 RAT kit
Athenese-DX
1
X
X
33
NowCheck COVID-19 Ag test
Bionote
1
34
Novel Corona Virus (SARS-CoV-2) Ag Rapid Test kit
Bioperfectus
1
X
X
35
Covid-19 AG BSS
BIOSYNEX
1
36
Helix i-SARS-CoV-2 Ag Rapid Test
Cellex Biotech Co
1
37
COVID-19 Ag K-SeT
Coris Bioconcept
1
38
Liaison SARS-CoV-2 Ag
DiaSorin
1
39
COVID-19 Antigen Detection
DNA Diagnostic A/S
1
X
40
COVID-19 Ag ECO Teste
Eco Diagnostica
1
41
Inflammacheck CoronaCheck
Exhalation Technology LTD
1
42
GenBody COVAG025
GenBody
1
43
GENEDIA W COVID-19 Ag Test
Green Cross Medical Science Corp
1
44
Rapid COVID-19 Antigen Test
Healgen Scientific
1
45
Innova SARS-CoV-2 Antigen Rapid test
Innova Medical Group
1
46
Accucare PathoCatch Covid-19 Ag Detection Kit
Mylab
1
47
Orient Gene Rapid Covid-19 (Antigen) Self-Test
Orient Gene
1
X
X
48
GeneFinder COVID-19 Ag Plus Rapid Test
OSANG Healthcare
1
49
Green Spring SARS-CoV-2 Antigen Rapid Test Kit (Colloidal Gold)
Shenzhen Lvshiyuan Biotechnology
1
X
X
50
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Antigen Detection Kit (Colloidal Gold-Based)
Vazyme Medical Technology Co
1
51
2019-nCoV Antigen Test
Wondfo
1
Footnotes
The authors declare no conflicts of interest.
Supplemental digital content is available for this article. Direct URL citations are provided in the HTML and PDF versions of this article on the journalâs website,
www.jbievidencesynthesis.com
.
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# Comparison of diagnostic accuracy of rapid antigen tests for COVID-19 compared to the viral genetic test in adults: a systematic review and meta-analysis
[Ellyn Hirabayashi](https://pubmed.ncbi.nlm.nih.gov/?term="Hirabayashi%20E"[Author])
### Ellyn Hirabayashi
1Touro University Nevada, College of Osteopathic Medicine, Department of Basic Sciences, Henderson, NV, USA
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1, [Guadalupe Mercado](https://pubmed.ncbi.nlm.nih.gov/?term="Mercado%20G"[Author])
### Guadalupe Mercado
1Touro University Nevada, College of Osteopathic Medicine, Department of Basic Sciences, Henderson, NV, USA
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### Brandi Hull
1Touro University Nevada, College of Osteopathic Medicine, Department of Basic Sciences, Henderson, NV, USA
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### Sabrina Soin
1Touro University Nevada, College of Osteopathic Medicine, Department of Basic Sciences, Henderson, NV, USA
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### Sherli Koshy-Chenthittayil
1Touro University Nevada, College of Osteopathic Medicine, Department of Basic Sciences, Henderson, NV, USA
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1, [Sarina Raman](https://pubmed.ncbi.nlm.nih.gov/?term="Raman%20S"[Author])
### Sarina Raman
1Touro University Nevada, College of Osteopathic Medicine, Department of Basic Sciences, Henderson, NV, USA
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1, [Timothy Huang](https://pubmed.ncbi.nlm.nih.gov/?term="Huang%20T"[Author])
### Timothy Huang
1Touro University Nevada, College of Osteopathic Medicine, Department of Basic Sciences, Henderson, NV, USA
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1, [Chathushya Keerthisinghe](https://pubmed.ncbi.nlm.nih.gov/?term="Keerthisinghe%20C"[Author])
### Chathushya Keerthisinghe
1Touro University Nevada, College of Osteopathic Medicine, Department of Basic Sciences, Henderson, NV, USA
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1, [Shelby Feliciano](https://pubmed.ncbi.nlm.nih.gov/?term="Feliciano%20S"[Author])
### Shelby Feliciano
1Touro University Nevada, College of Osteopathic Medicine, Department of Basic Sciences, Henderson, NV, USA
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### Andrew Dongo
1Touro University Nevada, College of Osteopathic Medicine, Department of Basic Sciences, Henderson, NV, USA
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1, [James Kal](https://pubmed.ncbi.nlm.nih.gov/?term="Kal%20J"[Author])
### James Kal
1Touro University Nevada, College of Osteopathic Medicine, Department of Basic Sciences, Henderson, NV, USA
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1, [Azliyati Azizan](https://pubmed.ncbi.nlm.nih.gov/?term="Azizan%20A"[Author])
### Azliyati Azizan
1Touro University Nevada, College of Osteopathic Medicine, Department of Basic Sciences, Henderson, NV, USA
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1, [Karen Duus](https://pubmed.ncbi.nlm.nih.gov/?term="Duus%20K"[Author])
### Karen Duus
1Touro University Nevada, College of Osteopathic Medicine, Department of Basic Sciences, Henderson, NV, USA
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### Terry Else
1Touro University Nevada, College of Osteopathic Medicine, Department of Basic Sciences, Henderson, NV, USA
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1, [Megan DeArmond](https://pubmed.ncbi.nlm.nih.gov/?term="DeArmond%20M"[Author])
### Megan DeArmond
2Touro University Nevada, Jay Sexter Library, Henderson, NV, USA
3Touro University Nevada: JBI Affiliated Group, Henderson, NV, USA
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2,3,â, [Amy EL Stone](https://pubmed.ncbi.nlm.nih.gov/?term="Stone%20AEL"[Author])
### Amy EL Stone
1Touro University Nevada, College of Osteopathic Medicine, Department of Basic Sciences, Henderson, NV, USA
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1
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1Touro University Nevada, College of Osteopathic Medicine, Department of Basic Sciences, Henderson, NV, USA
2Touro University Nevada, Jay Sexter Library, Henderson, NV, USA
3Touro University Nevada: JBI Affiliated Group, Henderson, NV, USA
â
*Correspondence:* Megan DeArmond, mde\_armo@touro.edu
â
Corresponding author.
Collection date 2024 Oct.
Copyright Š 2024 The Author(s). Published by Wolters Kluwer Health, Inc. on Behalf of JBI.
This is an open access article distributed under the terms of the [Creative Commons Attribution-Non Commercial-No Derivatives License 4.0](https://creativecommons.org/licenses/by-nc-nd/4.0/) (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. [http://creativecommons.org/licenses/by-nc-nd/4.0/](https://creativecommons.org/licenses/by-nc-nd/4.0/)
[PMC Copyright notice](https://pmc.ncbi.nlm.nih.gov/about/copyright/)
PMCID: PMC11462910 PMID: [39188132](https://pubmed.ncbi.nlm.nih.gov/39188132/)
## Abstract
### Objective:
The objective of this review was to determine the diagnostic accuracy of the currently available and upcoming point-of-care rapid antigen tests (RATs) used in primary care settings relative to the viral genetic real-time reverse transcriptase polymerase chain reaction (RT-PCR) test as a reference for diagnosing COVID-19/SARS-CoV-2 in adults.
### Introduction:
Accurate COVID-19 point-of-care diagnostic tests are required for real-time identification of SARS-CoV-2 infection in individuals. Real-time RT-PCR is the accepted gold standard for diagnostic testing, requiring technical expertise and expensive equipment that are unavailable in most primary care locations. RATs are immunoassays that detect the presence of a specific viral protein, which implies a current infection with SARS-CoV-2. RATs are qualitative or semi-quantitative diagnostics that lack thresholds that provide a result within a short time frame, typically within the hour following sample collection. In this systematic review, we synthesized the current evidence regarding the accuracy of RATs for detecting SARS-CoV-2 compared with RT-PCR.
### Inclusion criteria:
Studies that included nonpregnant adults (18 years or older) with suspected SARS-CoV-2 infection, regardless of symptomology or disease severity, were included. The index test was any available SARS-CoV-2 point-of-care RAT. The reference test was any commercially distributed RT-PCRâbased test that detects the RNA genome of SARS-CoV-2 and has been validated by an independent third party. Custom or in-house RT-PCR tests were also considered, with appropriate validation documentation. The diagnosis of interest was COVID-19 disease and SARS-CoV-2 infection. This review considered cross-sectional and cohort studies that examined the diagnostic accuracy of COVID-19/SARS-CoV-2 infection where the participants had both index and reference tests performed.
### Methods:
The keywords and index terms contained in relevant articles were used to develop a full search strategy for PubMed and adapted for Embase, Scopus, Qinsight, and the WHO COVID-19 databases. Studies published from November 2019 to July 12, 2022, were included, as SARS-CoV-2 emerged in late 2019 and is the cause of a continuing pandemic. Studies that met the inclusion criteria were critically appraised using QUADAS-2. Using a customized tool, data were extracted from included studies and were verified prior to analysis. The pooled sensitivity, specificity, positive predictive, and negative predictive values were calculated and presented with 95% CIs. When heterogeneity was observed, outlier analysis was conducted, and the results were generated by removing outliers.
### Results:
Meta-analysis was performed on 91 studies of 581 full-text articles retrieved that provided true-positive, true-negative, false-positive, and false-negative values. RATs can identify individuals who have COVID-19 with high reliability (positive predictive value 97.7%; negative predictive value 95.2%) when considering overall performance. However, the lower level of sensitivity (67.1%) suggests that negative test results likely need to be retested through an additional method.
### Conclusions:
Most reported RAT brands had only a few studies comparing their performance with RT-PCR. Overall, a positive RAT result is an excellent predictor of a positive diagnosis of COVID-19. We recommend that Rocheâs SARS-CoV-2 Rapid Antigen Test and Abbottâs BinaxNOW tests be used in primary care settings, with the understanding that negative results need to be confirmed through RT-PCR. We recommend adherence to the STARD guidelines when reporting on diagnostic data.
### Review registration:
PROSPERO CRD42020224250
**Keywords:** COVID19, point of care, rapid antigen tests, respiratory infection, SARS-CoV-2
## Summary of Findings
Test accuracy of STANDARD Q COVID-19 Antigen test from SD Biosensor for COVID-19 or SARS-CoV-2 infection in symptomatic adults
| | | | |
|---|---|---|---|
| Sensitivity | 0\.782 (95% CI: 0.587 to 0.900) | | |
| Specificity | 0\.984 (95% CI: 0.949 to 0.995) | | |
| Prevalences | 0\.5% | 5% | 10% |
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/table/TU1/)
| Outcome | â of studies (â of patients) | Study design | Factors that may decrease certainty of evidence | Effect per 1000 patients tested | Test accuracy certainty of evidence | | | | | | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Risk of bias | Indirectness | Inconsistency | Imprecision | Publication bias | Pre-test probability of 0.5% (95% CI) | Pre-test probability of 5% (95% CI) | Pre-test probability of 10% (95% CI) | | | | |
| **True positives** | 4 studies (3179 patients) | cross-sectional (cohort type accuracy study) | not serious | not serious | very seriousa | not serious | none | 4 (3 to 5) | 39 (29 to 45) | 78 (59 to 90) | â¨â¨âŻâŻ Low |
| **False negatives** | 1 (0 to 2) | 11 (5 to 21) | 22 (10 to 41) | | | | | | | | |
| **True negatives** | 4 studies (3179 patients) | cross-sectional (cohort type accuracy study) | not serious | not serious | seriousa | not serious | none | 979 (944 to 990) | 935 (902 to 945) | 886 (854 to 896) | â¨â¨â¨âŻ Moderate |
| **False positives** | 16 (5 to 51) | 15 (5 to 48) | 14 (4 to 46) | | | | | | | | |
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/table/TU2/)
Explanations:
a. High heterogeneity across studies.
Test accuracy of PanBio by Abbott for COVID-19 or SARS-CoV-2 infection in symptomatic adults
| | | | |
|---|---|---|---|
| Sensitivity | 0\.780 (95% CI: 0.610 to 0.889) | | |
| Specificity | 0\.999 (95% CI: 0.993 to 1.000) | | |
| Prevalences | 0\.5% | 5% | 10% |
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/table/TU3/)
| Outcome | â of studies (â of patients) | Study design | Factors that may decrease certainty of evidence | Effect per 1000 patients tested | Test accuracy certainty of evidence | | | | | | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Risk of bias | Indirectness | Inconsistency | Imprecision | Publication bias | Pre-test probability of 0.5% (95% CI) | Pre-test probability of 5% (95% CI) | Pre-test probability of 10% (95% CI) | | | | |
| **True positives** | 2 studies (1324 patients) | cross-sectional (cohort type accuracy study) | not serious | not serious | very seriousa | not serious | none | 4 (3 to 4) | 39 (31 to 44) | 78 (61 to 89) | â¨â¨âŻâŻ Low |
| **False negatives** | 1 (1 to 2) | 11 (6 to 19) | 22 (11 to 39) | | | | | | | | |
| **True negatives** | 2 studies (1324 patients) | cross-sectional (cohort type accuracy study) | not serious | not serious | not serious | not serious | none | 994 (988 to 995) | 949 (943 to 950) | 899 (894 to 900) | â¨â¨â¨â¨ High |
| **False positives** | 1 (0 to 7) | 1 (0 to 7) | 1 (0 to 6) | | | | | | | | |
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/table/TU4/)
Explanations:
a. High heterogeneity across studies.
Test accuracy of Roche SARS-CoV-2 Rapid Antigen Test for COVID-19 or SARS-CoV-2 infection in symptomatic adults
| | | | |
|---|---|---|---|
| Sensitivity | 0\.812 (95% CI: 0.762 to 0.855) | | |
| Specificity | 0\.996 (95% CI: 0.974 to 0.999) | | |
| Prevalences | 0\.5% | 5% | 10% |
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/table/TU5/)
| Outcome | â of studies (â of patients) | Study design | Factors that may decrease certainty of evidence | Effect per 1000 patients tested | Test accuracy certainty of evidence | | | | | | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Risk of bias | Indirectness | Inconsistency | Imprecision | Publication bias | Pre-test probability of 0.5% (95% CI) | Pre-test probability of 5% (95% CI) | Pre-test probability of 10% (95% CI) | | | | |
| **True positives** | 2 studies (874 patients) | cross-sectional (cohort type accuracy study) | not serious | not serious | not serious | not serious | none | 4 (4 to 4) | 41 (38 to 43) | 81 (76 to 86) | â¨â¨â¨â¨ High |
| **False negatives** | 1 (1 to 1) | 9 (7 to 12) | 19 (14 to 24) | | | | | | | | |
| **True negatives** | 2 studies (874 patients) | cross-sectional (cohort type accuracy study) | not serious | not serious | not serious | not serious | none | 991 (969 to 994) | 946 (925 to 949) | 896 (877 to 899) | â¨â¨â¨â¨ High |
| **False positives** | 4 (1 to 26) | 4 (1 to 25) | 4 (1 to 23) | | | | | | | | |
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/table/TU6/)
Test accuracy of BinaxNOW by Abbott for COVID-19 or SARS-CoV-2 infection in symptomatic adults
| | | | |
|---|---|---|---|
| Sensitivity | 0\.867 (95% CI: 0.797 to 0.919) | | |
| Specificity | 0\.988 (95% CI: 0.974 to 0.996) | | |
| Prevalences | 0\.5% | 5% | 10% |
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/table/TU7/)
| Outcome | â of studies (â of patients) | Study design | Factors that may decrease certainty of evidence | Effect per 1000 patients tested | Test accuracy certainty of evidence | | | | | | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Risk of bias | Indirectness | Inconsistency | Imprecision | Publication bias | Pre-test probability of 0.5% (95% CI) | Pre-test probability of 5% (95% CI) | Pre-test probability of 10% (95% CI) | | | | |
| **True positives** | 1 study 642 patients | cross-sectional (cohort type accuracy study) | not serious | not serious | not serious | not serious | none | 4 (4 to 5) | 43 (40 to 46) | 87 (80 to 92) | â¨â¨â¨â¨ High |
| **False negatives** | 1 (0 to 1) | 7 (4 to 10) | 13 (8 to 20) | | | | | | | | |
| **True negatives** | 1 study 642 patients | cross-sectional (cohort type accuracy study) | not serious | not serious | not serious | not serious | none | 983 (969 to 991) | 939 (925 to 946) | 889 (877 to 896) | â¨â¨â¨â¨ High |
| **False positives** | 12 (4 to 26) | 11 (4 to 25) | 11 (4 to 23) | | | | | | | | |
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/table/TU8/)
## Introduction
According to the World Health Organization, as of August 2024, there were more than 775 million confirmed cases of COVID-19 caused by the virus SARS-CoV-2 and more than 7 million deaths.[1](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R1) In addition to recently updated vaccines, testing and accurate diagnosis of SARS-CoV-2 has been a key tool in fighting the pandemic.[2](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R2) Based on the current statistics of new cases[1](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R1) showing that the virus remains in circulation within human and animal populations,[3](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R3) accurate diagnostic testing is required to prevent future outbreaks that can lead to additional loss of life.
Accurate COVID-19 point-of-care (POC) diagnostic tests are required for real-time identification of SARS-CoV-2 infections in individuals. Early and accurate identification of potential cases leads to better control of virus transmission and early treatment interventions for individuals at high risk of severe disease. At this point, asymptomatic screening for SARS-CoV-2 infection has fallen out of fashion, with most public locations not requiring tests as part of day-to-day life. However, symptomatic individuals who present at primary care locations need to be diagnosed quickly and reliably. Real-time reverse transcriptase PCR (qRT-PCR or RT-PCR) is the accepted gold standard for diagnostic testing[4](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R4) and is available in many health care settings. However, RT-PCR requires technical expertise and expensive equipment that are not available in most primary care locations. Additionally, samples are required to be collected at the POC and sent to off-site laboratories for testing. The time delay between visiting the primary care provider and receiving results can increase transmission and delay appropriate treatment. For SARS-CoV-2 infections, RT-PCR detects viral RNA but is unable to discriminate between transmissible and replicating viruses and RNA remaining after the infection has been contained by the immune system.[5](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R5) Primary care providers should have access to reliable POC rapid antigen tests (RATs) for COVID-19, similar to those that are available for many other infectious diseases. Evaluation of the accuracy of POC diagnostic tests is needed to utilize these tests with confidence.[6](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R6)
Rapid antigen tests are immunoassays that detect the presence of a specific viral protein, glycan, or nucleic acid, which implies a current infection with SARS-CoV-2. RATs are useful for identifying infectious viruses as they detect viral proteins, which are cleared before the remaining viral RNA.[5](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R5) The accuracy of these tests compared with the gold standard RT-PCR appears to vary depending on the manufacturer. However, many studies have reported disparate accuracy results compared with manufacturersâ reported results.[7](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R7)â[12](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R12) In this systematic review, we synthesized the current evidence regarding RAT accuracy for the detection of SARS-CoV-2, and considered the overall performance of these techniques compared with the gold standard RT-PCR.
A search of PROSPERO, DARE (Database of Abstracts of Reviews of Effects), PubMed, the Cochrane Database of Systematic Reviews, JBI Registration of Systematic Review Titles, and *JBI Evidence Synthesis* was conducted in November 2020. We identified 1 review in PROSPERO[13](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R13) and 2 systematic reviews in the Cochrane Database of Systematic Reviews,[14](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R14),[15](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R15) each of which became available after our title registration in PROSPERO and the JBI Registration of Systematic Review Titles in June 2020. The PROSPERO review examined peer-reviewed publications for tests commercially available before August 15, 2020.[13](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R13) Our systematic review included additional sources for tests, including gray literature available from the manufacturers, and included search results from tests not yet commercially available. The literature searches of the 2 Cochrane reviews ended in May 2020[14](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R14),[15](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R15) and were updated in July 2022, with a search that ended in March 2021.[16](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R16) In the time since then, significant amounts of research and numbers of tests have become available, warranting an additional review. With the rapidly changing environment around COVID-19, our review adds to those published with a longer, more recent timeline. Additionally, our question is of a more general nature of POC diagnostic accuracy for primary care settings anywhere in the world. Our review has important implications for health care providers caring for patients in both resource-rich and resource-poor regions.
We framed our review question using the population index test reference test diagnosis (PIRD) mnemonic, which is commonly used for diagnostic reviews.[17](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R17) The objective of this systematic review was to synthesize the best available evidence related to the diagnostic accuracy of the available POC RATs (index test) relative to a certified medical laboratory viral genetic RT-PCR test (reference test) for the diagnosis of COVID-19/SARS-CoV-2 in adults 18 years and older. The rationale for combining both test types in this systematic review was to provide a comprehensive comparison of RT-PCR with the POC RATs. As the COVID-19 pandemic continues to rapidly evolve, the highest diagnostic accuracy, lowest cost, and quickest results are important considerations for monitoring and managing disease spread in a primary care setting. The aim of this study was to identify the rapid diagnostic tests that fit this requirement.
## Review question
What is the diagnostic accuracy of the currently available and upcoming POC RATs used in primary care settings relative to the viral genetic RT-PCR test as a reference for the diagnosis of COVID-19/SARS-CoV-2 in adults?
## Inclusion criteria
### Participants
The review examined studies that included nonpregnant adults (18 years and older) with suspected SARS-CoV-2 infection, regardless of symptomology or disease severity. Persons of any ethnicity or race in any geographic location were considered. Studies that included data from pregnant women or children within the study population that could be separated from the overall study data were included in the review. We excluded studies that only contained tests that could not be used in primary care settings, such as those that required larger equipment or specialized expertise. The setting of the study was recorded but not used as an exclusion criterion. Any non-primary care setting was initially an exclusion criterion,[18](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R18) but upon further discussion, the criterion was adjusted to focus on the RAT used rather than the setting in which the RAT was used.
### Index test
The index tests investigated in this review were any currently available or pre-market POC SARS-CoV-2 RATs. RATs are qualitative or semi-quantitative diagnostics that provide a result within a short time frame, typically within the hour following sample collection.[19](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R19) Tests could use any easily obtained bodily fluid or sample, including saliva, mucus, blood, urine, breath, or feces. Most of the studies considered used nasopharyngeal, nasal, or oropharyngeal swab specimens. RATs include a variety of techniques, such as chromogenic-based or fluorescence-based detection and lateral flow-based detection, but as a common denominator, all detect viral antigens from presently infected fluids and cells.[19](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R19) Tests that detect immunoglobulin against SARS-CoV-2 were excluded from this review, as antibodies develop upon resolution of SARS-CoV-2 infection or from vaccination and, therefore, are not used in the POC setting for diagnosing acute infection.[6](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R6)
### Reference test
The reference test was commercially distributed RT-PCRâbased tests that detect the RNA genome of SARS-CoV-2 and have been validated by an independent third party. Additionally, custom or in-house RT-PCR tests were considered with appropriate validation documentation. For example, Japanâs National Institute of Infectious Disease method was accepted as a validated RT-PCR test.[20](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R20) These tests must be performed in certified laboratories where personnel have been trained to perform RT-PCR assays.
### Diagnosis of interest
The diagnoses of interest were COVID-19 disease and SARS-CoV-2 infection.
### Types of studies
This review considered any English-language or English-translated cross-sectional or cohort study that examined the diagnostic accuracy (sensitivity and specificity, positive predictive value, negative predictive value) of COVID-19/SARS-CoV-2 infection where the participants had both index and reference tests performed. Case-control studies were excluded due to high risk of bias (see âAssessment of methodological qualityâ). Meta-analysis was performed on studies that provided true-positive (TP), true-negative (TN), false-positive (FP), and false-negative (FN) values. Studies published from November 2019 to July 12, 2022, were included, as SARS-CoV-2 emerged in late 2019 and is the cause of a continuing pandemic.
## Methods
This systematic review was conducted in accordance with JBI methodology for systematic reviews of diagnostic test accuracy[17](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R17) and follows our published protocol,[18](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R18) with exceptions noted throughout.
### Search strategy
The search strategies for all databases aimed to locate published and unpublished studies, including preprints. An initial limited search of several sources was undertaken to identify articles, review other search strategies, and search for published articles on the topic. These initial sources were PubMed, PROSPERO, *JBI Evidence Synthesis*, Cochrane Database of Systematic Reviews, DARE, and the Cochrane Central Register of Controlled Trials. The text words contained in the titles and abstracts of relevant articles and the articlesâ index terms were used to develop a full search strategy for PubMed. We adopted the Canadian Agency for Drugs and Technologies (CADTH) COVID-19 search string developed for PubMed.[21](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R21) Once a draft was fully developed, the PubMed search strategy was peer-reviewed by a medical librarian following the Peer Review of Electronic Search Strategy (PRESS) Guideline Statement.[22](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R22) After that initial pilot search, the search strategy was further edited and finalized for review. The search strategy, including all identified keywords and index terms, was adapted for each included information source.
The full search of MEDLINE (PubMed), Embase, Scopus, Qinsight (Quertle), and the World Health Organization (WHO) COVID-19 database was undertaken in July 2021 and updated on July 12, 2022 (with the exception of Qinsight, which was no longer available). See [Appendix I](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#A1) for the full search strategy. Scopus, Qinsight, and WHO COVID-19 include gray literature.
### Study selection
Following the search, all identified citations were collated and uploaded into EndNote v.X9.3.3. The EndNote edition was later upgraded to EndNote 20.5 (Clarivate Analytics, PA, USA). All duplicates were removed using a method developed and detailed by Bramer *et al*.[23](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R23) Titles and abstracts were screened first by 2 independent reviewers of the research team (EH, GM, BH, SS, SR, TH, CK, SF, AD, JK, AA, KD, TE, MD, AS) against the inclusion criteria using Google Sheets. Potentially relevant studies were retrieved in full, and their citation details were imported into a Google Sheet. The full texts of selected citations were assessed in detail against the inclusion criteria by at least 2 reviewers from the team independently (EH, GM, BH, SS, SR, TH, CK, SF, AD, JK, AA, KD, TE, MD, AS). Conflicts were resolved at the completion of each stage by a third reviewer (AS, AA, KD, TE). Reasons for the exclusion of full-text studies that did not meet the inclusion criteria were recorded and are provided in Supplemental Digital Content 1, <http://links.lww.com/SRX/A55>. The results of the search and screening are presented in a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram[24](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R24) (Figure [1](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#F1)).
#### Figure 1.
[](https://www.ncbi.nlm.nih.gov/core/lw/2.0/html/tileshop_pmc/tileshop_pmc_inline.html?title=Click%20on%20image%20to%20zoom&p=PMC3&id=11462910_srx-22-1939-g001.jpg)
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/figure/F1/)
Search results and study selection and inclusion process[24](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R24)
### Assessment of methodological quality
Selected studies were critically appraised by at least 2 reviewers from the team independently (EH, GM, BH, SS, SR, TH, CK, SF, AD, JK, AA, KD, TE, MD, AS) for risk of bias using the standardized critical appraisal instrument from the QUADAS-2.[25](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R25) QUADAS-2 provides a series of yes/no questions to appraise studies. At a minimum, we required the following questions to be answered âyesâ for a study to be included in the systematic review: \#2: Was a case-control design avoided? \#3: Did the study avoid inappropriate exclusions? \#6: Is the reference standard likely to correctly classify the target condition? \#8: Was there an appropriate interval between the index test and reference standard?
Studies that answered ânoâ or âunclearâ to any of these 4 QUADAS-2 questions were excluded. Disagreements were resolved through discussion or with an additional reviewer. The decision to exclude was based on the consensus of the 2 independent reviewers and, if needed, an additional reviewer (EH, GM, BH, SS, SR, TH, CK, SF, AD, JK, AA, KD, TE, MD, AS). Studies were excluded from data extraction if specificity and sensitivity were not presented or the data could not be used to calculate specificity and sensitivity. We did not exclude any studies due to low statistical power.
### Data extraction
We performed a pilot data extraction of 52 studies to determine the effectiveness of our initial data extraction tool. Based on the challenges of combining the extracted data from the pilot data extraction, a new custom data extraction tool was developed, building on the initial tool. The custom data extraction tool was modified from the original protocol to better separate and standardize the data during extraction. See [Appendix II](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#A2) for the updated data extraction tool. We identified specific portions of the data extraction tool to be standardized prior to data extraction, including the setting, sample, reference test, and index test. For these, we used drop downs for the data extractors to select from, including an âotherâ option that allowed the entering of data items not found in the initial pilot extraction. The extracted data were reviewed and verified prior to analysis. The final standardization of data was performed by 2 individuals (SK-C, AS) to ensure inter-extractor reliability.
For each study, we identified the primary (dominant) strain of SARS-CoV-2 circulating in the study country during the study time frame using CoVariants.org.[26](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R26) When specific dates or specific country-level data were not available, variants were estimated by the time frame of initial study submission and dominant strains in neighboring countries. Subgroup analyses were identified after pilot data extraction but prior to overall data extraction, and were used to refine the data extraction tool. The authors of studies missing key relevant information (such as TN, FN, TP, and FP) were contacted for additional information. If no reply was received on the first attempt, we attempted to contact the authors a second time. No additional information or data were retrieved from this effort.
### Data synthesis
Papers that reported the TP, FP, TN, and FN were pooled in statistical meta-analysis using the R statistical software (R Foundation for Statistical Computing, Vienna, Austria) packages meta[27](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R27) and dmetar.[28](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R28) Due to our custom data extraction tool, we were unable to utilize the JBI System for the Unified Management, Assessment and Review of Information (JBI SUMARI; JBI, Adelaide, Australia) software as initially planned.[18](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R18) Studies that did not include these 4 values were excluded from meta-analysis. As we expected this information to be included in all published studies, these criteria were not stated in our inclusion/exclusion criteria in the original protocol.[18](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R18) However, without these data, the combined accuracy data could not be accurately calculated. As an *a priori* decision, we only included RATs that were reported in at least 5 studies for the meta-analysis due to the minimum number of groups needed to fully benefit from the random-effects model in dmetar.[28](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R28) The pooled sensitivity, specificity, positive predictive, and negative predictive values were calculated assuming a random-effects model and presented with 95% CIs. The positive predictive and negative predictive values were calculated using the formulas TP/(TP+FP) and TN/(FN+TN) when not presented in the papers. Forest plots for the sensitivity and specificity were generated using the R package meta.[27](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R27) Potential subgroups that were proposed in our protocol included index tests used, symptomatic vs asymptomatic, and cycle threshold (Ct) values. Where statistical pooling was not possible, the findings were presented in narrative format, including tables and figures.
Heterogeneity was assessed using the *I* 2 value. When heterogeneity above 90% was observed, outlier analysis was conducted to identify studies contributing to overall heterogeneity. The R package dmetar was used to identify outliers based on their contribution to heterogeneity and the pooled value of the measurement.[28](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R28) This package examines the 95% CI of each study compared with the pooled 95% CI. When a study was removed, the data set was reanalyzed for heterogeneity. The results shown were generated by removing outliers. The code and the data used for data synthesis can be found at <https://github.com/skoshyc/covid_systematic_review_2023>.
### Assessing certainty in the evidence
The Summary of Findings were created using GRADEPro GDT software (McMaster University, ON, Canada).[29](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R29) The GRADE approach for grading the certainty of evidence for diagnostic test accuracy was used.[30](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R30) The following outcomes are included in the Summary of Findings: the review question; the index test names and types; the reference tests used; the population; the estimates of true negatives, true positives, false negatives, and false positives; the absolute difference between the index and reference tests for these values per 1000 patients; the sample size; the number of studies contained within the sample set; the GRADE (Grading of Recommendations Assessment, Development and Evaluation) quality of evidence for each finding; and any comments associated with the finding.
### Deviations from and clarifications to protocol
Title and abstract screening, full-text screening, critical appraisal, data extraction, and data synthesis were completed as described in our protocol[18](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R18) with the following exceptions.
#### Software and procedure flow
All steps were performed using Google Sheets set up specifically for our review. The full-text screening was adjusted to use a drop-down selection of prioritized reasons for exclusion. Reviewers selected the highest priority exclusion reason for excluded studies (Table [1](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#T1)). For critical appraisal, we used a drop-down setup for each question and the decision for inclusion or exclusion. The exclusions from the critical appraisal process were prioritized by question number from the JBI critical appraisal tool for diagnostic accuracy reviews.[25](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R25) We piloted and adjusted our data extraction tool using a subset of studies. This step was not specified in our published protocol.[18](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R18) We were not able to use JBI SUMARI due to our customized data extraction tool. We utilized R software with custom code instead. Rather than assessing heterogeneity visually as originally planned, we used the *I* 2 value. For the meta-analysis, we included only RATs reported in at least 5 studies.
##### Table 1.
Prioritized exclusion criteria for studies, as selected by reviewers during full-text screening
| | |
|---|---|
| 1 | Not RAT compared to RT-PCR |
| 2 | Results took more than 4 hours to determine after test was initiated |
| 3 | Diagnostic accuracy was not provided |
| 4 | Children were included in the analysis |
| 5 | Pregnant individuals were included in the analysis |
| 6 | Studies were dated prior to the emergence of COVID-19 |
| 7 | Study examined antibodies against COVID-19, not COVID-19 antigens |
| 8 | Test is incompatible with a standard primary care setting |
| 9 | Study is a review without primary data |
| 10 | Study is in a foreign language and not available in English |
| 11 | Duplicate article |
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/table/T1/)
RAT, rapid antigen test; RT-PCR, reverse transcriptase polymerase chain reaction.
#### Inclusion and exclusion criteria
We adjusted our inclusion/exclusion criteria to clarify several points. First, our protocol stated that we would exclude studies performed in non-primary care settings.[18](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R18) We included studies from non-primary care settings if the RAT being used could also be easily used in primary care settings. Instead, RATs that could not be performed in a primary care setting were excluded. Next, our protocol stated that the reference test considered was commercially available RT-PCR tests and that any RT-PCR test would be considered.[18](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R18) We considered and included studies where the reference test was a validated custom or in-house RT-PCR test. Third, we clarified that cross-sectional and cohort studies would be considered, but case-control studies were excluded for poor methodological quality.
## Results
### Study inclusion
A total of 3122 citations were identified from searches of databases and gray literature. After duplicates were removed through EndNote, 1204 records were screened for inclusion by title and abstract using JBI SUMARI (pilot search only) and Google Sheets. We examined the full text of 580 studies for inclusion based on our described criteria and excluded 319 (see Supplemental Digital Content 1, <http://links.lww.com/SRX/A55>. The most common reason for study exclusion was the inclusion of individuals younger than 18 years within the data set (n = 102). After removing studies based on our exclusion criteria, we critically appraised 261 studies. The primary reason for excluding studies after critical appraisal was the use of a case-control study design (n = 107 out of 118 excluded studies; see Supplemental Digital Content 2, <http://links.lww.com/SRX/A56>. After critical appraisal, we extracted data from 143 articles.[7](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R7),[8](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R8),[11](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R11),[31](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R31)â[170](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R170) From these articles, data from 91 studies were used for overall and subgroup analyses based on the data synthesis methods. See the full search results and study selection and inclusion process in Figure [1](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#F1).
### Methodological quality
The extracted studies had high certainty of evidence based on the GRADE analysis.[30](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R30) Given that we restricted our review to cross-sectional and cohort designs, all of the included studies began at âhighâ quality.
The majority of the studies had a low risk of bias based on the QUADAS-2 tool (Figure [2](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#F2) \[summary of risk of bias assessment\] and Supplemental Digital Content 3, <http://links.lww.com/SRX/A57> \[individual study analysis\]). While most papers stated that the reference test was performed at a different site or through a central public health laboratory, a few papers (16.0%) did not clearly indicate whether the reference test was interpreted without knowledge of the index test result (Q\#7). All studies used a validated RT-PCR as their reference test, but some papers (15.3%) used multiple RT-PCR kits (Q\#9). About 1 in 5 papers (20.8%) did not include all participants in their analysis (Q\#10). The reasons cited for these exclusions were a lost sample or inconclusive/invalid results on either the index or reference test.
#### Figure 2.
[](https://www.ncbi.nlm.nih.gov/core/lw/2.0/html/tileshop_pmc/tileshop_pmc_inline.html?title=Click%20on%20image%20to%20zoom&p=PMC3&id=11462910_srx-22-1939-g002.jpg)
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/figure/F2/)
Summary of risk of bias assessment of included studies. The percentage of included studies where the answer to each question from the QUADAS-2 tool25 was âyesâ (green, no stripes), ânoâ (red, diagonal stripes), or ânot clearâ (yellow, vertical stripes) are shown. Questions that required a âyesâ answer for the study to be included in the data extraction are not shown (\#2, \#3, \#6, and \#8).
The indirectness, publication bias, and impreciseness of the included studies represented minor or no concerns regarding the quality of evidence. The largest driver of the quality of evidence decrease was the high heterogeneity found across studies. This is discussed further in the review findings section.
### Characteristics of included studies
The studies included in our data extraction consisted of retrospective and prospective cohort studies and cross-sectional studies. In general, most studies collected a single subject sample that was used for the index and reference tests, or 2 samples were collected consecutively at the same encounter. On occasion, 2 samples were taken from different anatomical locations from the same subject (eg, a nasopharyngeal sample for RT-PCR and an anterior nares sample for RAT). Most studies used a design where the RAT was performed on-site with the participant, and the RT-PCR sample was stored cold and transferred to a central laboratory location. For some studies, the laboratory was on-site, such as a clinical laboratory associated with the hospital performing the study. However, many studies used central public health laboratories within their local health districts to perform the RT-PCR. A benefit of using a clinical laboratory instead of utilizing their own laboratory staff to run the RT-PCRs is that the clinical laboratory technicians are blinded to the RAT results because they are not involved in the study.
Where possible, we validated the reported sensitivity and specificity numbers in each study using the TP, FP, TN, and FN values. Not every study provided these numbers, so some reported sensitivity and specificity calculations could not be verified. The key findings of each paper are summarized in [Appendix III](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#A3).
The studies included in our meta-analysis were performed in a variety of settings (Table [2](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#T2)). The breadth of study locations demonstrates the generalizability of RATs across different levels of health care and the ease of use of these POC tests. While we focused on determining best practices for primary care settings, these findings are applicable to a wide range of health care locations.
#### Table 2.
Reported settings of included studies
| Location | \# of studies performed |
|---|---|
| COVID-19 testing site/screening location | 52 |
| Hospital - inpatient | 38 |
| Emergency department/room | 26 |
| College/university campus (medical center/hospital) | 25 |
| Hospital - outpatient | 15 |
| Primary care location | 15 |
| Not described/unclear | 8 |
| Long-term care facility (nursing home, rehab centers) | 5 |
| Public area (not a designated screening location) | 5 |
| College/university campus (non-medical) | 4 |
| Urgent care location | 1 |
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/table/T2/)
The studies were conducted in 44 countries across 6 continents starting in March 2020 through our search date in July 2022 (Figure [3](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#F3)A). We generated heatmaps showing the locations of dominant variants based on the countries of the studies (Figure [3](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#F3)B-D). Studies from the Beta and Gamma waves were less common (not shown). We had few studies completed during the dominance of the Omicron variants due to the dates of our searches (not shown).
#### Figure 3.
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/figure/F3/)
Maps of study locations. The heatmaps show the geography of the studies included in this review, illustrating the global nature of COVID-19 rapid antigen tests. (A) The number of included studies from each country is shown by heatmap. (BâD) The number of included studies from each country with data collected during the dominance of the Ancestral (B), Alpha (C), and Delta (D) strains of SARS-CoV-2 are shown by heatmap. Gray indicates that no included studies came from that country.
The included studies resulted in a total participant number of 212,874. There were 139 papers that either specified the number of participants, the number of samples, or both (Figure [4](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#F4)). The number of participants or samples ranged from 42 to 18,457, with a median of 635 participants. Overall, the studies included in the meta-analysis all shared the general design of testing subjectsâ samples collected at the same time with both RAT and RT-PCR.
#### Figure 4.
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/figure/F4/)
Numbers of participants/samples per included study. Studies were grouped by the number of participants. The number of studies for each group is shown.
The studies included in the analysis listed 50 commercially available RATs, whereas 3 studies described novel tests that were not yet commercially available ([Appendix IV](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#A4)). Tests reported in fewer than 5 studies were excluded from the meta-analysis, as described in the methods.[28](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R28) The reported diagnostic accuracy data for all studies can be found in [Appendix III](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#A3). Most studies reported using nasopharyngeal swabs to acquire the test sample (Table [3](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#T3)). Many studies reported using multiple sample sites in their analysis. However, few studies compared the accuracy of the tests from multiple sample sites.
#### Table 3.
Sample types collected for COVID-19 testing, as reported in included studies
| Sample type | \# of studies |
|---|---|
| Nasopharyngeal swabs | 128 |
| Oropharyngeal swabs/throat swabs | 41 |
| Nasal swabs | 37 |
| Other | 8 |
| Saliva | 7 |
| Blood | 2 |
| Bronchoalveolar lavage/bronchial sample | 1 |
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/table/T3/)
We did not restrict the use of reference tests to a specific manufacturer or target. The studies used a variety of RT-PCR tests as their reference test. All reference tests were either commercially available RT-PCRs or in-house primers based on national or international public health organization recommendations. Many studies used multiple reference tests due to the availability of the tests over the course of their studies. The most commonly reported reference test was the Roche cobas systems, with 30 studies reporting its use. Other common reference tests were Allplex assays by Seegene (23 studies), TaqPath assays by ThermoFisher (18 studies), and Xpert Xpress/GeneXpert assays by Cepheid (19 studies ). Seventeen studies reported a custom or in-house PCR assay based on published primers, and 15 studies did not report a specific RT-PCR assay.
