🕷️ Crawler Inspector

URL Lookup

Direct Parameter Lookup

Raw Queries and Responses

1. Shard Calculation

Query:

Response:

Calculated Shard: 18 (from laksa058)

2. Crawled Status Check

Query:

curl -X POST \
  'http://laksa018.int.ahrefs:8124/' \
  -H 'Content-Type: text/plain' \
  -H 'X-ClickHouse-Database: crawler3' \
  -H 'Authorization: Basic YXBpOg==' \
  -d 'SELECT getAhrefsURLFromUnparsed(src_unparsed) AS found_url, ifNull(toUnixTimestamp(download_stamp), 0) AS crawl_time, ifNull(toUnixTimestamp(props_url_first_seen), 0) AS first_indexed_time, download_http_code AS http_code, src_unparsed AS src_unparsed, src_root_hash AS src_root_hash, history_drop_reason AS history_drop_reason, meta_title AS meta_title, meta_descriptions AS meta_descriptions, attrs_boilerpipe_text AS attrs_boilerpipe_text, attrs_markdown AS attrs_markdown, attrs_readable_markdown AS attrs_readable_markdown, meta_canonical AS meta_canonical FROM crawler3.page_info_local FINAL PREWHERE (src_root_hash, src_unparsed) IN ((getAhrefsRootHashFromUnparsed(getAhrefsUnparsedNoserviceFromURL(\'https://www.hdruk.ac.uk/projects/false-positives/\')), getAhrefsUnparsedNoserviceFromURL(\'https://www.hdruk.ac.uk/projects/false-positives/\'))) FORMAT JSONEachRow'

Response:

