🕷️ Crawler Inspector

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Raw Queries and Responses

1. Shard Calculation

Query:

Response:

Calculated Shard: 16 (from laksa143)

2. Crawled Status Check

Query:

curl -X POST \
  'http://laksa016.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.bbc.com/news/54270373\')), getAhrefsUnparsedNoserviceFromURL(\'https://www.bbc.com/news/54270373\'))) FORMAT JSONEachRow'

Response:

{"found_url":"https:\/\/www.bbc.com\/news\/54270373","crawl_time":1772913634,"first_indexed_time":1601732449,"http_code":200,"src_unparsed":"com,bbc!www,\/news\/54270373 s443","src_root_hash":"1643509356818581016","history_drop_reason":null,"meta_title":"Coronavirus testing: What is a false positive?","meta_descriptions":["Some commentators say rising cases are just because of false positive results. But that's not true."],"attrs_boilerpipe_text":"3 October 2020\nSimon Maybin and Josephine Casserly\nMore or Less, BBC Radio 4\nReuters\nThere has been a lot of talk on social media about \"false positive\" test results after several commentators suggested they might be seriously skewing the coronavirus figures - but that is based on a misunderstanding of the impact of false positives.\nTalk Radio host Julia Hartley-Brewer has claimed that \"nine out of 10 of the positive cases of Covid we are finding in the community when we do random testing, when anyone just puts themselves forward, will be wrong. They will not be people who have got coronavirus.\"\nCould it be true that 90% of positive results from tests in the community - that means tests not carried out in hospitals - are false? The answer is \"no\" - there is no way that so-called false positives have had such an impact on the figures.\nHartley-Brewer referred to both \"random testing\" and \"anyone [who] just puts themselves forward\", which are different things, and the difference between them is important.\nAlso, there are many other signs that the rising number of positive tests is truly reflecting the virus spreading, for example a subsequent rise in Covid hospitalisations.\nWhat is a false positive?\nA false positive is when someone who does not have coronavirus, tests positive for it.\nNo test is 100% accurate - there will always be some people who test positive when they do not have the disease, or test negative when they do have it.\nFalse positives in any testing programme are important - especially when there is low prevalence of a disease - because they could potentially make us think there are significantly more cases of something than there really are.\nThe false positive rate usually refers to the number of people who are not infected but get positive results, as a proportion of all the people tested who really don't have the virus. We do not know what the precise rate is though.\nDr Paul Birrell, a statistician at the Medical Research Council's Biostatistics Unit at the University of Cambridge, says: \"The false positive rate is not well understood and could potentially vary according to where and why the test is being taken. A figure of 0.5% for the false positive rate is often assumed.\"\nRandomness is the key\nThe most important thing to know about the impact of false positives is that it varies hugely depending on who is being tested.\nWhat Hartley-Brewer said confused the idea of random testing with community testing for Covid. Those are two different situations, and false positives have a very different impact in each case.\nIf you tested 1,000 people at random for Covid-19 in early September, for example, data from the Office for National Statistics (ONS) infection study suggests you should have expected one of them to actually have the virus.\nWith a false positive rate of 0.8% - a figure used by Ms Hartley-Brewer and within the broad range of what we think might be the actual rate for community testing - you would get eight false positives. So in that context, it's true that roughly 90% of positives would be false.\nBut - crucially - the people going for community testing for Covid-19 (at places such as drive-through centres) are not a random sample of the public. They are people who\nhave symptoms\n, are in care homes or are in hot-spot areas.\nPA Media\nFigures for late September\nfrom Public Health England show that 7% of community tests were positive. That means of every 1,000 people tested, 70 were positive. Even with a false positive rate of 0.8%, seven of those would be false positives, but 63 would be true positives - the vast majority.\nSo the daily case count is not being skewed significantly by false positives. There will also be some false negatives, meaning that some people who actually have Covid are not being counted.