### Review findings
We compared the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for each index test across the published studies. A total of 91 studies were used for synthesis, as those studies provided the TP, FP, TN, and FN values.[8](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R8),[11](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R11),[32](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R32)â[34](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R34),[36](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R36)â[40](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R40),[46](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R46)â[49](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R49),[53](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R53)â[55](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R55),[58](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R58)â[60](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R60),[63](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R63),[66](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R66),[68](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R68),[71](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R71),[72](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R72),[74](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R74),[76](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R76)â[79](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R79),[81](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R81)â[88](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R88),[90](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R90),[93](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R93)â[95](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R95),[98](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R98)â[101](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R101),[103](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R103),[104](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R104),[106](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R106)â[108](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R108),[110](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R110),[115](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R115),[117](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R117),[118](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R118),[120](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R120),[123](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R123),[124](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R124),[127](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R127)â[129](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R129),[131](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R131)â[137](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R137),[140](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R140),[142](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R142),[143](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R143),[148](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R148),[150](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R150)â[157](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R157),[159](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R159)â[169](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R169) For the analysis of the index test, we considered the entries from the paper that specified the overall accuracy of the test across their entire study population.
We only included index tests examined in at least 5 studies for the pooled sensitivity, specificity, PPV, and NPV, which are shown in the forest plots. The tests meeting this criterion were STANDARD Q COVID-19 Ag Test (SD Biosensor; 27 studies), PanBio COVID-19 Ag Rapid Test Device (Abbott; 14 studies), SARS-CoV-2 Rapid Antigen Test (Roche Diagnostics; 11), and BinaxNOW COVID-19 Antigen (Abbott; 10 studies). All tests that were considered are listed in [Appendix IV](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#A4).
We considered the studies that were outliers in the pooled analysis. An outlier was defined as described in the methods. On removing the outliers, we observed that overall heterogeneity reduced considerably.
#### Sensitivity
The maximum sensitivity reported was 100%, which included the Flowflex COVID-19 Antigen test (ACON Labs) and STANDARD Q COVID-19 Ag Test (SD Biosensor; [Appendix IV](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#A4)). The heterogeneity of the data set was high when we considered the included studies,[11](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R11),[32](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R32)â[34](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R34),[36](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R36)â[39](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R39),[46](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R46),[48](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R48),[49](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R49),[55](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R55),[58](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R58),[59](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R59),[63](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R63),[66](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R66),[71](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R71),[76](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R76),[77](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R77),[79](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R79),[83](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R83)â[87](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R87),[93](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R93),[98](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R98),[99](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R99),[101](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R101),[103](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R103),[107](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R107),[108](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R108),[118](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R118),[123](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R123),[124](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R124),[127](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R127)â[129](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R129),[131](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R131),[132](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R132),[134](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R134)â[136](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R136),[142](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R142),[150](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R150),[151](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R151),[154](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R154),[155](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R155),[160](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R160),[161](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R161),[165](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R165),[166](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R166),[168](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R168),[169](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R169) as indicated by an *I* 2 value of 94.6% (95% CI 93.6â95.4%). The pooled sensitivity of these data was 67.0% (95% CI 62.6â71.1%). Each testâs pooled sensitivity is shown in Table [4](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#T4).
##### Table 4.
Pooled sensitivity of index tests (point-of-care SARS-CoV-2 rapid antigen tests), with outliers (as identified based on their contribution to heterogeneity)
| Test name | \# of studies | Pooled sensitivity | 95% CI | *I* 2 |
|---|---|---|---|---|
| STANDARD Q COVID-19 Ag (SD Biosensor) | 27 | 66\.0% | 59\.2-72.2% | 95\.3% |
| PanBio (Abbott) | 13 | 70\.2% | 61\.0-78.0% | 92\.7% |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 11 | 69\.3% | 61\.2-76.4% | 83\.1% |
| BinaxNOW (Abbott) | 10 | 62\.3% | 49\.4-73.6% | 94\.2% |
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/table/T4/)
On removing the outliers, the pooled sensitivity was 66.7% (95% CI 63.4â69.8%), with an *I* 2 value of 70.4%.[11](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R11),[32](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R32)â[34](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R34),[36](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R36),[39](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R39),[46](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R46),[48](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R48),[49](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R49),[55](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R55),[58](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R58),[66](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R66),[71](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R71),[76](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R76),[79](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R79),[84](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R84),[87](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R87),[107](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R107),[108](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R108),[118](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R118),[127](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R127)â[129](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R129),[131](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R131),[132](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R132),[134](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R134),[136](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R136),[142](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R142),[154](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R154),[169](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R169) The updated test subgroup results are shown in Table [5](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#T5). The individual sensitivities reported for the 4 tests included in the pooled analysis are shown in Figure [5](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#F5) (outliers removed). The high heterogeneity is still present in the large discrepancies in reported sensitivities and 95% CIs.
##### Table 5.
Pooled sensitivity of index tests (point-of-care SARS-CoV-2 rapid antigen tests), without outliers (as identified based on their contribution to heterogeneity)
| Test name | \# of studies | Pooled sensitivity | 95% CI | *I* 2 |
|---|---|---|---|---|
| STANDARD Q COVID-19 Ag (SD Biosensor) | 15 | 65\.4% | 61\.1-69.4% | 70\.0% |
| PanBio (Abbott) | 6 | 71\.0% | 64\.6-76.6% | 73\.8% |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 7 | 68\.5% | 60\.3-75.7% | 73\.3% |
| BinaxNOW (Abbott) | 2 | 54\.7% | 46\.0-63.1% | 0\.0% |
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/table/T5/)
##### Figure 5.
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/figure/F5/)
Diagnostic accuracy of COVID-19/SARS-CoV-2 infectionâsensitivity forest plot for the overall cohort. The forest plot shows the sensitivities and 95% CIs reported for the STANARD Q COVID-19 Ag Test (SD Biosensor), PanBio (Abbott), Roche SARS-CoV-2 Rapid Antigen Test (Roche), and BinaxNOW (Abbott) index tests (point-of-care SARS-CoV-2 rapid antigen tests) after outlier studies were removed. Pooled sensitivity and heterogeneity value (I2) for each index test are shown at the bottom of each test section. The pooled sensitivity and 95% CI of all reported tests on the forest plot are shown at the bottom. The vertical line at 0.671 represents the pooled sensitivity value for all shown tests. Boxes represent the reported sensitivity, and solid horizontal lines represent the 95% CI reported by each study.
#### Specificity
The maximum specificity recorded was 100%, and there were 27 index tests that had this value ([Appendix IV](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#A4)). As in the case of the sensitivity, the heterogeneity of the data set when we consider the included studies was high, as indicated by an *I* 2 value of 93.7% (95% CI 92.5â94.6%). The pooled specificity of these data was 99.6% (95% CI 99.3â99.8%).[11](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R11),[32](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R32)â[34](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R34),[36](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R36)â[39](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R39),[46](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R46),[48](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R48),[49](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R49),[55](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R55),[58](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R58),[59](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R59),[63](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R63),[66](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R66),[71](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R71),[76](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R76),[77](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R77),[79](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R79),[83](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R83)â[87](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R87),[93](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R93),[98](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R98),[99](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R99),[101](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R101),[103](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R103),[107](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R107),[108](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R108),[118](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R118),[123](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R123),[124](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R124),[127](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R127)â[129](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R129),[131](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R131),[132](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R132),[134](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R134)â[136](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R136),[142](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R142),[150](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R150),[151](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R151),[154](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R154),[155](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R155),[160](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R160),[161](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R161),[165](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R165),[166](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R166),[168](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R168),[169](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R169) Each testâs pooled specificity is shown in Table [6](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#T6).
##### Table 6.
Pooled specificity of index tests (point-of-care SARS-CoV-2 rapid antigen tests), with outliers (as identified based on their contribution to heterogeneity)
| Test name | \# of studies | Pooled specificity | 95% CI | *I* 2 |
|---|---|---|---|---|
| STANDARD Q COVID-19 Ag (SD Biosensor) | 27 | 99\.2% | 98\.4-99.6% | 95\.0% |
| PanBio (Abbott) | 13 | 99\.9% | 99\.6-100% | 62\.9% |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 11 | 99\.8% | 98\.9%-100% | 93\.8% |
| BinaxNOW (Abbott) | 10 | 99\.8% | 99\.5-99.9% | 87\.8% |
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/table/T6/)
On removing the outliers, the pooled specificity was 99.8% (95% CI 99.7â99.9%), with an *I* 2 value of 40.4%.[32](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R32)â[34](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R34),[36](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R36),[46](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R46),[49](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R49),[55](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R55),[58](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R58),[63](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R63),[66](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R66),[71](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R71),[77](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R77),[79](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R79),[83](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R83),[84](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R84),[87](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R87),[93](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R93),[99](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R99),[101](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R101),[103](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R103),[107](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R107),[108](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R108),[118](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R118),[123](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R123),[124](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R124),[129](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R129),[131](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R131),[132](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R132),[134](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R134)â[136](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R136),[142](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R142),[150](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R150),[154](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R154),[155](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R155),[166](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R166),[168](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R168),[169](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R169) The updated test subgroup results are shown in Table [7](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#T7). The individual specificities reported for the 4 tests included in the pooled analysis are shown in Figure [6](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#F6) (outliers removed). The high heterogeneity is still present in the large discrepancies in reported specificities and 95% CIs.
##### Table 7.
Pooled specificity of index tests (point-of-care SARS-CoV-2 rapid antigen tests), without outliers (as identified based on their contribution to heterogeneity)
| Test name | \# of studies | Pooled specificity | 95% CI | *I* 2 |
|---|---|---|---|---|
| STANDARD Q COVID-19 Ag (SD Biosensor) | 16 | 99\.6% | 99\.4-99.7% | 46\.7% |
| PanBio (Abbott) | 10 | 99\.9% | 99\.8-100.0% | 0\.0% |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 7 | 99\.9% | 99\.5-100.0% | 0\.0% |
| BinaxNOW (Abbott) | 6 | 99\.9% | 99\.7-100.0% | 16\.0% |
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/table/T7/)
##### Figure 6.
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/figure/F6/)
Diagnostic accuracy of COVID-19/SARS-CoV-2 infectionâspecificity forest plot for the overall cohort. The forest plot shows the specificities and 95% CIs reported for the STANARD Q COVID-19 Ag Test (SD Biosensor), PanBio (Abbott), Roche SARS-CoV-2 Rapid Antigen Test (Roche), and BinaxNOW (Abbott) index tests after outlier studies were removed. Pooled specificity and heterogeneity value (I2) for each index test are shown at the bottom of each test section. The pooled specificity and 95% CI of all reported tests on the forest plot are shown at the bottom. The vertical line at 0.996 represents the pooled specificity value for all shown tests. Boxes represent the reported specificity, and solid horizontal lines represent the 95% CI reported by each study.
#### Positive predictive value
The maximum recorded PPV was 100%, and there were 21 index tests that reported this value in at least 1 study ([Appendix IV](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#A4)). To obtain the pooled PPV, we assumed the formula PPV = TP/(TP + FP), as most papers stated it this way. After removing outliers, as with sensitivity and specificity, we obtained a pooled PPV value of 97.7% (95% CI 96.8â98.4%) and *I* 2 value of 0.0% (95% CI 0.0â34.8%).[11](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R11),[32](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R32)â[34](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R34),[36](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R36),[39](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R39),[46](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R46),[49](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R49),[55](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R55),[58](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R58),[63](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R63),[71](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R71),[77](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R77),[79](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R79),[83](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R83),[85](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R85),[87](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R87),[93](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R93),[99](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R99),[101](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R101),[103](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R103),[107](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R107),[108](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R108),[118](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R118),[123](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R123),[124](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R124),[129](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R129),[131](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R131),[132](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R132),[134](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R134)â[136](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R136),[142](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R142),[150](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R150),[151](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R151),[154](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R154),[155](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R155),[160](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R160),[161](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R161),[168](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R168),[169](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R169) The forest plot for the PPVs is shown in Figure [7](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#F7). Each testâs pooled PPV is shown in Table [8](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#T8).
##### Figure 7.
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/figure/F7/)
Diagnostic accuracy of COVID-19/SARS-CoV-2 infectionâpositive predictive values forest plot. The forest plot shows the positive predictive values (PPVs) and 95% CIs reported for the STANDARD Q (SD Biosensor), PanBio (Abbott), Roche SARS-CoV-2 Rapid Antigen Test (Roche), and BinaxNOW (Abbott) index tests after outlier studies were removed. Pooled PPV and heterogeneity value (I2) for each index test is shown at the bottom of each test section. The pooled PPV and 95% CI of all reported tests on the forest plot are shown at the bottom. The vertical line at 0.962 represents the pooled PPV for all shown tests. Boxes represent the reported PPV, and solid horizontal lines represent the 95% CI reported by each study. Some studies reported multiple sites and are included as an individual row for each site.
##### Table 8.
Pooled positive predictive values of index tests (point-of-care SARS-CoV-2 rapid antigen tests), without outliers (as identified based on their contribution to heterogeneity)
| Test name | \# of studies | Pooled PPV | 95% CI | *I* 2 |
|---|---|---|---|---|
| STANDARD Q COVID-19 Ag (SD Biosensor) | 18 | 96\.3% | 94\.8-97.4% | 24\.1% |
| PanBio (Abbott) | 12 | 98\.9% | 97\.4-99.5% | 0\.0% |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 8 | 98\.6% | 94\.4-99.6% | 0\.0% |
| BinaxNOW (Abbott) | 6 | 97\.3% | 92\.3-99.1% | 0\.0% |
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/table/T8/)
PPV, positive predictive value.
#### Negative predictive value
The maximum value was 100%, and included the Flowflex COVID-19 Antigen test (ACON Labs) and STANDARD Q COVID-19 Ag Test (SD Biosensor). To obtain the pooled NPV, we assumed the formula NPV = TN/(TN + FN), as most papers stated it this way. After removing outliers, as with sensitivity and specificity, we obtained a pooled NPV value of 95.2% (95% CI 94.3â95.9%) and *I* *2* value of 81.7% (95% CI 73.3â87.5%; see Table [9](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#T9) and Figure [8](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#F8)).[34](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R34),[36](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R36),[37](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R37),[46](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R46),[49](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R49),[58](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R58),[63](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R63),[76](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R76),[77](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R77),[83](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R83),[87](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R87),[98](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R98),[99](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R99),[118](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R118),[127](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R127)â[129](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R129),[131](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R131),[132](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R132),[136](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R136),[154](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R154),[168](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R168) The BinaxNOW (Abbott) subgroup of papers was excluded, as they all contributed substantially to the heterogeneity.
##### Table 9.
Pooled negative predictive values of index tests (point-of-care SARS-CoV-2 rapid antigen tests), without outliers (as identified based on their contribution to heterogeneity)
| Test name | \# of studies | Pooled NPV | 95% CI | *I* 2 |
|---|---|---|---|---|
| STANDARD Q COVID-19 Ag (SD Biosensor) | 15 | 95\.3% | 94\.0-96.2% | 84\.1% |
| PanBio (Abbott) | 4 | 95\.1% | 92\.9-96.6% | 87\.2% |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 3 | 94\.9% | 94\.0-95.7% | 39\.3% |
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/table/T9/)
NPV, negative predictive value.
##### Figure 8.
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/figure/F8/)
Diagnostic accuracy of COVID-19/SARS-CoV-2 infectionânegative predictive value forest plot. The forest plot shows the negative predictive value (NPV) and 95% CIs reported for the STANDARD Q (SD Biosensor), PanBio (Abbott), Roche SARS-CoV-2 Rapid Antigen Test (Roche), and BinaxNOW (Abbott) index tests after outlier studies were removed. Pooled NPV and heterogeneity value (I2) for each index test is shown at the bottom of each test section. The pooled NPV and 95% CI of all reported tests on the forest plot are shown at the bottom. The vertical line at 0.949 represents the pooled NPV for all shown tests. Boxes represent the reported value, and solid horizontal lines represent the 95% CI reported by each study. Some studies reported multiple sites and are included as an individual row for each site.
#### Symptomatic test subgroup
The protocols for testing and screening have changed over the course of the pandemic, and now widespread testing is uncommon. Symptom presentation has now replaced screening tests for most locations and businesses. Taking this into consideration, we performed an additional analysis of studies that reported subgroups of symptomatic and asymptomatic individuals. The symptomatic subgroup diagnostic accuracy may be the most relevant cohort for primary care settings, as most asymptomatic individuals will not present to their primary care providers to be screened for COVID-19.
We found differences in the accuracy of the index tests in subjects who were symptomatic or asymptomatic. There were 9 studies that examined symptomatic[34](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R34),[99](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R99),[103](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R103),[118](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R118),[128](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R128),[150](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R150),[160](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R160),[165](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R165),[166](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R166) and 11 studies that examined asymptomatic[34](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R34),[84](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R84),[99](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R99),[103](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R103),[118](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R118),[128](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R128),[135](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R135),[149](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R149),[150](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R150),[165](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R165),[166](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R166) subgroups, and provided the values used to calculate accuracy values (TP, FP, TN, and FN). If there was only 1 study in the group, *I* 2 was reported as âNA.â As with the overall analysis of the studies, there was high heterogeneity between the studies. Due to fewer studies reporting these subgroups, we did not have enough studies to remove outliers from these analyses. The symptomatic subgroups showed higher overall levels of sensitivity compared to the overall group (Table [10](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#T10) and Figure [9](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#F9)A). Specificity was slightly lower in the symptomatic subgroup than in the overall group (Table [10](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#T10) and Figure [9](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#F9)B). The symptomatic subgroup also had a slightly lower PPV and NPV (Table [11](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#T11)) compared with the overall group (Figure [10](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#F10)).
##### Table 10.
Sensitivity and specificity of index tests (point-of-care SARS-CoV-2 rapid antigen tests) in the symptomatic subgroup
| Test name | \# of studies | Sensitivity (95% CI) *I* 2 | Specificity (95% CI) *I* 2 |
|---|---|---|---|
| STANDARD Q COVID-19 Ag (SD Biosensor) | 4 | 78\.2% (58.7â90.0%) 96\.1% | 98\.4% (94.9â99.5%) 74\.9% |
| PanBio (Abbott) | 2 | 78\.0% (61.0â88.9%) 90\.7% | 99\.9% (99.3â100%) 0\.0% |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 2 | 81\.2% (76.2â85.5%) 0\.0% | 99\.6% (97.4â99.9%) 0\.0% |
| BinaxNOW (Abbott) | 1 | 86\.7% (79.7â91.9%) NA | 98\.8% (97.4â99.6%) NA |
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/table/T10/)
NA, not applicable.
##### Figure 9.
[](https://www.ncbi.nlm.nih.gov/core/lw/2.0/html/tileshop_pmc/tileshop_pmc_inline.html?title=Click%20on%20image%20to%20zoom&p=PMC3&id=11462910_srx-22-1939-g009.jpg)
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/figure/F9/)
Diagnostic accuracy of COVID-19/SARS-CoV-2 infectionâsensitivity and specificity forest plots for symptomatic subgroup. Forest plot shows the sensitivities (A) and specificities (B) and 95% CIs reported for the symptomatic subgroup for the STANDARD Q (SD Biosensor), PanBio (Abbott), Roche SARS-CoV-2 Rapid Antigen Test (Roche), and BinaxNOW (Abbott) index tests after outlier studies were removed. Pooled values and heterogeneity value (I2) for each index test are shown at the bottom of each test section. The pooled values and 95% CI of all reported tests on each forest plot are shown at the bottom. The vertical lines at 0.804 (sensitivity) and 0.994 (specificity) represent the pooled values for all shown tests. Boxes represent the reported sensitivity and specificity, and solid horizontal lines represent the 95% CI reported by each study.
##### Table 11.
Positive and negative predictive values of index tests (point-of-care SARS-CoV-2 rapid antigen tests) in the symptomatic subgroup
| Test name | \# of studies | Pooled PPV (95% CI) *I* 2 | Pooled NPV (95% CI) *I* 2 |
|---|---|---|---|
| STANDARD Q COVID-19 Ag (SD Biosensor) | 4 | 92\.1% (85.9-95.6%) 63\.2% | 94\.7% (89.0-97.5%) 93\.8% |
| PanBio (Abbott) | 2 | 99\.5% (96.3-99.9%) 0\.0% | 95\.5% (86.1-98.6%) 96\.5% |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 2 | 98\.7% (95.9-99.6%) 0\.0% | 93\.7% (85.0-97.5%) 92\.4% |
| BinaxNOW (Abbott) | 1 | 95\.1% (89.7-98.2%) NA | 96\.5% (94.6-97.9%) NA |
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/table/T11/)
NA, not applicable; NPV, negative predictive value; PPV, positive predictive value.
##### Figure 10.
[](https://www.ncbi.nlm.nih.gov/core/lw/2.0/html/tileshop_pmc/tileshop_pmc_inline.html?title=Click%20on%20image%20to%20zoom&p=PMC3&id=11462910_srx-22-1939-g010.jpg)
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/figure/F10/)
Diagnostic accuracy of COVID-19/SARS-CoV-2 infectionâpositive predictive value and negative predictive value forest plots for symptomatic subgroup. Forest plot shows the positive (A) and negative (B) predictive values (PPV/NPV) and 95% CIs reported for the symptomatic subgroups of the STANDARD Q (SD Biosensor), PanBio (Abbott), Roche SARS-CoV-2 Rapid Antigen Test (Roche), and BinaxNOW (Abbott) index tests after outlier studies were removed. Pooled values and heterogeneity values (I2) for each index test are shown at the bottom of each test section. The pooled values and 95% CI of all reported tests on the forest plot are shown at the bottom. The vertical lines at 0.971 (PPV) and 0.950 (NPV) represent the pooled values for all shown tests. Boxes represent the reported values, and solid horizontal lines represent the 95% CI reported by each study.
#### Asymptomatic test subgroup
Asymptomatic test performance is relevant in any screening situation. The asymptomatic samples resulted in overall lower sensitivity in the RATs (Table [12](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#T12) and Figure [11](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#F11)A), although specificity remained high (Table [12](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#T12) and Figure [11](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#F11)B).[34](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R34),[84](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R84),[99](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R99),[103](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R103),[118](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R118),[128](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R128),[135](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R135),[149](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R149),[150](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R150),[165](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R165),[166](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R166) The PPV was lower in the asymptomatic group compared with the symptomatic and overall groups. However, the NPV remained similar between the 3 groups. Additional information about the PPV and NPV for this subgroup can be found in Table [13](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#T13) and Figure [12](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#F12).
##### Table 12.
Sensitivity and specificity of index tests (point-of-care SARS-CoV-2 rapid antigen tests) in the asymptomatic subgroup
| Test name | \# of studies | Sensitivity (95% CI) *I* 2 | Specificity (95% CI) *I* 2 |
|---|---|---|---|
| STANDARD Q COVID-19 Ag (SD Biosensor) | 5 | 43\.8% (30.4-58.2%) 86\.3% | 99\.6% (99.4-99.7%) 0\.0% |
| PanBio (Abbott) | 3 | 57\.7% (29.1-81.9%) 78\.5% | 100\.0% (0.0-100.0%) 0\.0% |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 1 | 58\.8% (44.2-72.4%) NA | 100\.0% (99.1-100.0%) NA |
| BinaxNOW (Abbott) | 2 | 70\.8% (62.9-77.7%) 0\.0% | 99\.8% (99.5-99.9%) 72\.8% |
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/table/T12/)
NA, not applicable.
##### Figure 11.
[](https://www.ncbi.nlm.nih.gov/core/lw/2.0/html/tileshop_pmc/tileshop_pmc_inline.html?title=Click%20on%20image%20to%20zoom&p=PMC3&id=11462910_srx-22-1939-g011.jpg)
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/figure/F11/)
Diagnostic accuracy of COVID-19/SARS-CoV-2 infectionâsensitivity and specificity forest plots for asymptomatic subgroup. Forest plot shows the sensitivities (A) and specificities (B) and 95% CIs reported for the asymptomatic subgroup for the STANDARD Q (SD Biosensor), PanBio (Abbott), Roche SARS-CoV-2 Rapid Antigen Test (Roche), and BinaxNOW (Abbott) index tests after outlier studies were removed. Pooled values and heterogeneity value (I2) for each index test are shown at the bottom of each test section. The pooled values and 95% CI of all reported tests on each forest plot are shown at the bottom. The vertical lines at 0.537 (sensitivity) and 0.998 (specificity) represent the pooled values for all shown tests. Boxes represent the reported sensitivity and specificity, and solid horizontal lines represent the 95% CI reported by each study.
##### Table 13.
Positive and negative predictive values of index tests (point-of-care SARS-CoV-2 rapid antigen tests) in the asymptomatic subgroup
| Test name | \# of studies | PPV (95% CI) *I* 2 | NPV (95% CI) *I* 2 |
|---|---|---|---|
| STANDARD Q COVID-19 Ag (SD Biosensor) | 5 | 80\.4% (72.2-86.7%) 36\.4% | 97\.7% (95.1-98.9%) 97\.2% |
| PanBio (Abbott) | 3 | 100\.0% (0.0-100.0%) 0\.0% | 99\.1% (93.0-99.9%) 97\.4% |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 1 | 100\.0% (88.4-100.0%) NA | 95\.2% (92.7-97.0%) NA |
| BinaxNOW (Abbott) | 2 | 90\.3% (83.3-94.5%) 0\.0% | 99\.1% (97.7-99.7%) 95\.0% |
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/table/T13/)
NA, not applicable; NPV, negative predictive value; PPV, positive predictive value.
##### Figure 12.
[](https://www.ncbi.nlm.nih.gov/core/lw/2.0/html/tileshop_pmc/tileshop_pmc_inline.html?title=Click%20on%20image%20to%20zoom&p=PMC3&id=11462910_srx-22-1939-g012.jpg)
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/figure/F12/)
Diagnostic accuracy of COVID-19/SARS-CoV-2 infectionâpositive predictive value and negative predictive value forest plots for asymptomatic subgroup. Forest plot shows the positive (A) and negative (B) predictive values (PPV/NPV) and 95% CIs reported for the asymptomatic subgroups of the STANDARD Q (SD Biosensor), PanBio (Abbott), Roche SARS-CoV-2 Rapid Antigen Test (Roche), and BinaxNOW (Abbott) index tests after outlier studies were removed. Pooled values and heterogeneity values (I2) for each index test are shown at the bottom of each test section. The pooled values and 95% CI of all reported tests on the forest plot are shown at the bottom. The vertical lines at 0.904 (PPV) and 0.983 (NPV) represent the pooled values for all shown tests. Boxes represent the reported values, and solid horizontal lines represent the 95% CI reported by each study.
#### Summary of Findings
Based on our meta-analysis, Rocheâs SARS-CoV-2 Rapid Antigen Test and Abbottâs BinaxNOW tests meet the WHOâs recommendation of minimum diagnostic accuracy for symptomatic individuals (⼠80% sensitivity and ⼠97% specificity)[171](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R171) and can be reliably used in primary care settings (see the Summary of Findings). Other tests may also meet this standard, but we did not find sufficient studies for other tests. In the Summary of Findings, the effect per 1000 patients tested and certainty of evidence for test accuracy are shown for symptomatic adults using STANDARD Q, PanBio, Roche, and BinaxNOW.
Overall, RATs can identify individuals who have COVID-19 with high reliability when considering overall performance. However, the lower levels of sensitivity suggest that negative tests likely need to be retested through an additional method, such as RT-PCR or repeat testing over several days, when COVID-19 is suspected. Positive tests are highly likely to correctly diagnose SARS-CoV-2 infections, and based on our analyses, we recommend treating those patients as having a COVID-19 diagnosis. These results are likely driven by the symptomatic subject data, as subgroup analysis found higher reliability in symptomatic individuals than in asymptomatic individuals.
Considering only symptomatic individuals, RATs have a higher performance in correctly identifying negative cases, with similar reliability for detecting cases through a positive result. However, a sensitivity of 80% means that 1 in 5 people with a negative RAT have a false-negative result. Thus, negative COVID-19 RAT results in symptomatic patients should be interpreted with caution. As the symptomatic analysis of BinaxNOW included a single study and the same analysis of Rocheâs test had only 2 studies, more studies are needed to confirm these findings.
## Discussion
Rapid antigen tests are an important tool in infectious disease control. RATs are less expensive, require less expertise, and are better indicators of infectious virus than the gold standard diagnostic of RT-PCR.[5](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R5) RATs have limitations in their performance, including large discrepancies in diagnostic accuracy depending on the situation in which they are used.
### Discrepancies across studies and with manufacturer reported results
Of significant concern is the discrepancy between the manufacturerâs listed diagnostic accuracy and the accuracy found in this analysis. Based on the published accuracies on the manufacturersâ websites, the manufacturers overestimate the accuracy of their tests.[172](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R172)â[175](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R175) Our meta-analysis found the pooled sensitivity of the SD Biosensor STANDARD Q test to be 66.1%, while the manufacturerâs website lists the sensitivity as 85.0%.[175](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R175) For the Abbott tests, the pooled sensitivity from our analysis was 71.0% and 54.7% for PanBio and BinaxNOW tests, respectively. The product pages from the Abbott website list the sensitivities as 91.1% for PanBio and 84.6% for BinaxNOW.[172](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R172),[173](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R173) Roche specifies that their listed sensitivity is for Ct values \< 30 and reports a specificity of 95.5%[174](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R174) compared with our overall pooled sensitivity of 68.5%. These discrepancies can increase the errors in medical practice by falsely increasing the confidence providers have in the various RATs. The differences in accuracy between the collected studies, our meta-analysis, and the manufacturerâs reported values are likely driven by the same factors that may have contributed to the high heterogeneity in our results.
### Potential sources of heterogeneity
We found high heterogeneity across the studies included in our data extraction and meta-analysis. Potential sources of heterogeneity could include the prevalence of the virus during each studyâs data collection phase, the access to various manufacturersâ RATs, and the skill level at which the sample was taken.[176](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R176),[177](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R177) Additionally, the level of infection within each subject will vary greatly depending on their previous immunity, the day post-exposure, or the day post-symptom compared to when the RAT was performed.
Gold standard is RT-PCR but the threshold for a positive result varies by manufacturer and kit. While all reference tests were performed by qualified individuals based on reporting in the studies, the conditions in which the tests were performed are not reflective of ideal conditions. The number of samples that needed processing at a single time, as well as the general increased sense of urgency felt by public health employees, may have resulted in heterogeneity across the reference samples, which would increase heterogeneity across the sensitivity and specificity.
Variants that alter the test epitope can change the accuracy of the RATs. The accuracy of the RATs decreased as the variants mutated further from the Ancestral strain.[178](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R178) A recent study of RATs intended for Delta and Omicron variant detection found no differences in sensitivity,[179](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R179) while other studies have found a decrease in sensitivity between these 2 variants.[178](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R178) However, the tests in our review were developed and intended for use with the Ancestral strain. We examined the time frame and dominant variants of our studies to address this question. Further work is needed to have a better understanding of how changes in SARS-CoV-2 proteins affect RAT sensitivity. As novel variants emerge with distinct proteins (epitopes), the accuracy of the RATs will need to be reassessed.
### Clinical significance of symptomatic and asymptomatic testing
The relevance of asymptomatic testing is lower than in symptomatic individuals because asymptomatic individuals are unlikely to present in a primary care setting. The individuals most likely to present in our target setting of primary care are those who are symptomatic. However, asymptomatic testing may continue in some contexts, such as during outbreaks, prior to certain elective procedures, or as part of ongoing surveillance and epidemiological efforts. The lower accuracy in the RATs in the asymptomatic context could lead to additional viral spread because of a false-negative result. Given the reduced accuracy, health care providers should interpret a negative result with caution and follow-up with RT-PCR testing for cases with a high suspicion of infection. The likelihood of a negative result from a RAT to be a true negative is dependent on disease prevalence in the patientâs community. Health care practitioners in areas with high disease prevalence (10%) at the time of testing should assume that a negative result is positive 2.4% of the time. These situations make the overall test performance, and subgroup analyses of symptomatic and asymptomatic individuals, relevant across multiple health care settings.
Other systematic reviews of diagnostic accuracy have also noted similar sensitivity for symptomatic and asymptomatic cohorts.[180](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R180),[181](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R181) These studies associated viral load as measured by RT-PCR Ct value with the positivity of the RATs.[180](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R180),[181](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R181) The lower the Ct value, the more likely a RAT would detect the presence of viral protein.[180](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R180),[181](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R181) Conflicting studies have reported similar and disparate Ct values in asymptomatic compared with symptomatic individuals (reviewed in Puhach *et al*.[5](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R5)). Asymptomatic individuals are considered to be major sources of transmission due to behavior changes when an individual develops symptoms.[182](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R182) Additional studies are needed to understand the connection between detectable viral protein via RATs, Ct values determined by RT-PCR, and transmission as measured by cell culture assays, because the clear difference in RAT performance between symptomatic and asymptomatic subjects does not align with the comparative Ct values[5](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R5) and cell culture positivity[182](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R182) previously reported.
### Limitations of this review
One limitation of the review was that, due to author language proficiencies, the search strategies were limited to studies published in English. Records not available in English were not included in the review.
Heterogeneity can be studied and addressed in multiple ways, including outlier analysis and removal. The underlying source of heterogeneity is not immediately detectable in the data found within the studies and this could be investigated further. The high heterogeneity was an unexpected result. Revisions of this systematic review and meta-analysis could use a more stringent approach to reduce heterogeneity or better identify its sources through a different data extraction tool. Further, with additional collected data, more nuanced subgroup analyses could be performed.
Tied to symptom presentation, viral load has also been shown to impact RAT accuracy, with higher Ct values (lower viral loads) associated with decreased test accuracy.[180](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R180),[181](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R181) Our review did not examine the subgroups of Ct values, which is a limitation of our review. A challenge with subdividing the collected data from the included studies is that the studies that reported values for various Ct values divided their data in different ways. The lack of consistent division makes grouping for meta-analysis challenging. Further, the Ct values across different reference tests may not be comparable. Each kit, primer set, and polymerase used to complete an RT-PCR reference test may vary in their specificity and sensitivity.[183](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R183) The Ct values that are reported are dependent on reference test reagent efficiency as well as the sampleâs viral RNA load.[183](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R183) Further work needs to be done to be able to accurately compare the Ct values to RAT performance or to viral load.
Sample type also has an impact on test accuracy. The most common sample types were nasopharyngeal swabs. These swabs are uncomfortable for patients and require a trained health care professional for administration, limiting their use in wider settings. Nasal swabs and oropharyngeal swabs were present in about one-third of the studies each, and saliva samples were present in the selected studies. We did not analyze sample type within our meta-analysis due to a low number of studies identifying the sample location used specifically for the RAT compared with the RT-PCR tests. This is a limitation of our review. Other reviews have examined some of these sample types and found that anterior nares (nasal) swabs and nasopharyngeal swabs have similar sensitivities.[181](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R181) Saliva samples were noted to be of lower diagnostic accuracy than swabs.[181](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R181) Nasal swabs are a popular collection method and are found in many at-home and POC tests. These are easy to collect by anyone and have minimal associated discomfort, making them ideal for primary care settings. A potential future analysis on RAT accuracy could be performed to analyze the impact of nasal swab vs nasopharyngeal sample collection. These data may be more readily available as more studies are published regarding sample collections. The studies included in this analysis were primarily nasopharyngeal and most did not compare accuracy across sample types.
Given our experience with this systematic review and meta-analysis, it is clear that there are more parameters that would provide insight into the use of RATs in primary care settings that were not captured by our data extraction tool. These include potential sources of heterogeneity listed above, such as timing of RAT compared with symptom onset, and variations in sample collection methods.
## Conclusions
We found high heterogeneity across studies examining the same RATs, leading to an overall decrease in the quality of evidence presented here. Many tests have only a few studies comparing their performance to RT-PCR. Future diagnostic accuracy studies need to adhere to the STARD guidelines[184](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R184) to provide the best evidence to build recommendations on. Studies without diagnostic accuracy numbers (2 Ă 2 tables) were excluded from the meta-analysis, resulting in a limitation to our review. Overall, RATs are excellent at predicting when a positive result means a positive diagnosis of COVID-19. However, these tests have reduced capacity to allow a negative result to rule out COVID-19 as a diagnosis. Misidentifying SARS-CoV-2 infection for other respiratory viral infections can lead to potential viral spread among vulnerable patients and health care workers. Further, it can delay appropriate treatment in cases with high risk of complications. In the primary care setting, false-negative results should be considered for further testing via RT-PCR or repeat RATs over several days[185](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R185) when there is high suspicion of COVID-19, such as loss of taste or smell as a presenting symptom. Overall negative likelihood ratio is dependent on local prevalence, and health care practitioners should take into account their current community status when determining the best course of action for a negative RAT result.
### Recommendations for practice
Based on our findings, we recommend that Rocheâs SARS-CoV-2 Rapid Antigen Test and Abbottâs BinaxNOW tests be used in primary care settings, with the understanding that negative results need to be confirmed through RT-PCR or repeated testing over several days when COVID-19 is highly suspected. These tests are widely available, relatively inexpensive, and have good reliability.
### Recommendations for research
The primary recommendation for research is to adhere to the STARD guidelines when reporting on diagnostic data.[184](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R184) If all studies had adhered to these guidelines, that would have allowed significantly more information to be gleaned from the studies selected. The key components of these guidelines that would have greatly improved our meta-analysis are the inclusion of the STARD diagram or the cross-tabulation (also known as a contingency table or a 2 Ă 2 table).[184](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R184) We only included studies that reported the TP, FP, TN, and FN values (91/143 studies) in our meta-analysis. We further recommend that any subgroup analysis performed also include these components. Using the STARD guidelines improves generalizability of reported data,[184](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R184) whereas failing to adhere to these guidelines limits the usefulness of the published data in developing evidence-based practice recommendations.
As new variants emerge, new testing will be needed using high-quality, rigorous methods in populations of vulnerable subjects. As rapid testing will likely remain the first line diagnostic for primary and secondary care environments, and consecutive testing using RATs or RT-PCR will be used as confirmation of a negative diagnosis, identifying the most sensitive and specific tests will remain critically important.
## Author contributions
GM, BH and SS: These authors contributed equally to this work. SR and TH: These authors contributed equally to this work. AD and JK: These authors contributed equally to this work. KD and TE: These authors contributed equally to this work. MDeA and AE, LS: These authors contributed equally to this work.
## Acknowledgments
Linsey Bui for assistance with screening steps and Cheryl Vanier for discussions and critique.
## Funding
This work was supported by internal research support from Touro University Nevada and the Federal Work-Study program. The funder had no role in the content development.