{"found_url":"https:\/\/www.hdruk.ac.uk\/projects\/false-positives\/","crawl_time":1775486367,"first_indexed_time":1597879819,"http_code":200,"src_unparsed":"uk,ac,hdruk!www,\/projects\/false-positives\/ s443","src_root_hash":"6210257791817433618","history_drop_reason":null,"meta_title":"False Positive Tests - HDR UK","meta_descriptions":["\"False positives\" have been an issue since testing for COVID-19 pandemic began. As the volume of tests has significantly increased, it has become even more relevant."],"attrs_boilerpipe_text":"This webpage was created in August 2020.\nWhat is the issue?\nIncreasing numbers of prominent scientists and politicians have called for widespread testing for SARS-CoV-2 coronavirus (Covid-19) infection in populations where only a very small proportion of people currently have active infection, with or without obvious symptoms.\nBut,\nno diagnostic test is perfect in the real world\n, however well it may perform in controlled laboratory settings. Science and media coverage has so far paid a great deal of attention to the problem of\nfalse negative tests\n, where people infected with the virus have a negative test result when they should test positive. By contrast, there has been much less discussion about the problem of\nfalse positive tests\n, where people who do not have infection receive a positive test result when it should be negative.\nAs active viral infection becomes less and less common in any population, the problem of false positive tests increases, even with the best tests.\nEven with an almost perfect test, the lower the prevalence of infection, the higher will be the proportion of false positive results among all the positive results\n. This is really important for countries where the percentage of individuals in the community who are actively infected is currently very low, for example the UK, where <0.1% had active infection in early August 2020, according to the Office for National Statistics infection survey.\nExplore and understand this issue with our interactive tool\nWe have produced a simple, transparent,\ninteractive tool\nto help policy makers, the scientific community, health professionals, journalists and the public understand the problem of incorrect test results, especially false positives. It demonstrates how this problem may be addressed by doing confirmatory tests in people who are at very low risk of actually being infected and whose first test returns a positive result.\nAs an example, with an infection prevalence\n1\nof 0.05% or 1 in 2,000 (the average community prevalence in the UK in early August) and very optimistic test performance measures (sensitivity\n2\nof 80% and specificity\n3\n99.9%), the chance of a positive result being truly positive will be only 29% with one test. This increases to almost 100% if a second test is also positive. However, the percentage of positive results that are truly positive can fall to unacceptably low levels when infection is very uncommon in the population and test specificity is less than excellent.\nWe conclude that the crucial roles of extremely high test specificity and of confirmatory testing must be fully appreciated and incorporated into policy decisions to avoid unnecessary restrictions for whole populations, and for particular individuals, arising from widespread population testing for SARS-CoV-2 infection.\nThe tool was developed by Professor Cathie Sudlow, Director of the BHF Data Science Centre. Please\nclick here\nif you would like to use the tool to explore different scenarios yourself.\nFind out more about the\nBHF Data Science Centre\n.\nFootnotes\nInfection prevalence means the percentage of people currently infected with the virus in the population from which the individuals being tested are drawn.\nTest sensitivity means the percentage of all truly infected cases that will be correctly detected by the test.\nTest specificity means the percentage of all truly non-infected cases that will be correctly ruled out by test.\nFind out more about the BHF Data Science Centre\nAt HDR UK, we are committed to involving patients and members of the public to help influence and shape our work. If you are interested in the safe access and use of health data, sign up to HDR UK Voices to learn more about opportunities to get involved.\nSign up to HDR UK Voices\nHead over to our\nHealth Data Innovation Gateway\nto explore datasets, tools, papers and related resources used in health research across the UK.\nExplore our National Core Studies collection on the Gateway\nSubscribe to HIVE\n, our e-newsletter, to keep updated on our work and other matters related to health data science.\nFind out how we are championing the use of health data to respond to COVID-19","attrs_markdown":"[Skip to content](https:\/\/www.hdruk.ac.uk\/projects\/false-positives\/#content \"Skip to content\")\n\n[![HDR UK](https:\/\/www.hdruk.ac.uk\/wp-content\/themes\/hdruk\/assets\/img\/logo.svg)](https:\/\/www.hdruk.ac.uk\/)\n\n- [Visit the Gateway](https:\/\/healthdatagateway.org\/)\n- [Visit the Alliance](https:\/\/ukhealthdata.org\/)\n- [Visit HDR UK Futures](http:\/\/hdruklearn.org\/)\n\nFollow us on social media\n\n- [About](https:\/\/www.hdruk.ac.uk\/about-us\/)\n  - [What We Do](https:\/\/www.hdruk.ac.uk\/about-us\/what-we-do\/)\n  - [Who We Are](https:\/\/www.hdruk.ac.uk\/about-us\/who-we-are\/)\n  - [Quinquennial Review](https:\/\/www.hdruk.ac.uk\/quinquennial-review\/)\n  - [HDR UK Annual Prizes](https:\/\/www.hdruk.ac.uk\/hdr-uk-annual-prizes\/)\n  - [Our Policies](https:\/\/www.hdruk.ac.uk\/about-us\/policies\/)\n  - [Working with industry](https:\/\/www.hdruk.ac.uk\/about-us\/our-strategy\/working-with-industry\/)\n  - [Our Strategy](https:\/\/www.hdruk.ac.uk\/about-us\/our-strategy\/)\n  - [Our Annual Reports](https:\/\/www.hdruk.ac.uk\/about-us\/our-strategy\/annual-reports\/)\n  - [Impact Report](https:\/\/www.hdruk.ac.uk\/about-us\/impact-report\/)\n  - [Health Data Research UK Conference](https:\/\/www.hdruk.ac.uk\/about\/hdr-uk-conference\/)\n  - [Our Patient and Public Involvement and Engagement Strategy](https:\/\/www.hdruk.ac.uk\/about-us\/our-patient-and-public-involvement-and-engagement-strategy\/)\n  - [Involving and engaging patients and the public](https:\/\/www.hdruk.ac.uk\/about-us\/involving-and-engaging-patients-and-the-public\/)\n  - 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[BHF Data Science Centre](https:\/\/www.hdruk.ac.uk\/helping-with-health-data\/bhf-data-science-centre\/)\n  - [Data Saves Lives: Mental Health](https:\/\/www.hdruk.ac.uk\/helping-with-health-data\/data-saves-lives-mental-health\/)\n  - [HDR Global](https:\/\/www.hdruk.ac.uk\/helping-with-health-data\/hdr-global\/)\n  - [Health Data Research Hubs](https:\/\/www.hdruk.ac.uk\/helping-with-health-data\/health-data-research-hubs\/)\n  - [Population Research UK](https:\/\/www.hdruk.ac.uk\/helping-with-health-data\/population-research-uk\/)\n  - [The Sudlow Review](https:\/\/www.hdruk.ac.uk\/helping-with-health-data\/the-sudlow-review\/)\n- [Study and Train](https:\/\/www.hdruk.ac.uk\/study-and-train\/)\n  - [Study](https:\/\/www.hdruk.ac.uk\/study-and-train\/study\/)\n  - [Train](https:\/\/www.hdruk.ac.uk\/study-and-train\/train\/)\n  - [About the Training Team](https:\/\/www.hdruk.ac.uk\/study-and-train\/about-the-training-team\/)\n  - [Health Data Science Black Internship Programme](https:\/\/www.hdruk.ac.uk\/study-and-train\/health-data-science-black-internship-programme\/)\n- [News, Opinion and Events](https:\/\/www.hdruk.ac.uk\/news-opinion-events\/)\n  - [News](https:\/\/www.hdruk.ac.uk\/news-opinion-events\/news\/)\n  - [Opinion](https:\/\/www.hdruk.ac.uk\/news-opinion-events\/opinion\/)\n  - [Events](https:\/\/www.hdruk.ac.uk\/news-opinion-events\/events\/)\n\n- [Visit the Gateway](https:\/\/healthdatagateway.org\/)\n- [Visit the Alliance](https:\/\/ukhealthdata.org\/)\n- [Visit HDR UK Futures](http:\/\/hdruklearn.org\/)\n\nFollow us on social media\n\n1. [Home](https:\/\/www.hdruk.ac.uk\/)  \\|\n2. [Projects](https:\/\/www.hdruk.ac.uk\/research\/projects\/)\n\nProject\n\n# False Positive Tests\n\"False positives\" have been an issue since testing for COVID-19 pandemic began. As the volume of tests has significantly increased, it has become even more relevant. Find out more in this piece by Professor Cathie Sudlow, Director of the British Heart Foundation Data Science Centre; and check out our interactive tool developed to address the issue.\n\n![](https:\/\/www.hdruk.ac.uk\/wp-content\/uploads\/2021\/04\/COVID_tests.jpg)\n\nShare this page\n\n**This webpage was created in August 2020.**\n\n## What is the issue?\nIncreasing numbers of prominent scientists and politicians have called for widespread testing for SARS-CoV-2 coronavirus (Covid-19) infection in populations where only a very small proportion of people currently have active infection, with or without obvious symptoms.\n\nBut, **no diagnostic test is perfect in the real world**, however well it may perform in controlled laboratory settings. Science and media coverage has so far paid a great deal of attention to the problem of **false negative tests**, where people infected with the virus have a negative test result when they should test positive. By contrast, there has been much less discussion about the problem of **false positive tests**, where people who do not have infection receive a positive test result when it should be negative.\n\nAs active viral infection becomes less and less common in any population, the problem of false positive tests increases, even with the best tests. **Even with an almost perfect test, the lower the prevalence of infection, the higher will be the proportion of false positive results among all the positive results**. This is really important for countries where the percentage of individuals in the community who are actively infected is currently very low, for example the UK, where \\<0.1% had active infection in early August 2020, according to the Office for National Statistics infection survey.\n\n## Explore and understand this issue with our interactive tool\nWe have produced a simple, transparent, [interactive tool](https:\/\/www.hdruk.ac.uk\/wp-content\/uploads\/2020\/08\/200820-coronavirus-infection-testing-app.xlsx) to help policy makers, the scientific community, health professionals, journalists and the public understand the problem of incorrect test results, especially false positives. It demonstrates how this problem may be addressed by doing confirmatory tests in people who are at very low risk of actually being infected and whose first test returns a positive result.\n\nAs an example, with an infection prevalence1 of 0.05% or 1 in 2,000 (the average community prevalence in the UK in early August) and very optimistic test performance measures (sensitivity2 of 80% and specificity3 99.9%), the chance of a positive result being truly positive will be only 29% with one test. This increases to almost 100% if a second test is also positive. However, the percentage of positive results that are truly positive can fall to unacceptably low levels when infection is very uncommon in the population and test specificity is less than excellent.\n\nWe conclude that the crucial roles of extremely high test specificity and of confirmatory testing must be fully appreciated and incorporated into policy decisions to avoid unnecessary restrictions for whole populations, and for particular individuals, arising from widespread population testing for SARS-CoV-2 infection.