\nWhen we put it to Hartley-Brewer that she had misinterpreted explanations of the impact of false positives, she pointed us to other articles that also discussed the impact on random samples of the population, rather than on people who are much more likely to have the virus.\nThere are other signs of real positive results\nPeople do not get admitted to hospital by false positives, so if more people are in hospital with Covid, then you can be pretty sure that is due to genuine cases. The same is true of the number of deaths.\nDr Birrell says that to be certain cases really are increasing, the daily case count \"should always be considered alongside other information sources, such as the hospitalisations or deaths, or the community surveys run by the\nONS or REACT\n\".\nCorrection 7 October: The piece was corrected to show that 63 out of 1,000 people tested would be true positives if there was a 7% positivity rate and a 0.8% false positive rate.\nSOCIAL DISTANCING:\nWhat are the rules now?\nSUPPORT BUBBLES:\nWhat are they and who can be in yours?\nSCHOOLS:\nWhat will happen if children catch coronavirus?\nTESTING:\nWhat tests are available?\nLOOK-UP TOOL:\nCheck cases in your area\nMore or Less is on BBC Radio 4 at 09:30 BST on Wednesdays and repeated at 16:30 on Fridays and 20:00 on Sundays. It's also available on\nBBC Sounds.","attrs_markdown":"[Skip to content](https:\/\/www.bbc.com\/news\/54270373#main-content)\n\n[Register](https:\/\/session.bbc.com\/session?action=register&userOrigin=BBCS_BBC&ptrt=https%3A%2F%2Fwww.bbc.com%2Fnews%2F54270373)\n\n[Sign In](https:\/\/session.bbc.com\/session?userOrigin=BBCS_BBC&ptrt=https%3A%2F%2Fwww.bbc.com%2Fnews%2F54270373)\n\n- [Home](https:\/\/www.bbc.com\/)\n- [News](https:\/\/www.bbc.com\/news)\n- [Sport](https:\/\/www.bbc.com\/sport)\n- [Business](https:\/\/www.bbc.com\/business)\n- [Technology](https:\/\/www.bbc.com\/technology)\n- [Health](https:\/\/www.bbc.com\/health)\n- [Culture](https:\/\/www.bbc.com\/culture)\n- [Arts](https:\/\/www.bbc.com\/arts)\n- [Travel](https:\/\/www.bbc.com\/travel)\n- [Earth](https:\/\/www.bbc.com\/future-planet)\n- [Audio](https:\/\/www.bbc.com\/audio)\n- [Video](https:\/\/www.bbc.com\/video)\n- [Live](https:\/\/www.bbc.com\/live)\n\n- [Home](https:\/\/www.bbc.com\/home)\n- [News](https:\/\/www.bbc.com\/news)\n  - [US & Canada](https:\/\/www.bbc.com\/news\/us-canada)\n  - [UK](https:\/\/www.bbc.com\/news\/uk)\n    - [UK Politics](https:\/\/www.bbc.com\/news\/politics)\n    - [England](https:\/\/www.bbc.com\/news\/england)\n    - [N. 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[Adventures](https:\/\/www.bbc.com\/travel\/adventures)\n  - [The SpeciaList](https:\/\/www.bbc.com\/travel\/specialist)\n- [Earth](https:\/\/www.bbc.com\/future-planet)\n  - [Science](https:\/\/www.bbc.com\/innovation\/science)\n  - [Natural Wonders](https:\/\/www.bbc.com\/future-planet\/natural-wonders)\n  - [Climate Solutions](https:\/\/www.bbc.com\/future-planet\/solutions)\n  - [Sustainable Business](https:\/\/www.bbc.com\/future-planet\/sustainable-business)\n  - [Green Living](https:\/\/www.bbc.com\/future-planet\/green-living)\n- [Audio](https:\/\/www.bbc.com\/audio)\n  - [Podcast Categories](https:\/\/www.bbc.com\/audio\/categories)\n  - [Radio](https:\/\/www.bbc.com\/audio\/stations)\n  - [Audio FAQs](https:\/\/www.bbc.com\/undefined)\n- [Video](https:\/\/www.bbc.com\/video)\n  - [BBC Maestro](https:\/\/www.bbc.com\/video\/bbc-maestro)\n  - [Discover the World](https:\/\/www.bbc.com\/video\/discover-the-world)\n- [Live](https:\/\/www.bbc.com\/live)\n  - [Live News](https:\/\/www.bbc.com\/live\/news)\n  - [Live Sport](https:\/\/www.bbc.com\/live\/sport)\n\n[Home](https:\/\/www.bbc.com\/)\n\nNews\n\n[Sport](https:\/\/www.bbc.com\/sport)\n\nBusiness\n\nTechnology\n\n[Health](https:\/\/www.bbc.com\/health)\n\nCulture\n\nArts\n\nTravel\n\nEarth\n\nAudio\n\nVideo\n\nLive\n\n[Weather](https:\/\/www.bbc.com\/weather)\n\n[Newsletters](https:\/\/www.bbc.com\/newsletters)\n\n# Coronavirus testing: What is a false positive?\n3 October 2020\n\nShare\n\nSave\n\nSimon Maybin and Josephine CasserlyMore or Less, BBC Radio 4\n\nShare\n\nSave\n\n![Reuters A drive through testing centre](https:\/\/ichef.bbci.co.uk\/news\/480\/cpsprodpb\/5255\/production\/_114577012_mediaitem114577008.jpg.webp)Reuters\n\n**There has been a lot of talk on social media about \"false positive\" test results after several commentators suggested they might be seriously skewing the coronavirus figures - but that is based on a misunderstanding of the impact of false positives.**\n\nTalk Radio host Julia Hartley-Brewer has claimed that \"nine out of 10 of the positive cases of Covid we are finding in the community when we do random testing, when anyone just puts themselves forward, will be wrong. They will not be people who have got coronavirus.