## Supplementary Material
[srx-22-1939-s001.pdf](https://pmc.ncbi.nlm.nih.gov/articles/instance/11462910/bin/srx-22-1939-s001.pdf) (354.8KB, pdf)
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/figure/s001/)
[srx-22-1939-s002.pdf](https://pmc.ncbi.nlm.nih.gov/articles/instance/11462910/bin/srx-22-1939-s002.pdf) (216.1KB, pdf)
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/figure/s002/)
[srx-22-1939-s003.docx](https://pmc.ncbi.nlm.nih.gov/articles/instance/11462910/bin/srx-22-1939-s003.docx) (589.9KB, docx)
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/figure/s003/)
## Appendix I: Search strategy
The search strategy identified key terms in the question and searched terms related to COVID-19, rapid antigens, and sensitivity and specificity. The COVID-19 searches for PubMed, Embase, and Scopus were modified versions from CADTH COVID-19 literature searching strings (documented on <https://covid.cadth.ca/literature-searching-tools/cadth-covid-19-search-strings/#covid-19-medline>). The search was initially run on July 11, 2021, and rerun on July 12, 2022. All databases were rerun, with the exception of Qinsight, which was no longer available from Quertle as of April 2022.
| MEDLINE (PubMed) Search conducted July 11, 2021 Search reran July 12, 2022 Filters: English language; publication date October 31, 2019 to present | | |
|---|---|---|
| Search number | Query | Results retrieved |
| \#1 | (((âantigen sâ\[All Fields\] OR âantigeneâ\[All Fields\] OR âantigenesâ\[All Fields\] OR âantigenicâ\[All Fields\] OR âantigenicallyâ\[All Fields\] OR âantigenicitiesâ\[All Fields\] OR âantigenicityâ\[All Fields\] OR âantigenizedâ\[All Fields\] OR âantigensâ\[MeSH Terms\] OR âantigensâ\[All Fields\] OR âantigenâ\[All Fields\]) AND (âbasedâ\[All Fields\] OR âbasingâ\[All Fields\]) AND (âRapidâ\[All Fields\] OR ârapiditiesâ\[All Fields\] OR ârapidityâ\[All Fields\] OR ârapidnessâ\[All Fields\]) AND (âdetectâ\[All Fields\] OR âdetectabilitiesâ\[All Fields\] OR âdetectabilityâ\[All Fields\] OR âdetectableâ\[All Fields\] OR âdetectablesâ\[All Fields\] OR âdetectablyâ\[All Fields\] OR âdetectedâ\[All Fields\] OR âdetectibleâ\[All Fields\] OR âdetectingâ\[All Fields\] OR âdetectionâ\[All Fields\] OR âdetectionsâ\[All Fields\] OR âdetectsâ\[All Fields\]) AND (âresearch designâ\[MeSH Terms\] OR (âresearchâ\[All Fields\] AND âdesignâ\[All Fields\]) OR âresearch designâ\[All Fields\] OR âtest\*â\[All Fields\])) OR ((âantigensâ\[MeSH Terms\] OR âantigenâ\[Text Word\]) AND âtestâ\[Title/Abstract\]) OR âRADâ\[Title/Abstract\] OR ârapid antigen detectionâ\[Title/Abstract\] OR âRapid antigen assayâ\[Title/Abstract\] OR âRapid antigen detection testâ\[Title/Abstract\] OR âRADTâ\[Title/Abstract\] OR âRAgTâ\[Title/Abstract\] OR âVATâ\[All Fields\] OR âviral antigen test\*â\[Title/Abstract\] OR ((âantigens/analysisâ\[MeSH Terms\] OR âantigens/geneticsâ\[MeSH Terms\] OR âantigens/immunologyâ\[MeSH Terms\] OR âantigens/isolation and purificationâ\[MeSH Terms\] OR âantigens/ultrastructureâ\[MeSH Terms\] OR âantigens/virologyâ\[MeSH Terms\] OR (âantigensâ\[MeSH Terms\] OR âantigenâ\[Text Word\])) AND âtestâ\[Title/Abstract\]) OR (âRapidâ\[All Fields\] AND âpoint of careâ\[All Fields\] AND (âantigen sâ\[All Fields\] OR âantigeneâ\[All Fields\] OR âantigenesâ\[All Fields\] OR âantigenicâ\[All Fields\] OR âantigenicallyâ\[All Fields\] OR âantigenicitiesâ\[All Fields\] OR âantigenicityâ\[All Fields\] OR âantigenizedâ\[All Fields\] OR âantigensâ\[MeSH Terms\] OR âantigensâ\[All Fields\] OR âantigenâ\[All Fields\]))) AND 2019/10/31:2021/12/31\[Date - Publication\] | |
| \#2 | (((âcoronavirusâ\[MeSH Terms:noexp\] OR âbetacoronavirusâ\[MeSH Terms:noexp\] OR âCoronavirus Infectionsâ\[MeSH Terms:noexp\]) AND (âDisease Outbreaksâ\[MeSH Terms:noexp\] OR âepidemicsâ\[MeSH Terms:noexp\] OR âpandemicsâ\[MeSH Terms\])) OR âCOVID-19 testingâ\[MeSH Terms\] OR âCOVID-19 drug treatmentâ\[Supplementary Concept\] OR âCOVID-19 serotherapyâ\[Supplementary Concept\] OR âCOVID-19 vaccinesâ\[MeSH Terms\] OR âspike protein sars cov 2â\[Supplementary Concept\] OR âCOVID-19â\[Supplementary Concept\] OR âSARS-CoV-2â\[MeSH Terms\] OR ânCoVâ\[Title/Abstract\] OR ânCoVâ\[Transliterated Title\] OR â2019nCoVâ\[Title/Abstract\] OR â2019nCoVâ\[Transliterated Title\] OR âcovid19\*â\[Title/Abstract\] OR âcovid19\*â\[Transliterated Title\] OR âCOVIDâ\[Title/Abstract\] OR âCOVIDâ\[Transliterated Title\] OR âSARS-CoV-2â\[Title/Abstract\] OR âSARS-CoV-2â\[Transliterated Title\] OR âSARSCOV-2â\[Title/Abstract\] OR âSARSCOV2â\[Title/Abstract\] OR âSARSCOV2â\[Transliterated Title\] OR âSevere Acute Respiratory Syndrome Coronavirus 2â\[Title/Abstract\] OR ((âsevere acute respiratory syndromeâ\[Title/Abstract\] OR âsevere acute respiratory syndromeâ\[Transliterated Title\]) AND âcorona virus 2â\[Title/Abstract\]) OR ânew coronavirusâ\[Title/Abstract\] OR (ânewâ\[Transliterated Title\] AND âcoronavirusâ\[Transliterated Title\]) OR ânovel coronavirusâ\[Title/Abstract\] OR ânovel coronavirusâ\[Transliterated Title\] OR ânovel corona virusâ\[Title/Abstract\] OR (ânovelâ\[Transliterated Title\] AND âcorona virusâ\[Transliterated Title\]) OR ânovel CoVâ\[Title/Abstract\] OR (ânovelâ\[Transliterated Title\] AND âCoVâ\[Transliterated Title\]) OR ânovel HCoVâ\[Title/Abstract\] OR (ânovelâ\[Transliterated Title\] AND âHCoVâ\[Transliterated Title\]) OR ((â19â\[Title/Abstract\] OR â19â\[Transliterated Title\] OR â2019â\[Title/Abstract\] OR â2019â\[Transliterated Title\] OR âWuhanâ\[Title/Abstract\] OR âWuhanâ\[Transliterated Title\] OR âHubeiâ\[Title/Abstract\] OR âHubeiâ\[Transliterated Title\]) AND (âcoronavirus\*â\[Title/Abstract\] OR âcoronavirus\*â\[Transliterated Title\] OR âcorona virus\*â\[Title/Abstract\] OR âcorona virus\*â\[Transliterated Title\] OR âCoVâ\[Title/Abstract\] OR âCoVâ\[Transliterated Title\] OR âHCoVâ\[Title/Abstract\] OR âHCoVâ\[Transliterated Title\])) OR ((âcoronavirus\*â\[Title/Abstract\] OR âcoronavirus\*â\[Transliterated Title\] OR âcorona virus\*â\[Title/Abstract\] OR âcorona virus\*â\[Transliterated Title\] OR âbetacoronavirus\*â\[Title/Abstract\]) AND (âoutbreak\*â\[Title/Abstract\] OR âoutbreak\*â\[Transliterated Title\] OR âepidemic\*â\[Title/Abstract\] OR âepidemic\*â\[Transliterated Title\] OR âpandemic\*â\[Title/Abstract\] OR âpandemic\*â\[Transliterated Title\] OR âcrisisâ\[Title/Abstract\] OR âcrisisâ\[Transliterated Title\])) OR ((âWuhanâ\[Title/Abstract\] OR âWuhanâ\[Transliterated Title\] OR âHubeiâ\[Title/Abstract\] OR âHubeiâ\[Transliterated Title\]) AND (âpneumoniaâ\[Title/Abstract\] OR âpneumoniaâ\[Transliterated Title\]))) AND 2019/10/31:2021/12/31\[Date - Publication\] | |
| \#3 | âpredictive value of testsâ\[MeSH Terms\] OR âpredictive value of testsâ\[All Fields\] OR âSensitivity and Specificityâ\[MeSH Terms\] OR âSensitivity and Specificityâ\[All Fields\] | |
| \#4 | \#1 AND \#2 AND \#3 | 239 |
| Reran search July 12, 2022 | 373 | |
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/table/TU9/)
| Qinsight (Quertle) Search conducted July 11, 2021 | | |
|---|---|---|
| Search number | Query | Results retrieved |
| \#1 | covid | |
| \#2 | rapid antigen test | |
| \#3 | sensitivity and specificity | |
| \#4 | \#1 AND \#2 AND \#3 | 204 |
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/table/TU10/)
| Embase Search conducted on July 11, 2021 Search reran on July 12, 2022 Filters: English language; publication date October 31, 2019 to present | | |
|---|---|---|
| Search number | Query | Results retrieved |
| \#1 | ((âsars-related coronavirusâ/exp OR âcoronavirinaeâ/exp OR âbetacoronavirusâ/exp OR âcoronavirus infectionâ/exp) AND (âepidemicâ/exp OR âpandemicâ/exp)) OR (âsevere acute respiratory syndrome coronavirus 2â/exp OR âsars coronavirus 2 test kitâ/exp OR âsars-cov-2 OR (clinical isolate wuhan/wiv04/2019)â/exp OR âcoronavirus disease 2019â/exp) OR ((ncov\* OR 2019ncov OR 19ncov OR covid19\* OR covid OR âsars cov 2â OR âsarscov 2â OR âsars cov2â OR sarscov2 OR severe) AND (acute AND respiratory AND syndrome AND coronavirus AND 2 OR severe) OR (acute AND respiratory AND syndrome AND corona AND virus AND 2)) OR (new OR novel OR â19â OR â2019â OR wuhan OR hubei OR china OR chinese) AND (coronavirus\* OR corona) AND (virus\* OR betacoronavirus\* OR cov OR hcov) OR (coronavirus\* OR corona) AND (virus\* OR betacoronavirus\*) AND (pandemic\* OR epidemic\* OR outbreak\* OR crisis) OR (wuhan OR hubei) NEAR/5 pneumonia | |
| \#2 | rapid antigen testâ/exp OR ârapid antigen detection testâ/exp OR (rapid AND antigen AND test) | |
| \#3 | (âpredictive valueâ/exp OR âsensitivity and specificityâ/exp) OR (âpredictive valueâ OR âsensitivity and specificityâ) | |
| \#4 | \#1 AND \#2 AND \#3 | 212 |
| Reran search July 12, 2022 | 410 | |
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/table/TU11/)
| WHO Covid-19 Database <https://search.bvsalud.org/global-literature-on-novel-coronavirus-2019-ncov/> Search conducted July 11, 2021 Search reran on July 12, 2022 | | |
|---|---|---|
| Search number | Query | Results retrieved |
| \#1 | tw:(rapid antigen test) | |
| \#2 | tw:(predictive value) | |
| \#3 | tw:(sensitivity and specificity) | |
| \#4 | la:(âenâ) | |
| \#5 | \#1 AND (\#2 OR \#3) AND \#4 | 627 |
| Reran search July 12, 2022 | 702 | |
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/table/TU12/)
| Scopus Search conducted July 11, 2021 Search reran on July 12, 2022 Filters English Language; Publication year greater than 2018 | | |
|---|---|---|
| Search number | Query | Results retrieved |
| \#1 | ( TITLE-ABS-KEY ( {coronavirus} OR {betacoronavirus} OR {coronavirus infections} ) AND TITLE-ABS-KEY ( {disease outbreaks} OR {epidemics} OR {pandemics} ) OR TITLE-ABS-KEY ( ( ncov\* ) OR {2019nvoc} OR {19ncov} OR {covid19\*} OR[15](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R15) OR {sars-cov-2} OR {severe acute respiratory syndrome coronavirus 2} OR {severe Acute Respiratory Syndrome Corona Virus 2} ) OR TITLE-ABS-KEY ( ( new 2/3 coronavirus\* ) OR ( new W/3 betacoronavirus\* ) OR ( new W/3 cov ) OR ( new W/3 hcov ) OR ( novel W/3 coronavirus\* ) ) OR TITLE-ABS-KEY ( ( corona AND virus\* W/3 epidemic\* ) OR ( corona AND virus\* W/3 outbreak\* ) OR ( corona AND virus\* W/3 crisis ) OR ( betacoronavirus\* W/3 pandemic\* ) ) OR TITLE-ABS-KEY ( ( corona AND virus\* W/3 epidemic\* ) OR ( corona AND virus\* W/3 outbreak\* ) OR ( corona AND virus\* W/3 crisis ) OR ( betacoronavirus\* W/3 pandemic\* ) OR ( betacoronavirus\* W/3 epidemic\* ) OR ( betacoronavirus\* W/3 outbreak\* ) OR ( betacoronavirus\* W/3 crisis ) ) ) AND PUBYEAR \> 2018 | |
| \#2 | ( TITLE-ABS-KEY ( {rapid antigen test} OR ârapid antigen test\*â ) OR TITLE-ABS-KEY ( ârapidâ AND âantigenâ AND âtestâ ) ) AND PUBYEAR \> 2018 | |
| \#3 | ( TITLE-ABS-KEY ( {predictive value} OR {sensitivity and specificity} ) AND TITLE-ABS-KEY ( âpredictive valueâ OR âsensitivity and specificityâ ) ) AND PUBYEAR \> 2018 | |
| \#4 | \#1 AND \#2 AND \#3 | 176 |
| Reran search July 12, 2022 | 462 | |
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/table/TU13/)
## Appendix II: Data extraction instrument
| Field name | Entry type |
|---|---|
| Data extractor | Free-text |
| Data validated by | Free-text |
| Article \# | Free-text |
| Article first author | Free-text |
| Article title | Free-text |
| Month, year | Free-text |
| DOI/PMID/other identifier | Free-text |
| Country | Free-text |
| Setting/context | Drop-down |
| Primary care location | |
| Hospital â inpatient | |
| COVID-19 testing site/screening location | |
| Urgent care location | |
| Emergency dept/room | |
| Public area (not a designated screening location) | |
| College/university campus (non-medical) | |
| Long-term care facility (nursing home, rehab centers) | |
| Not described/unclear | |
| Hospital â outpatient | |
| College/university campus (medical center/hospital) | |
| Year/time frame for data collection | Free-text |
| Participant characteristics (age range, gender breakdown, rural/urban, etc) | Free-text |
| Number of participants | Free-text |
| Sample type | Drop-down |
| Nasopharyngeal swabs (NP) | |
| Blood (Bld) | |
| Bronchoalveolar lavage (BAL)/bronchial sample | |
| Nasal swabs (NS) | |
| Oropharyngeal swabs (OP) | |
| Other | |
| Saliva (Sal) | |
| Throat swabs (TS) | |
| Sample type if other | Free-text |
| Reference test description | Drop-down |
| Abbott RealTime SARS-CoV-2 (Abbott) | |
| Alinity m SARS-CoV-2 AMP (Abbott) | |
| Allplex assays (Seegene) | |
| ARGENE SARS-CoV-2 R-Gene (Biomerieux) | |
| BD Max (Becton-Dickinson) | |
| BGI 2019-nCoV Real-time Fluorescent RT-PCR kit (BGI Genomics) | |
| Biofire | |
| CDC 2019-nCoV Real-Time RT-PCR Diagnostic Panel | |
| Cobas Kits/Systems (Roche) | |
| COVID-19 Multiplex RT-PCR kit (DIANA Biotech) | |
| COVID-19 Real-time PCR kit (HBRT-COVID-19) (Chaozhou Hybribio Biochemistry Ltd., China) | |
| Covidsure Multiplex RT-PCR kit (Trivitron Healthcare Labsystems Diagnostics) | |
| CRSP SARS-CoV-2 (Clinical Research Sequencing Platform, Harvard/MIT) | |
| Custom/In-house SARS-2 primers | |
| DAAN Gene RT-PCR COVID-19 (DaAnGene) | |
| FTD SARS-CoV-2 Assay (Fast Track Diagnostics, Luxembourg) | |
| GENECUBE (Toyobo Co., Ltd.) | |
| GeneFinder COVID-19 Plus RealAmp Kit (Osang Healthcare Co., Ltd) | |
| Genesig Real-time PCR Coronavirus assay/Z-Path-COVID-19-CE (Primerdesign) | |
| GenomeCoV19 Detection kit (ABM) | |
| IDT SARS-CoV-2 (2019-nCoV) multiplex CDC qPCR probe Assay (Integrated DNA Technologies) | |
| Japanese National Institute of Infectious Diseases (NIID) | |
| LabTurbo AIO COVID-19 RNA Testing Kit | |
| LightMix SarbecoV (TIB Microbiol) | |
| Luna Universal Probe One-Step RT-PCR for Detection of COVID-19 (SignaGen Labs) | |
| Meril COVID-19 One-Step RT-PCR Kit | |
| MutaPLEX Coronavirus Real-time-RT-PCR kit (Immundiagnostik AG) | |
| NeuMoDx SARS-CoV-2 Assay (Qiagen) | |
| Novel Coronavirus (2019-nCoV) Real Time Multiplex RT-PCR kit (Liferiver) | |
| Panther Fusion or Aptima SARS-CoV-2 assay (Hologic) | |
| PCR Biosystems | |
| PerkinElmer SARS-CoV-2 Real-time RT-PCR Assay | |
| Real-Q 2019-nCoV Detection Kit (Biosewoom) | |
| REALQUALITY RQ-SARS-CoV-2 kit (AB Analitica) | |
| RealStar SARS-CoV-2 RT-PCR kit (Altona) | |
| RIDAGENE SARS-CoV-2 (R-Bio-pharm) | |
| Sansure Biotech COVID-19 Nucleic Acid Test kit | |
| Shimadzu Ampdirect 2019 novel coronavirus detection kit | |
| Simplexa (DiaSorin) | |
| Specific Test Not Described | |
| Standard M nCoV Real-Time Detection Kit (SD Biosenor) | |
| Takara Bio SARS-CoV-2 direct detection RT-qPCR kit | |
| TaqPath COVID-19 Combo kit (Applied Biosystems/ThermoFisher) | |
| VIASURE (CerTest) | |
| Vitassay (Vitassay) | |
| Xpert Xpress SARS-CoV-2/GeneXpert (Cepheid) | |
| Reference test if other | Free-text |
| Reference test comments (if any) | Free-text |
| Index test description | Drop-down |
| STANDARD Q COVID-19 Ag Test | |
| PanBio COVID-19 Ag Rapid Test Device | |
| SARS-CoV-2 Rapid Antigen Test | |
| BinaxNOW COVID-19 Antigen | |
| Rapid Test Ag 2019-nCov | |
| SARS-CoV-2 Ag | |
| Custom/Novel/In-house | |
| COVISTIX (COVIDMARK) Covid 19 Antigen Rapid Test Device | |
| AMP Rapid Test SARS-CoV-2 Ag | |
| BD Veritor COVID-19 Rapid Antigen Test | |
| CerTest SARS-CoV-2 | |
| Espline SARS-CoV-2 | |
| SARS-CoV-2 Antigen Rapid Test | |
| HUMASIS COVID-19 Ag Test | |
| Mologic Covid-19 Rapid Antigen Test | |
| BIOCREDIT COVID-19 Ag | |
| Rida Quick SARS-CoV-2 Antigen Test | |
| STANDARD F COVID-19 Ag FIA | |
| RapidTesta SARS-CoV-2 | |
| Fluorecare SARS-CoV-2 Spike Protein Test kit (Colloidal Gold) | |
| CLINITEST Rapid COVID-19 Antigen Test | |
| Immupass VivaDiag | |
| COVID-VIRO COVID-19 Ag Rapid Test | |
| Flowflex COVID-19 Antigen test | |
| COVID-19 Antigen Rapid Test | |
| Alltest COVID-19 ART Antigen Rapid Test | |
| COVID-19 Antigen Rapid Test | |
| COVID-19 RAT kit | |
| NowCheck COVID-19 Ag test | |
| Novel Corona Virus (SARS-CoV-2) Ag Rapid Test kit | |
| Covid-19 AG BSS | |
| Helix i-SARS-CoV-2 Ag Rapid Test | |
| COVID-19 Ag K-SeT | |
| Liaison SARS-CoV-2 Ag | |
| COVID-19 Antigen Detection | |
| COVID-19 Ag ECO Teste | |
| Inflammacheck CoronaCheck | |
| GenBody COVAG025 | |
| GENEDIA W COVID-19 Ag Test | |
| Rapid COVID-19 Antigen Test | |
| Innova SARS-CoV-2 Antigen Rapid test | |
| Accucare PathoCatch Covid-19 Ag Detection Kit | |
| Orient Gene Rapid Covid-19 (Antigen) Self-Test | |
| GeneFinder COVID-19 Ag Plus Rapid Test | |
| Green Spring SARS-CoV-2 Antigen Rapid Test Kit (Colloidal Gold) | |
| Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Antigen Detection Kit (Colloidal Gold-Based) | |
| 2019-nCoV Antigen Test | |
| Index test if other | Free-text |
| Index test comments (if any) | Free-text |
| Subgroups (if any; include overall) | Free-text |
| True positive (TP) | Free-text |
| False positive (FP) | Free-text |
| True negative (TN) | Free-text |
| False negative (FN) | Free-text |
| Sensitivity (TP/\[TP+FN\]) | Free-text |
| Sensitivity 95% CI (low, high) | Free-text |
| Specificity (TN/\[TN+FP\]) | Free-text |
| Specificity 95% CI (low, high) | Free-text |
| Positive predictive value PPV (TP/\[TP+FP\]) | Free-text |
| Negative predictive values NPV (TN/\[FN+TN\]) | Free-text |
| Description of main results (include adverse events from tests) | Free-text |
| Exclusion reasons (if any) | Free-text |
| Notes | Free-text |
| Need to contact authors? Put contact info here | Free-text |
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/table/TU14/)
## Appendix III: Characteristics of included studies
| Author, year | Article title | Index test description | Sensitivity (TP/\[TP+FN\]) | Sensitivity 95% CI (low, high) | Specificity (TN/\[TN+FP\]) | Specificity 95% CI (low, high) |
|---|---|---|---|---|---|---|
| Abdelrazik, *et al.* [31](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R31) Mar 2021 | Potential use of antigen-based rapid test for SARS-CoV-2 in respiratory specimens in low-resource settings in Egypt for symptomatic patients and high-risk contacts | RapiGen (BioCredit) | 43\.1 | | | |
| Abusrewil, *et al.* [32](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R32) Dec 2021 | Time scale performance of rapid antigen testing for SARS-CoV-2: evaluation of ten rapid antigen assays | PanBio (Abbott) | 76\.92 | 46\.19, 94.96 | 100 | |
| Flowflex COVID-19 Antigen test (ACON Labs) | 100 | 78\.20, 100 | 100 | | | |
| AMP Rapid Test SARS-CoV-2 Ag (AMP Diagnostics) | 85\.71 | 42\.13, 99.64 | 100 | | | |
| COVID-19 Antigen Rapid Test (Assut Europe) | 71\.43 | 29\.04, 96.33 | 100 | | | |
| Novel Corona Virus (SARS-CoV-2) Ag Rapid Test kit (Bioperfectus) | 80 | 44\.39, 94.78 | 100 | | | |
| CerTest SARS-CoV-2 (Certest Biotech) | 62\.5 | 24\.49, 91.48 | 100 | | | |
| Espline SARS-CoV-2 (Fujirebio) | 80 | 44\.39, 97.48 | 100 | | | |
| Fluorecare (Colloidal Gold/Fluorescent) SARS-CoV-2 Spike Protein Test kit (Shenzen Microprofit) | 91\.67 | 61\.52, 99.79 | 100 | | | |
| Orient Gene Rapid Covid-19 (Antigen) Self-Test (Orient Gene) | 50 | 18\.71, 81.29 | 100 | | | |
| RapiGen (BioCredit) | 62\.5 | 35\.4, 84.80 | 100 | | | |
| Afzal, *et al.* [33](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R33) Sep 2021 | Diagnostic accuracy of PANBIO COVID-19 rapid antigen method for screening in emergency cases | PanBio (Abbott) | 90\.47 | | 100 | |
| Akashi, *et al.* [34](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R34) Feb 2022 | A prospective clinical evaluation of the diagnostic accuracy of the SARS-CoV-2 rapid antigen test using anterior nasal samples | Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 72\.7 | 63\.4, 80.8 | 100 | 99\.5, 100 |
| Al-Alawi, *et al.* [35](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R35) Jan 2021 | Evaluation of four rapid antigen tests for detection of SARS-CoV-2 virus | STANDARD Q COVID-19 Ag (SD Biosensor) | 65\.8 | 48\.65, 80.37 | 100 | 87\.66, 100 |
| PCL COVID19 Ag Rapid FIA Antigen Test (PCL) | 69\.8 | 55\.66, 81.66 | 94\.1 | 80\.32, 99.28 | | |
| RapiGen (BioCredit) | 64 | 49\.19, 77.08 | 100 | 86\.28, 100 | | |
| Sofia SARS Rapid Antigen FIA/Sofia 2 (Quidel) | 64\.3 | 50\.36, 76.64 | 100 | 84\.56, 100 | | |
| Aleem, *et al.* [36](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R36) Jan 2022 | Diagnostic accuracy of STANDARD Q COVID-19 antigen detection kit in comparison with RT-PCR assay using nasopharyngeal samples in India | STANDARD Q COVID-19 Ag (SD Biosensor) | 54\.43 | 42\.83, 65.69 | 99\.24 | 97\.79, 99.84 |
| Alghounaim, *et al.* [37](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R37) Dec 2021 | The performance of two rapid antigen tests during population-level screening for SARS-CoV-2 infection | Liaison | 43\.3 | 30\.6, 56.8 | 99\.9 | 99\.3, 100 |
| STANDARD Q COVID-19 Ag (SD Biosensor) | 30\.6 | 19\.6, 43.7 | 98\.8 | 97\.8, 99.4 | | |
| Allan-Blitz, *et al.* [38](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R38) Sep 2021 | A real-world comparison of SARS-CoV-2 rapid antigen testing versus PCR testing in Florida | BinaxNOW (Abbott) - all sample types PCR | 49\.2 | 47\.4, 50.9 | 98\.8 | 98\.6, 98.9 |
| BinaxNOW (Abbott) - Anterior Nares PCR | 47\.5 | 39\.1, 56.1 | 100 | 99\.3, 100 | | |
| BinaxNOW (Abbott) - Nasopharyngeal Fluid PCR | 46\.1 | 37\.3, 55.1 | 99\.7 | 98\.9, 100 | | |
| BinaxNOW (Abbott) - Oral Fluid PCR | 49\.37 | 47\.5, 51.2 | 98\.7 | 98\.5, 98.8 | | |
| Amer, *et al.* [39](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R39) Oct 2021 | Diagnostic performance of rapid antigen test for COVID-19 and the effect of viral load, sampling time, subject's clinical and laboratory parameters on test accuracy (preprint) | STANDARD Q COVID-19 Ag (SD Biosensor) | 78\.2 | 67, 86 | 64\.2 | 38, 83 |
| Anastasiou, *et al.* [40](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R40) Apr 2021 | Fast detection of SARS-CoV-2 RNA directly from respiratory samples using a loop-mediated isothermal amplification (LAMP) test | Custom/Novel/In-house | 68\.8 | 57\.3, 78.4 | 100 | 90\.6, 100 |
| Avgoulea, *et al.* [41](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R41) Apr 2022 | Field evaluation of the new rapid NG-Test(ÂŽ) SARS-CoV-2 Ag for diagnosis of COVID-19 in the emergency department of an academic referral hospital | Custom/Novel/In-house - NP sample | 81 | 73, 87 | 99 | 95, 100 |
| Custom/Novel/In-house - OP sample | 51 | 42, 59 | 100 | 96, 100 | | |
| Babu, *et al.* [42](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R42) Jul 2021 | The burden of active infection and anti-SARS-CoV-2 IgG antibodies in the general population: Results from a statewide sentinel-based population survey in Karnataka, India | STANDARD Q COVID-19 Ag (SD Biosensor) | Not reported | | | |
| Bachman, *et al.* [43](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R43) Aug 2021 | Clinical validation of an open-access SARS-CoV-2 antigen detection lateral flow assay, compared to commercially available assays | Custom/Novel/In-house - PCR collected by NP | 69 | 60, 78 | 97 | 88, 100 |
| BinaxNOW (Abbott) - PCR collected by NP | 82 | 73, 88 | 100 | 94, 100 | | |
| Sofia SARS Rapid Antigen FIA/Sofia 2 (Quidel) - PCR collected by NP | 74 | 64, 82 | 98 | 91, 100 | | |
| Custom/Novel/In-house - PCR collected by NS | 83 | 74, 90 | 97 | 91, 100 | | |
| BinaxNOW (Abbott) - PCR collected by NS | 91 | 84, 96 | 94 | 85, 98 | | |
| Sofia SARS Rapid Antigen FIA/Sofia 2 (Quidel) - PCR collected by NS | 86 | 77, 92 | 96 | 89, 99 | | |
| Basso, *et al.* [44](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R44) Feb 2021 | Salivary SARS-CoV-2 antigen rapid detection: a prospective cohort study | Espline SARS-CoV-2 (Fujirebio) | 48 | | 100 | |
| Blairon, *et al.* [45](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R45) Aug 2020 | Implementation of rapid SARS-CoV-2 antigenic testing in a laboratory without access to molecular methods: experiences of a general hospital | Respi-Strip (Coris BioConcept) | 30 | 16\.7, 47.9 | 100 | |
| Bond, *et al.* [46](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R46) May 2022 | Utility of SARS-CoV-2 rapid antigen testing for patient triage in the emergency department: a clinical implementation study in Melbourne, Australia | PanBio (Abbott) | 75\.5 | 69\.9, 80.4 | 100 | 99\.8, 100 |
| Borro, *et al.* [47](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R47) Apr 2022 | SARS-CoV-2 transmission control measures in the emergency department: the role of rapid antigenic testing in asymptomatic subjects | Green Spring "SARS-CoV-2 Antigen Rapid Test Kit (Colloidal Gold)" - standard protocol | 79\.8 | | 100 | |
| Green Spring "SARS-CoV-2 Antigen Rapid Test Kit (Colloidal Gold)" - UTM modified protocol | 70\.7 | | 100 | | | |
| Green Spring "SARS-CoV-2 Antigen Rapid Test Kit (Colloidal Gold)" - UTM modified protocol | 43\.9 | | 100 | | | |
| Boum, *et al.* [48](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R48) May 2021 | Performance and operational feasibility of antigen and antibody rapid diagnostic tests for COVID-19 in symptomatic and asymptomatic patients in Cameroon: a clinical, prospective, diagnostic accuracy study | STANDARD Q COVID-19 Ag (SD Biosensor) | 58\.4 | 53\.0, 64.8 | 93\.2 | 88\.0, 97.0 |
| Bulilete, *et al.* [49](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R49) Feb 2021 | Panbio⢠rapid antigen test for SARS-CoV-2 has acceptable accuracy in symptomatic patients in primary health care | PanBio (Abbott) | 71\.4 | 63\.1, 78.7 | 99\.8 | 99\.4, 99.9 |
| Burdino, *et al.* [50](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R50) Oct 2021 | SARS-CoV-2 microfluidic antigen point-of-care testing in emergency room patients during COVID-19 pandemic | SARS-CoV-2 Ag (LumiraDx) | 90\.1 | 86\.2, 93.1 | 99\.4 | 98\.6, 99.8 |
| Bwogi, *et al.* [7](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R7) May 2022 | Field evaluation of the performance of seven antigen rapid diagnostic tests for the diagnosis of SARs-CoV-2 virus infection in Uganda | Immupass VivaDiag (VivaChek Biotech) | 30\.2 | 18\.0, 46.1 | 94\.1 | 90\.1, 96.6 |
| MEDsan SARS-CoV-2 Antigne Rapid Test | 13 | 8\.1, 20.3 | 100 | 96\.9, 100 | | |
| Novegent COVID-19 Antigen Rapid Test Kit (Colloidal gold) | 46 | 36\.3, 56.0 | 89\.9 | 83\.3, 94.1 | | |
| PanBio (Abbott) | 49\.4 | 38\.7, 60.1 | 100 | 96\.4, 100 | | |
| PCL COVID19 Ag Rapid FIA Antigen Test (PCL) | 37\.6 | 28\.2, 48.1 | 89\.9 | 80\.8, 94.9 | | |
| RapiGen (BioCredit) | 27\.4 | 20\.5, 35.6 | 98\.2 | 93\.1, 99.6 | | |
| Respi-Strip (Coris BioConcept) | 19\.4 | 11\.5, 30.9 | 99\.2 | 94\.5, 99.9 | | |
| Caruana, *et al.* [51](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R51) Apr 2021 | Implementing SARS-CoV-2 rapid antigen testing in the emergency ward of a Swiss university hospital: the INCREASE Study | PanBio (Abbott) | 41\.2 | | 99\.5 | |
| BD Veritor COVID-19 Rapid Antigen Test (Becton-Dickinson) | 41\.2 | | 99\.7 | | | |
| Exdia (Precision Biosensor) | 48\.3 | | 99\.5 | | | |
| STANDARD Q COVID-19 Ag (SD Biosensor) | 41\.2 | | 99\.7 | | | |
| Caruana, *et al.* [52](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R52) May 2021 | The dark side of SARS-CoV-2 rapid antigen testing: screening asymptomatic patients | STANDARD Q COVID-19 Ag (SD Biosensor) | 28\.6 | | 98\.2 | |
| Cassuto, *et al.* [53](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R53) Jul 2021 | Evaluation of a SARS-CoV-2 antigen-detecting rapid diagnostic test as a self-test: diagnostic performance and usability | COVIDâVIRO nasal swab test | 96\.88 | 83\.78, 99.92 | 100 | 98\.19, 100.00 |
| Cattelan, *et al.* [8](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R8) Mar 2022 | Rapid antigen test LumiraDx(TM) vs real time polymerase chain reaction for the diagnosis of SARS-CoV-2 infection: a retrospective cohort study | SARS-CoV-2 Ag (LumiraDx) | 76\.3 | 70\.8, 81.8 | 94\.4 | 88\.3, 100 |
| Cento, *et al.* [54](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R54) May 2021 | Frontline screening for SARS-CoV-2 infection at emergency department admission by third generation rapid antigen test: can we spare RT-qPCR? | SARS-CoV-2 Ag (LumiraDx) | 85\.6 | 82, 89 | 97\.05 | 96, 98 |
| Cerutti, *et al.* [55](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R55) Nov 2020 | Urgent need of rapid tests for SARS CoV-2 antigen detection: evaluation of the SD-Biosensor antigen test for SARS-CoV-2 | STANDARD Q COVID-19 Ag (SD Biosensor) | 70\.6 | | 100 | |
| Chaimayo, *et al.* [56](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R56) Nov 2020 | Rapid SARS-CoV-2 antigen detection assay in comparison with real-time RT-PCR assay for laboratory diagnosis of COVID-19 in Thailand | STANDARD Q COVID-19 Ag (SD Biosensor) | 98\.33 | 91\.06, 99.6 | 98\.73 | 97\.06, 99.59 |
| Cheng, *et al.* [57](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R57) May 2022 | Evaluation of a rapid antigen test for the diagnosis of SARS-CoV-2 during the COVID-19 pandemic | Enimmune Speedy COVID-19 AG Rapid Test - Heping | 69\.1 | 68\.8, 69.5 | 99\.1 | 99\.1, 99.1 |
| PanBio (Abbott) - RenAi | 62 | 61\.6, 62.3 | 99\.9 | 99\.9, 99.9 | | |
| VTRUST COVID-19 Antigen Rapid Test (Taidoc Technology Corporation) - YangMing | 78\.6 | 78\.2, 78.9 | 98\.2 | 98\.2, 98.3 | | |
| VTRUST COVID-19 Antigen Rapid Test (Taidoc Technology Corporation) - Zhongxiao | 60\.5 | 60\.1, 60.8 | 99\.1 | 99\.0, 99.1 | | |
| Enimmune Speedy COVID-19 AG Rapid Test - Zhongxing | 64\.6 | 64\.3, 64.8 | 98\.3 | 98\.3, 98.3 | | |
| Choudhary, *et al.* [58](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R58) Apr 2022 | Validation of rapid SARS-CoV-2 antigen detection test as a screening tool for detection of Covid-19 infection at district hospital in northern India | Standard Q COVID-19 Ag (SD Biosensor) | 55\.04 | 46\.43, 63.35 | 99\.2 | 98\.15, 99.66 |
| Cottone, *et al.* [59](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R59) May 2022 | Pitfalls of SARS-CoV-2 antigen testing at emergency department | Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 45\.5 | 35\.6, 55.8 | 98\.1 | 96\.1, 99.2 |
| Cubas-Atienzar, *et al.* [60](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R60) May 2021 | Accuracy of the Mologic COVID-19 rapid antigen test: a prospective multi-centre analytical and clinical evaluation | Mologic Covid-19 Rapid Antigen Test (Mologic Ltd. United Kingdom) - Northumberland | 86 | 76\.9, 92.6 | 97\.5 | 93\.8, 99.3 |
| Mologic Covid-19 Rapid Antigen Test (Mologic Ltd. United Kingdom) - Yorkshire | 84\.6 | 54\.6, 98.1 | 100 | 91\.2, 100 | | |
| Dierks, *et al.* [61](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R61) May 2021 | Diagnosing SARS-CoV-2 with antigen testing, transcription-mediated amplification and real-time PCR | SARS-CoV-2 Ag (LumiraDx) | 45\.45 | 20\.22, 73.26 | 99\.54 | 98\.17, 99.88 |
| NADAL COVID-19 Antigen Rapid Test (New Art Laboratories/nal von minden) | 14\.29 | 1\.94, 58.35 | 76\.44 | 70\.16, 81.74 | | |
| Escribano, *et al.* [62](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R62) Feb 2022 | Different performance of three point-of-care SARS-CoV-2 antigen detection devices in symptomatic patients and close asymptomatic contacts: a real-life study | PanBio (Abbott) - Close Asymptomatic Contacts | 33\.3 | 11\.8, 61.6 | | |
| SGTI-Flex - Close Asymptomatic Contacts | 84\.6 | 54\.5, 98.1 | | | | |
| NovaGen - Close Asymptomatic Contacts | 55\.5 | 30\.7, 78.4 | | | | |
| PanBio (Abbott)-COVID-19 Suspected Cases | 71\.1 | 55\.6, 83.6 | | | | |
| SGTI-Flex - COVID-19 Suspected Cases | 68\.8 | 55\.7, 80 | | | | |
| NovaGen - COVID-19 Suspected Cases | 84\.6 | 72\.0, 93.1 | | | | |
| EscrivĂĄ, *et al.* [63](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R63) Aug 2021 | The effectiveness of rapid antigen test-based for SARS-CoV-2 detection in nursing homes in Valencia, Spain | PanBio (Abbott) | 85 | 90, 99 | 100 | 100, 100 |
| FaĂco-Filho, *et al.* [64](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R64) Mar 2022 | Evaluation of the Panbio⢠COVID-19 Ag rapid test at an emergency room in a hospital in SĂŁo Paulo, Brazil | PanBio (Abbott) | Not reported | | | |
| Farfour, *et al.* [65](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R65) Mar 2021 | The Panbio COVID-19 Ag rapid test: which performances are for COVID-19 diagnosis? | PanBio (Abbott) | Not reported | | | |
| Fernandez-Montero, *et al.* [66](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R66) Jul 2021 | Validation of a rapid antigen test as a screening tool for SARS-CoV-2 infection in asymptomatic populations. Sensitivity, specificity and predictive values | Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 71\.43 | 56\.74, 83.42 | 99\.68 | 99\.37, 99.86 |
| FertĂŠ, *et al.* [67](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R67) Jun 2021 | Accuracy of COVID-19 rapid antigenic tests compared to RT-PCR in a student population: the StudyCov study | PanBio (Abbott) | 63\.5 | 49\.0, 76.4 | 100 | 99\.4, 100 |
| Fitoussi, *et al.* [68](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R68) Oct 2021 | Analytical performance of the point-of-care BIOSYNEX COVID-19 Ag BSS for the detection of SARSâCoVâ2 nucleocapsid protein in nasopharyngeal swabs: a prospective field evaluation during the COVID-19 third wave in France | BIOSYNEX Ag-RDT | 81\.80 | 79\.2, 84.1 | 99\.60 | 98\.9, 99.8 |
| Ford, *et al.* [69](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R69) Sep 2021 | Antigen test performance among children and adults at a SARS-CoV-2 community testing site | BinaxNOW (Abbott) - Exposed | 79\.80 | | 99\.70 | |
| BinaxNOW (Abbott) | 80\.80 | | 99\.90 | | | |
| Freire, *et al.* [11](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R11) Jun 2022 | Performance differences among commercially available antigen rapid tests for COVID-19 in Brazil | PanBio (Abbott) - NP Swab | 60\.00 | 45\.9, 73.0 | 100 | 69\.2, 100 |
| PanBio (Abbott) - NS Swab | 58\.20 | 44\.1, 71.4 | 100 | 69\.2, 100% | | |
| COVID-19 Ag ECO Teste (Eco Diagnostica) | 42\.90 | 30\.5, 56.0 | 83\.30 | 58\.6, 96.4 | | |
| STANDARD Q COVID-19 Ag (SD Biosensor) | 53\.00 | 40\.3, 65.4 | 86\.70 | 59\.5, 98.3 | | |
| CORIS Bioconcept1 Ag-RDT (Nanosens) | 9\.80 | 3\.7, 20.2 | 100 | 78\.2, 100 | | |
| CELLER WONDFO SARSCOV2 Ag-RDT | 47\.20 | 33\.3, 61.4 | 100 | 69\.2, 100 | | |
| NowCheck COVID-19 Ag test (Bionote) | 60 | 45\.9, 73.0 | 100 | 66\.4, 100 | | |
| Ag-RDT COVID-19 (Acro Biotech) | 81\.10 | 68\.0, 90.6 | 84\.60 | 54\.5, 98.1 | | |
| Galliez, *et al.* [70](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R70) Jun 2022 | Evaluation of the Panbio COVID-19 antigen rapid diagnostic test in subjects infected with omicron using different specimens | PanBio (Abbott) - NS Swab | 89 | 82\.4, 93.3 | 100 | 94\.4, 100 |
| PanBio (Abbott) - Oral Specimen | 12\.6 | 7\.9, 19.5 | 100 | 94\.4, 100 | | |
| Garcia-Cardenas, *et al.* [71](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R71) Sep 2021 | Analytical performances of the COVISTIX and Panbio antigen rapid tests for SARS-CoV-2 detection in an unselected population (all comers) | PanBio (Abbott) | 62% | 58, 64 | 99 | 99, 100 |
| COVISTIX Covid 19 Antigen Rapid Test Device | 81 | 76, 85 | 96 | 94, 98 | | |
| Garcia-Cardenas, *et al.* [72](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R72) May 2022 | Analytical performances of the COVISTIX⢠antigen rapid test for SARS-CoV-2 detection in an unselected population (all-comers) | COVISTIX Covid 19 Antigen Rapid Test Device | 81 | 75\.0, 85.0 | 96 | 94\.0, 98.0 |
| COVISTIX Covid 19 Antigen Rapid Test Device | 93 | 88, 98 | 98 | 97, 99 | | |
| GarcĂa-FernĂĄndez, *et al.* [73](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R73) Mar 2022 | Evaluation of the rapid antigen detection test STANDARD F COVID-19 Ag FIA for diagnosing SARS-CoV-2: experience from an emergency department | STANDARD F COVID-19 Ag FIA (SD Biosensor Inc.) | 84 | 76\.1, 89.7 | 99\.6 | 98\.5, 99.9 |
| GarcĂa-FiĂąana, *et al.* [74](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R74) Jul 2021 | Performance of the Innova SARS-CoV-2 antigen rapid lateral flow test in the Liverpool asymptomatic testing pilot: population based cohort study | Innova (recalled 06/2021) | 40 | 28\.5, 52.4 | 99\.9 | 99\.8, 99.99 |
| Goga, *et al.* [75](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R75) Mar 2022 | Utility of COVID-19 point-of-care antigen tests in low-middle income settings | RapiGen (BioCredit) | 34\.8 | 26\.1, 44.2 | 97\.6 | 93\.9, 99.3 |
| STANDARD Q COVID-19 Ag (SD Biosensor) | 49\.1 | 43\.3, 55.0 | 95\.7 | 93\.5, 97.3 | | |
| SARS-CoV-2 Ag (LumiraDx) | 63\.8 | 55\.9, 71.2 | 97 | 95\.5, 98.3 | | |
| GonzĂĄlez-Fiallo, *et al.* [76](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R76) Apr 2022 | Evaluation of SARS-CoV-2 rapid antigen tests in use on the Isle of Youth, Cuba | STANDARD Q COVID-19 Ag (SD Biosensor) | 75\.30% | 66\.0, 84.6 | 96\.10 | 94\.5, 97.6 |
| Gupta, *et al.* [77](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R77) Feb 2021 | Rapid chromatographic immunoassay-based evaluation of COVID-19: a cross-sectional, diagnostic test accuracy study & its implications for COVID-19 management in India | STANDARD Q COVID-19 Ag (SD Biosensor) | 81\.8 | 71\.3, 89.6 | 99\.6 | 97\.8, 99.9 |
| Harris, *et al.* [78](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R78) May 2021 | SARS-CoV-2 rapid antigen testing of symptomatic and asymptomatic individuals on the University of Arizona campus | Sofia SARS Rapid Antigen FIA/Sofia 2 (Quidel) | 91\.4 | | 100 | |