\n\nThe tool was developed by Professor Cathie Sudlow, Director of the BHF Data Science Centre. Please [click here](https:\/\/www.hdruk.ac.uk\/wp-content\/uploads\/2020\/08\/200820-coronavirus-infection-testing-app.xlsx) if you would like to use the tool to explore different scenarios yourself.  \n Find out more about the [BHF Data Science Centre](https:\/\/www.hdruk.ac.uk\/help-with-your-data\/bhf-data-science-centre\/).\n\n#### *Footnotes*\n1. *Infection prevalence means the percentage of people currently infected with the virus in the population from which the individuals being tested are drawn.*\n2. *Test sensitivity means the percentage of all truly infected cases that will be correctly detected by the test.*\n3. *Test specificity means the percentage of all truly non-infected cases that will be correctly ruled out by test.*\n\n[Find out more about the BHF Data Science Centre](https:\/\/www.hdruk.ac.uk\/helping-with-health-data\/bhf-data-science-centre\/)\n\nAt HDR UK, we are committed to involving patients and members of the public to help influence and shape our work. If you are interested in the safe access and use of health data, sign up to HDR UK Voices to learn more about opportunities to get involved.\n\n[Sign up to HDR UK Voices](https:\/\/www.hdruk.ac.uk\/what-is-health-data-research\/patient-and-public-involvement-and-engagement\/join-hdr-uk-voices\/hdr-uk-voices-sign-up\/)\n\nHead over to our [Health Data Innovation Gateway](https:\/\/www.healthdatagateway.org\/) to explore datasets, tools, papers and related resources used in health research across the UK.\n\n[Explore our National Core Studies collection on the Gateway](https:\/\/www.healthdatagateway.org\/collectioncategories\/national-core-studies)\n\n[Subscribe to HIVE](https:\/\/www.hdruk.ac.uk\/subscribe\/), our e-newsletter, to keep updated on our work and other matters related to health data science.\n\n[Find out how we are championing the use of health data to respond to COVID-19](https:\/\/www.hdruk.ac.uk\/covid-19\/)\n\nAreas of work\n\n[Science](https:\/\/www.hdruk.ac.uk\/search\/?_areas_of_work=science)\n\nScientific priorities\n\n[COVID-19](https:\/\/www.hdruk.ac.uk\/search\/?_research_priorities=covid-19)\n\nHealth priorities\n\n[COVID-19](https:\/\/www.hdruk.ac.uk\/search\/?_health_priorities=covid-19)\n\nSelected work\n\n[![](https:\/\/www.hdruk.ac.uk\/wp-content\/uploads\/2021\/12\/shutterstock_1789303814.jpg) News Story COVID-19 vaccine protects people of all body weights from hospitalisation and death, study of 9 million adults in England suggests 1 July 2022 Largest study of body mass index (BMI) and COVID-19 vaccine effectiveness using the QResearch platform suggests two doses are highly effective against severe disease for people who are...](https:\/\/www.hdruk.ac.uk\/news\/covid-19-vaccine-protects-people-of-all-body-weights-from-hospitalisation-and-death-study-of-9-million-adults-in-england-suggests\/)\n\n[![COVID-19 health data research](https:\/\/www.hdruk.ac.uk\/wp-content\/uploads\/2020\/10\/Gateway-COVID-2.jpg) News Most comprehensive analysis of COVID-19 data reveals previously unattributed deaths 9 June 2022 Study published in The Lancet Digital Health and supported by the BHF Data Science Centre used health data from 57 million people in England to build the most complete picture of the pandemic in a...](https:\/\/www.hdruk.ac.uk\/news\/most-comprehensive-analysis-of-covid-19-data-reveals-previously-unattributed-deaths\/)\n\n[![](https:\/\/www.hdruk.ac.uk\/wp-content\/uploads\/2021\/02\/covid_smaller.jpg) News COVID-19 variant Omicron is usually milder than Delta but also more likely to break through immune protection 25 April 2022 New paper from EAVE II team uses linked GP, hospital and lab data to analyse severity of omicron variant and effectiveness of vaccine boosters against symptomatic disease in Scotland](https:\/\/www.ed.ac.uk\/usher\/eave-ii\/key-outputs\/our-publications\/omicron-booster-effectiveness-symptomatic-disease)\n\n## Our funders\n[![Medical Research Council logo](https:\/\/www.hdruk.ac.uk\/wp-content\/uploads\/2020\/09\/ukri_mrcc.jpg)](https:\/\/www.ukri.org\/councils\/mrc\/)   [![NIHR National Institute for Health Research logo](https:\/\/www.hdruk.ac.uk\/wp-content\/uploads\/2020\/06\/nihr.jpg)](https:\/\/www.nihr.ac.uk\/)   [![British Heart Foundation logo](https:\/\/www.hdruk.ac.uk\/wp-content\/uploads\/2020\/06\/bhflogo.jpg)](https:\/\/www.bhf.org.uk\/)   [![Cancer Research UK logo](https:\/\/www.hdruk.ac.uk\/wp-content\/uploads\/2023\/09\/CRUK_logo-light-background-primary-RGB-300x145.jpg)](https:\/\/www.cancerresearchuk.org\/)   [![Economic and Social Research Council logo](https:\/\/www.hdruk.ac.uk\/wp-content\/uploads\/2020\/06\/esrc.jpg)](https:\/\/www.ukri.org\/councils\/esrc\/)   [![Engineering and Physical Sciences Research Council logo](https:\/\/www.hdruk.ac.uk\/wp-content\/uploads\/2020\/06\/epsrc2.jpg)](https:\/\/www.ukri.org\/councils\/epsrc\/)   [![Health and Care Research Wales logo](https:\/\/www.hdruk.ac.uk\/wp-content\/uploads\/2020\/06\/hscwales.jpg)](https:\/\/healthandcareresearchwales.org\/)   [![Chief Scientist Office logo](https:\/\/www.hdruk.ac.uk\/wp-content\/uploads\/2020\/06\/cso_logo.jpg)](https:\/\/www.cso.scot.nhs.uk\/)   [![HSC Public Health Agency Research and Development logo](https:\/\/www.hdruk.ac.uk\/wp-content\/uploads\/2020\/06\/hsc_rd_ni.jpg)](https:\/\/www.publichealth.hscni.net\/)\n\n[![HDR UK](https:\/\/www.hdruk.ac.uk\/wp-content\/themes\/hdruk\/assets\/img\/logo.svg)](https:\/\/www.hdruk.ac.uk\/)\n\nFollow us on social media\n\n- [Contact us](https:\/\/www.hdruk.ac.uk\/about-us\/contact-us\/)\n- [Subscribe to our mailing list](https:\/\/www.hdruk.ac.uk\/subscribe\/)\n- [Register of Interests](https:\/\/www.hdruk.ac.uk\/wp-content\/uploads\/2023\/04\/251027-Register-of-Interests-Board-and-SLT.pdf)\n- [Frequently Asked Questions](https:\/\/www.hdruk.ac.uk\/about-us\/what-is-health-data-research\/your-questions-answered\/)\n- [Job Vacancies](https:\/\/www.hdruk.ac.uk\/jobs\/)\n\n- [Terms and Conditions](https:\/\/www.hdruk.ac.uk\/terms-and-conditions\/)\n- [Privacy Policy](https:\/\/www.hdruk.ac.uk\/privacy-policy\/)\n- [Cookies](https:\/\/www.hdruk.ac.uk\/terms-and-conditions\/cookies\/)\n- [Registered charity number 1194431](https:\/\/www.hdruk.ac.uk\/about-us\/)\n\n©HDR UK 2026. All rights reserved. \\| Design and development by [Soapbox](https:\/\/www.designbysoapbox.com\/)","attrs_readable_markdown":"**This webpage was created in August 2020.