\"\n\nCould it be true that 90% of positive results from tests in the community - that means tests not carried out in hospitals - are false? The answer is \"no\" - there is no way that so-called false positives have had such an impact on the figures.\n\nHartley-Brewer referred to both \"random testing\" and \"anyone \\[who\\] just puts themselves forward\", which are different things, and the difference between them is important.\n\nAlso, there are many other signs that the rising number of positive tests is truly reflecting the virus spreading, for example a subsequent rise in Covid hospitalisations.\n\n## What is a false positive?\nA false positive is when someone who does not have coronavirus, tests positive for it.\n\nNo test is 100% accurate - there will always be some people who test positive when they do not have the disease, or test negative when they do have it.\n\nFalse positives in any testing programme are important - especially when there is low prevalence of a disease - because they could potentially make us think there are significantly more cases of something than there really are.\n\nThe false positive rate usually refers to the number of people who are not infected but get positive results, as a proportion of all the people tested who really don't have the virus. We do not know what the precise rate is though.\n\nDr Paul Birrell, a statistician at the Medical Research Council's Biostatistics Unit at the University of Cambridge, says: \"The false positive rate is not well understood and could potentially vary according to where and why the test is being taken. A figure of 0.5% for the false positive rate is often assumed.\"\n\n## Randomness is the key\nThe most important thing to know about the impact of false positives is that it varies hugely depending on who is being tested.\n\nWhat Hartley-Brewer said confused the idea of random testing with community testing for Covid. Those are two different situations, and false positives have a very different impact in each case.\n\nIf you tested 1,000 people at random for Covid-19 in early September, for example, data from the Office for National Statistics (ONS) infection study suggests you should have expected one of them to actually have the virus.\n\nWith a false positive rate of 0.8% - a figure used by Ms Hartley-Brewer and within the broad range of what we think might be the actual rate for community testing - you would get eight false positives. So in that context, it's true that roughly 90% of positives would be false.\n\nBut - crucially - the people going for community testing for Covid-19 (at places such as drive-through centres) are not a random sample of the public. They are people who [have symptoms](https:\/\/www.bbc.co.uk\/news\/health-51048366), are in care homes or are in hot-spot areas.\n\n![PA Media A car drives past a testing centre](https:\/\/ichef.bbci.co.uk\/images\/ic\/1024x1024\/p0hq72jn.png.webp)PA Media\n\n[Figures for late September](https:\/\/assets.publishing.service.gov.uk\/government\/uploads\/system\/uploads\/attachment_data\/file\/923668\/Weekly_COVID19_Surveillance_Report_week_40.pdf) from Public Health England show that 7% of community tests were positive. That means of every 1,000 people tested, 70 were positive. Even with a false positive rate of 0.8%, seven of those would be false positives, but 63 would be true positives - the vast majority.\n\nSo the daily case count is not being skewed significantly by false positives. There will also be some false negatives, meaning that some people who actually have Covid are not being counted.\n\nWhen we put it to Hartley-Brewer that she had misinterpreted explanations of the impact of false positives, she pointed us to other articles that also discussed the impact on random samples of the population, rather than on people who are much more likely to have the virus.\n\n## There are other signs of real positive results\nPeople do not get admitted to hospital by false positives, so if more people are in hospital with Covid, then you can be pretty sure that is due to genuine cases. The same is true of the number of deaths.\n\nDr Birrell says that to be certain cases really are increasing, the daily case count \"should always be considered alongside other information sources, such as the hospitalisations or deaths, or the community surveys run by the [ONS or REACT](https:\/\/www.bbc.co.uk\/news\/health-54387057)\".\n\n*Correction 7 October: The piece was corrected to show that 63 out of 1,000 people tested would be true positives if there was a 7% positivity rate and a 0.8% false positive rate.