| Holzner, *et al.* [79](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R79) Apr 2021 | SARS-CoV-2 rapid antigen test: fast-safe or dangerous? An analysis in the emergency department of an university hospital | STANDARD Q COVID-19 Ag (SD Biosensor) | 68\.8 | 66\.84, 70.73 | 99\.56 | 99\.3, 99.82 |
| Homza, *et al.* [80](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R80) Apr 2021 | Five antigen tests for SARS-CoV-2: virus viability matters | Ecotest (Assure Tech) | 75\.7 | 66\.5, 83.5 | 96\.7 | 93\.3, 98.7 |
| Immupass VivaDiag (VivaChek Biotech) | 41\.8 | 31\.5, 52.6 | 96 | 92\.0, 98.4 | | |
| ND Covid (NDFOS) | 70\.1 | 58\.6, 80 | 56\.1 | 46\.5, 65.4 | | |
| SARS-CoV-2 Antigen Rapid Test (JoysBio) | 57\.8 | 46\.9, 68.1 | 98\.5 | 94\.8, 99.8 | | |
| STANDARD Q COVID-19 Ag (SD Biosensor) | 61\.9 | 45\.6, 76.4 | 99 | 94\.4, 100 | | |
| HĂśrber, *et al.* [81](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R81) Jun 2022 | Evaluation of a laboratory-based high-throughput SARS-CoV-2 antigen assay | CoV2Ag assay (Siemens Healthineers, Eschborn, Germany) | 88\.50 | 83\.7, 91.9 | 99\.50 | 97\.4, 99.9 |
| Ifko, *et al.* [82](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R82) Jul 2021 | Diagnostic validation of two SARS-CoV-2 immunochromatographic tests in Slovenian and Croatian hospitals | NADAL COVID-19 Antigen Rapid Test (New Art Laboratories/nal von minden) | 84\.61 | 54\.55, 98.08 | 100 | 90\.75, 100 |
| NADAL COVID-19 Antigen Rapid Test (New Art Laboratories/nal von minden) | 86\.96 | 66\.41, 97.23 | 88\.24 | 80\.35, 93.77 | | |
| Igloi, *et al.* [83](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R83) May 2021 | Clinical evaluation of Roche SD Biosensor rapid antigen test for SARS-CoV-2 in municipal health service testing site, the Netherlands | STANDARD Q COVID-19 Ag (SD Biosensor) | 84\.9 | 79\.1, 89.4 | 99\.5 | 98\.7, 99.8 |
| Jakobsen, *et al.* [84](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R84) Jun 2021 | Accuracy and cost description of rapid antigen test compared with reverse transcriptase-polymerase chain reaction for SARS-CoV-2 detection | STANDARD Q COVID-19 Ag (SD Biosensor) | 69\.7 | | 99\.5 | |
| Jakobsen, *et al.* [85](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R85) Feb 2022 | Accuracy of anterior nasal swab rapid antigen tests compared with RT-PCR for massive SARS-CoV-2 screening in low prevalence population | STANDARD Q COVID-19 Ag (SD Biosensor) | 48\.5 | | 100 | |
| Jeewandara, *et al.* [86](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R86) Mar 2022 | Sensitivity and specificity of two WHO approved SARS-CoV2 antigen assays in detecting patients with SARS-CoV2 infection | STANDARD Q COVID-19 Ag (SD Biosensor) | 36\.24 | 33\.1, 39.5 | 97\.6 | 97, 98 |
| PanBio (Abbott) | 52\.6 | 46\.7, 58.5 | 99\.6 | 99\.2, 99.8 | | |
| Jegerlehner, *et al.* [87](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R87) Jul 2021 | Diagnostic accuracy of a SARS-CoV-2 rapid antigen test in real-life clinical settings | STANDARD Q COVID-19 Ag (SD Biosensor) | 65\.3 | 56\.8, 73.1 | 99\.9 | 99\.5, 100 |
| PCL COVID19 Ag Rapid FIA Antigen Test (PCL) | 30\.2 | 18\.3, 44.3 | 98\.1 | 96\.0, 99.3 | | |
| Jegerlehner, *et al.* [88](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R88) Jun 2022 | Diagnostic accuracy of SARS-CoV-2 saliva antigen testing in a real-life clinical setting | PCL COVID19 Ag Rapid FIA Antigen Test (PCL) | 30\.2 | 18\.3, 44.3 | 98\.1 | 96\.0, 99.3 |
| Jirungda, *et al.* [89](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R89) May 2022 | Clinical performance of the STANDARD F COVID-19 AG FIA for the detection of SARS-COV-2 infection | STANDARD F COVID-19 Ag FIA (SD Biosensor Inc.) | 98\.8 | | 89\.7 | |
| Kahn, *et al.* [90](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R90) Aug 2021 | Performance of antigen testing for diagnosis of COVID-19: a direct comparison of a lateral flow device to nucleic acid amplification based tests | STANDARD F COVID-19 Ag FIA (SD Biosensor Inc.) | 59\.4 | | 99 | |
| Kessler, *et al.* [91](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R91) Mar 2022 | Identification of contagious SARS-CoV-2 infected individuals by Roche's Rapid Antigen Test | Roche SARS-CoV-2 Rapid Antigen Test (Roche)- Central Lab | | | | |
| Kim, *et al.* [92](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R92) Apr 2021 | Development and clinical evaluation of an immunochromatography-based rapid antigen test (GenBody⢠COVAG025) for COVID-19 diagnosis | GenBody COVAG025 (GenBody) | Not reported | | | |
| GenBody COVAG025 (GenBody) - Prospective | 94 | 87\.4, 97.77 | 100 | 96\.38, 100 | | |
| GenBody COVAG025 (GenBody) - Retrospective | 90 | 73\.47, 97.89 | 98 | 92\.96, 99.76 | | |
| King, *et al.* [93](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R93) Sep 2021 | Validation of the Panbio⢠COVID-19 Antigen Rapid Test (Abbott) to screen for SARS-CoV-2 infection in Sint Maarten: a diagnostic accuracy study | PanBio (Abbott) | 84 | 76\.2, 90.1 | 99\.9 | 99\.6, 100 |
| Kiyasu, *et al.* [94](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R94) Jul 2021 | Prospective analytical performance evaluation of the QuickNaviâ˘-COVID19 Ag for asymptomatic individuals | QuickNavi-COVID19 Ag | 80\.3 | 73\.9, 85.7 | 100 | 99\.7, 100 |
| Klajmon, *et al.* [95](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R95) Dec 2021 | Comparison of antigen tests and qPCR in rapid diagnostics of infections caused by SARS-CoV-2 virus | Humasis COVID-19 Ag Test kit (Humasis Co., Ltd.) | 91\.49 | 79\.62, 97.63 | 97\.9 | 93\.99, 99.57 |
| Klein, *et al.* [96](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R96) May 2021 | Head-to-head performance comparison of self-collected nasal versus professional-collected nasopharyngeal swab for a WHO-listed SARS-CoV-2 antigen-detecting rapid diagnostic test | PanBio (Abbott) - NMT | 84\.4 | 71\.2, 92.3 | 99\.2 | 97\.1, 99.8 |
| PanBio (Abbott) - NP Swab | 88\.9 | 76\.5, 95.5 | 99\.2 | 97\.1, 99.8 | | |
| Kohmer, *et al.* [97](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R97) Jan 2021 | The comparative clinical performance of four SARS-CoV-2 rapid antigen tests and their correlation to infectivity in vitro | SARS-CoV-2 Ag (LumiraDx) | 50 | 38\.1, 61.9 | 100 | 86\.8, 100 |
| NADAL COVID-19 Antigen Rapid Test (New Art Laboratories/nal von minden) | 24\.3 | 15\.1, 35.7 | 100 | 86\.8, 100 | | |
| Rida Quick SARS-CoV-2 (R-Biopharm) | 39\.2 | 28, 51.2 | 96\.2 | 80\.4, 99.9 | | |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 43\.2 | 37\.8, 55.3 | 100 | 86\.8, 100 | | |
| Korenkov, *et al.* [98](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R98) Aug 2021 | Evaluation of a rapid antigen test to detect SARS-CoV-2 infection and identify potentially infectious individuals | STANDARD Q COVID-19 Ag (SD Biosensor) | 100 | 88\.3, 100 | 71\.91 | 61\.82, 80.20 |
| Korenkov, *et al.* [99](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R99) May 2021 | Assessment of SARS-CoV-2 infectivity by a rapid antigen detection test | STANDARD Q COVID-19 Ag (SD Biosensor) | 42\.86 | | | 99\.89 |
| KrĂźger, *et al.* [100](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R100) Aug 2021 | Evaluation of accuracy, exclusivity, limit-of-detection and ease-of-use of LumiraDxâ˘: an antigen-detecting point-of-care device for SARS-CoV-2 | SARS-CoV-2 Ag (LumiraDx) - Berlin | 80\.2 | 70\.3, 87.5 | 99\.5 | 97\.1, 100 |
| SARS-CoV-2 Ag (LumiraDx) - Heidelberg | 84\.6 | 7\.9, 91.4 | 99\.3 | 97\.9, 99.7 | | |
| SARS-CoV-2 Ag (LumiraDx) | 82\.2 | 75\.2, 87.5 | 99\.3 | 97\.9, 99.7 | | |
| KrĂźger, *et al.* [101](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R101) Dec 2021 | Accuracy and ease-of-use of seven point-of-care SARS-CoV-2 antigen-detecting tests: A multi-centre clinical evaluation | Fluorecare (Colloidal Gold/Fluorescent) SARS-CoV-2 Spike Protein Test kit (Shenzen Microprofit) - Germany | 66\.7 | 41\.7, 84.8 | 93\.1 | 91\.0, 94.8 |
| RapiGen (BioCredit) - Brazil | 74\.4 | 65\.8, 81.4 | 98\.9 | 97\.2, 99.6 | | |
| STANDARD F COVID-19 Ag FIA (SD Biosensor Inc.) - Brazil | 77\.5 | 69\.2, 84.1 | 97\.9 | 95\.7, 99 | | |
| NowCheck COVID-19 Ag test (Bionote) - Brazil | 89\.2 | 81\.7, 93.9 | 97\.3 | 94\.8, 98.6 | | |
| RapiGen (BioCredit) - Germany | 52 | 33\.5, 70 | 100 | 99\.7, 100 | | |
| STANDARD Q COVID-19 Ag (SD Biosensor) - Germany | 76\.2 | 68\.0, 82.8 | 99\.3 | 98\.8, 99.6 | | |
| Espline SARS-CoV-2 (Fujirebio) - Germany | 79\.5 | 71\.1, 85.9 | 100 | 99\.4, 100 | | |
| Mologic Covid-19 Rapid Antigen Test (Mologic Ltd. United Kingdom) - Germany | 90\.1 | 85\.1, 93.6 | 100 | 99\.2, 100 | | |
| STANDARD F COVID-19 Ag FIA (SD Biosensor Inc.) | 75\.5 | 68\.2, 81.5 | 97\.2 | 96\.0, 98.1 | | |
| STANDARD Q COVID-19 Ag (SD Biosensor) | 81\.9 | 76\.4, 86.3 | 99 | 98\.5, 99.4 | | |
| RapiGen (BioCredit) | 70\.4 | 62\.4, 77.3 | 99\.7 | 99\.3, 99.9 | | |
| KrĂźger, *et al.* [102](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R102) Dec 2022 | A multi-center clinical diagnostic accuracy study of Surestatus - an affordable, WHO emergency-use-listed, rapid, point-of-care, antigen-detecting diagnostic test for SARS-CoV-2 (preprint) | SureStatus | 82\.4 | 76\.6, 87.1 | 98\.5 | 97\.4, 99.1 |
| KrĂźger, *et al.* [103](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R103) May 2021 | The Abbott PanBio WHO emergency use listed, rapid, antigen-detecting point-of-care diagnostic test for SARS-CoV-2-Evaluation of the accuracy and ease-of-use | PanBio (Abbott) | 86\.8 | 79\.0, 92.0 | 99\.9 | 99\.4, 100 |
| Kurihara, *et al.* [104](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R104) Jul 2021 | The evaluation of a novel digital immunochromatographic assay with silver amplification to detect SARS-CoV-2 | Custom/Novel/In-house | 74\.7 | 64\.0, 83.6 | 99\.8 | 99\.5, 100 |
| PanBio (Abbott) | Not reported | | | | | |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche) | Not reported | | | | | |
| Espline SARS-CoV-2 (Fujirebio) | Not reported | | | | | |
| Kweon, *et al.* [105](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R105) May 2022 | Positivity of rapid antigen testing for SARS-CoV-2 with serial followed-up nasopharyngeal swabs in hospitalized patients due to COVID-19 | STANDARD Q COVID-19 Ag (SD Biosensor) - E gene | 43\.9 | 37\.7, 50.3 | | |
| QuickNavi-COVID19 Ag | Not reported | | | | | |
| STANDARD Q COVID-19 Ag (SD Biosensor) RdRp gene | 43\.9 | 37\.7, 50.3 | | | | |
| Kyritsi, *et al.* [106](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R106) Aug 2021 | Rapid Test Ag 2019-nCoV (PROGNOSIS, BIOTECH, Larissa, Greece); performance evaluation in hospital setting with real time RT-PCR | Rapid Test Ag 2019-nCov (PROGNOSIS, BIOTECH, Greece) | 85\.5 | 79\.1, 90.5 | 99\.8 | 98\.8, 100 |
| Rapid Test Ag 2019-nCoV (PROGNOSIS, BIOTECH, Larissa, Greece); performance evaluation in hospital setting with real time RT-PCR | Rapid Test Ag 2019-nCov (PROGNOSIS, BIOTECH, Greece): 1 part/thousand prevalence | 85\.5 | 79\.1, 90.5 | 99\.8 | 98\.8, 100 | |
| Rapid Test Ag 2019-nCoV (PROGNOSIS, BIOTECH, Larissa, Greece); performance evaluation in hospital setting with real time RT-PCR | Rapid Test Ag 2019-nCov (PROGNOSIS, BIOTECH, Greece): 1 percent prevalence | 85\.5 | 79\.1, 90.5 | 99\.8 | 98\.8, 100 | |
| Rapid Test Ag 2019-nCoV (PROGNOSIS, BIOTECH, Larissa, Greece); performance evaluation in hospital setting with real time RT-PCR | Rapid Test Ag 2019-nCov (PROGNOSIS, BIOTECH, Greece): 5 percent prevalence | 85\.5 | 79\.1, 90.5 | 99\.8 | 98\.8, 100 | |
| Landaverde, *et al.* [107](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R107) Mar 2022 | Comparison of BinaxNOW TM and SARS-CoV-2 qRT-PCR detection of the omicron variant from matched anterior nares swabs (preprint) | BinaxNOW (Abbott) | 53\.9 | | 100 | |
| Layer, *et al.* [108](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R108) Feb 2022 | SARS-CoV-2 screening strategies for returning international travellers: evaluation of a rapid antigen test approach | Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 59 | | 100 | |
| LeGoff, *et al.* [109](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R109) Oct 2021 | Evaluation of a saliva molecular point of care for the detection of SARS-CoV-2 in ambulatory care | EasyCov (SkillCell-Alcen, France) | 34 | 26, 44 | 97 | 96, 98 |
| STANDARD Q COVID-19 Ag (SD Biosensor) | 85 | 77, 91 | 99 | 98, 99 | | |
| Leixner, *et al.* [110](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R110) Jul 2021 | Evaluation of the AMP SARS-CoV-2 rapid antigen test in a hospital setting | AMP Rapid Test SARS-CoV-2 Ag (AMP Diagnostics) | 69\.15 | 58\.8, 78.3 | 99\.66 | 98\.1, 100 |
| Linares, *et al.* [111](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R111) Oct 2020 | Panbio antigen rapid test is reliable to diagnose SARS-CoV-2 infection in the first 7 days after the onset of symptoms | PanBio (Abbott) | 73\.3 | 62\.2, 83.8 | 100 | |
| Lindner, *et al.* [112](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R112) Apr 2021a | Head-to-head comparison of SARS-CoV-2 antigen-detecting rapid test with self-collected nasal swab versus professional-collected nasopharyngeal swab | STANDARD Q COVID-19 Ag (SD Biosensor)-NMT | 74\.4 | 58\.9, 85.4 | 99\.2 | 97\.1, 99.8 |
| STANDARD Q COVID-19 Ag (SD Biosensor)-NP | 79\.5 | 64\.5, 89.2 | 99\.6 | 97\.8, 100 | | |
| Lindner, *et al.* [113](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R113) Apr 2021b | Head-to-head comparison of SARS-CoV-2 antigen-detecting rapid test with professional-collected nasal versus nasopharyngeal swab | STANDARD Q COVID-19 Ag (SD Biosensor)-NMT | 80\.5 | 66\.0, 89.8 | 98\.6 | 94\.9, 99.6 |
| STANDARD Q COVID-19 Ag (SD Biosensor)-NP | 73\.2 | 58\.1, 84.3 | 99\.3 | 96\.0, 100 | | |
| Lindner, *et al.* [114](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R114) May 2021 | Diagnostic accuracy and feasibility of patient self-testing with a SARS-CoV-2 antigen-detecting rapid test | STANDARD Q COVID-19 Ag (SD Biosensor)-Professional | 85 | 70\.9, 92.9 | 99\.1 | 94\.8, 99.5 |
| STANDARD Q COVID-19 Ag (SD Biosensor)-Self testing | 82\.5 | 68\.1, 91.3 | 100 | 96\.5, 100 | | |
| Mandal, *et al.* [115](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R115) May 2022 | Diagnostic performance of SARS-CoV-2 rapid antigen test in relation to RT-PCR CqValue | Espline SARS-CoV-2 (Fujirebio) | 63\.60% | 54\.7, 71.9 | 97\.90 | 93\.6, 99.6 |
| Mane, *et al.* [116](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R116) May 2022 | Diagnostic performance of oral swab specimen for SARS-CoV-2 detection with rapid point-of-care lateral flow antigen test | PathoCatch (Accucare) | Not reported | | | |
| PathoCatch (Accucare) - oral swabs | Not reported | | | | | |
| Maniscalco, *et al.* [117](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R117) Aug 2021 | A rapid antigen detection test to diagnose SARS-CoV-2 infection using exhaled breath condensate by a modified Inflammacheck(ÂŽ) device | Inflammacheck (Exhalation Technology LTD) | 92\.3 | 64\.0, 99.8 | 98\.9 | 94\.1, 100.0 |
| MasiĂĄ, *et al.* [118](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R118) Jan 2021 | Nasopharyngeal Panbio COVID-19 antigen performed at point-of-care has a high sensitivity in symptomatic and asymptomatic patients with higher risk for transmission and older age | PanBio (Abbott) | 68\.1 | | 100 | |
| Mizrahi, *et al.* [119](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R119) Nov 2021 | The Coris BioConcept COVID 19 Ag Respi-Strip, a field experience feedback | Respi-Strip (Coris BioConcept) - Coris-Ag: 30-min reading (n = 294) | 45\.2 | | 100 | |
| Respi-Strip (Coris BioConcept) - Period 1 (n = 158) | 59\.3 | | 100 | | | |
| Respi-Strip (Coris BioConcept) - Period 2 (n = 136) | 20 | | 100 | | | |
| Møller, *et al.* [120](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R120) Jan 2022 | Diagnostic performance, user acceptability, and safety of unsupervised SARS-CoV-2 rapid antigen-detecting tests performed at home | SARS-CoV-2 Antigen Rapid Test (Hangzhou Immuno Biotech Co Ltd, China). | 62\.1 | 50\.1, 72.9 | 100 | 98\.9, 100 |
| COVID-19 Antigen Detection Kit (DNA Diagnostic A/S, Denmark) | 65\.7 | 49\.2, 79.2 | 100 | 99, 100 | | |
| PanBio (Abbott) | Not estimable | | 100 | 95\.6, 100 | | |
| Nagura-Ikeda, *et al.* [121](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R121) Aug 2020 | Clinical evaluation of self-collected saliva by quantitative reverse transcription-PCR (RT-qPCR), direct RT-qPCR, reverse transcriptionâloop-mediated isothermal amplification, and a rapid antigen test to diagnose COVID-19 | Espline SARS-CoV-2 (Fujirebio) | 11\.7 | | | |
| Nikolai, *et al.* [122](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R122) Aug 2021 | Anterior nasal versus nasal mid-turbinate sampling for a SARS-CoV-2 antigen-detecting rapid test: does localisation or professional collection matter? | STANDARD Q COVID-19 Ag (SD Biosensor) - Prof.-sampling: All (N =36), Prof AN | 86\.1 | 71\.3, 93.9 | 100 | 95\.7, 100 |
| STANDARD Q COVID-19 Ag (SD Biosensor) - Self-sampling: All (N=34), Prof. NP | 91\.2 | 77, 97 | 100 | 94\.2, 100 | | |
| STANDARD Q COVID-19 Ag (SD Biosensor) - Self-sampling: All (N=34), Self NMT | 91\.2 | 77\.0, 97 | 98\.4 | 91\.4, 99.9 | | |
| NĂłra, *et al.* [123](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R123) Feb 2022 | Evaluating the field performance of multiple SARS-Cov-2 antigen rapid tests using nasopharyngeal swab samples | PanBio (Abbott) | Not reported | | | |
| CoV2Ag assay (Siemens Healthineers, Eschborn, Germany) | Not reported | | | | | |
| GenBody COVAG025 (GenBody) | Not reported | | | | | |
| GENEDIA W COVID-19 Ag Test (Green Cross Medical Science Corp.) | Not reported | | | | | |
| Humasis COVID-19 Ag Test kit (Humasis Co., Ltd.) | Not reported | | | | | |
| Immupass VivaDiag (VivaChek Biotech) | Not reported | | | | | |
| Helix i-SARS-CoV-2 Ag Rapid Test (Cellex Biotech Co.) | Not reported | | | | | |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche) | Not reported | | | | | |
| Rapid COVID-19 Antigen Test (Healgen Scientific) | Not reported | | | | | |
| Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Antigen Detection Kit (Colloidal Gold-Based) Nanjing Vazyme Medical Technology Co | Not reported | | | | | |
| Okoye, *et al.* [124](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R124) Feb 2022 | Diagnostic accuracy of a rapid diagnostic test for the early detection of COVID-19 | BinaxNOW (Abbott) | 91\.84 | 80\.40, 97.73 | 99\.95 | 99\.81, 99.99 |
| Onsongo, *et al.* [125](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R125) Feb 2022 | Performance of a rapid antigen test for SARS-CoV-2 in Kenya | NowCheck COVID-19 Ag test (Bionote) | Not reported | | | |
| Osmanodja, *et al.* [126](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R126) May 2021 | Accuracy of a novel sars-cov-2 antigen-detecting rapid diagnostic test from standardized self-collected anterior nasal swabs | Custom/Novel/In-house | 88\.6 | 78\.7, 94.9 | 99\.7 | 98\.2, 100 |
| Paap, *et al.* [127](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R127) Jun 2022 | Clinical evaluation of single-swab sampling for rapid COVID-19 detection in outbreak settings in Dutch nursing homes | Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 50\.9 | | 89 | |
| Pandey, *et al.* [128](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R128) Aug 2021 | Comparison of the rapid antigen testing method with RT-qPCR for the diagnosis of COVID-19 | STANDARD Q COVID-19 Ag (SD Biosensor) | 53\.6 | 39\.7, 67.0 | 97\.3 | 94\.6, 98.9 |
| Park, *et al.* [129](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R129) Feb 2022 | Analysis of the efficacy of universal screening of coronavirus disease with antigen-detecting rapid diagnostic tests at point-or-care settings and sharing the experience of admission protocolâa pilot study | STANDARD Q COVID-19 Ag (SD Biosensor) | 68\.3 | | 99\.5 | |
| Peacock, *et al.* [130](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R130) Jan 2022 | Utility of COVID-19 antigen testing in the emergency department | BinaxNOW (Abbott) | 76\.9 | 69\.9, 82.9 | 98\.6 | 97\.2, 99.4 |
| PeĂąa, *et al.* [131](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R131) Apr 2021 | Performance of SARS-CoV-2 rapid antigen test compared with real-time RT-PCR in asymptomatic individuals | STANDARD Q COVID-19 Ag (SD Biosensor) | 69\.86 | 58\.56, 9.18*\[typo in paper\]* | 99\.61 | 98\.86, 99.87 |
| PeĂąa-Rodriguez, *et al.* [132](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R132) Feb 2021 | Performance evaluation of a lateral flow assay for nasopharyngeal antigen detection for SARS-CoV-2 diagnosis | STANDARD Q COVID-19 Ag (SD Biosensor) | 75\.9 | 66\.5, 83.8 | 100 | 98\.6, 100 |
| Peronace, *et al.* [133](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R133) May 2022 | Validation of GeneFinder COVID-19 Ag plus rapid test and its potential utility to slowing infection waves: a single-center laboratory evaluation study | GeneFinder COVID-19 Ag Plus Rapid Test | 96\.03 | 91\.55, 98.53 | 99\.78 | 98\.77, 99.99 |
| Pilarowski, *et al.* [134](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R134) Jan 2021 | Performance characteristics of a rapid SARS-CoV-2 antigen detection assay at a public plaza testing site in San Francisco | BinaxNOW (Abbott) | 57\.7 | 36\.9, 76.6 | 100 | 99\.6, 100 |
| Pollock, *et al.* [135](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R135) Apr 2021 | Performance and implementation evaluation of the Abbott BinaxNOW Rapid Antigen Test in a high-throughput drive-through community testing site in Massachusetts | BinaxNOW (Abbott) | 84\.1 | 77\.4, 89.4 | 99\.6 | 99\.1, 99.9 |
| Poopalasingam, *et al.* [136](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R136) Feb 2022 | Determining the reliability of rapid SARS-CoV-2 antigen detection in fully vaccinated individuals | STANDARD Q COVID-19 Ag (SD Biosensor) | 57\.3 | 46\.1, 67.9 | 99\.7 | 98\.8, 99.9 |
| Prost, *et al.* [137](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R137) Dec 2021 | Evaluation of a rapid in vitro diagnostic test device for detection of SARS-CoV-2 antigen in nasal swabs | SARS-CoV-2 Antigen Rapid Test (Hangzhou Immuno Biotech Co Ltd, China). | 97\.3 | 94\.2, 99.0 | 99\.5 | 97\.3, 100 |
| Rahman, *et al.* [138](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R138) Nov 2021 | Clinical evaluation of SARS-CoV-2 antigen-based rapid diagnostic test kit for detection of COVID-19 cases in Bangladesh | STANDARD Q COVID-19 Ag (SD Biosensor)- Adults | 85\.76 | 81\.25, 89.54 | | |
| Rana, *et al.* [139](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R139) Sept 2021 | Evaluation of the currently used antigen-based rapid diagnostic test for the detection of SARS CoV-2 virus in respiratory specimens | STANDARD Q COVID-19 Ag (SD Biosensor) | 37\.5 | | 99\.79 | |
| Rastawicki, *et al.* [140](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R140) Jan 2021 | Evaluation of PCL rapid point of care antigen test for detection of SARS-CoV-2 in nasopharyngeal swabs | PCL COVID19 Ag Rapid FIA Antigen Test (PCL) | 38\.9 | | 83\.3 | |
| Rohde, *et al.* [142](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R142) Feb 2022 | Diagnostic accuracy and feasibility of a rapid SARS-CoV-2 antigen test in general practice - a prospective multicenter validation and implementation study | Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 78\.3 | 70\.9, 84.6 | 99\.5 | 99, 99.8 |
| Salcedo, *et al.* [143](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R143) Feb 2022 | Comparative Evaluation of Rapid Isothermal Amplification and Antigen Assays for Screening Testing of SARS-CoV-2 | Custom/Novel/In-house | Not reported | | | |
| Salvagno, *et al.* [144](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R144) Jan 2021 | Clinical assessment of the Roche SARS-CoV-2 rapid antigen test | STANDARD Q COVID-19 Ag (SD Biosensor) | 72\.5 | 64\.6, 79.5 | 99\.4 | 96\.8, 100 |
| Salvagno, *et al.* [145](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R145) May 2021 | Real-world assessment of Fluorecare SARS-CoV-2 Spike Protein Test Kit | Fluorecare (Colloidal Gold/Fluorescent) SARS-CoV-2 Spike Protein Test kit (Shenzen Microprofit) | 27\.5 | 21\.8, 33.7 | 99\.2 | 95\.5, 100 |
| Savage, *et al.* [146](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R146) Jun 2022 | A prospective diagnostic evaluation of accuracy of self-taken and healthcare worker-taken swabs for rapid COVID-19 testing | Covios COVID-19 Antigen Rapid Dianostic test-Health-care worker taken swab | 78\.4 | 69\.0, 87.8 | 98\.9 | 97\.3, 100.0 |
| Covios COVID-19 Antigen Rapid Dianostic test-Self-taken swab | 90\.5 | 83\.9, 97.2 | 99\.4 | 98\.3, 100.0 | | |
| Schildgen, *et al.* [147](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R147) Jan 2021 | Limits and opportunities of SARS-CoV-2 antigen rapid tests: an experienced-based perspective | PanBio (Abbott) | 50 | 35, 64 | 77\.4 | 60, 89 |
| RapiGen (BioCredit) | 33\.3 | 21, 48 | 87\.1 | 71, 95 | | |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 88\.1 | 75, 95 | 19\.4 | 9, 36 | | |
| Selvabai, *et al.* [148](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R148) Apr 2022 | Diagnostic Efficacy of COVID-19 Rapid Antigen Detection Card in Diagnosis of SARS-CoV-2 | Athenese-DX COVID-19 RAT kit | 74\.19 | | 100 | |
| Shaw, *et al.* [149](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R149) Jul 2021 | Evaluation of the Abbott Panbio(TM) COVID-19 Ag rapid antigen test for the detection of SARS-CoV-2 in asymptomatic Canadians | PanBio (Abbott) | Not reported | | | |
| Siddiqui, *et al.* [150](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R150) Dec 2021 | Implementation and Accuracy of BinaxNOW Rapid Antigen COVID-19 Test in Asymptomatic and Symptomatic Populations in a High-Volume Self-Referred Testing Site | BinaxNOW (Abbott) | 81 | 75, 86 | 99\.8 | 100\.0, 100.0 |
| Sitoe, *et al.* [151](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R151) Feb 2022 | Performance Evaluation of the STANDARD(TM) Q COVID-19 and Panbio(TM) COVID-19 Antigen Tests in Detecting SARS-CoV-2 during High Transmission Period in Mozambique | PanBio (Abbott) | 41\.3 | 34\.6, 48.4 | 98\.2 | 96\.2, 99.3 |
| STANDARD Q COVID-19 Ag (SD Biosensor) | 45 | 39\.9, 50.2 | 97\.6 | 95\.3, 99.0 | | |
| SkvarÄ[152](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R152) Apr 2022 | Clinical validation of two immunochromatographic SARS-CoV-2 antigen tests in near hospital facilities | Immupass VivaDiag (VivaChek Biotech) | 90\.6 | 84\.94, 94.36 | 100 | 99\.41, 100.0 |
| Alltest Covid19 Ag test | 94\.37 | 89\.20, 97.54 | 100 | 98\.83, 100.0 | | |
| Smith, *et al.* [153](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R153) Jun 2021 | Clinical Evaluation of Sofia Rapid Antigen Assay for Detection of Severe Acute Respiratory Syndrome Coronavirus 2 among Emergency Department to Hospital Admissions | Sofia SARS Rapid Antigen FIA/Sofia 2 (Quidel) | 76\.6 | 71, 82 | 99\.7 | 99\.0, 100 |
| Soleimani, *et al.* [141](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R141) May 2021 | Rapid COVID-19 antigenic tests: usefulness of a modified method for diagnosis | PanBio (Abbott) | 75 | 68\.9, 80.4 | | |
| COVID19-Speed/Biospeedia COVID19 Antigen test (Biospeedia) | 65\.5 | 59\.0, 71.6 | 100 | | | |
| Stohr, *et al.* [154](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R154) May 2022 | Self-testing for the detection of SARS-CoV-2 infection with rapid antigen tests for people with suspected COVID-19 in the community | BD Veritor COVID-19 Rapid Antigen Test (Becton-Dickinson) | 49\.1 | 41\.7, 56.5 | 99\.9 | 99\.7, 100.0 |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 61\.5 | 54\.6, 68.3 | 99\.7 | 99\.4, 99.9 | | |
| Surasi, *et al.* [155](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R155) Nov 2021 | Effectiveness of Abbott BinaxNOW rapid antigen test for detection of SARS-CoV-2 infections in outbreak among horse racetrack workers, California, USA | BinaxNOW (Abbott) | 43\.3 | 34\.6, 52.4 | 100 | 99\.4, 100.0 |
| Suzuki, *et al.* [156](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R156) May 2022 | Analytical performance of rapid antigen tests for the detection of SARS-CoV-2 during widespread circulation of the Omicron variant | QuickNavi-COVID19 Ag | 94\.2 | 91\.6, 96.3 | 99\.5 | 98\.7, 99.9 |
| Suzuki, *et al.* [157](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R157) Jan 2022 | Diagnostic performance of a novel digital immunoassay (RapidTesta SARS-CoV-2): A prospective observational study with nasopharyngeal samples | RapidTesta SARS-CoV-2 | 71\.6 | 59\.9, 81.5 | 99\.2 | 98\.5, 99.7 |
| RapidTesta SARS-CoV-2 | 78\.4 | 67\.3, 87.1 | 97\.6 | 96\.5, 98.5 | | |
| Terpos, *et al.* [158](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R158) May 2021 | Clinical Application of a New SARS-CoV-2 Antigen Detection Kit (Colloidal Gold) in the Detection of COVID-19 | Custom/Novel/In-house | Not reported | | | |
| Thakur, *et al.* [159](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R159) Nov 2021 | Utility of Antigen-Based Rapid Diagnostic Test for Detection of SARS-CoV-2 Virus in Routine Hospital Settings | PathoCatch (Accucare) | 34\.5 | 24\.5, 45.6 | 99\.8 | 99\.1, 100 |
| Thell, *et al.* [160](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R160) Nov 2021 | Evaluation of a novel, rapid antigen detection test for the diagnosis of SARS-CoV-2 | Roche SARS-CoV-2 Rapid Antigen Test (Roche)-Emergency Dept | 77\.9 | 70\.0, 84.6 | 98\.1 | 94\.6, 99.6 |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche)-Primary Health Care | 84\.4 | 74\.4, 91.7 | 100 | 97\.8, 100.0 | | |
| Thirion-Romero, *et al.* [161](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R161) Oct 2021 | Evaluation of Panbio rapid antigen test for SARS-CoV-2 in symptomatic patients and their contacts: a multicenter study | PanBio (Abbott) | 54\.2 | 51\.2, 57.2 | 98\.5 | 97\.7, 99.2 |
| Tonelotto, *et al.* [162](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R162) Jan 2022 | Efficacy of Fluorecare SARS-CoV-2 Spike Protein Test Kit for SARS-CoV-2 detection in nasopharyngeal samples of 121 individuals working in a manufacturing company | Fluorecare (Colloidal Gold/Fluorescent) SARS-CoV-2 Spike Protein Test kit (Shenzen Microprofit) | 84\.6 | 54\.6, 98.1 | 100 | 98\.6, 100.0 |
| Toptan, *et al.* [163](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R163) Feb 2021 | Evaluation of a SARS-CoV-2 rapid antigen test: potential to help reduce community spread? | Rida Quick SARS-CoV-2 (R-Biopharm)-Berlin | 77\.6 | | 100 | |
| Rida Quick SARS-CoV-2 (R-Biopharm)-Frankfurt | 50 | | 100 | | | |
| Trobajo-SanmartĂn, *et al.* [164](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R164) Mar 2021 | Evaluation of the rapid antigen test CerTest SARS-CoV-2 as an alternative COVID-19 diagnosis technique | CerTest SARS-CoV-2 (Certest Biotech) | 78\.75 | 67\.89, 86.79 | 100 | 97\.08, 99.94 |
| Turcato, *et al.* [165](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R165) Mar 2021 | Clinical application of a rapid antigen test for the detection of SARS-CoV-2 infection in symptomatic and asymptomatic patients evaluated in the emergency department: a preliminary report | Standard Q COVID-19 Ag (SD Biosensor) | 80\.3 | 74\.9, 85.4 | 99\.1 | 98\.6, 99.3 |
| Turcato, *et al.* [166](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R166) Jan 2022 | Rapid antigen test to identify COVID-19 infected patients with and without symptoms admitted to the emergency department | Standard Q COVID-19 Ag (SD Biosensor) | 82\.9 | 81\.0, 84.8 | 99\.1 | 98\.8, 99.3 |
| Van der Moeren, *et al.* [167](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R167) May 2021 | Evaluation of the test accuracy of a SARS-CoV-2 rapid antigen test in symptomatic community dwelling individuals in the Netherlands | BD Veritor COVID-19 Rapid Antigen Test (Becton-Dickinson) | 94\.1 | 71\.1, 100 | 100 | 98\.9, 100 |
| BD Veritor COVID-19 Rapid Antigen Test (Becton-Dickinson)-Visual | 94\.1 | 71\.1, 100 | 100 | 98\.9, 100 | | |
| Van Honacker, *et al.* [168](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R168) Aug 2021 | Comparison of five SARS-CoV-2 rapid antigen tests in a hospital setting and performance of one antigen assay in routine practice. A useful tool to guide isolation precautions? | Standard Q COVID-19 Ag (SD Biosensor) | 54\.2 | | 99\.7 | |
| von Ahnen, *et al.* [169](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R169) Mar 2022 | Evaluation of a rapid-antigen test for COVID-19 in an asymptomatic collective: a prospective study | Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 92\.3 | 78\.0, 100 | 100 | 100\.0, 100.0 |
| Wertenauer, *et al.* [170](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R170) Mar 2022 | Diagnostic performance of rapid antigen testing for SARS-CoV-2: the COVid-19 AntiGen (COVAG) study | PanBio (Abbott) | 56\.8 | | 99\.9 | |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 60\.4 | | 99\.7 | | | |
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/table/TU15/)
## Appendix IV: Rapid antigen tests from included studies
| | Name | Company | Study count | Reported 100% sensitivity in at least 1 study | Reported 100% specificity in at least 1 study | Reported 100% positive predictive value in at least 1 study | Reported 100% negative predictive value in at least 1 study |
|---|---|---|---|---|---|---|---|
| 1 | STANDARD Q COVID-19 Ag Test | SD Biosensor Inc. | 28 | X | X | X | X |
| 2 | PanBio COVID-19 Ag Rapid Test Device | Abbott | 14 | | X | X | |
| 3 | SARS-CoV-2 Rapid Antigen Test | Roche Diagnostics | 11 | | X | X | |
| 4 | BinaxNOW COVID-19 Antigen | Abbott | 10 | | X | X | |
| 5 | Rapid Test Ag 2019-nCov | ProGnosis Biotech | 4 | | | | |
| 6 | SARS-CoV-2 Ag | LumiraDx | 3 | | X | | |
| 7 | Custom/Novel/In-house | N/A | 3 | | | | |
| 8 | COVISTIX (COVIDMARK) Covid 19 Antigen Rapid Test Device | Sorrento Therapeutics | 3 | | | | |
| 9 | AMP Rapid Test SARS-CoV-2 Ag | AMP Diagnostics | 2 | | X | X | |
| 10 | BD Veritor COVID-19 Rapid Antigen Test | Becton-Dickinson | 2 | | X | X | |
| 11 | CerTest SARS-CoV-2 | Certest Biotec | 2 | | X | X | |
| 12 | Espline SARS-CoV-2 | Fujirebio | 2 | | X | X | |
| 13 | SARS-CoV-2 Antigen Rapid Test | Hangzhou Immuno Biotech Co Ltd | 2 | | X | | |
| 14 | HUMASIS COVID-19 Ag Test | Humasis Co., Ltd | 2 | | | | |
| 15 | Mologic Covid-19 Rapid Antigen Test | Mologic Ltd. United Kingdom | 2 | | X | X | |
| 16 | NADAL COVID-19 Ag Rapid Test | New Art Laboratories/nal von minden | 2 | | X | X | |
| 17 | Quick Navi-COVID 19 Ag | Otsuka Pharmaceutical Co., Ltd. | 2 | | X | | |
| 18 | PCL COVID19 Ag Rapid FIA Antigen Test | PCL, Inc. | 2 | | | | |
| 19 | Sofia SARS Rapid Antigen FIA/Sofia 2 | Quidel | 2 | | X | X | |
| 20 | BIOCREDIT COVID-19 Ag | RapiGen, Inc. | 2 | | X | X | |
| 21 | Rida Quick SARS-CoV-2 Antigen Test | R-Biopharm AG | 2 | | X | X | |
| 22 | STANDARD F COVID-19 Ag FIA | SD Biosensor Inc | 2 | | | | |
| 23 | RapidTesta SARS-CoV-2 | Sekisui Medical Co., Ltd | 2 | | | | |
| 24 | Fluorecare SARS-CoV-2 Spike Protein Test kit (Colloidal Gold) | Shenzen Microprofit Biotech Co., Ltd. | 2 | | X | X | |
| 25 | CLINITEST Rapid COVID-19 Antigen Test | Siemens Healthineers | 2 | | | | |
| 26 | Immupass VivaDiag | VivaChek Biotech | 2 | | X | | |
| 27 | COVID-VIRO COVID-19 Ag Rapid Test | AAZ | 1 | | X | X | |
| 28 | Flowflex COVID-19 Antigen test | ACON Labs | 1 | X | X | X | X |
| 29 | COVID-19 Antigen Rapid Test | Acro Biotech, Inc. | 1 | | | | |
| 30 | Alltest COVID-19 ART Antigen Rapid Test | ALLTEST | 1 | | X | | |
| 31 | COVID-19 Antigen Rapid Test | Assut Europe | 1 | | X | X | |
| 32 | COVID-19 RAT kit | Athenese-DX | 1 | | X | X | |
| 33 | NowCheck COVID-19 Ag test | Bionote | 1 | | | | |
| 34 | Novel Corona Virus (SARS-CoV-2) Ag Rapid Test kit | Bioperfectus | 1 | | X | X | |
| 35 | Covid-19 AG BSS | BIOSYNEX | 1 | | | | |
| 36 | Helix i-SARS-CoV-2 Ag Rapid Test | Cellex Biotech Co | 1 | | | | |
| 37 | COVID-19 Ag K-SeT | Coris Bioconcept | 1 | | | | |
| 38 | Liaison SARS-CoV-2 Ag | DiaSorin | 1 | | | | |
| 39 | COVID-19 Antigen Detection | DNA Diagnostic A/S | 1 | | X | | |
| 40 | COVID-19 Ag ECO Teste | Eco Diagnostica | 1 | | | | |
| 41 | Inflammacheck CoronaCheck | Exhalation Technology LTD | 1 | | | | |
| 42 | GenBody COVAG025 | GenBody | 1 | | | | |
| 43 | GENEDIA W COVID-19 Ag Test | Green Cross Medical Science Corp | 1 | | | | |
| 44 | Rapid COVID-19 Antigen Test | Healgen Scientific | 1 | | | | |
| 45 | Innova SARS-CoV-2 Antigen Rapid test | Innova Medical Group | 1 | | | | |
| 46 | Accucare PathoCatch Covid-19 Ag Detection Kit | Mylab | 1 | | | | |
| 47 | Orient Gene Rapid Covid-19 (Antigen) Self-Test | Orient Gene | 1 | | X | X | |
| 48 | GeneFinder COVID-19 Ag Plus Rapid Test | OSANG Healthcare | 1 | | | | |
| 49 | Green Spring SARS-CoV-2 Antigen Rapid Test Kit (Colloidal Gold) | Shenzhen Lvshiyuan Biotechnology | 1 | | X | X | |
| 50 | Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Antigen Detection Kit (Colloidal Gold-Based) | Vazyme Medical Technology Co | 1 | | | | |
| 51 | 2019-nCoV Antigen Test | Wondfo | 1 | | | | |
[Open in a new tab](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/table/TU15a/)
## Footnotes
The authors declare no conflicts of interest.