**\n\n## What is the issue?\nIncreasing numbers of prominent scientists and politicians have called for widespread testing for SARS-CoV-2 coronavirus (Covid-19) infection in populations where only a very small proportion of people currently have active infection, with or without obvious symptoms.\n\nBut, **no diagnostic test is perfect in the real world**, however well it may perform in controlled laboratory settings. Science and media coverage has so far paid a great deal of attention to the problem of **false negative tests**, where people infected with the virus have a negative test result when they should test positive. By contrast, there has been much less discussion about the problem of **false positive tests**, where people who do not have infection receive a positive test result when it should be negative.\n\nAs active viral infection becomes less and less common in any population, the problem of false positive tests increases, even with the best tests. **Even with an almost perfect test, the lower the prevalence of infection, the higher will be the proportion of false positive results among all the positive results**. This is really important for countries where the percentage of individuals in the community who are actively infected is currently very low, for example the UK, where \\<0.1% had active infection in early August 2020, according to the Office for National Statistics infection survey.\n\n## Explore and understand this issue with our interactive tool\nWe have produced a simple, transparent, [interactive tool](https:\/\/www.hdruk.ac.uk\/wp-content\/uploads\/2020\/08\/200820-coronavirus-infection-testing-app.xlsx) to help policy makers, the scientific community, health professionals, journalists and the public understand the problem of incorrect test results, especially false positives. It demonstrates how this problem may be addressed by doing confirmatory tests in people who are at very low risk of actually being infected and whose first test returns a positive result.\n\nAs an example, with an infection prevalence1 of 0.05% or 1 in 2,000 (the average community prevalence in the UK in early August) and very optimistic test performance measures (sensitivity2 of 80% and specificity3 99.9%), the chance of a positive result being truly positive will be only 29% with one test. This increases to almost 100% if a second test is also positive. However, the percentage of positive results that are truly positive can fall to unacceptably low levels when infection is very uncommon in the population and test specificity is less than excellent.\n\nWe conclude that the crucial roles of extremely high test specificity and of confirmatory testing must be fully appreciated and incorporated into policy decisions to avoid unnecessary restrictions for whole populations, and for particular individuals, arising from widespread population testing for SARS-CoV-2 infection.\n\nThe tool was developed by Professor Cathie Sudlow, Director of the BHF Data Science Centre. Please [click here](https:\/\/www.hdruk.ac.uk\/wp-content\/uploads\/2020\/08\/200820-coronavirus-infection-testing-app.xlsx) if you would like to use the tool to explore different scenarios yourself.  \n Find out more about the [BHF Data Science Centre](https:\/\/www.hdruk.ac.uk\/help-with-your-data\/bhf-data-science-centre\/).\n\n#### *Footnotes*\n1. *Infection prevalence means the percentage of people currently infected with the virus in the population from which the individuals being tested are drawn.*\n2. *Test sensitivity means the percentage of all truly infected cases that will be correctly detected by the test.*\n3. *Test specificity means the percentage of all truly non-infected cases that will be correctly ruled out by test.*\n\n[Find out more about the BHF Data Science Centre](https:\/\/www.hdruk.ac.uk\/helping-with-health-data\/bhf-data-science-centre\/)\n\nAt HDR UK, we are committed to involving patients and members of the public to help influence and shape our work. If you are interested in the safe access and use of health data, sign up to HDR UK Voices to learn more about opportunities to get involved.\n\n[Sign up to HDR UK Voices](https:\/\/www.hdruk.ac.uk\/what-is-health-data-research\/patient-and-public-involvement-and-engagement\/join-hdr-uk-voices\/hdr-uk-voices-sign-up\/)\n\nHead over to our [Health Data Innovation Gateway](https:\/\/www.healthdatagateway.org\/) to explore datasets, tools, papers and related resources used in health research across the UK.\n\n[Explore our National Core Studies collection on the Gateway](https:\/\/www.healthdatagateway.org\/collectioncategories\/national-core-studies)\n\n[Subscribe to HIVE](https:\/\/www.hdruk.ac.uk\/subscribe\/), our e-newsletter, to keep updated on our work and other matters related to health data science.\n\n[Find out how we are championing the use of health data to respond to COVID-19](https:\/\/www.hdruk.ac.uk\/covid-19\/)","meta_canonical":null}