*\n\n![Banner image reading 'more about coronavirus'](https:\/\/ichef.bbci.co.uk\/images\/ic\/1024x1024\/p0hq72jn.png.webp)\n\n- SOCIAL DISTANCING: [What are the rules now?](https:\/\/www.bbc.co.uk\/news\/uk-51506729)\n- SUPPORT BUBBLES: [What are they and who can be in yours?](https:\/\/www.bbc.co.uk\/news\/health-52637354)\n- SCHOOLS: [What will happen if children catch coronavirus?](https:\/\/www.bbc.co.uk\/news\/education-51643556)\n- TESTING: [What tests are available?](https:\/\/www.bbc.co.uk\/news\/health-51943612)\n- LOOK-UP TOOL: [Check cases in your area](https:\/\/www.bbc.co.uk\/news\/uk-51768274)\n\n![Banner](https:\/\/ichef.bbci.co.uk\/images\/ic\/1024x1024\/p0hq72jn.png.webp)\n\nMore or Less is on BBC Radio 4 at 09:30 BST on Wednesdays and repeated at 16:30 on Fridays and 20:00 on Sundays. It's also available on [BBC Sounds.](https:\/\/www.bbc.co.uk\/sounds\/series\/p02nrss1)\n\n![Presentational grey line](https:\/\/ichef.bbci.co.uk\/images\/ic\/1024x1024\/p0hq72jn.png.webp)\n\n![Reality Check branding](https:\/\/ichef.bbci.co.uk\/images\/ic\/1024x1024\/p0hq72jn.png.webp)\n\n[What claims do you want BBC Reality Check to investigate? Get in touch](http:\/\/www.bbc.co.uk\/news\/uk-41928747)\n\n[Read more from Reality Check](http:\/\/www.bbc.co.uk\/realitycheck)\n\n[Follow us on Twitter](https:\/\/twitter.com\/bbcrealitycheck)\n\n![Presentational grey line](https:\/\/ichef.bbci.co.uk\/images\/ic\/1024x1024\/p0hq72jn.png.webp)\n\n[Coronavirus testing](https:\/\/www.bbc.com\/news\/topics\/ck2l9qxx17nt)\n\n[BBC Verify](https:\/\/www.bbc.com\/news\/topics\/cp7r8vgl2rgt)\n\n[Coronavirus pandemic](https:\/\/www.bbc.com\/news\/topics\/cyz0z8w0ydwt)\n\n***\nRelated\n\n[Covid testing lab was 'like building site' - court](https:\/\/www.bbc.com\/news\/articles\/c0je1n88624o)\n\n[Lockdown could have been avoided - key findings from Covid inquiry](https:\/\/www.bbc.com\/news\/articles\/cpq1q49r08go)\n\n[Covid firm issued result for unused test - court](https:\/\/www.bbc.com\/news\/articles\/c620lpdve4go)\n\n***\nMore from the BBC\n\n[19 hrs ago ![An image appearing to show a large explosion with a green \"AI-generated\" label](https:\/\/ichef.bbci.co.uk\/images\/ic\/1024x1024\/p0hq72jn.png.webp) AI-generated Iran war videos surge as creators use new tech to cash in The US-Israel war with Iran is being monetised by online creators with AI-generated misinformation. 19 hrs ago](https:\/\/www.bbc.com\/news\/articles\/ckg8wvz427vo)\n\n[3 days ago ![Plumes of smoke rise following reported explosions in Tehran on March 2, 2026](https:\/\/ichef.bbci.co.uk\/images\/ic\/1024x1024\/p0hq72jn.png.webp) Ros Atkins on...how has President Trump's message on war changed? 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All rights reserved. The BBC is not responsible for the content of external sites. [**Read about our approach to external linking.**](https:\/\/www.bbc.co.uk\/editorialguidelines\/guidance\/feeds-and-links)","attrs_readable_markdown":"3 October 2020\n\nSimon Maybin and Josephine CasserlyMore or Less, BBC Radio 4\n\n![Reuters A drive through testing centre](https:\/\/ichef.bbci.co.uk\/news\/480\/cpsprodpb\/5255\/production\/_114577012_mediaitem114577008.jpg.webp)Reuters\n\n**There has been a lot of talk on social media about \"false positive\" test results after several commentators suggested they might be seriously skewing the coronavirus figures - but that is based on a misunderstanding of the impact of false positives.**\n\nTalk Radio host Julia Hartley-Brewer has claimed that \"nine out of 10 of the positive cases of Covid we are finding in the community when we do random testing, when anyone just puts themselves forward, will be wrong. They will not be people who have got coronavirus.\"\n\nCould it be true that 90% of positive results from tests in the community - that means tests not carried out in hospitals - are false? The answer is \"no\" - there is no way that so-called false positives have had such an impact on the figures.\n\nHartley-Brewer referred to both \"random testing\" and \"anyone \\[who\\] just puts themselves forward\", which are different things, and the difference between them is important.\n\nAlso, there are many other signs that the rising number of positive tests is truly reflecting the virus spreading, for example a subsequent rise in Covid hospitalisations.\n\nWhat is a false positive?\n\nA false positive is when someone who does not have coronavirus, tests positive for it.\n\nNo test is 100% accurate - there will always be some people who test positive when they do not have the disease, or test negative when they do have it.\n\nFalse positives in any testing programme are important - especially when there is low prevalence of a disease - because they could potentially make us think there are significantly more cases of something than there really are.