Supplemental digital content is available for this article. Direct URL citations are provided in the HTML and PDF versions of this article on the journalâs website, [www.jbievidencesynthesis.com](http://www.jbievidencesynthesis.com/).
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| Readable Markdown | ## Abstract
### Objective:
The objective of this review was to determine the diagnostic accuracy of the currently available and upcoming point-of-care rapid antigen tests (RATs) used in primary care settings relative to the viral genetic real-time reverse transcriptase polymerase chain reaction (RT-PCR) test as a reference for diagnosing COVID-19/SARS-CoV-2 in adults.
### Introduction:
Accurate COVID-19 point-of-care diagnostic tests are required for real-time identification of SARS-CoV-2 infection in individuals. Real-time RT-PCR is the accepted gold standard for diagnostic testing, requiring technical expertise and expensive equipment that are unavailable in most primary care locations. RATs are immunoassays that detect the presence of a specific viral protein, which implies a current infection with SARS-CoV-2. RATs are qualitative or semi-quantitative diagnostics that lack thresholds that provide a result within a short time frame, typically within the hour following sample collection. In this systematic review, we synthesized the current evidence regarding the accuracy of RATs for detecting SARS-CoV-2 compared with RT-PCR.
### Inclusion criteria:
Studies that included nonpregnant adults (18 years or older) with suspected SARS-CoV-2 infection, regardless of symptomology or disease severity, were included. The index test was any available SARS-CoV-2 point-of-care RAT. The reference test was any commercially distributed RT-PCRâbased test that detects the RNA genome of SARS-CoV-2 and has been validated by an independent third party. Custom or in-house RT-PCR tests were also considered, with appropriate validation documentation. The diagnosis of interest was COVID-19 disease and SARS-CoV-2 infection. This review considered cross-sectional and cohort studies that examined the diagnostic accuracy of COVID-19/SARS-CoV-2 infection where the participants had both index and reference tests performed.
### Methods:
The keywords and index terms contained in relevant articles were used to develop a full search strategy for PubMed and adapted for Embase, Scopus, Qinsight, and the WHO COVID-19 databases. Studies published from November 2019 to July 12, 2022, were included, as SARS-CoV-2 emerged in late 2019 and is the cause of a continuing pandemic. Studies that met the inclusion criteria were critically appraised using QUADAS-2. Using a customized tool, data were extracted from included studies and were verified prior to analysis. The pooled sensitivity, specificity, positive predictive, and negative predictive values were calculated and presented with 95% CIs. When heterogeneity was observed, outlier analysis was conducted, and the results were generated by removing outliers.
### Results:
Meta-analysis was performed on 91 studies of 581 full-text articles retrieved that provided true-positive, true-negative, false-positive, and false-negative values. RATs can identify individuals who have COVID-19 with high reliability (positive predictive value 97.7%; negative predictive value 95.2%) when considering overall performance. However, the lower level of sensitivity (67.1%) suggests that negative test results likely need to be retested through an additional method.
### Conclusions:
Most reported RAT brands had only a few studies comparing their performance with RT-PCR. Overall, a positive RAT result is an excellent predictor of a positive diagnosis of COVID-19. We recommend that Rocheâs SARS-CoV-2 Rapid Antigen Test and Abbottâs BinaxNOW tests be used in primary care settings, with the understanding that negative results need to be confirmed through RT-PCR. We recommend adherence to the STARD guidelines when reporting on diagnostic data.
### Review registration:
PROSPERO CRD42020224250
**Keywords:** COVID19, point of care, rapid antigen tests, respiratory infection, SARS-CoV-2
## Summary of Findings
Test accuracy of STANDARD Q COVID-19 Antigen test from SD Biosensor for COVID-19 or SARS-CoV-2 infection in symptomatic adults
| | | | |
|---|---|---|---|
| Sensitivity | 0\.782 (95% CI: 0.587 to 0.900) | | |
| Specificity | 0\.984 (95% CI: 0.949 to 0.995) | | |
| Prevalences | 0\.5% | 5% | 10% |
| Outcome | â of studies (â of patients) | Study design | Factors that may decrease certainty of evidence | Effect per 1000 patients tested | Test accuracy certainty of evidence | | | | | | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Risk of bias | Indirectness | Inconsistency | Imprecision | Publication bias | Pre-test probability of 0.5% (95% CI) | Pre-test probability of 5% (95% CI) | Pre-test probability of 10% (95% CI) | | | | |
| **True positives** | 4 studies (3179 patients) | cross-sectional (cohort type accuracy study) | not serious | not serious | very seriousa | not serious | none | 4 (3 to 5) | 39 (29 to 45) | 78 (59 to 90) | â¨â¨âŻâŻ Low |
| **False negatives** | 1 (0 to 2) | 11 (5 to 21) | 22 (10 to 41) | | | | | | | | |
| **True negatives** | 4 studies (3179 patients) | cross-sectional (cohort type accuracy study) | not serious | not serious | seriousa | not serious | none | 979 (944 to 990) | 935 (902 to 945) | 886 (854 to 896) | â¨â¨â¨âŻ Moderate |
| **False positives** | 16 (5 to 51) | 15 (5 to 48) | 14 (4 to 46) | | | | | | | | |
Explanations:
a. High heterogeneity across studies.
Test accuracy of PanBio by Abbott for COVID-19 or SARS-CoV-2 infection in symptomatic adults
| | | | |
|---|---|---|---|
| Sensitivity | 0\.780 (95% CI: 0.610 to 0.889) | | |
| Specificity | 0\.999 (95% CI: 0.993 to 1.000) | | |
| Prevalences | 0\.5% | 5% | 10% |
| Outcome | â of studies (â of patients) | Study design | Factors that may decrease certainty of evidence | Effect per 1000 patients tested | Test accuracy certainty of evidence | | | | | | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Risk of bias | Indirectness | Inconsistency | Imprecision | Publication bias | Pre-test probability of 0.5% (95% CI) | Pre-test probability of 5% (95% CI) | Pre-test probability of 10% (95% CI) | | | | |
| **True positives** | 2 studies (1324 patients) | cross-sectional (cohort type accuracy study) | not serious | not serious | very seriousa | not serious | none | 4 (3 to 4) | 39 (31 to 44) | 78 (61 to 89) | â¨â¨âŻâŻ Low |
| **False negatives** | 1 (1 to 2) | 11 (6 to 19) | 22 (11 to 39) | | | | | | | | |
| **True negatives** | 2 studies (1324 patients) | cross-sectional (cohort type accuracy study) | not serious | not serious | not serious | not serious | none | 994 (988 to 995) | 949 (943 to 950) | 899 (894 to 900) | â¨â¨â¨â¨ High |
| **False positives** | 1 (0 to 7) | 1 (0 to 7) | 1 (0 to 6) | | | | | | | | |
Explanations:
a. High heterogeneity across studies.
Test accuracy of Roche SARS-CoV-2 Rapid Antigen Test for COVID-19 or SARS-CoV-2 infection in symptomatic adults
| | | | |
|---|---|---|---|
| Sensitivity | 0\.812 (95% CI: 0.762 to 0.855) | | |
| Specificity | 0\.996 (95% CI: 0.974 to 0.999) | | |
| Prevalences | 0\.5% | 5% | 10% |
| Outcome | â of studies (â of patients) | Study design | Factors that may decrease certainty of evidence | Effect per 1000 patients tested | Test accuracy certainty of evidence | | | | | | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Risk of bias | Indirectness | Inconsistency | Imprecision | Publication bias | Pre-test probability of 0.5% (95% CI) | Pre-test probability of 5% (95% CI) | Pre-test probability of 10% (95% CI) | | | | |
| **True positives** | 2 studies (874 patients) | cross-sectional (cohort type accuracy study) | not serious | not serious | not serious | not serious | none | 4 (4 to 4) | 41 (38 to 43) | 81 (76 to 86) | â¨â¨â¨â¨ High |
| **False negatives** | 1 (1 to 1) | 9 (7 to 12) | 19 (14 to 24) | | | | | | | | |
| **True negatives** | 2 studies (874 patients) | cross-sectional (cohort type accuracy study) | not serious | not serious | not serious | not serious | none | 991 (969 to 994) | 946 (925 to 949) | 896 (877 to 899) | â¨â¨â¨â¨ High |
| **False positives** | 4 (1 to 26) | 4 (1 to 25) | 4 (1 to 23) | | | | | | | | |
Test accuracy of BinaxNOW by Abbott for COVID-19 or SARS-CoV-2 infection in symptomatic adults
| | | | |
|---|---|---|---|
| Sensitivity | 0\.867 (95% CI: 0.797 to 0.919) | | |
| Specificity | 0\.988 (95% CI: 0.974 to 0.996) | | |
| Prevalences | 0\.5% | 5% | 10% |
| Outcome | â of studies (â of patients) | Study design | Factors that may decrease certainty of evidence | Effect per 1000 patients tested | Test accuracy certainty of evidence | | | | | | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Risk of bias | Indirectness | Inconsistency | Imprecision | Publication bias | Pre-test probability of 0.5% (95% CI) | Pre-test probability of 5% (95% CI) | Pre-test probability of 10% (95% CI) | | | | |
| **True positives** | 1 study 642 patients | cross-sectional (cohort type accuracy study) | not serious | not serious | not serious | not serious | none | 4 (4 to 5) | 43 (40 to 46) | 87 (80 to 92) | â¨â¨â¨â¨ High |
| **False negatives** | 1 (0 to 1) | 7 (4 to 10) | 13 (8 to 20) | | | | | | | | |
| **True negatives** | 1 study 642 patients | cross-sectional (cohort type accuracy study) | not serious | not serious | not serious | not serious | none | 983 (969 to 991) | 939 (925 to 946) | 889 (877 to 896) | â¨â¨â¨â¨ High |
| **False positives** | 12 (4 to 26) | 11 (4 to 25) | 11 (4 to 23) | | | | | | | | |
## Introduction
According to the World Health Organization, as of August 2024, there were more than 775 million confirmed cases of COVID-19 caused by the virus SARS-CoV-2 and more than 7 million deaths.[1](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R1) In addition to recently updated vaccines, testing and accurate diagnosis of SARS-CoV-2 has been a key tool in fighting the pandemic.[2](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R2) Based on the current statistics of new cases[1](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R1) showing that the virus remains in circulation within human and animal populations,[3](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R3) accurate diagnostic testing is required to prevent future outbreaks that can lead to additional loss of life.
Accurate COVID-19 point-of-care (POC) diagnostic tests are required for real-time identification of SARS-CoV-2 infections in individuals. Early and accurate identification of potential cases leads to better control of virus transmission and early treatment interventions for individuals at high risk of severe disease. At this point, asymptomatic screening for SARS-CoV-2 infection has fallen out of fashion, with most public locations not requiring tests as part of day-to-day life. However, symptomatic individuals who present at primary care locations need to be diagnosed quickly and reliably. Real-time reverse transcriptase PCR (qRT-PCR or RT-PCR) is the accepted gold standard for diagnostic testing[4](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R4) and is available in many health care settings. However, RT-PCR requires technical expertise and expensive equipment that are not available in most primary care locations. Additionally, samples are required to be collected at the POC and sent to off-site laboratories for testing. The time delay between visiting the primary care provider and receiving results can increase transmission and delay appropriate treatment. For SARS-CoV-2 infections, RT-PCR detects viral RNA but is unable to discriminate between transmissible and replicating viruses and RNA remaining after the infection has been contained by the immune system.[5](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R5) Primary care providers should have access to reliable POC rapid antigen tests (RATs) for COVID-19, similar to those that are available for many other infectious diseases. Evaluation of the accuracy of POC diagnostic tests is needed to utilize these tests with confidence.[6](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R6)
Rapid antigen tests are immunoassays that detect the presence of a specific viral protein, glycan, or nucleic acid, which implies a current infection with SARS-CoV-2. RATs are useful for identifying infectious viruses as they detect viral proteins, which are cleared before the remaining viral RNA.[5](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R5) The accuracy of these tests compared with the gold standard RT-PCR appears to vary depending on the manufacturer. However, many studies have reported disparate accuracy results compared with manufacturersâ reported results.[7](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R7)â[12](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R12) In this systematic review, we synthesized the current evidence regarding RAT accuracy for the detection of SARS-CoV-2, and considered the overall performance of these techniques compared with the gold standard RT-PCR.
A search of PROSPERO, DARE (Database of Abstracts of Reviews of Effects), PubMed, the Cochrane Database of Systematic Reviews, JBI Registration of Systematic Review Titles, and *JBI Evidence Synthesis* was conducted in November 2020. We identified 1 review in PROSPERO[13](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R13) and 2 systematic reviews in the Cochrane Database of Systematic Reviews,[14](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R14),[15](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R15) each of which became available after our title registration in PROSPERO and the JBI Registration of Systematic Review Titles in June 2020. The PROSPERO review examined peer-reviewed publications for tests commercially available before August 15, 2020.[13](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R13) Our systematic review included additional sources for tests, including gray literature available from the manufacturers, and included search results from tests not yet commercially available. The literature searches of the 2 Cochrane reviews ended in May 2020[14](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R14),[15](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R15) and were updated in July 2022, with a search that ended in March 2021.[16](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R16) In the time since then, significant amounts of research and numbers of tests have become available, warranting an additional review. With the rapidly changing environment around COVID-19, our review adds to those published with a longer, more recent timeline. Additionally, our question is of a more general nature of POC diagnostic accuracy for primary care settings anywhere in the world. Our review has important implications for health care providers caring for patients in both resource-rich and resource-poor regions.
We framed our review question using the population index test reference test diagnosis (PIRD) mnemonic, which is commonly used for diagnostic reviews.[17](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R17) The objective of this systematic review was to synthesize the best available evidence related to the diagnostic accuracy of the available POC RATs (index test) relative to a certified medical laboratory viral genetic RT-PCR test (reference test) for the diagnosis of COVID-19/SARS-CoV-2 in adults 18 years and older. The rationale for combining both test types in this systematic review was to provide a comprehensive comparison of RT-PCR with the POC RATs. As the COVID-19 pandemic continues to rapidly evolve, the highest diagnostic accuracy, lowest cost, and quickest results are important considerations for monitoring and managing disease spread in a primary care setting. The aim of this study was to identify the rapid diagnostic tests that fit this requirement.
## Review question
What is the diagnostic accuracy of the currently available and upcoming POC RATs used in primary care settings relative to the viral genetic RT-PCR test as a reference for the diagnosis of COVID-19/SARS-CoV-2 in adults?
## Inclusion criteria
### Participants
The review examined studies that included nonpregnant adults (18 years and older) with suspected SARS-CoV-2 infection, regardless of symptomology or disease severity. Persons of any ethnicity or race in any geographic location were considered. Studies that included data from pregnant women or children within the study population that could be separated from the overall study data were included in the review. We excluded studies that only contained tests that could not be used in primary care settings, such as those that required larger equipment or specialized expertise. The setting of the study was recorded but not used as an exclusion criterion. Any non-primary care setting was initially an exclusion criterion,[18](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R18) but upon further discussion, the criterion was adjusted to focus on the RAT used rather than the setting in which the RAT was used.
### Index test
The index tests investigated in this review were any currently available or pre-market POC SARS-CoV-2 RATs. RATs are qualitative or semi-quantitative diagnostics that provide a result within a short time frame, typically within the hour following sample collection.[19](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R19) Tests could use any easily obtained bodily fluid or sample, including saliva, mucus, blood, urine, breath, or feces. Most of the studies considered used nasopharyngeal, nasal, or oropharyngeal swab specimens. RATs include a variety of techniques, such as chromogenic-based or fluorescence-based detection and lateral flow-based detection, but as a common denominator, all detect viral antigens from presently infected fluids and cells.[19](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R19) Tests that detect immunoglobulin against SARS-CoV-2 were excluded from this review, as antibodies develop upon resolution of SARS-CoV-2 infection or from vaccination and, therefore, are not used in the POC setting for diagnosing acute infection.[6](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R6)
### Reference test
The reference test was commercially distributed RT-PCRâbased tests that detect the RNA genome of SARS-CoV-2 and have been validated by an independent third party. Additionally, custom or in-house RT-PCR tests were considered with appropriate validation documentation. For example, Japanâs National Institute of Infectious Disease method was accepted as a validated RT-PCR test.[20](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R20) These tests must be performed in certified laboratories where personnel have been trained to perform RT-PCR assays.
### Diagnosis of interest
The diagnoses of interest were COVID-19 disease and SARS-CoV-2 infection.
### Types of studies
This review considered any English-language or English-translated cross-sectional or cohort study that examined the diagnostic accuracy (sensitivity and specificity, positive predictive value, negative predictive value) of COVID-19/SARS-CoV-2 infection where the participants had both index and reference tests performed. Case-control studies were excluded due to high risk of bias (see âAssessment of methodological qualityâ). Meta-analysis was performed on studies that provided true-positive (TP), true-negative (TN), false-positive (FP), and false-negative (FN) values. Studies published from November 2019 to July 12, 2022, were included, as SARS-CoV-2 emerged in late 2019 and is the cause of a continuing pandemic.
## Methods
This systematic review was conducted in accordance with JBI methodology for systematic reviews of diagnostic test accuracy[17](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R17) and follows our published protocol,[18](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R18) with exceptions noted throughout.
### Search strategy
The search strategies for all databases aimed to locate published and unpublished studies, including preprints. An initial limited search of several sources was undertaken to identify articles, review other search strategies, and search for published articles on the topic. These initial sources were PubMed, PROSPERO, *JBI Evidence Synthesis*, Cochrane Database of Systematic Reviews, DARE, and the Cochrane Central Register of Controlled Trials. The text words contained in the titles and abstracts of relevant articles and the articlesâ index terms were used to develop a full search strategy for PubMed. We adopted the Canadian Agency for Drugs and Technologies (CADTH) COVID-19 search string developed for PubMed.[21](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R21) Once a draft was fully developed, the PubMed search strategy was peer-reviewed by a medical librarian following the Peer Review of Electronic Search Strategy (PRESS) Guideline Statement.[22](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R22) After that initial pilot search, the search strategy was further edited and finalized for review. The search strategy, including all identified keywords and index terms, was adapted for each included information source.
The full search of MEDLINE (PubMed), Embase, Scopus, Qinsight (Quertle), and the World Health Organization (WHO) COVID-19 database was undertaken in July 2021 and updated on July 12, 2022 (with the exception of Qinsight, which was no longer available). See [Appendix I](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#A1) for the full search strategy. Scopus, Qinsight, and WHO COVID-19 include gray literature.
### Study selection
Following the search, all identified citations were collated and uploaded into EndNote v.X9.3.3. The EndNote edition was later upgraded to EndNote 20.5 (Clarivate Analytics, PA, USA). All duplicates were removed using a method developed and detailed by Bramer *et al*.[23](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R23) Titles and abstracts were screened first by 2 independent reviewers of the research team (EH, GM, BH, SS, SR, TH, CK, SF, AD, JK, AA, KD, TE, MD, AS) against the inclusion criteria using Google Sheets. Potentially relevant studies were retrieved in full, and their citation details were imported into a Google Sheet. The full texts of selected citations were assessed in detail against the inclusion criteria by at least 2 reviewers from the team independently (EH, GM, BH, SS, SR, TH, CK, SF, AD, JK, AA, KD, TE, MD, AS). Conflicts were resolved at the completion of each stage by a third reviewer (AS, AA, KD, TE). Reasons for the exclusion of full-text studies that did not meet the inclusion criteria were recorded and are provided in Supplemental Digital Content 1, <http://links.lww.com/SRX/A55>. The results of the search and screening are presented in a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram[24](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R24) (Figure [1](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#F1)).
#### Figure 1.
[](https://www.ncbi.nlm.nih.gov/core/lw/2.0/html/tileshop_pmc/tileshop_pmc_inline.html?title=Click%20on%20image%20to%20zoom&p=PMC3&id=11462910_srx-22-1939-g001.jpg)
Search results and study selection and inclusion process[24](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R24)
### Assessment of methodological quality
Selected studies were critically appraised by at least 2 reviewers from the team independently (EH, GM, BH, SS, SR, TH, CK, SF, AD, JK, AA, KD, TE, MD, AS) for risk of bias using the standardized critical appraisal instrument from the QUADAS-2.[25](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R25) QUADAS-2 provides a series of yes/no questions to appraise studies. At a minimum, we required the following questions to be answered âyesâ for a study to be included in the systematic review: \#2: Was a case-control design avoided? \#3: Did the study avoid inappropriate exclusions? \#6: Is the reference standard likely to correctly classify the target condition? \#8: Was there an appropriate interval between the index test and reference standard?
Studies that answered ânoâ or âunclearâ to any of these 4 QUADAS-2 questions were excluded. Disagreements were resolved through discussion or with an additional reviewer. The decision to exclude was based on the consensus of the 2 independent reviewers and, if needed, an additional reviewer (EH, GM, BH, SS, SR, TH, CK, SF, AD, JK, AA, KD, TE, MD, AS). Studies were excluded from data extraction if specificity and sensitivity were not presented or the data could not be used to calculate specificity and sensitivity. We did not exclude any studies due to low statistical power.
### Data extraction
We performed a pilot data extraction of 52 studies to determine the effectiveness of our initial data extraction tool. Based on the challenges of combining the extracted data from the pilot data extraction, a new custom data extraction tool was developed, building on the initial tool. The custom data extraction tool was modified from the original protocol to better separate and standardize the data during extraction. See [Appendix II](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#A2) for the updated data extraction tool. We identified specific portions of the data extraction tool to be standardized prior to data extraction, including the setting, sample, reference test, and index test. For these, we used drop downs for the data extractors to select from, including an âotherâ option that allowed the entering of data items not found in the initial pilot extraction. The extracted data were reviewed and verified prior to analysis. The final standardization of data was performed by 2 individuals (SK-C, AS) to ensure inter-extractor reliability.
For each study, we identified the primary (dominant) strain of SARS-CoV-2 circulating in the study country during the study time frame using CoVariants.org.[26](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R26) When specific dates or specific country-level data were not available, variants were estimated by the time frame of initial study submission and dominant strains in neighboring countries. Subgroup analyses were identified after pilot data extraction but prior to overall data extraction, and were used to refine the data extraction tool. The authors of studies missing key relevant information (such as TN, FN, TP, and FP) were contacted for additional information. If no reply was received on the first attempt, we attempted to contact the authors a second time. No additional information or data were retrieved from this effort.
### Data synthesis
Papers that reported the TP, FP, TN, and FN were pooled in statistical meta-analysis using the R statistical software (R Foundation for Statistical Computing, Vienna, Austria) packages meta[27](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R27) and dmetar.[28](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R28) Due to our custom data extraction tool, we were unable to utilize the JBI System for the Unified Management, Assessment and Review of Information (JBI SUMARI; JBI, Adelaide, Australia) software as initially planned.[18](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R18) Studies that did not include these 4 values were excluded from meta-analysis. As we expected this information to be included in all published studies, these criteria were not stated in our inclusion/exclusion criteria in the original protocol.[18](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R18) However, without these data, the combined accuracy data could not be accurately calculated. As an *a priori* decision, we only included RATs that were reported in at least 5 studies for the meta-analysis due to the minimum number of groups needed to fully benefit from the random-effects model in dmetar.[28](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R28) The pooled sensitivity, specificity, positive predictive, and negative predictive values were calculated assuming a random-effects model and presented with 95% CIs. The positive predictive and negative predictive values were calculated using the formulas TP/(TP+FP) and TN/(FN+TN) when not presented in the papers. Forest plots for the sensitivity and specificity were generated using the R package meta.[27](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R27) Potential subgroups that were proposed in our protocol included index tests used, symptomatic vs asymptomatic, and cycle threshold (Ct) values. Where statistical pooling was not possible, the findings were presented in narrative format, including tables and figures.
Heterogeneity was assessed using the *I* 2 value. When heterogeneity above 90% was observed, outlier analysis was conducted to identify studies contributing to overall heterogeneity. The R package dmetar was used to identify outliers based on their contribution to heterogeneity and the pooled value of the measurement.[28](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R28) This package examines the 95% CI of each study compared with the pooled 95% CI. When a study was removed, the data set was reanalyzed for heterogeneity. The results shown were generated by removing outliers. The code and the data used for data synthesis can be found at <https://github.com/skoshyc/covid_systematic_review_2023>.
### Assessing certainty in the evidence
The Summary of Findings were created using GRADEPro GDT software (McMaster University, ON, Canada).[29](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R29) The GRADE approach for grading the certainty of evidence for diagnostic test accuracy was used.[30](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R30) The following outcomes are included in the Summary of Findings: the review question; the index test names and types; the reference tests used; the population; the estimates of true negatives, true positives, false negatives, and false positives; the absolute difference between the index and reference tests for these values per 1000 patients; the sample size; the number of studies contained within the sample set; the GRADE (Grading of Recommendations Assessment, Development and Evaluation) quality of evidence for each finding; and any comments associated with the finding.
### Deviations from and clarifications to protocol
Title and abstract screening, full-text screening, critical appraisal, data extraction, and data synthesis were completed as described in our protocol[18](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R18) with the following exceptions.
#### Software and procedure flow
All steps were performed using Google Sheets set up specifically for our review. The full-text screening was adjusted to use a drop-down selection of prioritized reasons for exclusion. Reviewers selected the highest priority exclusion reason for excluded studies (Table [1](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#T1)). For critical appraisal, we used a drop-down setup for each question and the decision for inclusion or exclusion. The exclusions from the critical appraisal process were prioritized by question number from the JBI critical appraisal tool for diagnostic accuracy reviews.[25](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R25) We piloted and adjusted our data extraction tool using a subset of studies. This step was not specified in our published protocol.[18](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R18) We were not able to use JBI SUMARI due to our customized data extraction tool. We utilized R software with custom code instead. Rather than assessing heterogeneity visually as originally planned, we used the *I* 2 value. For the meta-analysis, we included only RATs reported in at least 5 studies.
##### Table 1.
Prioritized exclusion criteria for studies, as selected by reviewers during full-text screening
| | |
|---|---|
| 1 | Not RAT compared to RT-PCR |
| 2 | Results took more than 4 hours to determine after test was initiated |
| 3 | Diagnostic accuracy was not provided |
| 4 | Children were included in the analysis |
| 5 | Pregnant individuals were included in the analysis |
| 6 | Studies were dated prior to the emergence of COVID-19 |
| 7 | Study examined antibodies against COVID-19, not COVID-19 antigens |
| 8 | Test is incompatible with a standard primary care setting |
| 9 | Study is a review without primary data |
| 10 | Study is in a foreign language and not available in English |
| 11 | Duplicate article |
RAT, rapid antigen test; RT-PCR, reverse transcriptase polymerase chain reaction.
#### Inclusion and exclusion criteria
We adjusted our inclusion/exclusion criteria to clarify several points. First, our protocol stated that we would exclude studies performed in non-primary care settings.[18](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R18) We included studies from non-primary care settings if the RAT being used could also be easily used in primary care settings. Instead, RATs that could not be performed in a primary care setting were excluded. Next, our protocol stated that the reference test considered was commercially available RT-PCR tests and that any RT-PCR test would be considered.[18](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R18) We considered and included studies where the reference test was a validated custom or in-house RT-PCR test. Third, we clarified that cross-sectional and cohort studies would be considered, but case-control studies were excluded for poor methodological quality.
## Results
### Study inclusion
A total of 3122 citations were identified from searches of databases and gray literature. After duplicates were removed through EndNote, 1204 records were screened for inclusion by title and abstract using JBI SUMARI (pilot search only) and Google Sheets. We examined the full text of 580 studies for inclusion based on our described criteria and excluded 319 (see Supplemental Digital Content 1, <http://links.lww.com/SRX/A55>. The most common reason for study exclusion was the inclusion of individuals younger than 18 years within the data set (n = 102). After removing studies based on our exclusion criteria, we critically appraised 261 studies. The primary reason for excluding studies after critical appraisal was the use of a case-control study design (n = 107 out of 118 excluded studies; see Supplemental Digital Content 2, <http://links.lww.com/SRX/A56>. After critical appraisal, we extracted data from 143 articles.[7](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R7),[8](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R8),[11](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R11),[31](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R31)â[170](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R170) From these articles, data from 91 studies were used for overall and subgroup analyses based on the data synthesis methods. See the full search results and study selection and inclusion process in Figure [1](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#F1).
### Methodological quality
The extracted studies had high certainty of evidence based on the GRADE analysis.[30](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R30) Given that we restricted our review to cross-sectional and cohort designs, all of the included studies began at âhighâ quality.
The majority of the studies had a low risk of bias based on the QUADAS-2 tool (Figure [2](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#F2) \[summary of risk of bias assessment\] and Supplemental Digital Content 3, <http://links.lww.com/SRX/A57> \[individual study analysis\]). While most papers stated that the reference test was performed at a different site or through a central public health laboratory, a few papers (16.0%) did not clearly indicate whether the reference test was interpreted without knowledge of the index test result (Q\#7). All studies used a validated RT-PCR as their reference test, but some papers (15.3%) used multiple RT-PCR kits (Q\#9). About 1 in 5 papers (20.8%) did not include all participants in their analysis (Q\#10). The reasons cited for these exclusions were a lost sample or inconclusive/invalid results on either the index or reference test.
#### Figure 2.
[](https://www.ncbi.nlm.nih.gov/core/lw/2.0/html/tileshop_pmc/tileshop_pmc_inline.html?title=Click%20on%20image%20to%20zoom&p=PMC3&id=11462910_srx-22-1939-g002.jpg)
Summary of risk of bias assessment of included studies. The percentage of included studies where the answer to each question from the QUADAS-2 tool25 was âyesâ (green, no stripes), ânoâ (red, diagonal stripes), or ânot clearâ (yellow, vertical stripes) are shown. Questions that required a âyesâ answer for the study to be included in the data extraction are not shown (\#2, \#3, \#6, and \#8).
The indirectness, publication bias, and impreciseness of the included studies represented minor or no concerns regarding the quality of evidence. The largest driver of the quality of evidence decrease was the high heterogeneity found across studies. This is discussed further in the review findings section.
### Characteristics of included studies
The studies included in our data extraction consisted of retrospective and prospective cohort studies and cross-sectional studies. In general, most studies collected a single subject sample that was used for the index and reference tests, or 2 samples were collected consecutively at the same encounter. On occasion, 2 samples were taken from different anatomical locations from the same subject (eg, a nasopharyngeal sample for RT-PCR and an anterior nares sample for RAT). Most studies used a design where the RAT was performed on-site with the participant, and the RT-PCR sample was stored cold and transferred to a central laboratory location. For some studies, the laboratory was on-site, such as a clinical laboratory associated with the hospital performing the study. However, many studies used central public health laboratories within their local health districts to perform the RT-PCR. A benefit of using a clinical laboratory instead of utilizing their own laboratory staff to run the RT-PCRs is that the clinical laboratory technicians are blinded to the RAT results because they are not involved in the study.
Where possible, we validated the reported sensitivity and specificity numbers in each study using the TP, FP, TN, and FN values. Not every study provided these numbers, so some reported sensitivity and specificity calculations could not be verified. The key findings of each paper are summarized in [Appendix III](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#A3).
The studies included in our meta-analysis were performed in a variety of settings (Table [2](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#T2)). The breadth of study locations demonstrates the generalizability of RATs across different levels of health care and the ease of use of these POC tests. While we focused on determining best practices for primary care settings, these findings are applicable to a wide range of health care locations.
#### Table 2.
Reported settings of included studies
| Location | \# of studies performed |
|---|---|
| COVID-19 testing site/screening location | 52 |
| Hospital - inpatient | 38 |
| Emergency department/room | 26 |
| College/university campus (medical center/hospital) | 25 |
| Hospital - outpatient | 15 |
| Primary care location | 15 |
| Not described/unclear | 8 |
| Long-term care facility (nursing home, rehab centers) | 5 |
| Public area (not a designated screening location) | 5 |
| College/university campus (non-medical) | 4 |
| Urgent care location | 1 |
The studies were conducted in 44 countries across 6 continents starting in March 2020 through our search date in July 2022 (Figure [3](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#F3)A). We generated heatmaps showing the locations of dominant variants based on the countries of the studies (Figure [3](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#F3)B-D). Studies from the Beta and Gamma waves were less common (not shown). We had few studies completed during the dominance of the Omicron variants due to the dates of our searches (not shown).
#### Figure 3.
Maps of study locations. The heatmaps show the geography of the studies included in this review, illustrating the global nature of COVID-19 rapid antigen tests. (A) The number of included studies from each country is shown by heatmap. (BâD) The number of included studies from each country with data collected during the dominance of the Ancestral (B), Alpha (C), and Delta (D) strains of SARS-CoV-2 are shown by heatmap. Gray indicates that no included studies came from that country.
The included studies resulted in a total participant number of 212,874. There were 139 papers that either specified the number of participants, the number of samples, or both (Figure [4](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#F4)). The number of participants or samples ranged from 42 to 18,457, with a median of 635 participants. Overall, the studies included in the meta-analysis all shared the general design of testing subjectsâ samples collected at the same time with both RAT and RT-PCR.
#### Figure 4.
Numbers of participants/samples per included study. Studies were grouped by the number of participants. The number of studies for each group is shown.
The studies included in the analysis listed 50 commercially available RATs, whereas 3 studies described novel tests that were not yet commercially available ([Appendix IV](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#A4)). Tests reported in fewer than 5 studies were excluded from the meta-analysis, as described in the methods.[28](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R28) The reported diagnostic accuracy data for all studies can be found in [Appendix III](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#A3). Most studies reported using nasopharyngeal swabs to acquire the test sample (Table [3](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#T3)). Many studies reported using multiple sample sites in their analysis. However, few studies compared the accuracy of the tests from multiple sample sites.
#### Table 3.
Sample types collected for COVID-19 testing, as reported in included studies
| Sample type | \# of studies |
|---|---|
| Nasopharyngeal swabs | 128 |
| Oropharyngeal swabs/throat swabs | 41 |
| Nasal swabs | 37 |
| Other | 8 |
| Saliva | 7 |
| Blood | 2 |
| Bronchoalveolar lavage/bronchial sample | 1 |
We did not restrict the use of reference tests to a specific manufacturer or target. The studies used a variety of RT-PCR tests as their reference test. All reference tests were either commercially available RT-PCRs or in-house primers based on national or international public health organization recommendations. Many studies used multiple reference tests due to the availability of the tests over the course of their studies. The most commonly reported reference test was the Roche cobas systems, with 30 studies reporting its use. Other common reference tests were Allplex assays by Seegene (23 studies), TaqPath assays by ThermoFisher (18 studies), and Xpert Xpress/GeneXpert assays by Cepheid (19 studies ). Seventeen studies reported a custom or in-house PCR assay based on published primers, and 15 studies did not report a specific RT-PCR assay.
### Review findings
We compared the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for each index test across the published studies. A total of 91 studies were used for synthesis, as those studies provided the TP, FP, TN, and FN values.[8](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R8),[11](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R11),[32](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R32)â[34](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R34),[36](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R36)â[40](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R40),[46](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R46)â[49](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R49),[53](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R53)â[55](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R55),[58](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R58)â[60](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R60),[63](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R63),[66](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R66),[68](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R68),[71](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R71),[72](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R72),[74](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R74),[76](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R76)â[79](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R79),[81](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R81)â[88](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R88),[90](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R90),[93](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R93)â[95](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R95),[98](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R98)â[101](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R101),[103](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R103),[104](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R104),[106](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R106)â[108](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R108),[110](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R110),[115](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R115),[117](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R117),[118](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R118),[120](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R120),[123](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R123),[124](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R124),[127](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R127)â[129](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R129),[131](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R131)â[137](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R137),[140](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R140),[142](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R142),[143](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R143),[148](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R148),[150](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R150)â[157](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R157),[159](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R159)â[169](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R169) For the analysis of the index test, we considered the entries from the paper that specified the overall accuracy of the test across their entire study population.
We only included index tests examined in at least 5 studies for the pooled sensitivity, specificity, PPV, and NPV, which are shown in the forest plots. The tests meeting this criterion were STANDARD Q COVID-19 Ag Test (SD Biosensor; 27 studies), PanBio COVID-19 Ag Rapid Test Device (Abbott; 14 studies), SARS-CoV-2 Rapid Antigen Test (Roche Diagnostics; 11), and BinaxNOW COVID-19 Antigen (Abbott; 10 studies). All tests that were considered are listed in [Appendix IV](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#A4).
We considered the studies that were outliers in the pooled analysis. An outlier was defined as described in the methods. On removing the outliers, we observed that overall heterogeneity reduced considerably.
#### Sensitivity
The maximum sensitivity reported was 100%, which included the Flowflex COVID-19 Antigen test (ACON Labs) and STANDARD Q COVID-19 Ag Test (SD Biosensor; [Appendix IV](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#A4)). The heterogeneity of the data set was high when we considered the included studies,[11](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R11),[32](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R32)â[34](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R34),[36](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R36)â[39](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R39),[46](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R46),[48](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R48),[49](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R49),[55](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R55),[58](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R58),[59](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R59),[63](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R63),[66](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R66),[71](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R71),[76](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R76),[77](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R77),[79](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R79),[83](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R83)â[87](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R87),[93](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R93),[98](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R98),[99](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R99),[101](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R101),[103](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R103),[107](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R107),[108](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R108),[118](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R118),[123](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R123),[124](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R124),[127](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R127)â[129](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R129),[131](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R131),[132](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R132),[134](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R134)â[136](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R136),[142](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R142),[150](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R150),[151](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R151),[154](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R154),[155](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R155),[160](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R160),[161](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R161),[165](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R165),[166](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R166),[168](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R168),[169](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R169) as indicated by an *I* 2 value of 94.6% (95% CI 93.6â95.4%). The pooled sensitivity of these data was 67.0% (95% CI 62.6â71.1%). Each testâs pooled sensitivity is shown in Table [4](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#T4).
##### Table 4.
Pooled sensitivity of index tests (point-of-care SARS-CoV-2 rapid antigen tests), with outliers (as identified based on their contribution to heterogeneity)
| Test name | \# of studies | Pooled sensitivity | 95% CI | *I* 2 |
|---|---|---|---|---|
| STANDARD Q COVID-19 Ag (SD Biosensor) | 27 | 66\.0% | 59\.2-72.2% | 95\.3% |
| PanBio (Abbott) | 13 | 70\.2% | 61\.0-78.0% | 92\.7% |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 11 | 69\.3% | 61\.2-76.4% | 83\.1% |
| BinaxNOW (Abbott) | 10 | 62\.3% | 49\.4-73.6% | 94\.2% |
On removing the outliers, the pooled sensitivity was 66.7% (95% CI 63.4â69.8%), with an *I* 2 value of 70.4%.[11](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R11),[32](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R32)â[34](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R34),[36](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R36),[39](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R39),[46](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R46),[48](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R48),[49](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R49),[55](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R55),[58](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R58),[66](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R66),[71](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R71),[76](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R76),[79](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R79),[84](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R84),[87](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R87),[107](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R107),[108](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R108),[118](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R118),[127](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R127)â[129](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R129),[131](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R131),[132](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R132),[134](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R134),[136](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R136),[142](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R142),[154](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R154),[169](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R169) The updated test subgroup results are shown in Table [5](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#T5). The individual sensitivities reported for the 4 tests included in the pooled analysis are shown in Figure [5](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#F5) (outliers removed). The high heterogeneity is still present in the large discrepancies in reported sensitivities and 95% CIs.