3. Robots.txt Check

Query:

Response:

4. Spam/Ban Check

Query:

Response:

5. Seen Status Check

ℹ️ Skipped - page is already crawled

📄

INDEXABLE

✅

CRAWLED

4 days ago

🤖

ROBOTS ALLOWED

Page Info Filters

Filter	Status	Condition	Details
HTTP status	PASS	`download_http_code = 200`	HTTP 200
Age cutoff	PASS	`download_stamp > now() - 6 MONTH`	0.2 months ago
History drop	PASS	`isNull(history_drop_reason)`	No drop reason
Spam/ban	PASS	`fh_dont_index != 1 AND ml_spam_score = 0`	ml_spam_score=0
Canonical	PASS	`meta_canonical IS NULL OR = '' OR = src_unparsed`	Not set

Page Details

Property	Value
URL	https://www.hdruk.ac.uk/projects/false-positives/
Last Crawled	2026-04-06 14:39:27 (4 days ago)
First Indexed	2020-08-19 23:30:19 (5 years ago)
HTTP Status Code	200
Meta Title	False Positive Tests - HDR UK
Meta Description	"False positives" have been an issue since testing for COVID-19 pandemic began. As the volume of tests has significantly increased, it has become even more relevant.
Meta Canonical	null
Boilerpipe Text	This webpage was created in August 2020. What is the issue? Increasing numbers of prominent scientists and politicians have called for widespread testing for SARS-CoV-2 coronavirus (Covid-19) infection in populations where only a very small proportion of people currently have active infection, with or without obvious symptoms. But, no diagnostic test is perfect in the real world , however well it may perform in controlled laboratory settings. Science and media coverage has so far paid a great deal of attention to the problem of false negative tests , where people infected with the virus have a negative test result when they should test positive. By contrast, there has been much less discussion about the problem of false positive tests , where people who do not have infection receive a positive test result when it should be negative. As active viral infection becomes less and less common in any population, the problem of false positive tests increases, even with the best tests. Even with an almost perfect test, the lower the prevalence of infection, the higher will be the proportion of false positive results among all the positive results . This is really important for countries where the percentage of individuals in the community who are actively infected is currently very low, for example the UK, where <0.1% had active infection in early August 2020, according to the Office for National Statistics infection survey. Explore and understand this issue with our interactive tool We have produced a simple, transparent, interactive tool to help policy makers, the scientific community, health professionals, journalists and the public understand the problem of incorrect test results, especially false positives. It demonstrates how this problem may be addressed by doing confirmatory tests in people who are at very low risk of actually being infected and whose first test returns a positive result. As an example, with an infection prevalence 1 of 0.05% or 1 in 2,000 (the average community prevalence in the UK in early August) and very optimistic test performance measures (sensitivity 2 of 80% and specificity 3 99.9%), the chance of a positive result being truly positive will be only 29% with one test. This increases to almost 100% if a second test is also positive. However, the percentage of positive results that are truly positive can fall to unacceptably low levels when infection is very uncommon in the population and test specificity is less than excellent. We conclude that the crucial roles of extremely high test specificity and of confirmatory testing must be fully appreciated and incorporated into policy decisions to avoid unnecessary restrictions for whole populations, and for particular individuals, arising from widespread population testing for SARS-CoV-2 infection. The tool was developed by Professor Cathie Sudlow, Director of the BHF Data Science Centre. Please click here if you would like to use the tool to explore different scenarios yourself. Find out more about the BHF Data Science Centre . Footnotes Infection prevalence means the percentage of people currently infected with the virus in the population from which the individuals being tested are drawn. Test sensitivity means the percentage of all truly infected cases that will be correctly detected by the test. Test specificity means the percentage of all truly non-infected cases that will be correctly ruled out by test. Find out more about the BHF Data Science Centre At HDR UK, we are committed to involving patients and members of the public to help influence and shape our work. If you are interested in the safe access and use of health data, sign up to HDR UK Voices to learn more about opportunities to get involved. Sign up to HDR UK Voices Head over to our Health Data Innovation Gateway to explore datasets, tools, papers and related resources used in health research across the UK. Explore our National Core Studies collection on the Gateway Subscribe to HIVE , our e-newsletter, to keep updated on our work and other matters related to health data science. Find out how we are championing the use of health data to respond to COVID-19
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[Home](https://www.hdruk.ac.uk/) \\| 2. [Projects](https://www.hdruk.ac.uk/research/projects/) Project # False Positive Tests "False positives" have been an issue since testing for COVID-19 pandemic began. As the volume of tests has significantly increased, it has become even more relevant. Find out more in this piece by Professor Cathie Sudlow, Director of the British Heart Foundation Data Science Centre; and check out our interactive tool developed to address the issue. ![](https://www.hdruk.ac.uk/wp-content/uploads/2021/04/COVID_tests.jpg) Share this page This webpage was created in August 2020. ## What is the issue? Increasing numbers of prominent scientists and politicians have called for widespread testing for SARS-CoV-2 coronavirus (Covid-19) infection in populations where only a very small proportion of people currently have active infection, with or without obvious symptoms. But, no diagnostic test is perfect in the real world, however well it may perform in controlled laboratory settings. Science and media coverage has so far paid a great deal of attention to the problem of false negative tests, where people infected with the virus have a negative test result when they should test positive. By contrast, there has been much less discussion about the problem of false positive tests, where people