\n\nThe false positive rate usually refers to the number of people who are not infected but get positive results, as a proportion of all the people tested who really don't have the virus. We do not know what the precise rate is though.\n\nDr Paul Birrell, a statistician at the Medical Research Council's Biostatistics Unit at the University of Cambridge, says: \"The false positive rate is not well understood and could potentially vary according to where and why the test is being taken. A figure of 0.5% for the false positive rate is often assumed.\"\n\nRandomness is the key\n\nThe most important thing to know about the impact of false positives is that it varies hugely depending on who is being tested.\n\nWhat Hartley-Brewer said confused the idea of random testing with community testing for Covid. Those are two different situations, and false positives have a very different impact in each case.\n\nIf you tested 1,000 people at random for Covid-19 in early September, for example, data from the Office for National Statistics (ONS) infection study suggests you should have expected one of them to actually have the virus.\n\nWith a false positive rate of 0.8% - a figure used by Ms Hartley-Brewer and within the broad range of what we think might be the actual rate for community testing - you would get eight false positives. So in that context, it's true that roughly 90% of positives would be false.\n\nBut - crucially - the people going for community testing for Covid-19 (at places such as drive-through centres) are not a random sample of the public. They are people who [have symptoms](https:\/\/www.bbc.co.uk\/news\/health-51048366), are in care homes or are in hot-spot areas.\n\n![PA Media A car drives past a testing centre](https:\/\/ichef.bbci.co.uk\/images\/ic\/1024x1024\/p0hq72jn.png.webp)PA Media\n\n[Figures for late September](https:\/\/assets.publishing.service.gov.uk\/government\/uploads\/system\/uploads\/attachment_data\/file\/923668\/Weekly_COVID19_Surveillance_Report_week_40.pdf) from Public Health England show that 7% of community tests were positive. That means of every 1,000 people tested, 70 were positive. Even with a false positive rate of 0.8%, seven of those would be false positives, but 63 would be true positives - the vast majority.\n\nSo the daily case count is not being skewed significantly by false positives. There will also be some false negatives, meaning that some people who actually have Covid are not being counted.\n\nWhen we put it to Hartley-Brewer that she had misinterpreted explanations of the impact of false positives, she pointed us to other articles that also discussed the impact on random samples of the population, rather than on people who are much more likely to have the virus.\n\nThere are other signs of real positive results\n\nPeople do not get admitted to hospital by false positives, so if more people are in hospital with Covid, then you can be pretty sure that is due to genuine cases. The same is true of the number of deaths.\n\nDr Birrell says that to be certain cases really are increasing, the daily case count \"should always be considered alongside other information sources, such as the hospitalisations or deaths, or the community surveys run by the [ONS or REACT](https:\/\/www.bbc.co.uk\/news\/health-54387057)\".\n\n*Correction 7 October: The piece was corrected to show that 63 out of 1,000 people tested would be true positives if there was a 7% positivity rate and a 0.8% false positive rate.*\n\n![Banner image reading 'more about coronavirus'](https:\/\/ichef.bbci.co.uk\/images\/ic\/1024x1024\/p0hq72jn.png.webp)\n\n- SOCIAL DISTANCING: [What are the rules now?](https:\/\/www.bbc.co.uk\/news\/uk-51506729)\n- SUPPORT BUBBLES: [What are they and who can be in yours?](https:\/\/www.bbc.co.uk\/news\/health-52637354)\n- SCHOOLS: [What will happen if children catch coronavirus?](https:\/\/www.bbc.co.uk\/news\/education-51643556)\n- TESTING: [What tests are available?](https:\/\/www.bbc.co.uk\/news\/health-51943612)\n- LOOK-UP TOOL: [Check cases in your area](https:\/\/www.bbc.co.uk\/news\/uk-51768274)\n\n![Banner](https:\/\/ichef.bbci.co.uk\/images\/ic\/1024x1024\/p0hq72jn.png.webp)\n\nMore or Less is on BBC Radio 4 at 09:30 BST on Wednesdays and repeated at 16:30 on Fridays and 20:00 on Sundays. It's also available on [BBC Sounds.](https:\/\/www.bbc.co.uk\/sounds\/series\/p02nrss1)\n\n![Presentational grey line](https:\/\/ichef.bbci.co.uk\/images\/ic\/1024x1024\/p0hq72jn.png.webp)\n\n![Reality Check branding](https:\/\/ichef.bbci.co.uk\/images\/ic\/1024x1024\/p0hq72jn.png.webp)\n\n![Presentational grey line](https:\/\/ichef.bbci.co.uk\/images\/ic\/1024x1024\/p0hq72jn.png.webp)","meta_canonical":null}

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Meta Title	Coronavirus testing: What is a false positive?