##### Table 5.
Pooled sensitivity of index tests (point-of-care SARS-CoV-2 rapid antigen tests), without outliers (as identified based on their contribution to heterogeneity)
| Test name | \# of studies | Pooled sensitivity | 95% CI | *I* 2 |
|---|---|---|---|---|
| STANDARD Q COVID-19 Ag (SD Biosensor) | 15 | 65\.4% | 61\.1-69.4% | 70\.0% |
| PanBio (Abbott) | 6 | 71\.0% | 64\.6-76.6% | 73\.8% |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 7 | 68\.5% | 60\.3-75.7% | 73\.3% |
| BinaxNOW (Abbott) | 2 | 54\.7% | 46\.0-63.1% | 0\.0% |
##### Figure 5.
Diagnostic accuracy of COVID-19/SARS-CoV-2 infectionâsensitivity forest plot for the overall cohort. The forest plot shows the sensitivities and 95% CIs reported for the STANARD Q COVID-19 Ag Test (SD Biosensor), PanBio (Abbott), Roche SARS-CoV-2 Rapid Antigen Test (Roche), and BinaxNOW (Abbott) index tests (point-of-care SARS-CoV-2 rapid antigen tests) after outlier studies were removed. Pooled sensitivity and heterogeneity value (I2) for each index test are shown at the bottom of each test section. The pooled sensitivity and 95% CI of all reported tests on the forest plot are shown at the bottom. The vertical line at 0.671 represents the pooled sensitivity value for all shown tests. Boxes represent the reported sensitivity, and solid horizontal lines represent the 95% CI reported by each study.
#### Specificity
The maximum specificity recorded was 100%, and there were 27 index tests that had this value ([Appendix IV](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#A4)). As in the case of the sensitivity, the heterogeneity of the data set when we consider the included studies was high, as indicated by an *I* 2 value of 93.7% (95% CI 92.5â94.6%). The pooled specificity of these data was 99.6% (95% CI 99.3â99.8%).[11](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R11),[32](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R32)â[34](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R34),[36](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R36)â[39](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R39),[46](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R46),[48](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R48),[49](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R49),[55](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R55),[58](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R58),[59](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R59),[63](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R63),[66](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R66),[71](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R71),[76](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R76),[77](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R77),[79](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R79),[83](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R83)â[87](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R87),[93](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R93),[98](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R98),[99](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R99),[101](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R101),[103](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R103),[107](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R107),[108](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R108),[118](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R118),[123](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R123),[124](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R124),[127](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R127)â[129](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R129),[131](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R131),[132](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R132),[134](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R134)â[136](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R136),[142](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R142),[150](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R150),[151](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R151),[154](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R154),[155](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R155),[160](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R160),[161](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R161),[165](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R165),[166](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R166),[168](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R168),[169](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R169) Each testâs pooled specificity is shown in Table [6](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#T6).
##### Table 6.
Pooled specificity of index tests (point-of-care SARS-CoV-2 rapid antigen tests), with outliers (as identified based on their contribution to heterogeneity)
| Test name | \# of studies | Pooled specificity | 95% CI | *I* 2 |
|---|---|---|---|---|
| STANDARD Q COVID-19 Ag (SD Biosensor) | 27 | 99\.2% | 98\.4-99.6% | 95\.0% |
| PanBio (Abbott) | 13 | 99\.9% | 99\.6-100% | 62\.9% |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 11 | 99\.8% | 98\.9%-100% | 93\.8% |
| BinaxNOW (Abbott) | 10 | 99\.8% | 99\.5-99.9% | 87\.8% |
On removing the outliers, the pooled specificity was 99.8% (95% CI 99.7â99.9%), with an *I* 2 value of 40.4%.[32](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R32)â[34](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R34),[36](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R36),[46](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R46),[49](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R49),[55](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R55),[58](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R58),[63](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R63),[66](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R66),[71](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R71),[77](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R77),[79](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R79),[83](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R83),[84](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R84),[87](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R87),[93](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R93),[99](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R99),[101](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R101),[103](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R103),[107](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R107),[108](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R108),[118](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R118),[123](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R123),[124](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R124),[129](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R129),[131](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R131),[132](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R132),[134](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R134)â[136](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R136),[142](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R142),[150](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R150),[154](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R154),[155](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R155),[166](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R166),[168](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R168),[169](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R169) The updated test subgroup results are shown in Table [7](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#T7). The individual specificities reported for the 4 tests included in the pooled analysis are shown in Figure [6](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#F6) (outliers removed). The high heterogeneity is still present in the large discrepancies in reported specificities and 95% CIs.
##### Table 7.
Pooled specificity of index tests (point-of-care SARS-CoV-2 rapid antigen tests), without outliers (as identified based on their contribution to heterogeneity)
| Test name | \# of studies | Pooled specificity | 95% CI | *I* 2 |
|---|---|---|---|---|
| STANDARD Q COVID-19 Ag (SD Biosensor) | 16 | 99\.6% | 99\.4-99.7% | 46\.7% |
| PanBio (Abbott) | 10 | 99\.9% | 99\.8-100.0% | 0\.0% |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 7 | 99\.9% | 99\.5-100.0% | 0\.0% |
| BinaxNOW (Abbott) | 6 | 99\.9% | 99\.7-100.0% | 16\.0% |
##### Figure 6.
Diagnostic accuracy of COVID-19/SARS-CoV-2 infectionâspecificity forest plot for the overall cohort. The forest plot shows the specificities and 95% CIs reported for the STANARD Q COVID-19 Ag Test (SD Biosensor), PanBio (Abbott), Roche SARS-CoV-2 Rapid Antigen Test (Roche), and BinaxNOW (Abbott) index tests after outlier studies were removed. Pooled specificity and heterogeneity value (I2) for each index test are shown at the bottom of each test section. The pooled specificity and 95% CI of all reported tests on the forest plot are shown at the bottom. The vertical line at 0.996 represents the pooled specificity value for all shown tests. Boxes represent the reported specificity, and solid horizontal lines represent the 95% CI reported by each study.
#### Positive predictive value
The maximum recorded PPV was 100%, and there were 21 index tests that reported this value in at least 1 study ([Appendix IV](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#A4)). To obtain the pooled PPV, we assumed the formula PPV = TP/(TP + FP), as most papers stated it this way. After removing outliers, as with sensitivity and specificity, we obtained a pooled PPV value of 97.7% (95% CI 96.8â98.4%) and *I* 2 value of 0.0% (95% CI 0.0â34.8%).[11](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R11),[32](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R32)â[34](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R34),[36](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R36),[39](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R39),[46](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R46),[49](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R49),[55](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R55),[58](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R58),[63](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R63),[71](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R71),[77](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R77),[79](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R79),[83](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R83),[85](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R85),[87](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R87),[93](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R93),[99](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R99),[101](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R101),[103](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R103),[107](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R107),[108](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R108),[118](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R118),[123](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R123),[124](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R124),[129](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R129),[131](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R131),[132](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R132),[134](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R134)â[136](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R136),[142](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R142),[150](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R150),[151](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R151),[154](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R154),[155](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R155),[160](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R160),[161](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R161),[168](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R168),[169](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R169) The forest plot for the PPVs is shown in Figure [7](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#F7). Each testâs pooled PPV is shown in Table [8](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#T8).
##### Figure 7.
Diagnostic accuracy of COVID-19/SARS-CoV-2 infectionâpositive predictive values forest plot. The forest plot shows the positive predictive values (PPVs) and 95% CIs reported for the STANDARD Q (SD Biosensor), PanBio (Abbott), Roche SARS-CoV-2 Rapid Antigen Test (Roche), and BinaxNOW (Abbott) index tests after outlier studies were removed. Pooled PPV and heterogeneity value (I2) for each index test is shown at the bottom of each test section. The pooled PPV and 95% CI of all reported tests on the forest plot are shown at the bottom. The vertical line at 0.962 represents the pooled PPV for all shown tests. Boxes represent the reported PPV, and solid horizontal lines represent the 95% CI reported by each study. Some studies reported multiple sites and are included as an individual row for each site.
##### Table 8.
Pooled positive predictive values of index tests (point-of-care SARS-CoV-2 rapid antigen tests), without outliers (as identified based on their contribution to heterogeneity)
| Test name | \# of studies | Pooled PPV | 95% CI | *I* 2 |
|---|---|---|---|---|
| STANDARD Q COVID-19 Ag (SD Biosensor) | 18 | 96\.3% | 94\.8-97.4% | 24\.1% |
| PanBio (Abbott) | 12 | 98\.9% | 97\.4-99.5% | 0\.0% |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 8 | 98\.6% | 94\.4-99.6% | 0\.0% |
| BinaxNOW (Abbott) | 6 | 97\.3% | 92\.3-99.1% | 0\.0% |
PPV, positive predictive value.
#### Negative predictive value
The maximum value was 100%, and included the Flowflex COVID-19 Antigen test (ACON Labs) and STANDARD Q COVID-19 Ag Test (SD Biosensor). To obtain the pooled NPV, we assumed the formula NPV = TN/(TN + FN), as most papers stated it this way. After removing outliers, as with sensitivity and specificity, we obtained a pooled NPV value of 95.2% (95% CI 94.3â95.9%) and *I* *2* value of 81.7% (95% CI 73.3â87.5%; see Table [9](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#T9) and Figure [8](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#F8)).[34](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R34),[36](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R36),[37](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R37),[46](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R46),[49](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R49),[58](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R58),[63](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R63),[76](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R76),[77](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R77),[83](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R83),[87](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R87),[98](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R98),[99](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R99),[118](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R118),[127](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R127)â[129](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R129),[131](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R131),[132](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R132),[136](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R136),[154](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R154),[168](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R168) The BinaxNOW (Abbott) subgroup of papers was excluded, as they all contributed substantially to the heterogeneity.
##### Table 9.
Pooled negative predictive values of index tests (point-of-care SARS-CoV-2 rapid antigen tests), without outliers (as identified based on their contribution to heterogeneity)
| Test name | \# of studies | Pooled NPV | 95% CI | *I* 2 |
|---|---|---|---|---|
| STANDARD Q COVID-19 Ag (SD Biosensor) | 15 | 95\.3% | 94\.0-96.2% | 84\.1% |
| PanBio (Abbott) | 4 | 95\.1% | 92\.9-96.6% | 87\.2% |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 3 | 94\.9% | 94\.0-95.7% | 39\.3% |
NPV, negative predictive value.
##### Figure 8.
Diagnostic accuracy of COVID-19/SARS-CoV-2 infectionânegative predictive value forest plot. The forest plot shows the negative predictive value (NPV) and 95% CIs reported for the STANDARD Q (SD Biosensor), PanBio (Abbott), Roche SARS-CoV-2 Rapid Antigen Test (Roche), and BinaxNOW (Abbott) index tests after outlier studies were removed. Pooled NPV and heterogeneity value (I2) for each index test is shown at the bottom of each test section. The pooled NPV and 95% CI of all reported tests on the forest plot are shown at the bottom. The vertical line at 0.949 represents the pooled NPV for all shown tests. Boxes represent the reported value, and solid horizontal lines represent the 95% CI reported by each study. Some studies reported multiple sites and are included as an individual row for each site.
#### Symptomatic test subgroup
The protocols for testing and screening have changed over the course of the pandemic, and now widespread testing is uncommon. Symptom presentation has now replaced screening tests for most locations and businesses. Taking this into consideration, we performed an additional analysis of studies that reported subgroups of symptomatic and asymptomatic individuals. The symptomatic subgroup diagnostic accuracy may be the most relevant cohort for primary care settings, as most asymptomatic individuals will not present to their primary care providers to be screened for COVID-19.
We found differences in the accuracy of the index tests in subjects who were symptomatic or asymptomatic. There were 9 studies that examined symptomatic[34](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R34),[99](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R99),[103](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R103),[118](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R118),[128](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R128),[150](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R150),[160](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R160),[165](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R165),[166](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R166) and 11 studies that examined asymptomatic[34](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R34),[84](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R84),[99](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R99),[103](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R103),[118](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R118),[128](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R128),[135](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R135),[149](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R149),[150](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R150),[165](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R165),[166](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R166) subgroups, and provided the values used to calculate accuracy values (TP, FP, TN, and FN). If there was only 1 study in the group, *I* 2 was reported as âNA.â As with the overall analysis of the studies, there was high heterogeneity between the studies. Due to fewer studies reporting these subgroups, we did not have enough studies to remove outliers from these analyses. The symptomatic subgroups showed higher overall levels of sensitivity compared to the overall group (Table [10](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#T10) and Figure [9](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#F9)A). Specificity was slightly lower in the symptomatic subgroup than in the overall group (Table [10](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#T10) and Figure [9](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#F9)B). The symptomatic subgroup also had a slightly lower PPV and NPV (Table [11](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#T11)) compared with the overall group (Figure [10](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#F10)).
##### Table 10.
Sensitivity and specificity of index tests (point-of-care SARS-CoV-2 rapid antigen tests) in the symptomatic subgroup
| Test name | \# of studies | Sensitivity (95% CI) *I* 2 | Specificity (95% CI) *I* 2 |
|---|---|---|---|
| STANDARD Q COVID-19 Ag (SD Biosensor) | 4 | 78\.2% (58.7â90.0%) 96\.1% | 98\.4% (94.9â99.5%) 74\.9% |
| PanBio (Abbott) | 2 | 78\.0% (61.0â88.9%) 90\.7% | 99\.9% (99.3â100%) 0\.0% |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 2 | 81\.2% (76.2â85.5%) 0\.0% | 99\.6% (97.4â99.9%) 0\.0% |
| BinaxNOW (Abbott) | 1 | 86\.7% (79.7â91.9%) NA | 98\.8% (97.4â99.6%) NA |
NA, not applicable.
##### Figure 9.
[](https://www.ncbi.nlm.nih.gov/core/lw/2.0/html/tileshop_pmc/tileshop_pmc_inline.html?title=Click%20on%20image%20to%20zoom&p=PMC3&id=11462910_srx-22-1939-g009.jpg)
Diagnostic accuracy of COVID-19/SARS-CoV-2 infectionâsensitivity and specificity forest plots for symptomatic subgroup. Forest plot shows the sensitivities (A) and specificities (B) and 95% CIs reported for the symptomatic subgroup for the STANDARD Q (SD Biosensor), PanBio (Abbott), Roche SARS-CoV-2 Rapid Antigen Test (Roche), and BinaxNOW (Abbott) index tests after outlier studies were removed. Pooled values and heterogeneity value (I2) for each index test are shown at the bottom of each test section. The pooled values and 95% CI of all reported tests on each forest plot are shown at the bottom. The vertical lines at 0.804 (sensitivity) and 0.994 (specificity) represent the pooled values for all shown tests. Boxes represent the reported sensitivity and specificity, and solid horizontal lines represent the 95% CI reported by each study.
##### Table 11.
Positive and negative predictive values of index tests (point-of-care SARS-CoV-2 rapid antigen tests) in the symptomatic subgroup
| Test name | \# of studies | Pooled PPV (95% CI) *I* 2 | Pooled NPV (95% CI) *I* 2 |
|---|---|---|---|
| STANDARD Q COVID-19 Ag (SD Biosensor) | 4 | 92\.1% (85.9-95.6%) 63\.2% | 94\.7% (89.0-97.5%) 93\.8% |
| PanBio (Abbott) | 2 | 99\.5% (96.3-99.9%) 0\.0% | 95\.5% (86.1-98.6%) 96\.5% |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 2 | 98\.7% (95.9-99.6%) 0\.0% | 93\.7% (85.0-97.5%) 92\.4% |
| BinaxNOW (Abbott) | 1 | 95\.1% (89.7-98.2%) NA | 96\.5% (94.6-97.9%) NA |
NA, not applicable; NPV, negative predictive value; PPV, positive predictive value.
##### Figure 10.
[](https://www.ncbi.nlm.nih.gov/core/lw/2.0/html/tileshop_pmc/tileshop_pmc_inline.html?title=Click%20on%20image%20to%20zoom&p=PMC3&id=11462910_srx-22-1939-g010.jpg)
Diagnostic accuracy of COVID-19/SARS-CoV-2 infectionâpositive predictive value and negative predictive value forest plots for symptomatic subgroup. Forest plot shows the positive (A) and negative (B) predictive values (PPV/NPV) and 95% CIs reported for the symptomatic subgroups of the STANDARD Q (SD Biosensor), PanBio (Abbott), Roche SARS-CoV-2 Rapid Antigen Test (Roche), and BinaxNOW (Abbott) index tests after outlier studies were removed. Pooled values and heterogeneity values (I2) for each index test are shown at the bottom of each test section. The pooled values and 95% CI of all reported tests on the forest plot are shown at the bottom. The vertical lines at 0.971 (PPV) and 0.950 (NPV) represent the pooled values for all shown tests. Boxes represent the reported values, and solid horizontal lines represent the 95% CI reported by each study.
#### Asymptomatic test subgroup
Asymptomatic test performance is relevant in any screening situation. The asymptomatic samples resulted in overall lower sensitivity in the RATs (Table [12](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#T12) and Figure [11](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#F11)A), although specificity remained high (Table [12](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#T12) and Figure [11](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#F11)B).[34](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R34),[84](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R84),[99](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R99),[103](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R103),[118](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R118),[128](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R128),[135](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R135),[149](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R149),[150](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R150),[165](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R165),[166](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R166) The PPV was lower in the asymptomatic group compared with the symptomatic and overall groups. However, the NPV remained similar between the 3 groups. Additional information about the PPV and NPV for this subgroup can be found in Table [13](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#T13) and Figure [12](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#F12).
##### Table 12.
Sensitivity and specificity of index tests (point-of-care SARS-CoV-2 rapid antigen tests) in the asymptomatic subgroup
| Test name | \# of studies | Sensitivity (95% CI) *I* 2 | Specificity (95% CI) *I* 2 |
|---|---|---|---|
| STANDARD Q COVID-19 Ag (SD Biosensor) | 5 | 43\.8% (30.4-58.2%) 86\.3% | 99\.6% (99.4-99.7%) 0\.0% |
| PanBio (Abbott) | 3 | 57\.7% (29.1-81.9%) 78\.5% | 100\.0% (0.0-100.0%) 0\.0% |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 1 | 58\.8% (44.2-72.4%) NA | 100\.0% (99.1-100.0%) NA |
| BinaxNOW (Abbott) | 2 | 70\.8% (62.9-77.7%) 0\.0% | 99\.8% (99.5-99.9%) 72\.8% |
NA, not applicable.
##### Figure 11.
[](https://www.ncbi.nlm.nih.gov/core/lw/2.0/html/tileshop_pmc/tileshop_pmc_inline.html?title=Click%20on%20image%20to%20zoom&p=PMC3&id=11462910_srx-22-1939-g011.jpg)
Diagnostic accuracy of COVID-19/SARS-CoV-2 infectionâsensitivity and specificity forest plots for asymptomatic subgroup. Forest plot shows the sensitivities (A) and specificities (B) and 95% CIs reported for the asymptomatic subgroup for the STANDARD Q (SD Biosensor), PanBio (Abbott), Roche SARS-CoV-2 Rapid Antigen Test (Roche), and BinaxNOW (Abbott) index tests after outlier studies were removed. Pooled values and heterogeneity value (I2) for each index test are shown at the bottom of each test section. The pooled values and 95% CI of all reported tests on each forest plot are shown at the bottom. The vertical lines at 0.537 (sensitivity) and 0.998 (specificity) represent the pooled values for all shown tests. Boxes represent the reported sensitivity and specificity, and solid horizontal lines represent the 95% CI reported by each study.
##### Table 13.
Positive and negative predictive values of index tests (point-of-care SARS-CoV-2 rapid antigen tests) in the asymptomatic subgroup
| Test name | \# of studies | PPV (95% CI) *I* 2 | NPV (95% CI) *I* 2 |
|---|---|---|---|
| STANDARD Q COVID-19 Ag (SD Biosensor) | 5 | 80\.4% (72.2-86.7%) 36\.4% | 97\.7% (95.1-98.9%) 97\.2% |
| PanBio (Abbott) | 3 | 100\.0% (0.0-100.0%) 0\.0% | 99\.1% (93.0-99.9%) 97\.4% |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 1 | 100\.0% (88.4-100.0%) NA | 95\.2% (92.7-97.0%) NA |
| BinaxNOW (Abbott) | 2 | 90\.3% (83.3-94.5%) 0\.0% | 99\.1% (97.7-99.7%) 95\.0% |
NA, not applicable; NPV, negative predictive value; PPV, positive predictive value.
##### Figure 12.
[](https://www.ncbi.nlm.nih.gov/core/lw/2.0/html/tileshop_pmc/tileshop_pmc_inline.html?title=Click%20on%20image%20to%20zoom&p=PMC3&id=11462910_srx-22-1939-g012.jpg)
Diagnostic accuracy of COVID-19/SARS-CoV-2 infectionâpositive predictive value and negative predictive value forest plots for asymptomatic subgroup. Forest plot shows the positive (A) and negative (B) predictive values (PPV/NPV) and 95% CIs reported for the asymptomatic subgroups of the STANDARD Q (SD Biosensor), PanBio (Abbott), Roche SARS-CoV-2 Rapid Antigen Test (Roche), and BinaxNOW (Abbott) index tests after outlier studies were removed. Pooled values and heterogeneity values (I2) for each index test are shown at the bottom of each test section. The pooled values and 95% CI of all reported tests on the forest plot are shown at the bottom. The vertical lines at 0.904 (PPV) and 0.983 (NPV) represent the pooled values for all shown tests. Boxes represent the reported values, and solid horizontal lines represent the 95% CI reported by each study.
#### Summary of Findings
Based on our meta-analysis, Rocheâs SARS-CoV-2 Rapid Antigen Test and Abbottâs BinaxNOW tests meet the WHOâs recommendation of minimum diagnostic accuracy for symptomatic individuals (⼠80% sensitivity and ⼠97% specificity)[171](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R171) and can be reliably used in primary care settings (see the Summary of Findings). Other tests may also meet this standard, but we did not find sufficient studies for other tests. In the Summary of Findings, the effect per 1000 patients tested and certainty of evidence for test accuracy are shown for symptomatic adults using STANDARD Q, PanBio, Roche, and BinaxNOW.
Overall, RATs can identify individuals who have COVID-19 with high reliability when considering overall performance. However, the lower levels of sensitivity suggest that negative tests likely need to be retested through an additional method, such as RT-PCR or repeat testing over several days, when COVID-19 is suspected. Positive tests are highly likely to correctly diagnose SARS-CoV-2 infections, and based on our analyses, we recommend treating those patients as having a COVID-19 diagnosis. These results are likely driven by the symptomatic subject data, as subgroup analysis found higher reliability in symptomatic individuals than in asymptomatic individuals.
Considering only symptomatic individuals, RATs have a higher performance in correctly identifying negative cases, with similar reliability for detecting cases through a positive result. However, a sensitivity of 80% means that 1 in 5 people with a negative RAT have a false-negative result. Thus, negative COVID-19 RAT results in symptomatic patients should be interpreted with caution. As the symptomatic analysis of BinaxNOW included a single study and the same analysis of Rocheâs test had only 2 studies, more studies are needed to confirm these findings.
## Discussion
Rapid antigen tests are an important tool in infectious disease control. RATs are less expensive, require less expertise, and are better indicators of infectious virus than the gold standard diagnostic of RT-PCR.[5](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R5) RATs have limitations in their performance, including large discrepancies in diagnostic accuracy depending on the situation in which they are used.
### Discrepancies across studies and with manufacturer reported results
Of significant concern is the discrepancy between the manufacturerâs listed diagnostic accuracy and the accuracy found in this analysis. Based on the published accuracies on the manufacturersâ websites, the manufacturers overestimate the accuracy of their tests.[172](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R172)â[175](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R175) Our meta-analysis found the pooled sensitivity of the SD Biosensor STANDARD Q test to be 66.1%, while the manufacturerâs website lists the sensitivity as 85.0%.[175](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R175) For the Abbott tests, the pooled sensitivity from our analysis was 71.0% and 54.7% for PanBio and BinaxNOW tests, respectively. The product pages from the Abbott website list the sensitivities as 91.1% for PanBio and 84.6% for BinaxNOW.[172](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R172),[173](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R173) Roche specifies that their listed sensitivity is for Ct values \< 30 and reports a specificity of 95.5%[174](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R174) compared with our overall pooled sensitivity of 68.5%. These discrepancies can increase the errors in medical practice by falsely increasing the confidence providers have in the various RATs. The differences in accuracy between the collected studies, our meta-analysis, and the manufacturerâs reported values are likely driven by the same factors that may have contributed to the high heterogeneity in our results.
### Potential sources of heterogeneity
We found high heterogeneity across the studies included in our data extraction and meta-analysis. Potential sources of heterogeneity could include the prevalence of the virus during each studyâs data collection phase, the access to various manufacturersâ RATs, and the skill level at which the sample was taken.[176](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R176),[177](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R177) Additionally, the level of infection within each subject will vary greatly depending on their previous immunity, the day post-exposure, or the day post-symptom compared to when the RAT was performed.
Gold standard is RT-PCR but the threshold for a positive result varies by manufacturer and kit. While all reference tests were performed by qualified individuals based on reporting in the studies, the conditions in which the tests were performed are not reflective of ideal conditions. The number of samples that needed processing at a single time, as well as the general increased sense of urgency felt by public health employees, may have resulted in heterogeneity across the reference samples, which would increase heterogeneity across the sensitivity and specificity.
Variants that alter the test epitope can change the accuracy of the RATs. The accuracy of the RATs decreased as the variants mutated further from the Ancestral strain.[178](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R178) A recent study of RATs intended for Delta and Omicron variant detection found no differences in sensitivity,[179](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R179) while other studies have found a decrease in sensitivity between these 2 variants.[178](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R178) However, the tests in our review were developed and intended for use with the Ancestral strain. We examined the time frame and dominant variants of our studies to address this question. Further work is needed to have a better understanding of how changes in SARS-CoV-2 proteins affect RAT sensitivity. As novel variants emerge with distinct proteins (epitopes), the accuracy of the RATs will need to be reassessed.
### Clinical significance of symptomatic and asymptomatic testing
The relevance of asymptomatic testing is lower than in symptomatic individuals because asymptomatic individuals are unlikely to present in a primary care setting. The individuals most likely to present in our target setting of primary care are those who are symptomatic. However, asymptomatic testing may continue in some contexts, such as during outbreaks, prior to certain elective procedures, or as part of ongoing surveillance and epidemiological efforts. The lower accuracy in the RATs in the asymptomatic context could lead to additional viral spread because of a false-negative result. Given the reduced accuracy, health care providers should interpret a negative result with caution and follow-up with RT-PCR testing for cases with a high suspicion of infection. The likelihood of a negative result from a RAT to be a true negative is dependent on disease prevalence in the patientâs community. Health care practitioners in areas with high disease prevalence (10%) at the time of testing should assume that a negative result is positive 2.4% of the time. These situations make the overall test performance, and subgroup analyses of symptomatic and asymptomatic individuals, relevant across multiple health care settings.
Other systematic reviews of diagnostic accuracy have also noted similar sensitivity for symptomatic and asymptomatic cohorts.[180](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R180),[181](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R181) These studies associated viral load as measured by RT-PCR Ct value with the positivity of the RATs.[180](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R180),[181](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R181) The lower the Ct value, the more likely a RAT would detect the presence of viral protein.[180](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R180),[181](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R181) Conflicting studies have reported similar and disparate Ct values in asymptomatic compared with symptomatic individuals (reviewed in Puhach *et al*.[5](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R5)). Asymptomatic individuals are considered to be major sources of transmission due to behavior changes when an individual develops symptoms.[182](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R182) Additional studies are needed to understand the connection between detectable viral protein via RATs, Ct values determined by RT-PCR, and transmission as measured by cell culture assays, because the clear difference in RAT performance between symptomatic and asymptomatic subjects does not align with the comparative Ct values[5](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R5) and cell culture positivity[182](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R182) previously reported.
### Limitations of this review
One limitation of the review was that, due to author language proficiencies, the search strategies were limited to studies published in English. Records not available in English were not included in the review.
Heterogeneity can be studied and addressed in multiple ways, including outlier analysis and removal. The underlying source of heterogeneity is not immediately detectable in the data found within the studies and this could be investigated further. The high heterogeneity was an unexpected result. Revisions of this systematic review and meta-analysis could use a more stringent approach to reduce heterogeneity or better identify its sources through a different data extraction tool. Further, with additional collected data, more nuanced subgroup analyses could be performed.
Tied to symptom presentation, viral load has also been shown to impact RAT accuracy, with higher Ct values (lower viral loads) associated with decreased test accuracy.[180](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R180),[181](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R181) Our review did not examine the subgroups of Ct values, which is a limitation of our review. A challenge with subdividing the collected data from the included studies is that the studies that reported values for various Ct values divided their data in different ways. The lack of consistent division makes grouping for meta-analysis challenging. Further, the Ct values across different reference tests may not be comparable. Each kit, primer set, and polymerase used to complete an RT-PCR reference test may vary in their specificity and sensitivity.[183](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R183) The Ct values that are reported are dependent on reference test reagent efficiency as well as the sampleâs viral RNA load.[183](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R183) Further work needs to be done to be able to accurately compare the Ct values to RAT performance or to viral load.
Sample type also has an impact on test accuracy. The most common sample types were nasopharyngeal swabs. These swabs are uncomfortable for patients and require a trained health care professional for administration, limiting their use in wider settings. Nasal swabs and oropharyngeal swabs were present in about one-third of the studies each, and saliva samples were present in the selected studies. We did not analyze sample type within our meta-analysis due to a low number of studies identifying the sample location used specifically for the RAT compared with the RT-PCR tests. This is a limitation of our review. Other reviews have examined some of these sample types and found that anterior nares (nasal) swabs and nasopharyngeal swabs have similar sensitivities.[181](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R181) Saliva samples were noted to be of lower diagnostic accuracy than swabs.[181](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R181) Nasal swabs are a popular collection method and are found in many at-home and POC tests. These are easy to collect by anyone and have minimal associated discomfort, making them ideal for primary care settings. A potential future analysis on RAT accuracy could be performed to analyze the impact of nasal swab vs nasopharyngeal sample collection. These data may be more readily available as more studies are published regarding sample collections. The studies included in this analysis were primarily nasopharyngeal and most did not compare accuracy across sample types.
Given our experience with this systematic review and meta-analysis, it is clear that there are more parameters that would provide insight into the use of RATs in primary care settings that were not captured by our data extraction tool. These include potential sources of heterogeneity listed above, such as timing of RAT compared with symptom onset, and variations in sample collection methods.
## Conclusions
We found high heterogeneity across studies examining the same RATs, leading to an overall decrease in the quality of evidence presented here. Many tests have only a few studies comparing their performance to RT-PCR. Future diagnostic accuracy studies need to adhere to the STARD guidelines[184](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R184) to provide the best evidence to build recommendations on. Studies without diagnostic accuracy numbers (2 Ă 2 tables) were excluded from the meta-analysis, resulting in a limitation to our review. Overall, RATs are excellent at predicting when a positive result means a positive diagnosis of COVID-19. However, these tests have reduced capacity to allow a negative result to rule out COVID-19 as a diagnosis. Misidentifying SARS-CoV-2 infection for other respiratory viral infections can lead to potential viral spread among vulnerable patients and health care workers. Further, it can delay appropriate treatment in cases with high risk of complications. In the primary care setting, false-negative results should be considered for further testing via RT-PCR or repeat RATs over several days[185](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R185) when there is high suspicion of COVID-19, such as loss of taste or smell as a presenting symptom. Overall negative likelihood ratio is dependent on local prevalence, and health care practitioners should take into account their current community status when determining the best course of action for a negative RAT result.
### Recommendations for practice
Based on our findings, we recommend that Rocheâs SARS-CoV-2 Rapid Antigen Test and Abbottâs BinaxNOW tests be used in primary care settings, with the understanding that negative results need to be confirmed through RT-PCR or repeated testing over several days when COVID-19 is highly suspected. These tests are widely available, relatively inexpensive, and have good reliability.
### Recommendations for research
The primary recommendation for research is to adhere to the STARD guidelines when reporting on diagnostic data.[184](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R184) If all studies had adhered to these guidelines, that would have allowed significantly more information to be gleaned from the studies selected. The key components of these guidelines that would have greatly improved our meta-analysis are the inclusion of the STARD diagram or the cross-tabulation (also known as a contingency table or a 2 Ă 2 table).[184](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R184) We only included studies that reported the TP, FP, TN, and FN values (91/143 studies) in our meta-analysis. We further recommend that any subgroup analysis performed also include these components. Using the STARD guidelines improves generalizability of reported data,[184](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R184) whereas failing to adhere to these guidelines limits the usefulness of the published data in developing evidence-based practice recommendations.
As new variants emerge, new testing will be needed using high-quality, rigorous methods in populations of vulnerable subjects. As rapid testing will likely remain the first line diagnostic for primary and secondary care environments, and consecutive testing using RATs or RT-PCR will be used as confirmation of a negative diagnosis, identifying the most sensitive and specific tests will remain critically important.
## Author contributions
GM, BH and SS: These authors contributed equally to this work. SR and TH: These authors contributed equally to this work. AD and JK: These authors contributed equally to this work. KD and TE: These authors contributed equally to this work. MDeA and AE, LS: These authors contributed equally to this work.
## Acknowledgments
Linsey Bui for assistance with screening steps and Cheryl Vanier for discussions and critique.
## Funding
This work was supported by internal research support from Touro University Nevada and the Federal Work-Study program. The funder had no role in the content development.
## Supplementary Material
## Appendix I: Search strategy
The search strategy identified key terms in the question and searched terms related to COVID-19, rapid antigens, and sensitivity and specificity. The COVID-19 searches for PubMed, Embase, and Scopus were modified versions from CADTH COVID-19 literature searching strings (documented on <https://covid.cadth.ca/literature-searching-tools/cadth-covid-19-search-strings/#covid-19-medline>). The search was initially run on July 11, 2021, and rerun on July 12, 2022. All databases were rerun, with the exception of Qinsight, which was no longer available from Quertle as of April 2022.