who do not have infection receive a positive test result when it should be negative. As active viral infection becomes less and less common in any population, the problem of false positive tests increases, even with the best tests. Even with an almost perfect test, the lower the prevalence of infection, the higher will be the proportion of false positive results among all the positive results. This is really important for countries where the percentage of individuals in the community who are actively infected is currently very low, for example the UK, where \<0.1% had active infection in early August 2020, according to the Office for National Statistics infection survey. ## Explore and understand this issue with our interactive tool We have produced a simple, transparent, [interactive tool](https://www.hdruk.ac.uk/wp-content/uploads/2020/08/200820-coronavirus-infection-testing-app.xlsx) to help policy makers, the scientific community, health professionals, journalists and the public understand the problem of incorrect test results, especially false positives. It demonstrates how this problem may be addressed by doing confirmatory tests in people who are at very low risk of actually being infected and whose first test returns a positive result. As an example, with an infection prevalence1 of 0.05% or 1 in 2,000 (the average community prevalence in the UK in early August) and very optimistic test performance measures (sensitivity2 of 80% and specificity3 99.9%), the chance of a positive result being truly positive will be only 29% with one test. This increases to almost 100% if a second test is also positive. However, the percentage of positive results that are truly positive can fall to unacceptably low levels when infection is very uncommon in the population and test specificity is less than excellent. We conclude that the crucial roles of extremely high test specificity and of confirmatory testing must be fully appreciated and incorporated into policy decisions to avoid unnecessary restrictions for whole populations, and for particular individuals, arising from widespread population testing for SARS-CoV-2 infection. The tool was developed by Professor Cathie Sudlow, Director of the BHF Data Science Centre. Please [click here](https://www.hdruk.ac.uk/wp-content/uploads/2020/08/200820-coronavirus-infection-testing-app.xlsx) if you would like to use the tool to explore different scenarios yourself. Find out more about the [BHF Data Science Centre](https://www.hdruk.ac.uk/help-with-your-data/bhf-data-science-centre/). #### Footnotes 1. Infection prevalence means the percentage of people currently infected with the virus in the population from which the individuals being tested are drawn. 2. Test sensitivity means the percentage of all truly infected cases that will be correctly detected by the test. 3. Test specificity means the percentage of all truly non-infected cases that will be correctly ruled out by test. [Find out more about the BHF Data Science Centre](https://www.hdruk.ac.uk/helping-with-health-data/bhf-data-science-centre/) At HDR UK, we are committed to involving patients and members of the public to help influence and shape our work. If you are interested in the safe access and use of health data, sign up to HDR UK Voices to learn more about opportunities to get involved. [Sign up to HDR UK Voices](https://www.hdruk.ac.uk/what-is-health-data-research/patient-and-public-involvement-and-engagement/join-hdr-uk-voices/hdr-uk-voices-sign-up/) Head over to our [Health Data Innovation Gateway](https://www.healthdatagateway.org/) to explore datasets, tools, papers and related resources used in health research across the UK. [Explore our National Core Studies collection on the Gateway](https://www.healthdatagateway.org/collectioncategories/national-core-studies) [Subscribe to HIVE](https://www.hdruk.ac.uk/subscribe/), our e-newsletter, to keep updated on our work and other matters related to health data science. [Find out how we are championing the use of health data to respond to COVID-19](https://www.hdruk.ac.uk/covid-19/) Areas of work [Science](https://www.hdruk.ac.uk/search/?_areas_of_work=science) Scientific priorities [COVID-19](https://www.hdruk.ac.uk/search/?_research_priorities=covid-19) Health priorities [COVID-19](https://www.hdruk.ac.uk/search/?_health_priorities=covid-19) Selected work [![](https://www.hdruk.ac.uk/wp-content/uploads/2021/12/shutterstock_1789303814.jpg) News Story COVID-19 vaccine protects people of all body weights from hospitalisation and death, study of 9 million adults in England suggests 1 July 2022 Largest study of body mass index (BMI) and COVID-19 vaccine effectiveness using the QResearch platform suggests two doses are highly effective against severe disease for people who are...](https://www.hdruk.ac.uk/news/covid-19-vaccine-protects-people-of-all-body-weights-from-hospitalisation-and-death-study-of-9-million-adults-in-england-suggests/) [![COVID-19 health data research](https://www.hdruk.ac.uk/wp-content/uploads/2020/10/Gateway-COVID-2.jpg) News Most comprehensive analysis of COVID-19 data reveals previously unattributed deaths 9 June 2022 Study published in The Lancet Digital Health and supported by the BHF Data Science Centre used health data from 57 million people in England to build the most complete picture of the pandemic in a...](https://www.hdruk.ac.uk/news/most-comprehensive-analysis-of-covid-19-data-reveals-previously-unattributed-deaths/) [![](https://www.hdruk.ac.uk/wp-content/uploads/2021/02/covid_smaller.jpg) News COVID-19 variant Omicron is usually milder than Delta but also more likely to break through immune protection 25 April 2022 New paper from EAVE II team uses linked GP, hospital and lab data to analyse severity of omicron variant and effectiveness of vaccine boosters against symptomatic disease in Scotland](https://www.ed.ac.uk/usher/eave-ii/key-outputs/our-publications/omicron-booster-effectiveness-symptomatic-disease) ## Our funders [![Medical Research Council logo](https://www.hdruk.ac.uk/wp-content/uploads/2020/09/ukri_mrcc.jpg)](https://www.ukri.org/councils/mrc/) [![NIHR National Institute for Health Research logo](https://www.hdruk.ac.uk/wp-content/uploads/2020/06/nihr.jpg)](https://www.nihr.ac.uk/) [![British Heart Foundation logo](https://www.hdruk.ac.uk/wp-content/uploads/2020/06/bhflogo.jpg)](https://www.bhf.org.uk/) [![Cancer Research UK logo](https://www.hdruk.ac.uk/wp-content/uploads/2023/09/CRUK_logo-light-background-primary-RGB-300x145.jpg)](https://www.cancerresearchuk.org/) [![Economic