Meta Description	Some commentators say rising cases are just because of false positive results. But that's not true.
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Boilerpipe Text	3 October 2020 Simon Maybin and Josephine Casserly More or Less, BBC Radio 4 Reuters There has been a lot of talk on social media about "false positive" test results after several commentators suggested they might be seriously skewing the coronavirus figures - but that is based on a misunderstanding of the impact of false positives. Talk Radio host Julia Hartley-Brewer has claimed that "nine out of 10 of the positive cases of Covid we are finding in the community when we do random testing, when anyone just puts themselves forward, will be wrong. They will not be people who have got coronavirus." Could it be true that 90% of positive results from tests in the community - that means tests not carried out in hospitals - are false? The answer is "no" - there is no way that so-called false positives have had such an impact on the figures. Hartley-Brewer referred to both "random testing" and "anyone [who] just puts themselves forward", which are different things, and the difference between them is important. Also, there are many other signs that the rising number of positive tests is truly reflecting the virus spreading, for example a subsequent rise in Covid hospitalisations. What is a false positive? A false positive is when someone who does not have coronavirus, tests positive for it. No test is 100% accurate - there will always be some people who test positive when they do not have the disease, or test negative when they do have it. False positives in any testing programme are important - especially when there is low prevalence of a disease - because they could potentially make us think there are significantly more cases of something than there really are. The false positive rate usually refers to the number of people who are not infected but get positive results, as a proportion of all the people tested who really don't have the virus. We do not know what the precise rate is though. Dr Paul Birrell, a statistician at the Medical Research Council's Biostatistics Unit at the University of Cambridge, says: "The false positive rate is not well understood and could potentially vary according to where and why the test is being taken. A figure of 0.5% for the false positive rate is often assumed." Randomness is the key The most important thing to know about the impact of false positives is that it varies hugely depending on who is being tested. What Hartley-Brewer said confused the idea of random testing with community testing for Covid. Those are two different situations, and false positives have a very different impact in each case. If you tested 1,000 people at random for Covid-19 in early September, for example, data from the Office for National Statistics (ONS) infection study suggests you should have expected one of them to actually have the virus. With a false positive rate of 0.8% - a figure used by Ms Hartley-Brewer and within the broad range of what we think might be the actual rate for community testing - you would get eight false positives. So in that context, it's true that roughly 90% of positives would be false. But - crucially - the people going for community testing for Covid-19 (at places such as drive-through centres) are not a random sample of the public. They are people who have symptoms , are in care homes or are in hot-spot areas. PA Media Figures for late September from Public Health England show that 7% of community tests were positive. That means of every 1,000 people tested, 70 were positive. Even with a false positive rate of 0.8%, seven of those would be false positives, but 63 would be true positives - the vast majority. So the daily case count is not being skewed significantly by false positives. There will also be some false negatives, meaning that some people who actually have Covid are not being counted. When we put it to Hartley-Brewer that she had misinterpreted explanations of the impact of false positives, she pointed us to other articles that also discussed the impact on random samples of the population, rather than on people who are much more likely to have the virus. There are other signs of real positive results People do not get admitted to hospital by false positives, so if more people are in hospital with Covid, then you can be pretty sure that is due to genuine cases. The same is true of the number of deaths. Dr Birrell says that to be certain cases really are increasing, the daily case count "should always be considered alongside other information sources, such as the hospitalisations or deaths, or the community surveys run by the ONS or REACT ". Correction 7 October: The piece was corrected to show that 63 out of 1,000 people tested would be true positives if there was a 7% positivity rate and a 0.8% false positive rate. SOCIAL DISTANCING: What are the rules now? SUPPORT BUBBLES: What are they and who can be in yours? SCHOOLS: What will happen if children catch coronavirus? TESTING: What tests are available? LOOK-UP TOOL: Check cases in your area More or Less is on BBC Radio 4 at 09:30 BST on Wednesdays and repeated at 16:30 on Fridays and 20:00 on Sundays. It's also available on BBC Sounds.