| MEDLINE (PubMed) Search conducted July 11, 2021 Search reran July 12, 2022 Filters: English language; publication date October 31, 2019 to present | | |
|---|---|---|
| Search number | Query | Results retrieved |
| \#1 | (((âantigen sâ\[All Fields\] OR âantigeneâ\[All Fields\] OR âantigenesâ\[All Fields\] OR âantigenicâ\[All Fields\] OR âantigenicallyâ\[All Fields\] OR âantigenicitiesâ\[All Fields\] OR âantigenicityâ\[All Fields\] OR âantigenizedâ\[All Fields\] OR âantigensâ\[MeSH Terms\] OR âantigensâ\[All Fields\] OR âantigenâ\[All Fields\]) AND (âbasedâ\[All Fields\] OR âbasingâ\[All Fields\]) AND (âRapidâ\[All Fields\] OR ârapiditiesâ\[All Fields\] OR ârapidityâ\[All Fields\] OR ârapidnessâ\[All Fields\]) AND (âdetectâ\[All Fields\] OR âdetectabilitiesâ\[All Fields\] OR âdetectabilityâ\[All Fields\] OR âdetectableâ\[All Fields\] OR âdetectablesâ\[All Fields\] OR âdetectablyâ\[All Fields\] OR âdetectedâ\[All Fields\] OR âdetectibleâ\[All Fields\] OR âdetectingâ\[All Fields\] OR âdetectionâ\[All Fields\] OR âdetectionsâ\[All Fields\] OR âdetectsâ\[All Fields\]) AND (âresearch designâ\[MeSH Terms\] OR (âresearchâ\[All Fields\] AND âdesignâ\[All Fields\]) OR âresearch designâ\[All Fields\] OR âtest\*â\[All Fields\])) OR ((âantigensâ\[MeSH Terms\] OR âantigenâ\[Text Word\]) AND âtestâ\[Title/Abstract\]) OR âRADâ\[Title/Abstract\] OR ârapid antigen detectionâ\[Title/Abstract\] OR âRapid antigen assayâ\[Title/Abstract\] OR âRapid antigen detection testâ\[Title/Abstract\] OR âRADTâ\[Title/Abstract\] OR âRAgTâ\[Title/Abstract\] OR âVATâ\[All Fields\] OR âviral antigen test\*â\[Title/Abstract\] OR ((âantigens/analysisâ\[MeSH Terms\] OR âantigens/geneticsâ\[MeSH Terms\] OR âantigens/immunologyâ\[MeSH Terms\] OR âantigens/isolation and purificationâ\[MeSH Terms\] OR âantigens/ultrastructureâ\[MeSH Terms\] OR âantigens/virologyâ\[MeSH Terms\] OR (âantigensâ\[MeSH Terms\] OR âantigenâ\[Text Word\])) AND âtestâ\[Title/Abstract\]) OR (âRapidâ\[All Fields\] AND âpoint of careâ\[All Fields\] AND (âantigen sâ\[All Fields\] OR âantigeneâ\[All Fields\] OR âantigenesâ\[All Fields\] OR âantigenicâ\[All Fields\] OR âantigenicallyâ\[All Fields\] OR âantigenicitiesâ\[All Fields\] OR âantigenicityâ\[All Fields\] OR âantigenizedâ\[All Fields\] OR âantigensâ\[MeSH Terms\] OR âantigensâ\[All Fields\] OR âantigenâ\[All Fields\]))) AND 2019/10/31:2021/12/31\[Date - Publication\] | |
| \#2 | (((âcoronavirusâ\[MeSH Terms:noexp\] OR âbetacoronavirusâ\[MeSH Terms:noexp\] OR âCoronavirus Infectionsâ\[MeSH Terms:noexp\]) AND (âDisease Outbreaksâ\[MeSH Terms:noexp\] OR âepidemicsâ\[MeSH Terms:noexp\] OR âpandemicsâ\[MeSH Terms\])) OR âCOVID-19 testingâ\[MeSH Terms\] OR âCOVID-19 drug treatmentâ\[Supplementary Concept\] OR âCOVID-19 serotherapyâ\[Supplementary Concept\] OR âCOVID-19 vaccinesâ\[MeSH Terms\] OR âspike protein sars cov 2â\[Supplementary Concept\] OR âCOVID-19â\[Supplementary Concept\] OR âSARS-CoV-2â\[MeSH Terms\] OR ânCoVâ\[Title/Abstract\] OR ânCoVâ\[Transliterated Title\] OR â2019nCoVâ\[Title/Abstract\] OR â2019nCoVâ\[Transliterated Title\] OR âcovid19\*â\[Title/Abstract\] OR âcovid19\*â\[Transliterated Title\] OR âCOVIDâ\[Title/Abstract\] OR âCOVIDâ\[Transliterated Title\] OR âSARS-CoV-2â\[Title/Abstract\] OR âSARS-CoV-2â\[Transliterated Title\] OR âSARSCOV-2â\[Title/Abstract\] OR âSARSCOV2â\[Title/Abstract\] OR âSARSCOV2â\[Transliterated Title\] OR âSevere Acute Respiratory Syndrome Coronavirus 2â\[Title/Abstract\] OR ((âsevere acute respiratory syndromeâ\[Title/Abstract\] OR âsevere acute respiratory syndromeâ\[Transliterated Title\]) AND âcorona virus 2â\[Title/Abstract\]) OR ânew coronavirusâ\[Title/Abstract\] OR (ânewâ\[Transliterated Title\] AND âcoronavirusâ\[Transliterated Title\]) OR ânovel coronavirusâ\[Title/Abstract\] OR ânovel coronavirusâ\[Transliterated Title\] OR ânovel corona virusâ\[Title/Abstract\] OR (ânovelâ\[Transliterated Title\] AND âcorona virusâ\[Transliterated Title\]) OR ânovel CoVâ\[Title/Abstract\] OR (ânovelâ\[Transliterated Title\] AND âCoVâ\[Transliterated Title\]) OR ânovel HCoVâ\[Title/Abstract\] OR (ânovelâ\[Transliterated Title\] AND âHCoVâ\[Transliterated Title\]) OR ((â19â\[Title/Abstract\] OR â19â\[Transliterated Title\] OR â2019â\[Title/Abstract\] OR â2019â\[Transliterated Title\] OR âWuhanâ\[Title/Abstract\] OR âWuhanâ\[Transliterated Title\] OR âHubeiâ\[Title/Abstract\] OR âHubeiâ\[Transliterated Title\]) AND (âcoronavirus\*â\[Title/Abstract\] OR âcoronavirus\*â\[Transliterated Title\] OR âcorona virus\*â\[Title/Abstract\] OR âcorona virus\*â\[Transliterated Title\] OR âCoVâ\[Title/Abstract\] OR âCoVâ\[Transliterated Title\] OR âHCoVâ\[Title/Abstract\] OR âHCoVâ\[Transliterated Title\])) OR ((âcoronavirus\*â\[Title/Abstract\] OR âcoronavirus\*â\[Transliterated Title\] OR âcorona virus\*â\[Title/Abstract\] OR âcorona virus\*â\[Transliterated Title\] OR âbetacoronavirus\*â\[Title/Abstract\]) AND (âoutbreak\*â\[Title/Abstract\] OR âoutbreak\*â\[Transliterated Title\] OR âepidemic\*â\[Title/Abstract\] OR âepidemic\*â\[Transliterated Title\] OR âpandemic\*â\[Title/Abstract\] OR âpandemic\*â\[Transliterated Title\] OR âcrisisâ\[Title/Abstract\] OR âcrisisâ\[Transliterated Title\])) OR ((âWuhanâ\[Title/Abstract\] OR âWuhanâ\[Transliterated Title\] OR âHubeiâ\[Title/Abstract\] OR âHubeiâ\[Transliterated Title\]) AND (âpneumoniaâ\[Title/Abstract\] OR âpneumoniaâ\[Transliterated Title\]))) AND 2019/10/31:2021/12/31\[Date - Publication\] | |
| \#3 | âpredictive value of testsâ\[MeSH Terms\] OR âpredictive value of testsâ\[All Fields\] OR âSensitivity and Specificityâ\[MeSH Terms\] OR âSensitivity and Specificityâ\[All Fields\] | |
| \#4 | \#1 AND \#2 AND \#3 | 239 |
| Reran search July 12, 2022 | 373 | |
| Qinsight (Quertle) Search conducted July 11, 2021 | | |
|---|---|---|
| Search number | Query | Results retrieved |
| \#1 | covid | |
| \#2 | rapid antigen test | |
| \#3 | sensitivity and specificity | |
| \#4 | \#1 AND \#2 AND \#3 | 204 |
| Embase Search conducted on July 11, 2021 Search reran on July 12, 2022 Filters: English language; publication date October 31, 2019 to present | | |
|---|---|---|
| Search number | Query | Results retrieved |
| \#1 | ((âsars-related coronavirusâ/exp OR âcoronavirinaeâ/exp OR âbetacoronavirusâ/exp OR âcoronavirus infectionâ/exp) AND (âepidemicâ/exp OR âpandemicâ/exp)) OR (âsevere acute respiratory syndrome coronavirus 2â/exp OR âsars coronavirus 2 test kitâ/exp OR âsars-cov-2 OR (clinical isolate wuhan/wiv04/2019)â/exp OR âcoronavirus disease 2019â/exp) OR ((ncov\* OR 2019ncov OR 19ncov OR covid19\* OR covid OR âsars cov 2â OR âsarscov 2â OR âsars cov2â OR sarscov2 OR severe) AND (acute AND respiratory AND syndrome AND coronavirus AND 2 OR severe) OR (acute AND respiratory AND syndrome AND corona AND virus AND 2)) OR (new OR novel OR â19â OR â2019â OR wuhan OR hubei OR china OR chinese) AND (coronavirus\* OR corona) AND (virus\* OR betacoronavirus\* OR cov OR hcov) OR (coronavirus\* OR corona) AND (virus\* OR betacoronavirus\*) AND (pandemic\* OR epidemic\* OR outbreak\* OR crisis) OR (wuhan OR hubei) NEAR/5 pneumonia | |
| \#2 | rapid antigen testâ/exp OR ârapid antigen detection testâ/exp OR (rapid AND antigen AND test) | |
| \#3 | (âpredictive valueâ/exp OR âsensitivity and specificityâ/exp) OR (âpredictive valueâ OR âsensitivity and specificityâ) | |
| \#4 | \#1 AND \#2 AND \#3 | 212 |
| Reran search July 12, 2022 | 410 | |
| WHO Covid-19 Database <https://search.bvsalud.org/global-literature-on-novel-coronavirus-2019-ncov/> Search conducted July 11, 2021 Search reran on July 12, 2022 | | |
|---|---|---|
| Search number | Query | Results retrieved |
| \#1 | tw:(rapid antigen test) | |
| \#2 | tw:(predictive value) | |
| \#3 | tw:(sensitivity and specificity) | |
| \#4 | la:(âenâ) | |
| \#5 | \#1 AND (\#2 OR \#3) AND \#4 | 627 |
| Reran search July 12, 2022 | 702 | |
| Scopus Search conducted July 11, 2021 Search reran on July 12, 2022 Filters English Language; Publication year greater than 2018 | | |
|---|---|---|
| Search number | Query | Results retrieved |
| \#1 | ( TITLE-ABS-KEY ( {coronavirus} OR {betacoronavirus} OR {coronavirus infections} ) AND TITLE-ABS-KEY ( {disease outbreaks} OR {epidemics} OR {pandemics} ) OR TITLE-ABS-KEY ( ( ncov\* ) OR {2019nvoc} OR {19ncov} OR {covid19\*} OR[15](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R15) OR {sars-cov-2} OR {severe acute respiratory syndrome coronavirus 2} OR {severe Acute Respiratory Syndrome Corona Virus 2} ) OR TITLE-ABS-KEY ( ( new 2/3 coronavirus\* ) OR ( new W/3 betacoronavirus\* ) OR ( new W/3 cov ) OR ( new W/3 hcov ) OR ( novel W/3 coronavirus\* ) ) OR TITLE-ABS-KEY ( ( corona AND virus\* W/3 epidemic\* ) OR ( corona AND virus\* W/3 outbreak\* ) OR ( corona AND virus\* W/3 crisis ) OR ( betacoronavirus\* W/3 pandemic\* ) ) OR TITLE-ABS-KEY ( ( corona AND virus\* W/3 epidemic\* ) OR ( corona AND virus\* W/3 outbreak\* ) OR ( corona AND virus\* W/3 crisis ) OR ( betacoronavirus\* W/3 pandemic\* ) OR ( betacoronavirus\* W/3 epidemic\* ) OR ( betacoronavirus\* W/3 outbreak\* ) OR ( betacoronavirus\* W/3 crisis ) ) ) AND PUBYEAR \> 2018 | |
| \#2 | ( TITLE-ABS-KEY ( {rapid antigen test} OR ârapid antigen test\*â ) OR TITLE-ABS-KEY ( ârapidâ AND âantigenâ AND âtestâ ) ) AND PUBYEAR \> 2018 | |
| \#3 | ( TITLE-ABS-KEY ( {predictive value} OR {sensitivity and specificity} ) AND TITLE-ABS-KEY ( âpredictive valueâ OR âsensitivity and specificityâ ) ) AND PUBYEAR \> 2018 | |
| \#4 | \#1 AND \#2 AND \#3 | 176 |
| Reran search July 12, 2022 | 462 | |
## Appendix II: Data extraction instrument
| Field name | Entry type |
|---|---|
| Data extractor | Free-text |
| Data validated by | Free-text |
| Article \# | Free-text |
| Article first author | Free-text |
| Article title | Free-text |
| Month, year | Free-text |
| DOI/PMID/other identifier | Free-text |
| Country | Free-text |
| Setting/context | Drop-down |
| Primary care location | |
| Hospital â inpatient | |
| COVID-19 testing site/screening location | |
| Urgent care location | |
| Emergency dept/room | |
| Public area (not a designated screening location) | |
| College/university campus (non-medical) | |
| Long-term care facility (nursing home, rehab centers) | |
| Not described/unclear | |
| Hospital â outpatient | |
| College/university campus (medical center/hospital) | |
| Year/time frame for data collection | Free-text |
| Participant characteristics (age range, gender breakdown, rural/urban, etc) | Free-text |
| Number of participants | Free-text |
| Sample type | Drop-down |
| Nasopharyngeal swabs (NP) | |
| Blood (Bld) | |
| Bronchoalveolar lavage (BAL)/bronchial sample | |
| Nasal swabs (NS) | |
| Oropharyngeal swabs (OP) | |
| Other | |
| Saliva (Sal) | |
| Throat swabs (TS) | |
| Sample type if other | Free-text |
| Reference test description | Drop-down |
| Abbott RealTime SARS-CoV-2 (Abbott) | |
| Alinity m SARS-CoV-2 AMP (Abbott) | |
| Allplex assays (Seegene) | |
| ARGENE SARS-CoV-2 R-Gene (Biomerieux) | |
| BD Max (Becton-Dickinson) | |
| BGI 2019-nCoV Real-time Fluorescent RT-PCR kit (BGI Genomics) | |
| Biofire | |
| CDC 2019-nCoV Real-Time RT-PCR Diagnostic Panel | |
| Cobas Kits/Systems (Roche) | |
| COVID-19 Multiplex RT-PCR kit (DIANA Biotech) | |
| COVID-19 Real-time PCR kit (HBRT-COVID-19) (Chaozhou Hybribio Biochemistry Ltd., China) | |
| Covidsure Multiplex RT-PCR kit (Trivitron Healthcare Labsystems Diagnostics) | |
| CRSP SARS-CoV-2 (Clinical Research Sequencing Platform, Harvard/MIT) | |
| Custom/In-house SARS-2 primers | |
| DAAN Gene RT-PCR COVID-19 (DaAnGene) | |
| FTD SARS-CoV-2 Assay (Fast Track Diagnostics, Luxembourg) | |
| GENECUBE (Toyobo Co., Ltd.) | |
| GeneFinder COVID-19 Plus RealAmp Kit (Osang Healthcare Co., Ltd) | |
| Genesig Real-time PCR Coronavirus assay/Z-Path-COVID-19-CE (Primerdesign) | |
| GenomeCoV19 Detection kit (ABM) | |
| IDT SARS-CoV-2 (2019-nCoV) multiplex CDC qPCR probe Assay (Integrated DNA Technologies) | |
| Japanese National Institute of Infectious Diseases (NIID) | |
| LabTurbo AIO COVID-19 RNA Testing Kit | |
| LightMix SarbecoV (TIB Microbiol) | |
| Luna Universal Probe One-Step RT-PCR for Detection of COVID-19 (SignaGen Labs) | |
| Meril COVID-19 One-Step RT-PCR Kit | |
| MutaPLEX Coronavirus Real-time-RT-PCR kit (Immundiagnostik AG) | |
| NeuMoDx SARS-CoV-2 Assay (Qiagen) | |
| Novel Coronavirus (2019-nCoV) Real Time Multiplex RT-PCR kit (Liferiver) | |
| Panther Fusion or Aptima SARS-CoV-2 assay (Hologic) | |
| PCR Biosystems | |
| PerkinElmer SARS-CoV-2 Real-time RT-PCR Assay | |
| Real-Q 2019-nCoV Detection Kit (Biosewoom) | |
| REALQUALITY RQ-SARS-CoV-2 kit (AB Analitica) | |
| RealStar SARS-CoV-2 RT-PCR kit (Altona) | |
| RIDAGENE SARS-CoV-2 (R-Bio-pharm) | |
| Sansure Biotech COVID-19 Nucleic Acid Test kit | |
| Shimadzu Ampdirect 2019 novel coronavirus detection kit | |
| Simplexa (DiaSorin) | |
| Specific Test Not Described | |
| Standard M nCoV Real-Time Detection Kit (SD Biosenor) | |
| Takara Bio SARS-CoV-2 direct detection RT-qPCR kit | |
| TaqPath COVID-19 Combo kit (Applied Biosystems/ThermoFisher) | |
| VIASURE (CerTest) | |
| Vitassay (Vitassay) | |
| Xpert Xpress SARS-CoV-2/GeneXpert (Cepheid) | |
| Reference test if other | Free-text |
| Reference test comments (if any) | Free-text |
| Index test description | Drop-down |
| STANDARD Q COVID-19 Ag Test | |
| PanBio COVID-19 Ag Rapid Test Device | |
| SARS-CoV-2 Rapid Antigen Test | |
| BinaxNOW COVID-19 Antigen | |
| Rapid Test Ag 2019-nCov | |
| SARS-CoV-2 Ag | |
| Custom/Novel/In-house | |
| COVISTIX (COVIDMARK) Covid 19 Antigen Rapid Test Device | |
| AMP Rapid Test SARS-CoV-2 Ag | |
| BD Veritor COVID-19 Rapid Antigen Test | |
| CerTest SARS-CoV-2 | |
| Espline SARS-CoV-2 | |
| SARS-CoV-2 Antigen Rapid Test | |
| HUMASIS COVID-19 Ag Test | |
| Mologic Covid-19 Rapid Antigen Test | |
| BIOCREDIT COVID-19 Ag | |
| Rida Quick SARS-CoV-2 Antigen Test | |
| STANDARD F COVID-19 Ag FIA | |
| RapidTesta SARS-CoV-2 | |
| Fluorecare SARS-CoV-2 Spike Protein Test kit (Colloidal Gold) | |
| CLINITEST Rapid COVID-19 Antigen Test | |
| Immupass VivaDiag | |
| COVID-VIRO COVID-19 Ag Rapid Test | |
| Flowflex COVID-19 Antigen test | |
| COVID-19 Antigen Rapid Test | |
| Alltest COVID-19 ART Antigen Rapid Test | |
| COVID-19 Antigen Rapid Test | |
| COVID-19 RAT kit | |
| NowCheck COVID-19 Ag test | |
| Novel Corona Virus (SARS-CoV-2) Ag Rapid Test kit | |
| Covid-19 AG BSS | |
| Helix i-SARS-CoV-2 Ag Rapid Test | |
| COVID-19 Ag K-SeT | |
| Liaison SARS-CoV-2 Ag | |
| COVID-19 Antigen Detection | |
| COVID-19 Ag ECO Teste | |
| Inflammacheck CoronaCheck | |
| GenBody COVAG025 | |
| GENEDIA W COVID-19 Ag Test | |
| Rapid COVID-19 Antigen Test | |
| Innova SARS-CoV-2 Antigen Rapid test | |
| Accucare PathoCatch Covid-19 Ag Detection Kit | |
| Orient Gene Rapid Covid-19 (Antigen) Self-Test | |
| GeneFinder COVID-19 Ag Plus Rapid Test | |
| Green Spring SARS-CoV-2 Antigen Rapid Test Kit (Colloidal Gold) | |
| Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Antigen Detection Kit (Colloidal Gold-Based) | |
| 2019-nCoV Antigen Test | |
| Index test if other | Free-text |
| Index test comments (if any) | Free-text |
| Subgroups (if any; include overall) | Free-text |
| True positive (TP) | Free-text |
| False positive (FP) | Free-text |
| True negative (TN) | Free-text |
| False negative (FN) | Free-text |
| Sensitivity (TP/\[TP+FN\]) | Free-text |
| Sensitivity 95% CI (low, high) | Free-text |
| Specificity (TN/\[TN+FP\]) | Free-text |
| Specificity 95% CI (low, high) | Free-text |
| Positive predictive value PPV (TP/\[TP+FP\]) | Free-text |
| Negative predictive values NPV (TN/\[FN+TN\]) | Free-text |
| Description of main results (include adverse events from tests) | Free-text |
| Exclusion reasons (if any) | Free-text |
| Notes | Free-text |
| Need to contact authors? Put contact info here | Free-text |
## Appendix III: Characteristics of included studies
| Author, year | Article title | Index test description | Sensitivity (TP/\[TP+FN\]) | Sensitivity 95% CI (low, high) | Specificity (TN/\[TN+FP\]) | Specificity 95% CI (low, high) |
|---|---|---|---|---|---|---|
| Abdelrazik, *et al.* [31](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R31) Mar 2021 | Potential use of antigen-based rapid test for SARS-CoV-2 in respiratory specimens in low-resource settings in Egypt for symptomatic patients and high-risk contacts | RapiGen (BioCredit) | 43\.1 | | | |
| Abusrewil, *et al.* [32](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R32) Dec 2021 | Time scale performance of rapid antigen testing for SARS-CoV-2: evaluation of ten rapid antigen assays | PanBio (Abbott) | 76\.92 | 46\.19, 94.96 | 100 | |
| Flowflex COVID-19 Antigen test (ACON Labs) | 100 | 78\.20, 100 | 100 | | | |
| AMP Rapid Test SARS-CoV-2 Ag (AMP Diagnostics) | 85\.71 | 42\.13, 99.64 | 100 | | | |
| COVID-19 Antigen Rapid Test (Assut Europe) | 71\.43 | 29\.04, 96.33 | 100 | | | |
| Novel Corona Virus (SARS-CoV-2) Ag Rapid Test kit (Bioperfectus) | 80 | 44\.39, 94.78 | 100 | | | |
| CerTest SARS-CoV-2 (Certest Biotech) | 62\.5 | 24\.49, 91.48 | 100 | | | |
| Espline SARS-CoV-2 (Fujirebio) | 80 | 44\.39, 97.48 | 100 | | | |
| Fluorecare (Colloidal Gold/Fluorescent) SARS-CoV-2 Spike Protein Test kit (Shenzen Microprofit) | 91\.67 | 61\.52, 99.79 | 100 | | | |
| Orient Gene Rapid Covid-19 (Antigen) Self-Test (Orient Gene) | 50 | 18\.71, 81.29 | 100 | | | |
| RapiGen (BioCredit) | 62\.5 | 35\.4, 84.80 | 100 | | | |
| Afzal, *et al.* [33](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R33) Sep 2021 | Diagnostic accuracy of PANBIO COVID-19 rapid antigen method for screening in emergency cases | PanBio (Abbott) | 90\.47 | | 100 | |
| Akashi, *et al.* [34](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R34) Feb 2022 | A prospective clinical evaluation of the diagnostic accuracy of the SARS-CoV-2 rapid antigen test using anterior nasal samples | Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 72\.7 | 63\.4, 80.8 | 100 | 99\.5, 100 |
| Al-Alawi, *et al.* [35](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R35) Jan 2021 | Evaluation of four rapid antigen tests for detection of SARS-CoV-2 virus | STANDARD Q COVID-19 Ag (SD Biosensor) | 65\.8 | 48\.65, 80.37 | 100 | 87\.66, 100 |
| PCL COVID19 Ag Rapid FIA Antigen Test (PCL) | 69\.8 | 55\.66, 81.66 | 94\.1 | 80\.32, 99.28 | | |
| RapiGen (BioCredit) | 64 | 49\.19, 77.08 | 100 | 86\.28, 100 | | |
| Sofia SARS Rapid Antigen FIA/Sofia 2 (Quidel) | 64\.3 | 50\.36, 76.64 | 100 | 84\.56, 100 | | |
| Aleem, *et al.* [36](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R36) Jan 2022 | Diagnostic accuracy of STANDARD Q COVID-19 antigen detection kit in comparison with RT-PCR assay using nasopharyngeal samples in India | STANDARD Q COVID-19 Ag (SD Biosensor) | 54\.43 | 42\.83, 65.69 | 99\.24 | 97\.79, 99.84 |
| Alghounaim, *et al.* [37](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R37) Dec 2021 | The performance of two rapid antigen tests during population-level screening for SARS-CoV-2 infection | Liaison | 43\.3 | 30\.6, 56.8 | 99\.9 | 99\.3, 100 |
| STANDARD Q COVID-19 Ag (SD Biosensor) | 30\.6 | 19\.6, 43.7 | 98\.8 | 97\.8, 99.4 | | |
| Allan-Blitz, *et al.* [38](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R38) Sep 2021 | A real-world comparison of SARS-CoV-2 rapid antigen testing versus PCR testing in Florida | BinaxNOW (Abbott) - all sample types PCR | 49\.2 | 47\.4, 50.9 | 98\.8 | 98\.6, 98.9 |
| BinaxNOW (Abbott) - Anterior Nares PCR | 47\.5 | 39\.1, 56.1 | 100 | 99\.3, 100 | | |
| BinaxNOW (Abbott) - Nasopharyngeal Fluid PCR | 46\.1 | 37\.3, 55.1 | 99\.7 | 98\.9, 100 | | |
| BinaxNOW (Abbott) - Oral Fluid PCR | 49\.37 | 47\.5, 51.2 | 98\.7 | 98\.5, 98.8 | | |
| Amer, *et al.* [39](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R39) Oct 2021 | Diagnostic performance of rapid antigen test for COVID-19 and the effect of viral load, sampling time, subject's clinical and laboratory parameters on test accuracy (preprint) | STANDARD Q COVID-19 Ag (SD Biosensor) | 78\.2 | 67, 86 | 64\.2 | 38, 83 |
| Anastasiou, *et al.* [40](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R40) Apr 2021 | Fast detection of SARS-CoV-2 RNA directly from respiratory samples using a loop-mediated isothermal amplification (LAMP) test | Custom/Novel/In-house | 68\.8 | 57\.3, 78.4 | 100 | 90\.6, 100 |
| Avgoulea, *et al.* [41](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R41) Apr 2022 | Field evaluation of the new rapid NG-Test(ÂŽ) SARS-CoV-2 Ag for diagnosis of COVID-19 in the emergency department of an academic referral hospital | Custom/Novel/In-house - NP sample | 81 | 73, 87 | 99 | 95, 100 |
| Custom/Novel/In-house - OP sample | 51 | 42, 59 | 100 | 96, 100 | | |
| Babu, *et al.* [42](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R42) Jul 2021 | The burden of active infection and anti-SARS-CoV-2 IgG antibodies in the general population: Results from a statewide sentinel-based population survey in Karnataka, India | STANDARD Q COVID-19 Ag (SD Biosensor) | Not reported | | | |
| Bachman, *et al.* [43](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R43) Aug 2021 | Clinical validation of an open-access SARS-CoV-2 antigen detection lateral flow assay, compared to commercially available assays | Custom/Novel/In-house - PCR collected by NP | 69 | 60, 78 | 97 | 88, 100 |
| BinaxNOW (Abbott) - PCR collected by NP | 82 | 73, 88 | 100 | 94, 100 | | |
| Sofia SARS Rapid Antigen FIA/Sofia 2 (Quidel) - PCR collected by NP | 74 | 64, 82 | 98 | 91, 100 | | |
| Custom/Novel/In-house - PCR collected by NS | 83 | 74, 90 | 97 | 91, 100 | | |
| BinaxNOW (Abbott) - PCR collected by NS | 91 | 84, 96 | 94 | 85, 98 | | |
| Sofia SARS Rapid Antigen FIA/Sofia 2 (Quidel) - PCR collected by NS | 86 | 77, 92 | 96 | 89, 99 | | |
| Basso, *et al.* [44](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R44) Feb 2021 | Salivary SARS-CoV-2 antigen rapid detection: a prospective cohort study | Espline SARS-CoV-2 (Fujirebio) | 48 | | 100 | |
| Blairon, *et al.* [45](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R45) Aug 2020 | Implementation of rapid SARS-CoV-2 antigenic testing in a laboratory without access to molecular methods: experiences of a general hospital | Respi-Strip (Coris BioConcept) | 30 | 16\.7, 47.9 | 100 | |
| Bond, *et al.* [46](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R46) May 2022 | Utility of SARS-CoV-2 rapid antigen testing for patient triage in the emergency department: a clinical implementation study in Melbourne, Australia | PanBio (Abbott) | 75\.5 | 69\.9, 80.4 | 100 | 99\.8, 100 |
| Borro, *et al.* [47](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R47) Apr 2022 | SARS-CoV-2 transmission control measures in the emergency department: the role of rapid antigenic testing in asymptomatic subjects | Green Spring "SARS-CoV-2 Antigen Rapid Test Kit (Colloidal Gold)" - standard protocol | 79\.8 | | 100 | |
| Green Spring "SARS-CoV-2 Antigen Rapid Test Kit (Colloidal Gold)" - UTM modified protocol | 70\.7 | | 100 | | | |
| Green Spring "SARS-CoV-2 Antigen Rapid Test Kit (Colloidal Gold)" - UTM modified protocol | 43\.9 | | 100 | | | |
| Boum, *et al.* [48](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R48) May 2021 | Performance and operational feasibility of antigen and antibody rapid diagnostic tests for COVID-19 in symptomatic and asymptomatic patients in Cameroon: a clinical, prospective, diagnostic accuracy study | STANDARD Q COVID-19 Ag (SD Biosensor) | 58\.4 | 53\.0, 64.8 | 93\.2 | 88\.0, 97.0 |
| Bulilete, *et al.* [49](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R49) Feb 2021 | Panbio⢠rapid antigen test for SARS-CoV-2 has acceptable accuracy in symptomatic patients in primary health care | PanBio (Abbott) | 71\.4 | 63\.1, 78.7 | 99\.8 | 99\.4, 99.9 |
| Burdino, *et al.* [50](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R50) Oct 2021 | SARS-CoV-2 microfluidic antigen point-of-care testing in emergency room patients during COVID-19 pandemic | SARS-CoV-2 Ag (LumiraDx) | 90\.1 | 86\.2, 93.1 | 99\.4 | 98\.6, 99.8 |
| Bwogi, *et al.* [7](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R7) May 2022 | Field evaluation of the performance of seven antigen rapid diagnostic tests for the diagnosis of SARs-CoV-2 virus infection in Uganda | Immupass VivaDiag (VivaChek Biotech) | 30\.2 | 18\.0, 46.1 | 94\.1 | 90\.1, 96.6 |
| MEDsan SARS-CoV-2 Antigne Rapid Test | 13 | 8\.1, 20.3 | 100 | 96\.9, 100 | | |
| Novegent COVID-19 Antigen Rapid Test Kit (Colloidal gold) | 46 | 36\.3, 56.0 | 89\.9 | 83\.3, 94.1 | | |
| PanBio (Abbott) | 49\.4 | 38\.7, 60.1 | 100 | 96\.4, 100 | | |
| PCL COVID19 Ag Rapid FIA Antigen Test (PCL) | 37\.6 | 28\.2, 48.1 | 89\.9 | 80\.8, 94.9 | | |
| RapiGen (BioCredit) | 27\.4 | 20\.5, 35.6 | 98\.2 | 93\.1, 99.6 | | |
| Respi-Strip (Coris BioConcept) | 19\.4 | 11\.5, 30.9 | 99\.2 | 94\.5, 99.9 | | |
| Caruana, *et al.* [51](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R51) Apr 2021 | Implementing SARS-CoV-2 rapid antigen testing in the emergency ward of a Swiss university hospital: the INCREASE Study | PanBio (Abbott) | 41\.2 | | 99\.5 | |
| BD Veritor COVID-19 Rapid Antigen Test (Becton-Dickinson) | 41\.2 | | 99\.7 | | | |
| Exdia (Precision Biosensor) | 48\.3 | | 99\.5 | | | |
| STANDARD Q COVID-19 Ag (SD Biosensor) | 41\.2 | | 99\.7 | | | |
| Caruana, *et al.* [52](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R52) May 2021 | The dark side of SARS-CoV-2 rapid antigen testing: screening asymptomatic patients | STANDARD Q COVID-19 Ag (SD Biosensor) | 28\.6 | | 98\.2 | |
| Cassuto, *et al.* [53](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R53) Jul 2021 | Evaluation of a SARS-CoV-2 antigen-detecting rapid diagnostic test as a self-test: diagnostic performance and usability | COVIDâVIRO nasal swab test | 96\.88 | 83\.78, 99.92 | 100 | 98\.19, 100.00 |
| Cattelan, *et al.* [8](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R8) Mar 2022 | Rapid antigen test LumiraDx(TM) vs real time polymerase chain reaction for the diagnosis of SARS-CoV-2 infection: a retrospective cohort study | SARS-CoV-2 Ag (LumiraDx) | 76\.3 | 70\.8, 81.8 | 94\.4 | 88\.3, 100 |
| Cento, *et al.* [54](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R54) May 2021 | Frontline screening for SARS-CoV-2 infection at emergency department admission by third generation rapid antigen test: can we spare RT-qPCR? | SARS-CoV-2 Ag (LumiraDx) | 85\.6 | 82, 89 | 97\.05 | 96, 98 |
| Cerutti, *et al.* [55](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R55) Nov 2020 | Urgent need of rapid tests for SARS CoV-2 antigen detection: evaluation of the SD-Biosensor antigen test for SARS-CoV-2 | STANDARD Q COVID-19 Ag (SD Biosensor) | 70\.6 | | 100 | |
| Chaimayo, *et al.* [56](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R56) Nov 2020 | Rapid SARS-CoV-2 antigen detection assay in comparison with real-time RT-PCR assay for laboratory diagnosis of COVID-19 in Thailand | STANDARD Q COVID-19 Ag (SD Biosensor) | 98\.33 | 91\.06, 99.6 | 98\.73 | 97\.06, 99.59 |
| Cheng, *et al.* [57](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R57) May 2022 | Evaluation of a rapid antigen test for the diagnosis of SARS-CoV-2 during the COVID-19 pandemic | Enimmune Speedy COVID-19 AG Rapid Test - Heping | 69\.1 | 68\.8, 69.5 | 99\.1 | 99\.1, 99.1 |
| PanBio (Abbott) - RenAi | 62 | 61\.6, 62.3 | 99\.9 | 99\.9, 99.9 | | |
| VTRUST COVID-19 Antigen Rapid Test (Taidoc Technology Corporation) - YangMing | 78\.6 | 78\.2, 78.9 | 98\.2 | 98\.2, 98.3 | | |
| VTRUST COVID-19 Antigen Rapid Test (Taidoc Technology Corporation) - Zhongxiao | 60\.5 | 60\.1, 60.8 | 99\.1 | 99\.0, 99.1 | | |
| Enimmune Speedy COVID-19 AG Rapid Test - Zhongxing | 64\.6 | 64\.3, 64.8 | 98\.3 | 98\.3, 98.3 | | |
| Choudhary, *et al.* [58](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R58) Apr 2022 | Validation of rapid SARS-CoV-2 antigen detection test as a screening tool for detection of Covid-19 infection at district hospital in northern India | Standard Q COVID-19 Ag (SD Biosensor) | 55\.04 | 46\.43, 63.35 | 99\.2 | 98\.15, 99.66 |
| Cottone, *et al.* [59](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R59) May 2022 | Pitfalls of SARS-CoV-2 antigen testing at emergency department | Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 45\.5 | 35\.6, 55.8 | 98\.1 | 96\.1, 99.2 |
| Cubas-Atienzar, *et al.* [60](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R60) May 2021 | Accuracy of the Mologic COVID-19 rapid antigen test: a prospective multi-centre analytical and clinical evaluation | Mologic Covid-19 Rapid Antigen Test (Mologic Ltd. United Kingdom) - Northumberland | 86 | 76\.9, 92.6 | 97\.5 | 93\.8, 99.3 |
| Mologic Covid-19 Rapid Antigen Test (Mologic Ltd. United Kingdom) - Yorkshire | 84\.6 | 54\.6, 98.1 | 100 | 91\.2, 100 | | |
| Dierks, *et al.* [61](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R61) May 2021 | Diagnosing SARS-CoV-2 with antigen testing, transcription-mediated amplification and real-time PCR | SARS-CoV-2 Ag (LumiraDx) | 45\.45 | 20\.22, 73.26 | 99\.54 | 98\.17, 99.88 |
| NADAL COVID-19 Antigen Rapid Test (New Art Laboratories/nal von minden) | 14\.29 | 1\.94, 58.35 | 76\.44 | 70\.16, 81.74 | | |
| Escribano, *et al.* [62](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R62) Feb 2022 | Different performance of three point-of-care SARS-CoV-2 antigen detection devices in symptomatic patients and close asymptomatic contacts: a real-life study | PanBio (Abbott) - Close Asymptomatic Contacts | 33\.3 | 11\.8, 61.6 | | |
| SGTI-Flex - Close Asymptomatic Contacts | 84\.6 | 54\.5, 98.1 | | | | |
| NovaGen - Close Asymptomatic Contacts | 55\.5 | 30\.7, 78.4 | | | | |
| PanBio (Abbott)-COVID-19 Suspected Cases | 71\.1 | 55\.6, 83.6 | | | | |
| SGTI-Flex - COVID-19 Suspected Cases | 68\.8 | 55\.7, 80 | | | | |
| NovaGen - COVID-19 Suspected Cases | 84\.6 | 72\.0, 93.1 | | | | |
| EscrivĂĄ, *et al.* [63](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R63) Aug 2021 | The effectiveness of rapid antigen test-based for SARS-CoV-2 detection in nursing homes in Valencia, Spain | PanBio (Abbott) | 85 | 90, 99 | 100 | 100, 100 |
| FaĂco-Filho, *et al.* [64](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R64) Mar 2022 | Evaluation of the Panbio⢠COVID-19 Ag rapid test at an emergency room in a hospital in SĂŁo Paulo, Brazil | PanBio (Abbott) | Not reported | | | |
| Farfour, *et al.* [65](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R65) Mar 2021 | The Panbio COVID-19 Ag rapid test: which performances are for COVID-19 diagnosis? | PanBio (Abbott) | Not reported | | | |
| Fernandez-Montero, *et al.* [66](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R66) Jul 2021 | Validation of a rapid antigen test as a screening tool for SARS-CoV-2 infection in asymptomatic populations. Sensitivity, specificity and predictive values | Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 71\.43 | 56\.74, 83.42 | 99\.68 | 99\.37, 99.86 |
| FertĂŠ, *et al.* [67](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R67) Jun 2021 | Accuracy of COVID-19 rapid antigenic tests compared to RT-PCR in a student population: the StudyCov study | PanBio (Abbott) | 63\.5 | 49\.0, 76.4 | 100 | 99\.4, 100 |
| Fitoussi, *et al.* [68](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R68) Oct 2021 | Analytical performance of the point-of-care BIOSYNEX COVID-19 Ag BSS for the detection of SARSâCoVâ2 nucleocapsid protein in nasopharyngeal swabs: a prospective field evaluation during the COVID-19 third wave in France | BIOSYNEX Ag-RDT | 81\.80 | 79\.2, 84.1 | 99\.60 | 98\.9, 99.8 |
| Ford, *et al.* [69](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R69) Sep 2021 | Antigen test performance among children and adults at a SARS-CoV-2 community testing site | BinaxNOW (Abbott) - Exposed | 79\.80 | | 99\.70 | |
| BinaxNOW (Abbott) | 80\.80 | | 99\.90 | | | |
| Freire, *et al.* [11](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R11) Jun 2022 | Performance differences among commercially available antigen rapid tests for COVID-19 in Brazil | PanBio (Abbott) - NP Swab | 60\.00 | 45\.9, 73.0 | 100 | 69\.2, 100 |
| PanBio (Abbott) - NS Swab | 58\.20 | 44\.1, 71.4 | 100 | 69\.2, 100% | | |
| COVID-19 Ag ECO Teste (Eco Diagnostica) | 42\.90 | 30\.5, 56.0 | 83\.30 | 58\.6, 96.4 | | |
| STANDARD Q COVID-19 Ag (SD Biosensor) | 53\.00 | 40\.3, 65.4 | 86\.70 | 59\.5, 98.3 | | |
| CORIS Bioconcept1 Ag-RDT (Nanosens) | 9\.80 | 3\.7, 20.2 | 100 | 78\.2, 100 | | |
| CELLER WONDFO SARSCOV2 Ag-RDT | 47\.20 | 33\.3, 61.4 | 100 | 69\.2, 100 | | |
| NowCheck COVID-19 Ag test (Bionote) | 60 | 45\.9, 73.0 | 100 | 66\.4, 100 | | |
| Ag-RDT COVID-19 (Acro Biotech) | 81\.10 | 68\.0, 90.6 | 84\.60 | 54\.5, 98.1 | | |
| Galliez, *et al.* [70](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R70) Jun 2022 | Evaluation of the Panbio COVID-19 antigen rapid diagnostic test in subjects infected with omicron using different specimens | PanBio (Abbott) - NS Swab | 89 | 82\.4, 93.3 | 100 | 94\.4, 100 |
| PanBio (Abbott) - Oral Specimen | 12\.6 | 7\.9, 19.5 | 100 | 94\.4, 100 | | |
| Garcia-Cardenas, *et al.* [71](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R71) Sep 2021 | Analytical performances of the COVISTIX and Panbio antigen rapid tests for SARS-CoV-2 detection in an unselected population (all comers) | PanBio (Abbott) | 62% | 58, 64 | 99 | 99, 100 |
| COVISTIX Covid 19 Antigen Rapid Test Device | 81 | 76, 85 | 96 | 94, 98 | | |
| Garcia-Cardenas, *et al.* [72](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R72) May 2022 | Analytical performances of the COVISTIX⢠antigen rapid test for SARS-CoV-2 detection in an unselected population (all-comers) | COVISTIX Covid 19 Antigen Rapid Test Device | 81 | 75\.0, 85.0 | 96 | 94\.0, 98.0 |
| COVISTIX Covid 19 Antigen Rapid Test Device | 93 | 88, 98 | 98 | 97, 99 | | |
| GarcĂa-FernĂĄndez, *et al.* [73](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R73) Mar 2022 | Evaluation of the rapid antigen detection test STANDARD F COVID-19 Ag FIA for diagnosing SARS-CoV-2: experience from an emergency department | STANDARD F COVID-19 Ag FIA (SD Biosensor Inc.) | 84 | 76\.1, 89.7 | 99\.6 | 98\.5, 99.9 |
| GarcĂa-FiĂąana, *et al.* [74](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R74) Jul 2021 | Performance of the Innova SARS-CoV-2 antigen rapid lateral flow test in the Liverpool asymptomatic testing pilot: population based cohort study | Innova (recalled 06/2021) | 40 | 28\.5, 52.4 | 99\.9 | 99\.8, 99.99 |
| Goga, *et al.* [75](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R75) Mar 2022 | Utility of COVID-19 point-of-care antigen tests in low-middle income settings | RapiGen (BioCredit) | 34\.8 | 26\.1, 44.2 | 97\.6 | 93\.9, 99.3 |
| STANDARD Q COVID-19 Ag (SD Biosensor) | 49\.1 | 43\.3, 55.0 | 95\.7 | 93\.5, 97.3 | | |
| SARS-CoV-2 Ag (LumiraDx) | 63\.8 | 55\.9, 71.2 | 97 | 95\.5, 98.3 | | |
| GonzĂĄlez-Fiallo, *et al.* [76](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R76) Apr 2022 | Evaluation of SARS-CoV-2 rapid antigen tests in use on the Isle of Youth, Cuba | STANDARD Q COVID-19 Ag (SD Biosensor) | 75\.30% | 66\.0, 84.6 | 96\.10 | 94\.5, 97.6 |
| Gupta, *et al.* [77](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R77) Feb 2021 | Rapid chromatographic immunoassay-based evaluation of COVID-19: a cross-sectional, diagnostic test accuracy study & its implications for COVID-19 management in India | STANDARD Q COVID-19 Ag (SD Biosensor) | 81\.8 | 71\.3, 89.6 | 99\.6 | 97\.8, 99.9 |
| Harris, *et al.* [78](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R78) May 2021 | SARS-CoV-2 rapid antigen testing of symptomatic and asymptomatic individuals on the University of Arizona campus | Sofia SARS Rapid Antigen FIA/Sofia 2 (Quidel) | 91\.4 | | 100 | |
| Holzner, *et al.* [79](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R79) Apr 2021 | SARS-CoV-2 rapid antigen test: fast-safe or dangerous? An analysis in the emergency department of an university hospital | STANDARD Q COVID-19 Ag (SD Biosensor) | 68\.8 | 66\.84, 70.73 | 99\.56 | 99\.3, 99.82 |
| Homza, *et al.* [80](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R80) Apr 2021 | Five antigen tests for SARS-CoV-2: virus viability matters | Ecotest (Assure Tech) | 75\.7 | 66\.5, 83.5 | 96\.7 | 93\.3, 98.7 |
| Immupass VivaDiag (VivaChek Biotech) | 41\.8 | 31\.5, 52.6 | 96 | 92\.0, 98.4 | | |
| ND Covid (NDFOS) | 70\.1 | 58\.6, 80 | 56\.1 | 46\.5, 65.4 | | |
| SARS-CoV-2 Antigen Rapid Test (JoysBio) | 57\.8 | 46\.9, 68.1 | 98\.5 | 94\.8, 99.8 | | |
| STANDARD Q COVID-19 Ag (SD Biosensor) | 61\.9 | 45\.6, 76.4 | 99 | 94\.4, 100 | | |
| HĂśrber, *et al.* [81](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R81) Jun 2022 | Evaluation of a laboratory-based high-throughput SARS-CoV-2 antigen assay | CoV2Ag assay (Siemens Healthineers, Eschborn, Germany) | 88\.50 | 83\.7, 91.9 | 99\.50 | 97\.4, 99.9 |
| Ifko, *et al.* [82](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R82) Jul 2021 | Diagnostic validation of two SARS-CoV-2 immunochromatographic tests in Slovenian and Croatian hospitals | NADAL COVID-19 Antigen Rapid Test (New Art Laboratories/nal von minden) | 84\.61 | 54\.55, 98.08 | 100 | 90\.75, 100 |