and Social Research Council logo](https://www.hdruk.ac.uk/wp-content/uploads/2020/06/esrc.jpg)](https://www.ukri.org/councils/esrc/) [![Engineering and Physical Sciences Research Council logo](https://www.hdruk.ac.uk/wp-content/uploads/2020/06/epsrc2.jpg)](https://www.ukri.org/councils/epsrc/) [![Health and Care Research Wales logo](https://www.hdruk.ac.uk/wp-content/uploads/2020/06/hscwales.jpg)](https://healthandcareresearchwales.org/) [![Chief Scientist Office logo](https://www.hdruk.ac.uk/wp-content/uploads/2020/06/cso_logo.jpg)](https://www.cso.scot.nhs.uk/) [![HSC Public Health Agency Research and Development logo](https://www.hdruk.ac.uk/wp-content/uploads/2020/06/hsc_rd_ni.jpg)](https://www.publichealth.hscni.net/) [![HDR UK](https://www.hdruk.ac.uk/wp-content/themes/hdruk/assets/img/logo.svg)](https://www.hdruk.ac.uk/) Follow us on social media - [Contact us](https://www.hdruk.ac.uk/about-us/contact-us/) - [Subscribe to our mailing list](https://www.hdruk.ac.uk/subscribe/) - [Register of Interests](https://www.hdruk.ac.uk/wp-content/uploads/2023/04/251027-Register-of-Interests-Board-and-SLT.pdf) - [Frequently Asked Questions](https://www.hdruk.ac.uk/about-us/what-is-health-data-research/your-questions-answered/) - [Job Vacancies](https://www.hdruk.ac.uk/jobs/) - [Terms and Conditions](https://www.hdruk.ac.uk/terms-and-conditions/) - [Privacy Policy](https://www.hdruk.ac.uk/privacy-policy/) - [Cookies](https://www.hdruk.ac.uk/terms-and-conditions/cookies/) - [Registered charity number 1194431](https://www.hdruk.ac.uk/about-us/) ©HDR UK 2026. 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Readable Markdown	This webpage was created in August 2020. ## What is the issue? Increasing numbers of prominent scientists and politicians have called for widespread testing for SARS-CoV-2 coronavirus (Covid-19) infection in populations where only a very small proportion of people currently have active infection, with or without obvious symptoms. But, no diagnostic test is perfect in the real world, however well it may perform in controlled laboratory settings. Science and media coverage has so far paid a great deal of attention to the problem of false negative tests, where people infected with the virus have a negative test result when they should test positive. By contrast, there has been much less discussion about the problem of false positive tests, where people who do not have infection receive a positive test result when it should be negative. As active viral infection becomes less and less common in any population, the problem of false positive tests increases, even with the best tests. Even with an almost perfect test, the lower the prevalence of infection, the higher will be the proportion of false positive results among all the positive results. This is really important for countries where the percentage of individuals in the community who are actively infected is currently very low, for example the UK, where \<0.1% had active infection in early August 2020, according to the Office for National Statistics infection survey. ## Explore and understand this issue with our interactive tool We have produced a simple, transparent, [interactive tool](https://www.hdruk.ac.uk/wp-content/uploads/2020/08/200820-coronavirus-infection-testing-app.xlsx) to help policy makers, the scientific community, health professionals, journalists and the public understand the problem of incorrect test results, especially false positives. It demonstrates how this problem may be addressed by doing confirmatory tests in people who are at very low risk of actually being infected and whose first test returns a positive result. As an example, with an infection prevalence1 of 0.05% or 1 in 2,000 (the average community prevalence in the UK in early August) and very optimistic test performance measures (sensitivity2 of 80% and specificity3 99.9%), the chance of a positive result being truly positive will be only 29% with one test. This increases to almost 100% if a second test is also positive. However, the percentage of positive results that are truly positive can fall to unacceptably low levels when infection is very uncommon in the population and test specificity is less than excellent. We conclude that the crucial roles of extremely high test specificity and of confirmatory testing must be fully appreciated and incorporated into policy decisions to avoid unnecessary restrictions for whole populations, and for particular individuals, arising from widespread population testing for SARS-CoV-2 infection. The tool was developed by Professor Cathie Sudlow, Director of the BHF Data Science Centre. Please [click here](https://www.hdruk.ac.uk/wp-content/uploads/2020/08/200820-coronavirus-infection-testing-app.xlsx) if you would like to use the tool to explore different scenarios yourself. Find out more about the [BHF Data Science Centre](https://www.hdruk.ac.uk/help-with-your-data/bhf-data-science-centre/). #### Footnotes 1. Infection prevalence means the percentage of people currently infected with the virus in the population from which the individuals being tested are drawn. 2. Test sensitivity means the percentage of all truly infected cases that will be correctly detected by the test. 3. Test specificity means the percentage of all truly non-infected cases that will be correctly ruled out by test. [Find out more about the BHF Data Science Centre](https://www.hdruk.ac.uk/helping-with-health-data/bhf-data-science-centre/) At HDR UK, we are committed to involving patients and members of the public to help influence and shape our work. If you are interested in the safe access and use of health data, sign up to HDR UK Voices to learn more about opportunities to get involved. [Sign up to HDR UK Voices](https://www.hdruk.ac.uk/what-is-health-data-research/patient-and-public-involvement-and-engagement/join-hdr-uk-voices/hdr-uk-voices-sign-up/) Head over to our [Health Data Innovation Gateway](https://www.healthdatagateway.org/) to explore datasets, tools, papers and related resources used in health research across the UK. [Explore our National Core Studies collection on the Gateway](https://www.healthdatagateway.org/collectioncategories/national-core-studies) [Subscribe to HIVE](https://www.hdruk.ac.uk/subscribe/), our e-newsletter, to keep updated on our work and other matters related to health data science. [Find out how we are championing the use of health data to respond to COVID-19](https://www.hdruk.ac.uk/covid-19/)
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