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Talk Radio host Julia Hartley-Brewer has claimed that "nine out of 10 of the positive cases of Covid we are finding in the community when we do random testing, when anyone just puts themselves forward, will be wrong. They will not be people who have got coronavirus." Could it be true that 90% of positive results from tests in the community - that means tests not carried out in hospitals - are false? The answer is "no" - there is no way that so-called false positives have had such an impact on the figures. Hartley-Brewer referred to both "random testing" and "anyone \[who\] just puts themselves forward", which are different things, and the difference between them is important. Also, there are many other signs that the rising number of positive tests is truly reflecting the virus spreading, for example a subsequent rise in Covid hospitalisations. ## What is a false positive? A false positive is when someone who does not have coronavirus, tests positive for it. No test is 100% accurate - there will always be some people who test positive when they do not have the disease, or test negative when they do have it. False positives in any testing programme are important - especially when there is low prevalence of a disease - because they could potentially make us think there are significantly more cases of something than there really are. The false positive rate usually refers to the number of people who are not infected but get positive results, as a proportion of all the people tested who really don't have the virus. We do not know what the precise rate is though. Dr Paul Birrell, a statistician at the Medical Research Council's Biostatistics Unit at the University of Cambridge, says: "The false positive rate is not well understood and could potentially vary according to where and why the test is being taken. A figure of 0.5% for the false positive rate is often assumed." ## Randomness is the key The most important thing to know about the impact of false positives is that it varies hugely depending on who is being tested. What Hartley-Brewer said confused the idea of random testing with community testing for Covid. Those are two different situations, and false positives have a very different impact in each case. If you tested 1,000 people at random for Covid-19 in early September, for example, data from the Office for National Statistics (ONS) infection study suggests you should have expected one of them to actually have the virus. With a false positive rate of 0.8% - a figure used by Ms Hartley-Brewer and within the broad range of what we think might be the actual rate for community testing - you would get eight false positives. So in that context, it's true that roughly 90% of positives would be false. But - crucially - the people going for community testing for Covid-19 (at places such as drive-through centres) are not a random sample of the public. They are people who [have symptoms](https://www.bbc.co.uk/news/health-51048366), are in care homes or are in hot-spot areas. ![PA Media A car drives past a testing centre](https://ichef.bbci.co.uk/images/ic/1024x1024/p0hq72jn.png.webp)PA Media [Figures for late September](https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/923668/Weekly_COVID19_Surveillance_Report_week_40.pdf) from Public Health England show that 7% of community tests were positive. That means of every 1,000 people tested, 70 were positive. Even with a false positive rate of 0.8%, seven of those would be false positives, but 63 would be true positives - the vast majority. So the daily case count is not being skewed significantly by false positives. There will also be some false negatives, meaning that some people who actually have Covid are not being counted. When we put it to Hartley-Brewer that she had misinterpreted explanations of the impact of false positives, she pointed us to other articles that also discussed the impact on random samples of the population, rather than on people who are much more likely to have the virus. ## There are other signs of real positive results People do not get admitted to hospital by false positives, so if more people are in hospital with Covid, then you can be pretty sure that is due to genuine cases. The same is true of the number of deaths. Dr Birrell says that to be certain cases really are increasing, the daily case count "should always be considered alongside other information sources, such as the hospitalisations or deaths, or the community surveys run by the [ONS or REACT](https://www.bbc.co.uk/news/health-54387057)". Correction 7 October: The piece was corrected to show that 63 out of 1,000 people tested would be true positives if there was a 7% positivity rate and a 0.8% false positive rate. ![Banner image reading 'more about coronavirus'](https://ichef.bbci.co.uk/images/ic/1024x1024/p0hq72jn.png.webp) - SOCIAL DISTANCING: [What are the rules now?](https://www.bbc.co.uk/news/uk-51506729) - SUPPORT BUBBLES: [What are they and who can be in yours?](https://www.bbc.co.uk/news/health-52637354) - SCHOOLS: [What will happen if children catch coronavirus?](https://www.bbc.co.uk/news/education-51643556) - TESTING: [What tests are available?](https://www.bbc.co.uk/news/health-51943612) - LOOK-UP TOOL: [Check cases in your area](https://www.bbc.co.uk/news/uk-51768274) ![Banner](https://ichef.bbci.co.uk/images/ic/1024x1024/p0hq72jn.png.webp) More or Less is on BBC Radio 4 at 09:30 BST on Wednesdays and repeated at 16:30 on Fridays and 20:00 on Sundays. 