| NADAL COVID-19 Antigen Rapid Test (New Art Laboratories/nal von minden) | 86\.96 | 66\.41, 97.23 | 88\.24 | 80\.35, 93.77 | | |
| Igloi, *et al.* [83](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R83) May 2021 | Clinical evaluation of Roche SD Biosensor rapid antigen test for SARS-CoV-2 in municipal health service testing site, the Netherlands | STANDARD Q COVID-19 Ag (SD Biosensor) | 84\.9 | 79\.1, 89.4 | 99\.5 | 98\.7, 99.8 |
| Jakobsen, *et al.* [84](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R84) Jun 2021 | Accuracy and cost description of rapid antigen test compared with reverse transcriptase-polymerase chain reaction for SARS-CoV-2 detection | STANDARD Q COVID-19 Ag (SD Biosensor) | 69\.7 | | 99\.5 | |
| Jakobsen, *et al.* [85](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R85) Feb 2022 | Accuracy of anterior nasal swab rapid antigen tests compared with RT-PCR for massive SARS-CoV-2 screening in low prevalence population | STANDARD Q COVID-19 Ag (SD Biosensor) | 48\.5 | | 100 | |
| Jeewandara, *et al.* [86](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R86) Mar 2022 | Sensitivity and specificity of two WHO approved SARS-CoV2 antigen assays in detecting patients with SARS-CoV2 infection | STANDARD Q COVID-19 Ag (SD Biosensor) | 36\.24 | 33\.1, 39.5 | 97\.6 | 97, 98 |
| PanBio (Abbott) | 52\.6 | 46\.7, 58.5 | 99\.6 | 99\.2, 99.8 | | |
| Jegerlehner, *et al.* [87](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R87) Jul 2021 | Diagnostic accuracy of a SARS-CoV-2 rapid antigen test in real-life clinical settings | STANDARD Q COVID-19 Ag (SD Biosensor) | 65\.3 | 56\.8, 73.1 | 99\.9 | 99\.5, 100 |
| PCL COVID19 Ag Rapid FIA Antigen Test (PCL) | 30\.2 | 18\.3, 44.3 | 98\.1 | 96\.0, 99.3 | | |
| Jegerlehner, *et al.* [88](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R88) Jun 2022 | Diagnostic accuracy of SARS-CoV-2 saliva antigen testing in a real-life clinical setting | PCL COVID19 Ag Rapid FIA Antigen Test (PCL) | 30\.2 | 18\.3, 44.3 | 98\.1 | 96\.0, 99.3 |
| Jirungda, *et al.* [89](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R89) May 2022 | Clinical performance of the STANDARD F COVID-19 AG FIA for the detection of SARS-COV-2 infection | STANDARD F COVID-19 Ag FIA (SD Biosensor Inc.) | 98\.8 | | 89\.7 | |
| Kahn, *et al.* [90](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R90) Aug 2021 | Performance of antigen testing for diagnosis of COVID-19: a direct comparison of a lateral flow device to nucleic acid amplification based tests | STANDARD F COVID-19 Ag FIA (SD Biosensor Inc.) | 59\.4 | | 99 | |
| Kessler, *et al.* [91](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R91) Mar 2022 | Identification of contagious SARS-CoV-2 infected individuals by Roche's Rapid Antigen Test | Roche SARS-CoV-2 Rapid Antigen Test (Roche)- Central Lab | | | | |
| Kim, *et al.* [92](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R92) Apr 2021 | Development and clinical evaluation of an immunochromatography-based rapid antigen test (GenBody⢠COVAG025) for COVID-19 diagnosis | GenBody COVAG025 (GenBody) | Not reported | | | |
| GenBody COVAG025 (GenBody) - Prospective | 94 | 87\.4, 97.77 | 100 | 96\.38, 100 | | |
| GenBody COVAG025 (GenBody) - Retrospective | 90 | 73\.47, 97.89 | 98 | 92\.96, 99.76 | | |
| King, *et al.* [93](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R93) Sep 2021 | Validation of the Panbio⢠COVID-19 Antigen Rapid Test (Abbott) to screen for SARS-CoV-2 infection in Sint Maarten: a diagnostic accuracy study | PanBio (Abbott) | 84 | 76\.2, 90.1 | 99\.9 | 99\.6, 100 |
| Kiyasu, *et al.* [94](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R94) Jul 2021 | Prospective analytical performance evaluation of the QuickNaviâ˘-COVID19 Ag for asymptomatic individuals | QuickNavi-COVID19 Ag | 80\.3 | 73\.9, 85.7 | 100 | 99\.7, 100 |
| Klajmon, *et al.* [95](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R95) Dec 2021 | Comparison of antigen tests and qPCR in rapid diagnostics of infections caused by SARS-CoV-2 virus | Humasis COVID-19 Ag Test kit (Humasis Co., Ltd.) | 91\.49 | 79\.62, 97.63 | 97\.9 | 93\.99, 99.57 |
| Klein, *et al.* [96](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R96) May 2021 | Head-to-head performance comparison of self-collected nasal versus professional-collected nasopharyngeal swab for a WHO-listed SARS-CoV-2 antigen-detecting rapid diagnostic test | PanBio (Abbott) - NMT | 84\.4 | 71\.2, 92.3 | 99\.2 | 97\.1, 99.8 |
| PanBio (Abbott) - NP Swab | 88\.9 | 76\.5, 95.5 | 99\.2 | 97\.1, 99.8 | | |
| Kohmer, *et al.* [97](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R97) Jan 2021 | The comparative clinical performance of four SARS-CoV-2 rapid antigen tests and their correlation to infectivity in vitro | SARS-CoV-2 Ag (LumiraDx) | 50 | 38\.1, 61.9 | 100 | 86\.8, 100 |
| NADAL COVID-19 Antigen Rapid Test (New Art Laboratories/nal von minden) | 24\.3 | 15\.1, 35.7 | 100 | 86\.8, 100 | | |
| Rida Quick SARS-CoV-2 (R-Biopharm) | 39\.2 | 28, 51.2 | 96\.2 | 80\.4, 99.9 | | |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 43\.2 | 37\.8, 55.3 | 100 | 86\.8, 100 | | |
| Korenkov, *et al.* [98](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R98) Aug 2021 | Evaluation of a rapid antigen test to detect SARS-CoV-2 infection and identify potentially infectious individuals | STANDARD Q COVID-19 Ag (SD Biosensor) | 100 | 88\.3, 100 | 71\.91 | 61\.82, 80.20 |
| Korenkov, *et al.* [99](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R99) May 2021 | Assessment of SARS-CoV-2 infectivity by a rapid antigen detection test | STANDARD Q COVID-19 Ag (SD Biosensor) | 42\.86 | | | 99\.89 |
| KrĂźger, *et al.* [100](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R100) Aug 2021 | Evaluation of accuracy, exclusivity, limit-of-detection and ease-of-use of LumiraDxâ˘: an antigen-detecting point-of-care device for SARS-CoV-2 | SARS-CoV-2 Ag (LumiraDx) - Berlin | 80\.2 | 70\.3, 87.5 | 99\.5 | 97\.1, 100 |
| SARS-CoV-2 Ag (LumiraDx) - Heidelberg | 84\.6 | 7\.9, 91.4 | 99\.3 | 97\.9, 99.7 | | |
| SARS-CoV-2 Ag (LumiraDx) | 82\.2 | 75\.2, 87.5 | 99\.3 | 97\.9, 99.7 | | |
| KrĂźger, *et al.* [101](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R101) Dec 2021 | Accuracy and ease-of-use of seven point-of-care SARS-CoV-2 antigen-detecting tests: A multi-centre clinical evaluation | Fluorecare (Colloidal Gold/Fluorescent) SARS-CoV-2 Spike Protein Test kit (Shenzen Microprofit) - Germany | 66\.7 | 41\.7, 84.8 | 93\.1 | 91\.0, 94.8 |
| RapiGen (BioCredit) - Brazil | 74\.4 | 65\.8, 81.4 | 98\.9 | 97\.2, 99.6 | | |
| STANDARD F COVID-19 Ag FIA (SD Biosensor Inc.) - Brazil | 77\.5 | 69\.2, 84.1 | 97\.9 | 95\.7, 99 | | |
| NowCheck COVID-19 Ag test (Bionote) - Brazil | 89\.2 | 81\.7, 93.9 | 97\.3 | 94\.8, 98.6 | | |
| RapiGen (BioCredit) - Germany | 52 | 33\.5, 70 | 100 | 99\.7, 100 | | |
| STANDARD Q COVID-19 Ag (SD Biosensor) - Germany | 76\.2 | 68\.0, 82.8 | 99\.3 | 98\.8, 99.6 | | |
| Espline SARS-CoV-2 (Fujirebio) - Germany | 79\.5 | 71\.1, 85.9 | 100 | 99\.4, 100 | | |
| Mologic Covid-19 Rapid Antigen Test (Mologic Ltd. United Kingdom) - Germany | 90\.1 | 85\.1, 93.6 | 100 | 99\.2, 100 | | |
| STANDARD F COVID-19 Ag FIA (SD Biosensor Inc.) | 75\.5 | 68\.2, 81.5 | 97\.2 | 96\.0, 98.1 | | |
| STANDARD Q COVID-19 Ag (SD Biosensor) | 81\.9 | 76\.4, 86.3 | 99 | 98\.5, 99.4 | | |
| RapiGen (BioCredit) | 70\.4 | 62\.4, 77.3 | 99\.7 | 99\.3, 99.9 | | |
| KrĂźger, *et al.* [102](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R102) Dec 2022 | A multi-center clinical diagnostic accuracy study of Surestatus - an affordable, WHO emergency-use-listed, rapid, point-of-care, antigen-detecting diagnostic test for SARS-CoV-2 (preprint) | SureStatus | 82\.4 | 76\.6, 87.1 | 98\.5 | 97\.4, 99.1 |
| KrĂźger, *et al.* [103](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R103) May 2021 | The Abbott PanBio WHO emergency use listed, rapid, antigen-detecting point-of-care diagnostic test for SARS-CoV-2-Evaluation of the accuracy and ease-of-use | PanBio (Abbott) | 86\.8 | 79\.0, 92.0 | 99\.9 | 99\.4, 100 |
| Kurihara, *et al.* [104](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R104) Jul 2021 | The evaluation of a novel digital immunochromatographic assay with silver amplification to detect SARS-CoV-2 | Custom/Novel/In-house | 74\.7 | 64\.0, 83.6 | 99\.8 | 99\.5, 100 |
| PanBio (Abbott) | Not reported | | | | | |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche) | Not reported | | | | | |
| Espline SARS-CoV-2 (Fujirebio) | Not reported | | | | | |
| Kweon, *et al.* [105](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R105) May 2022 | Positivity of rapid antigen testing for SARS-CoV-2 with serial followed-up nasopharyngeal swabs in hospitalized patients due to COVID-19 | STANDARD Q COVID-19 Ag (SD Biosensor) - E gene | 43\.9 | 37\.7, 50.3 | | |
| QuickNavi-COVID19 Ag | Not reported | | | | | |
| STANDARD Q COVID-19 Ag (SD Biosensor) RdRp gene | 43\.9 | 37\.7, 50.3 | | | | |
| Kyritsi, *et al.* [106](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R106) Aug 2021 | Rapid Test Ag 2019-nCoV (PROGNOSIS, BIOTECH, Larissa, Greece); performance evaluation in hospital setting with real time RT-PCR | Rapid Test Ag 2019-nCov (PROGNOSIS, BIOTECH, Greece) | 85\.5 | 79\.1, 90.5 | 99\.8 | 98\.8, 100 |
| Rapid Test Ag 2019-nCoV (PROGNOSIS, BIOTECH, Larissa, Greece); performance evaluation in hospital setting with real time RT-PCR | Rapid Test Ag 2019-nCov (PROGNOSIS, BIOTECH, Greece): 1 part/thousand prevalence | 85\.5 | 79\.1, 90.5 | 99\.8 | 98\.8, 100 | |
| Rapid Test Ag 2019-nCoV (PROGNOSIS, BIOTECH, Larissa, Greece); performance evaluation in hospital setting with real time RT-PCR | Rapid Test Ag 2019-nCov (PROGNOSIS, BIOTECH, Greece): 1 percent prevalence | 85\.5 | 79\.1, 90.5 | 99\.8 | 98\.8, 100 | |
| Rapid Test Ag 2019-nCoV (PROGNOSIS, BIOTECH, Larissa, Greece); performance evaluation in hospital setting with real time RT-PCR | Rapid Test Ag 2019-nCov (PROGNOSIS, BIOTECH, Greece): 5 percent prevalence | 85\.5 | 79\.1, 90.5 | 99\.8 | 98\.8, 100 | |
| Landaverde, *et al.* [107](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R107) Mar 2022 | Comparison of BinaxNOW TM and SARS-CoV-2 qRT-PCR detection of the omicron variant from matched anterior nares swabs (preprint) | BinaxNOW (Abbott) | 53\.9 | | 100 | |
| Layer, *et al.* [108](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R108) Feb 2022 | SARS-CoV-2 screening strategies for returning international travellers: evaluation of a rapid antigen test approach | Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 59 | | 100 | |
| LeGoff, *et al.* [109](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R109) Oct 2021 | Evaluation of a saliva molecular point of care for the detection of SARS-CoV-2 in ambulatory care | EasyCov (SkillCell-Alcen, France) | 34 | 26, 44 | 97 | 96, 98 |
| STANDARD Q COVID-19 Ag (SD Biosensor) | 85 | 77, 91 | 99 | 98, 99 | | |
| Leixner, *et al.* [110](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R110) Jul 2021 | Evaluation of the AMP SARS-CoV-2 rapid antigen test in a hospital setting | AMP Rapid Test SARS-CoV-2 Ag (AMP Diagnostics) | 69\.15 | 58\.8, 78.3 | 99\.66 | 98\.1, 100 |
| Linares, *et al.* [111](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R111) Oct 2020 | Panbio antigen rapid test is reliable to diagnose SARS-CoV-2 infection in the first 7 days after the onset of symptoms | PanBio (Abbott) | 73\.3 | 62\.2, 83.8 | 100 | |
| Lindner, *et al.* [112](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R112) Apr 2021a | Head-to-head comparison of SARS-CoV-2 antigen-detecting rapid test with self-collected nasal swab versus professional-collected nasopharyngeal swab | STANDARD Q COVID-19 Ag (SD Biosensor)-NMT | 74\.4 | 58\.9, 85.4 | 99\.2 | 97\.1, 99.8 |
| STANDARD Q COVID-19 Ag (SD Biosensor)-NP | 79\.5 | 64\.5, 89.2 | 99\.6 | 97\.8, 100 | | |
| Lindner, *et al.* [113](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R113) Apr 2021b | Head-to-head comparison of SARS-CoV-2 antigen-detecting rapid test with professional-collected nasal versus nasopharyngeal swab | STANDARD Q COVID-19 Ag (SD Biosensor)-NMT | 80\.5 | 66\.0, 89.8 | 98\.6 | 94\.9, 99.6 |
| STANDARD Q COVID-19 Ag (SD Biosensor)-NP | 73\.2 | 58\.1, 84.3 | 99\.3 | 96\.0, 100 | | |
| Lindner, *et al.* [114](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R114) May 2021 | Diagnostic accuracy and feasibility of patient self-testing with a SARS-CoV-2 antigen-detecting rapid test | STANDARD Q COVID-19 Ag (SD Biosensor)-Professional | 85 | 70\.9, 92.9 | 99\.1 | 94\.8, 99.5 |
| STANDARD Q COVID-19 Ag (SD Biosensor)-Self testing | 82\.5 | 68\.1, 91.3 | 100 | 96\.5, 100 | | |
| Mandal, *et al.* [115](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R115) May 2022 | Diagnostic performance of SARS-CoV-2 rapid antigen test in relation to RT-PCR CqValue | Espline SARS-CoV-2 (Fujirebio) | 63\.60% | 54\.7, 71.9 | 97\.90 | 93\.6, 99.6 |
| Mane, *et al.* [116](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R116) May 2022 | Diagnostic performance of oral swab specimen for SARS-CoV-2 detection with rapid point-of-care lateral flow antigen test | PathoCatch (Accucare) | Not reported | | | |
| PathoCatch (Accucare) - oral swabs | Not reported | | | | | |
| Maniscalco, *et al.* [117](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R117) Aug 2021 | A rapid antigen detection test to diagnose SARS-CoV-2 infection using exhaled breath condensate by a modified Inflammacheck(ÂŽ) device | Inflammacheck (Exhalation Technology LTD) | 92\.3 | 64\.0, 99.8 | 98\.9 | 94\.1, 100.0 |
| MasiĂĄ, *et al.* [118](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R118) Jan 2021 | Nasopharyngeal Panbio COVID-19 antigen performed at point-of-care has a high sensitivity in symptomatic and asymptomatic patients with higher risk for transmission and older age | PanBio (Abbott) | 68\.1 | | 100 | |
| Mizrahi, *et al.* [119](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R119) Nov 2021 | The Coris BioConcept COVID 19 Ag Respi-Strip, a field experience feedback | Respi-Strip (Coris BioConcept) - Coris-Ag: 30-min reading (n = 294) | 45\.2 | | 100 | |
| Respi-Strip (Coris BioConcept) - Period 1 (n = 158) | 59\.3 | | 100 | | | |
| Respi-Strip (Coris BioConcept) - Period 2 (n = 136) | 20 | | 100 | | | |
| Møller, *et al.* [120](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R120) Jan 2022 | Diagnostic performance, user acceptability, and safety of unsupervised SARS-CoV-2 rapid antigen-detecting tests performed at home | SARS-CoV-2 Antigen Rapid Test (Hangzhou Immuno Biotech Co Ltd, China). | 62\.1 | 50\.1, 72.9 | 100 | 98\.9, 100 |
| COVID-19 Antigen Detection Kit (DNA Diagnostic A/S, Denmark) | 65\.7 | 49\.2, 79.2 | 100 | 99, 100 | | |
| PanBio (Abbott) | Not estimable | | 100 | 95\.6, 100 | | |
| Nagura-Ikeda, *et al.* [121](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R121) Aug 2020 | Clinical evaluation of self-collected saliva by quantitative reverse transcription-PCR (RT-qPCR), direct RT-qPCR, reverse transcriptionâloop-mediated isothermal amplification, and a rapid antigen test to diagnose COVID-19 | Espline SARS-CoV-2 (Fujirebio) | 11\.7 | | | |
| Nikolai, *et al.* [122](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R122) Aug 2021 | Anterior nasal versus nasal mid-turbinate sampling for a SARS-CoV-2 antigen-detecting rapid test: does localisation or professional collection matter? | STANDARD Q COVID-19 Ag (SD Biosensor) - Prof.-sampling: All (N =36), Prof AN | 86\.1 | 71\.3, 93.9 | 100 | 95\.7, 100 |
| STANDARD Q COVID-19 Ag (SD Biosensor) - Self-sampling: All (N=34), Prof. NP | 91\.2 | 77, 97 | 100 | 94\.2, 100 | | |
| STANDARD Q COVID-19 Ag (SD Biosensor) - Self-sampling: All (N=34), Self NMT | 91\.2 | 77\.0, 97 | 98\.4 | 91\.4, 99.9 | | |
| NĂłra, *et al.* [123](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R123) Feb 2022 | Evaluating the field performance of multiple SARS-Cov-2 antigen rapid tests using nasopharyngeal swab samples | PanBio (Abbott) | Not reported | | | |
| CoV2Ag assay (Siemens Healthineers, Eschborn, Germany) | Not reported | | | | | |
| GenBody COVAG025 (GenBody) | Not reported | | | | | |
| GENEDIA W COVID-19 Ag Test (Green Cross Medical Science Corp.) | Not reported | | | | | |
| Humasis COVID-19 Ag Test kit (Humasis Co., Ltd.) | Not reported | | | | | |
| Immupass VivaDiag (VivaChek Biotech) | Not reported | | | | | |
| Helix i-SARS-CoV-2 Ag Rapid Test (Cellex Biotech Co.) | Not reported | | | | | |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche) | Not reported | | | | | |
| Rapid COVID-19 Antigen Test (Healgen Scientific) | Not reported | | | | | |
| Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Antigen Detection Kit (Colloidal Gold-Based) Nanjing Vazyme Medical Technology Co | Not reported | | | | | |
| Okoye, *et al.* [124](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R124) Feb 2022 | Diagnostic accuracy of a rapid diagnostic test for the early detection of COVID-19 | BinaxNOW (Abbott) | 91\.84 | 80\.40, 97.73 | 99\.95 | 99\.81, 99.99 |
| Onsongo, *et al.* [125](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R125) Feb 2022 | Performance of a rapid antigen test for SARS-CoV-2 in Kenya | NowCheck COVID-19 Ag test (Bionote) | Not reported | | | |
| Osmanodja, *et al.* [126](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R126) May 2021 | Accuracy of a novel sars-cov-2 antigen-detecting rapid diagnostic test from standardized self-collected anterior nasal swabs | Custom/Novel/In-house | 88\.6 | 78\.7, 94.9 | 99\.7 | 98\.2, 100 |
| Paap, *et al.* [127](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R127) Jun 2022 | Clinical evaluation of single-swab sampling for rapid COVID-19 detection in outbreak settings in Dutch nursing homes | Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 50\.9 | | 89 | |
| Pandey, *et al.* [128](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R128) Aug 2021 | Comparison of the rapid antigen testing method with RT-qPCR for the diagnosis of COVID-19 | STANDARD Q COVID-19 Ag (SD Biosensor) | 53\.6 | 39\.7, 67.0 | 97\.3 | 94\.6, 98.9 |
| Park, *et al.* [129](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R129) Feb 2022 | Analysis of the efficacy of universal screening of coronavirus disease with antigen-detecting rapid diagnostic tests at point-or-care settings and sharing the experience of admission protocolâa pilot study | STANDARD Q COVID-19 Ag (SD Biosensor) | 68\.3 | | 99\.5 | |
| Peacock, *et al.* [130](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R130) Jan 2022 | Utility of COVID-19 antigen testing in the emergency department | BinaxNOW (Abbott) | 76\.9 | 69\.9, 82.9 | 98\.6 | 97\.2, 99.4 |
| PeĂąa, *et al.* [131](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R131) Apr 2021 | Performance of SARS-CoV-2 rapid antigen test compared with real-time RT-PCR in asymptomatic individuals | STANDARD Q COVID-19 Ag (SD Biosensor) | 69\.86 | 58\.56, 9.18*\[typo in paper\]* | 99\.61 | 98\.86, 99.87 |
| PeĂąa-Rodriguez, *et al.* [132](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R132) Feb 2021 | Performance evaluation of a lateral flow assay for nasopharyngeal antigen detection for SARS-CoV-2 diagnosis | STANDARD Q COVID-19 Ag (SD Biosensor) | 75\.9 | 66\.5, 83.8 | 100 | 98\.6, 100 |
| Peronace, *et al.* [133](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R133) May 2022 | Validation of GeneFinder COVID-19 Ag plus rapid test and its potential utility to slowing infection waves: a single-center laboratory evaluation study | GeneFinder COVID-19 Ag Plus Rapid Test | 96\.03 | 91\.55, 98.53 | 99\.78 | 98\.77, 99.99 |
| Pilarowski, *et al.* [134](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R134) Jan 2021 | Performance characteristics of a rapid SARS-CoV-2 antigen detection assay at a public plaza testing site in San Francisco | BinaxNOW (Abbott) | 57\.7 | 36\.9, 76.6 | 100 | 99\.6, 100 |
| Pollock, *et al.* [135](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R135) Apr 2021 | Performance and implementation evaluation of the Abbott BinaxNOW Rapid Antigen Test in a high-throughput drive-through community testing site in Massachusetts | BinaxNOW (Abbott) | 84\.1 | 77\.4, 89.4 | 99\.6 | 99\.1, 99.9 |
| Poopalasingam, *et al.* [136](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R136) Feb 2022 | Determining the reliability of rapid SARS-CoV-2 antigen detection in fully vaccinated individuals | STANDARD Q COVID-19 Ag (SD Biosensor) | 57\.3 | 46\.1, 67.9 | 99\.7 | 98\.8, 99.9 |
| Prost, *et al.* [137](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R137) Dec 2021 | Evaluation of a rapid in vitro diagnostic test device for detection of SARS-CoV-2 antigen in nasal swabs | SARS-CoV-2 Antigen Rapid Test (Hangzhou Immuno Biotech Co Ltd, China). | 97\.3 | 94\.2, 99.0 | 99\.5 | 97\.3, 100 |
| Rahman, *et al.* [138](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R138) Nov 2021 | Clinical evaluation of SARS-CoV-2 antigen-based rapid diagnostic test kit for detection of COVID-19 cases in Bangladesh | STANDARD Q COVID-19 Ag (SD Biosensor)- Adults | 85\.76 | 81\.25, 89.54 | | |
| Rana, *et al.* [139](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R139) Sept 2021 | Evaluation of the currently used antigen-based rapid diagnostic test for the detection of SARS CoV-2 virus in respiratory specimens | STANDARD Q COVID-19 Ag (SD Biosensor) | 37\.5 | | 99\.79 | |
| Rastawicki, *et al.* [140](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R140) Jan 2021 | Evaluation of PCL rapid point of care antigen test for detection of SARS-CoV-2 in nasopharyngeal swabs | PCL COVID19 Ag Rapid FIA Antigen Test (PCL) | 38\.9 | | 83\.3 | |
| Rohde, *et al.* [142](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R142) Feb 2022 | Diagnostic accuracy and feasibility of a rapid SARS-CoV-2 antigen test in general practice - a prospective multicenter validation and implementation study | Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 78\.3 | 70\.9, 84.6 | 99\.5 | 99, 99.8 |
| Salcedo, *et al.* [143](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R143) Feb 2022 | Comparative Evaluation of Rapid Isothermal Amplification and Antigen Assays for Screening Testing of SARS-CoV-2 | Custom/Novel/In-house | Not reported | | | |
| Salvagno, *et al.* [144](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R144) Jan 2021 | Clinical assessment of the Roche SARS-CoV-2 rapid antigen test | STANDARD Q COVID-19 Ag (SD Biosensor) | 72\.5 | 64\.6, 79.5 | 99\.4 | 96\.8, 100 |
| Salvagno, *et al.* [145](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R145) May 2021 | Real-world assessment of Fluorecare SARS-CoV-2 Spike Protein Test Kit | Fluorecare (Colloidal Gold/Fluorescent) SARS-CoV-2 Spike Protein Test kit (Shenzen Microprofit) | 27\.5 | 21\.8, 33.7 | 99\.2 | 95\.5, 100 |
| Savage, *et al.* [146](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R146) Jun 2022 | A prospective diagnostic evaluation of accuracy of self-taken and healthcare worker-taken swabs for rapid COVID-19 testing | Covios COVID-19 Antigen Rapid Dianostic test-Health-care worker taken swab | 78\.4 | 69\.0, 87.8 | 98\.9 | 97\.3, 100.0 |
| Covios COVID-19 Antigen Rapid Dianostic test-Self-taken swab | 90\.5 | 83\.9, 97.2 | 99\.4 | 98\.3, 100.0 | | |
| Schildgen, *et al.* [147](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R147) Jan 2021 | Limits and opportunities of SARS-CoV-2 antigen rapid tests: an experienced-based perspective | PanBio (Abbott) | 50 | 35, 64 | 77\.4 | 60, 89 |
| RapiGen (BioCredit) | 33\.3 | 21, 48 | 87\.1 | 71, 95 | | |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 88\.1 | 75, 95 | 19\.4 | 9, 36 | | |
| Selvabai, *et al.* [148](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R148) Apr 2022 | Diagnostic Efficacy of COVID-19 Rapid Antigen Detection Card in Diagnosis of SARS-CoV-2 | Athenese-DX COVID-19 RAT kit | 74\.19 | | 100 | |
| Shaw, *et al.* [149](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R149) Jul 2021 | Evaluation of the Abbott Panbio(TM) COVID-19 Ag rapid antigen test for the detection of SARS-CoV-2 in asymptomatic Canadians | PanBio (Abbott) | Not reported | | | |
| Siddiqui, *et al.* [150](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R150) Dec 2021 | Implementation and Accuracy of BinaxNOW Rapid Antigen COVID-19 Test in Asymptomatic and Symptomatic Populations in a High-Volume Self-Referred Testing Site | BinaxNOW (Abbott) | 81 | 75, 86 | 99\.8 | 100\.0, 100.0 |
| Sitoe, *et al.* [151](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R151) Feb 2022 | Performance Evaluation of the STANDARD(TM) Q COVID-19 and Panbio(TM) COVID-19 Antigen Tests in Detecting SARS-CoV-2 during High Transmission Period in Mozambique | PanBio (Abbott) | 41\.3 | 34\.6, 48.4 | 98\.2 | 96\.2, 99.3 |
| STANDARD Q COVID-19 Ag (SD Biosensor) | 45 | 39\.9, 50.2 | 97\.6 | 95\.3, 99.0 | | |
| SkvarÄ[152](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R152) Apr 2022 | Clinical validation of two immunochromatographic SARS-CoV-2 antigen tests in near hospital facilities | Immupass VivaDiag (VivaChek Biotech) | 90\.6 | 84\.94, 94.36 | 100 | 99\.41, 100.0 |
| Alltest Covid19 Ag test | 94\.37 | 89\.20, 97.54 | 100 | 98\.83, 100.0 | | |
| Smith, *et al.* [153](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R153) Jun 2021 | Clinical Evaluation of Sofia Rapid Antigen Assay for Detection of Severe Acute Respiratory Syndrome Coronavirus 2 among Emergency Department to Hospital Admissions | Sofia SARS Rapid Antigen FIA/Sofia 2 (Quidel) | 76\.6 | 71, 82 | 99\.7 | 99\.0, 100 |
| Soleimani, *et al.* [141](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R141) May 2021 | Rapid COVID-19 antigenic tests: usefulness of a modified method for diagnosis | PanBio (Abbott) | 75 | 68\.9, 80.4 | | |
| COVID19-Speed/Biospeedia COVID19 Antigen test (Biospeedia) | 65\.5 | 59\.0, 71.6 | 100 | | | |
| Stohr, *et al.* [154](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R154) May 2022 | Self-testing for the detection of SARS-CoV-2 infection with rapid antigen tests for people with suspected COVID-19 in the community | BD Veritor COVID-19 Rapid Antigen Test (Becton-Dickinson) | 49\.1 | 41\.7, 56.5 | 99\.9 | 99\.7, 100.0 |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 61\.5 | 54\.6, 68.3 | 99\.7 | 99\.4, 99.9 | | |
| Surasi, *et al.* [155](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R155) Nov 2021 | Effectiveness of Abbott BinaxNOW rapid antigen test for detection of SARS-CoV-2 infections in outbreak among horse racetrack workers, California, USA | BinaxNOW (Abbott) | 43\.3 | 34\.6, 52.4 | 100 | 99\.4, 100.0 |
| Suzuki, *et al.* [156](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R156) May 2022 | Analytical performance of rapid antigen tests for the detection of SARS-CoV-2 during widespread circulation of the Omicron variant | QuickNavi-COVID19 Ag | 94\.2 | 91\.6, 96.3 | 99\.5 | 98\.7, 99.9 |
| Suzuki, *et al.* [157](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R157) Jan 2022 | Diagnostic performance of a novel digital immunoassay (RapidTesta SARS-CoV-2): A prospective observational study with nasopharyngeal samples | RapidTesta SARS-CoV-2 | 71\.6 | 59\.9, 81.5 | 99\.2 | 98\.5, 99.7 |
| RapidTesta SARS-CoV-2 | 78\.4 | 67\.3, 87.1 | 97\.6 | 96\.5, 98.5 | | |
| Terpos, *et al.* [158](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R158) May 2021 | Clinical Application of a New SARS-CoV-2 Antigen Detection Kit (Colloidal Gold) in the Detection of COVID-19 | Custom/Novel/In-house | Not reported | | | |
| Thakur, *et al.* [159](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R159) Nov 2021 | Utility of Antigen-Based Rapid Diagnostic Test for Detection of SARS-CoV-2 Virus in Routine Hospital Settings | PathoCatch (Accucare) | 34\.5 | 24\.5, 45.6 | 99\.8 | 99\.1, 100 |
| Thell, *et al.* [160](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R160) Nov 2021 | Evaluation of a novel, rapid antigen detection test for the diagnosis of SARS-CoV-2 | Roche SARS-CoV-2 Rapid Antigen Test (Roche)-Emergency Dept | 77\.9 | 70\.0, 84.6 | 98\.1 | 94\.6, 99.6 |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche)-Primary Health Care | 84\.4 | 74\.4, 91.7 | 100 | 97\.8, 100.0 | | |
| Thirion-Romero, *et al.* [161](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R161) Oct 2021 | Evaluation of Panbio rapid antigen test for SARS-CoV-2 in symptomatic patients and their contacts: a multicenter study | PanBio (Abbott) | 54\.2 | 51\.2, 57.2 | 98\.5 | 97\.7, 99.2 |
| Tonelotto, *et al.* [162](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R162) Jan 2022 | Efficacy of Fluorecare SARS-CoV-2 Spike Protein Test Kit for SARS-CoV-2 detection in nasopharyngeal samples of 121 individuals working in a manufacturing company | Fluorecare (Colloidal Gold/Fluorescent) SARS-CoV-2 Spike Protein Test kit (Shenzen Microprofit) | 84\.6 | 54\.6, 98.1 | 100 | 98\.6, 100.0 |
| Toptan, *et al.* [163](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R163) Feb 2021 | Evaluation of a SARS-CoV-2 rapid antigen test: potential to help reduce community spread? | Rida Quick SARS-CoV-2 (R-Biopharm)-Berlin | 77\.6 | | 100 | |
| Rida Quick SARS-CoV-2 (R-Biopharm)-Frankfurt | 50 | | 100 | | | |
| Trobajo-SanmartĂn, *et al.* [164](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R164) Mar 2021 | Evaluation of the rapid antigen test CerTest SARS-CoV-2 as an alternative COVID-19 diagnosis technique | CerTest SARS-CoV-2 (Certest Biotech) | 78\.75 | 67\.89, 86.79 | 100 | 97\.08, 99.94 |
| Turcato, *et al.* [165](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R165) Mar 2021 | Clinical application of a rapid antigen test for the detection of SARS-CoV-2 infection in symptomatic and asymptomatic patients evaluated in the emergency department: a preliminary report | Standard Q COVID-19 Ag (SD Biosensor) | 80\.3 | 74\.9, 85.4 | 99\.1 | 98\.6, 99.3 |
| Turcato, *et al.* [166](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R166) Jan 2022 | Rapid antigen test to identify COVID-19 infected patients with and without symptoms admitted to the emergency department | Standard Q COVID-19 Ag (SD Biosensor) | 82\.9 | 81\.0, 84.8 | 99\.1 | 98\.8, 99.3 |
| Van der Moeren, *et al.* [167](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R167) May 2021 | Evaluation of the test accuracy of a SARS-CoV-2 rapid antigen test in symptomatic community dwelling individuals in the Netherlands | BD Veritor COVID-19 Rapid Antigen Test (Becton-Dickinson) | 94\.1 | 71\.1, 100 | 100 | 98\.9, 100 |
| BD Veritor COVID-19 Rapid Antigen Test (Becton-Dickinson)-Visual | 94\.1 | 71\.1, 100 | 100 | 98\.9, 100 | | |
| Van Honacker, *et al.* [168](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R168) Aug 2021 | Comparison of five SARS-CoV-2 rapid antigen tests in a hospital setting and performance of one antigen assay in routine practice. A useful tool to guide isolation precautions? | Standard Q COVID-19 Ag (SD Biosensor) | 54\.2 | | 99\.7 | |
| von Ahnen, *et al.* [169](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R169) Mar 2022 | Evaluation of a rapid-antigen test for COVID-19 in an asymptomatic collective: a prospective study | Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 92\.3 | 78\.0, 100 | 100 | 100\.0, 100.0 |
| Wertenauer, *et al.* [170](https://pmc.ncbi.nlm.nih.gov/articles/PMC11462910/#R170) Mar 2022 | Diagnostic performance of rapid antigen testing for SARS-CoV-2: the COVid-19 AntiGen (COVAG) study | PanBio (Abbott) | 56\.8 | | 99\.9 | |
| Roche SARS-CoV-2 Rapid Antigen Test (Roche) | 60\.4 | | 99\.7 | | | |
## Appendix IV: Rapid antigen tests from included studies
| | Name | Company | Study count | Reported 100% sensitivity in at least 1 study | Reported 100% specificity in at least 1 study | Reported 100% positive predictive value in at least 1 study | Reported 100% negative predictive value in at least 1 study |
|---|---|---|---|---|---|---|---|
| 1 | STANDARD Q COVID-19 Ag Test | SD Biosensor Inc. | 28 | X | X | X | X |
| 2 | PanBio COVID-19 Ag Rapid Test Device | Abbott | 14 | | X | X | |
| 3 | SARS-CoV-2 Rapid Antigen Test | Roche Diagnostics | 11 | | X | X | |
| 4 | BinaxNOW COVID-19 Antigen | Abbott | 10 | | X | X | |
| 5 | Rapid Test Ag 2019-nCov | ProGnosis Biotech | 4 | | | | |
| 6 | SARS-CoV-2 Ag | LumiraDx | 3 | | X | | |
| 7 | Custom/Novel/In-house | N/A | 3 | | | | |
| 8 | COVISTIX (COVIDMARK) Covid 19 Antigen Rapid Test Device | Sorrento Therapeutics | 3 | | | | |
| 9 | AMP Rapid Test SARS-CoV-2 Ag | AMP Diagnostics | 2 | | X | X | |
| 10 | BD Veritor COVID-19 Rapid Antigen Test | Becton-Dickinson | 2 | | X | X | |
| 11 | CerTest SARS-CoV-2 | Certest Biotec | 2 | | X | X | |
| 12 | Espline SARS-CoV-2 | Fujirebio | 2 | | X | X | |
| 13 | SARS-CoV-2 Antigen Rapid Test | Hangzhou Immuno Biotech Co Ltd | 2 | | X | | |
| 14 | HUMASIS COVID-19 Ag Test | Humasis Co., Ltd | 2 | | | | |
| 15 | Mologic Covid-19 Rapid Antigen Test | Mologic Ltd. United Kingdom | 2 | | X | X | |
| 16 | NADAL COVID-19 Ag Rapid Test | New Art Laboratories/nal von minden | 2 | | X | X | |
| 17 | Quick Navi-COVID 19 Ag | Otsuka Pharmaceutical Co., Ltd. | 2 | | X | | |
| 18 | PCL COVID19 Ag Rapid FIA Antigen Test | PCL, Inc. | 2 | | | | |
| 19 | Sofia SARS Rapid Antigen FIA/Sofia 2 | Quidel | 2 | | X | X | |
| 20 | BIOCREDIT COVID-19 Ag | RapiGen, Inc. | 2 | | X | X | |
| 21 | Rida Quick SARS-CoV-2 Antigen Test | R-Biopharm AG | 2 | | X | X | |
| 22 | STANDARD F COVID-19 Ag FIA | SD Biosensor Inc | 2 | | | | |
| 23 | RapidTesta SARS-CoV-2 | Sekisui Medical Co., Ltd | 2 | | | | |
| 24 | Fluorecare SARS-CoV-2 Spike Protein Test kit (Colloidal Gold) | Shenzen Microprofit Biotech Co., Ltd. | 2 | | X | X | |
| 25 | CLINITEST Rapid COVID-19 Antigen Test | Siemens Healthineers | 2 | | | | |
| 26 | Immupass VivaDiag | VivaChek Biotech | 2 | | X | | |
| 27 | COVID-VIRO COVID-19 Ag Rapid Test | AAZ | 1 | | X | X | |
| 28 | Flowflex COVID-19 Antigen test | ACON Labs | 1 | X | X | X | X |
| 29 | COVID-19 Antigen Rapid Test | Acro Biotech, Inc. | 1 | | | | |
| 30 | Alltest COVID-19 ART Antigen Rapid Test | ALLTEST | 1 | | X | | |
| 31 | COVID-19 Antigen Rapid Test | Assut Europe | 1 | | X | X | |
| 32 | COVID-19 RAT kit | Athenese-DX | 1 | | X | X | |
| 33 | NowCheck COVID-19 Ag test | Bionote | 1 | | | | |
| 34 | Novel Corona Virus (SARS-CoV-2) Ag Rapid Test kit | Bioperfectus | 1 | | X | X | |
| 35 | Covid-19 AG BSS | BIOSYNEX | 1 | | | | |
| 36 | Helix i-SARS-CoV-2 Ag Rapid Test | Cellex Biotech Co | 1 | | | | |
| 37 | COVID-19 Ag K-SeT | Coris Bioconcept | 1 | | | | |
| 38 | Liaison SARS-CoV-2 Ag | DiaSorin | 1 | | | | |
| 39 | COVID-19 Antigen Detection | DNA Diagnostic A/S | 1 | | X | | |
| 40 | COVID-19 Ag ECO Teste | Eco Diagnostica | 1 | | | | |
| 41 | Inflammacheck CoronaCheck | Exhalation Technology LTD | 1 | | | | |
| 42 | GenBody COVAG025 | GenBody | 1 | | | | |
| 43 | GENEDIA W COVID-19 Ag Test | Green Cross Medical Science Corp | 1 | | | | |
| 44 | Rapid COVID-19 Antigen Test | Healgen Scientific | 1 | | | | |
| 45 | Innova SARS-CoV-2 Antigen Rapid test | Innova Medical Group | 1 | | | | |
| 46 | Accucare PathoCatch Covid-19 Ag Detection Kit | Mylab | 1 | | | | |
| 47 | Orient Gene Rapid Covid-19 (Antigen) Self-Test | Orient Gene | 1 | | X | X | |
| 48 | GeneFinder COVID-19 Ag Plus Rapid Test | OSANG Healthcare | 1 | | | | |
| 49 | Green Spring SARS-CoV-2 Antigen Rapid Test Kit (Colloidal Gold) | Shenzhen Lvshiyuan Biotechnology | 1 | | X | X | |
| 50 | Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Antigen Detection Kit (Colloidal Gold-Based) | Vazyme Medical Technology Co | 1 | | | | |
| 51 | 2019-nCoV Antigen Test | Wondfo | 1 | | | | |
## Footnotes
The authors declare no conflicts of interest.
Supplemental digital content is available for this article. Direct URL citations are provided in the HTML and PDF versions of this article on the journalâs website, [www.jbievidencesynthesis.com](http://www.jbievidencesynthesis.com/).
## Contributor Information
Ellyn Hirabayashi, Email: ehirabay@student.touro.edu.
Guadalupe Mercado, Email: gmercado3@student.touro.edu.
Brandi Hull, Email: bhull@student.touro.edu.
Sabrina Soin, Email: ssoin@student.touro.edu.
Sherli Koshy-Chenthittayil, Email: skoshy-c@touro.edu.
Sarina Raman, Email: sraman@student.touro.edu.
Timothy Huang, Email: thuang@student.touro.edu.
Chathushya Keerthisinghe, Email: ckeerthi@student.touro.edu.
Shelby Feliciano, Email: felicish@ohsu.edu.
Andrew Dongo, Email: adongo@student.touro.edu.
James Kal, Email: jkal@student.touro.edu.
Azliyati Azizan, Email: aazizan@touro.edu.
Karen Duus, Email: kduus@touro.edu.
Terry Else, Email: elseterryann@gmail.com.
Megan DeArmond, Email: mde\_armo@touro.edu.
Amy E.L. Stone, Email: amy.stone@unlv.edu.
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| Shard | 129 (laksa) |
| Root Hash | 7295144728021232729 |
| Unparsed URL | gov,nih!nlm,ncbi,pmc,/articles/PMC11462910/ s443 |