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The BBC's Analysis Editor Ros Atkins charts how the Trump administration’s messaging on war has shifted in his second term. 3 days ago](https://www.bbc.com/news/videos/c4g00zngg13o) [19 Dec 2025 ![BBC Analysis Editor Ros Atkins and a still of a damaged hospital in Khartoum](https://ichef.bbci.co.uk/images/ic/1024x1024/p0hq72jn.png.webp) Ros Atkins on… The alleged links between the UAE and Sudan's civil war BBC Analysis Editor Ros Atkins examines allegations of links between the UAE and Sudan’s RSF in the civil war, as international efforts continue to seek an end to the fighting. 19 Dec 2025](https://www.bbc.com/news/videos/cly5p1vkm39o) [4 Dec 2025 ![US Secretary of War Pete Hegseth speaks during a cabinet meeting alongside President Donald Trump and US Secretary of Commerce Howard Lutnick in the Cabinet Room of the White House in Washington DC. ](https://ichef.bbci.co.uk/images/ic/1024x1024/p0hq72jn.png.webp) What legal experts say about second US strike on Venezuela boat Several legal experts have told BBC Verify that there was no legal basis for the second strike on an alleged Venezuelan drug boat by the US military. 4 Dec 2025](https://www.bbc.com/news/articles/c3v15zkxpe0o) [10 Nov 2025 ![BBC Analysis Editor Ros Atkins in front of the BBC headquarters in London](https://ichef.bbci.co.uk/images/ic/1024x1024/p0hq72jn.png.webp) Ros Atkins on... the BBC resignations The BBC's Analysis Editor Ros Atkins looks at the resignations of BBC bosses - 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Readable Markdown	3 October 2020 Simon Maybin and Josephine CasserlyMore or Less, BBC Radio 4 ![Reuters A drive through testing centre](https://ichef.bbci.co.uk/news/480/cpsprodpb/5255/production/_114577012_mediaitem114577008.jpg.webp)Reuters There has been a lot of talk on social media about "false positive" test results after several commentators suggested they might be seriously skewing the coronavirus figures - but that is based on a misunderstanding of the impact of false positives. Talk Radio host Julia Hartley-Brewer has claimed that "nine out of 10 of the positive cases of Covid we are finding in the community when we do random testing, when anyone just puts themselves forward, will be wrong. They will not be people who have got coronavirus." Could it be true that 90% of positive results from tests in the community - that means tests not carried out in hospitals - are false? The answer is "no" - there is no way that so-called false positives have had such an impact on the figures. Hartley-Brewer referred to both "random testing" and "anyone \[who\] just puts themselves forward", which are different things, and the difference between them is important. Also, there are many other signs that the rising number of positive tests is truly reflecting the virus spreading, for example a subsequent rise in Covid hospitalisations. What is a false positive? A false positive is when someone who does not have coronavirus, tests positive for it. No test is 100% accurate - there will always be some people who test positive when they do not have the disease, or test negative when they do have it. False positives in any testing programme are important - especially when there is low prevalence of a disease - because they could potentially make us think there are significantly more cases of something than there really are. The false positive rate usually refers to the number of people who are not infected but get positive results, as a proportion of all the people tested who really don't have the virus. We do not know what the precise rate is though. Dr Paul Birrell, a statistician at the Medical Research Council's Biostatistics Unit at the University of Cambridge, says: "The false positive rate is not well understood and could potentially vary according to where and why the test is being taken. A figure of 0.5% for the false positive rate is often assumed." Randomness is the key The most important thing to know about the impact of false positives is that it varies hugely depending on who is being tested. What Hartley-Brewer said confused the idea of random testing with community testing for Covid. Those are two different situations, and false positives have a very different impact in each case. If you tested 1,000 people at random for Covid-19 in early September, for example, data from the Office for National Statistics (ONS) infection study suggests you should have expected one of them to actually have the virus. With a false positive rate of 0.8% - a figure used by Ms Hartley-Brewer and within the broad range of what we think might be the actual rate for community testing - you would get eight false positives. So in that context, it's true that roughly 90% of positives would be false. But - crucially - the people going for community testing for Covid-19 (at places such as drive-through centres) are not a random sample of the public. They are people who [have symptoms](https://www.bbc.co.uk/news/health-51048366), are in care homes or are in hot-spot areas. ![PA Media A car drives past a testing centre](https://ichef.bbci.co.uk/images/ic/1024x1024/p0hq72jn.png.webp)PA Media [Figures for late September](https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/923668/Weekly_COVID19_Surveillance_Report_week_40.pdf) from Public Health England show that 7% of community tests were positive. That means of every 1,000 people tested, 70 were positive. Even with a false positive rate of 0.8%, seven of those would be false positives, but 63 would be true positives - the vast majority. So the daily case count is not being skewed significantly by false positives. There will also be some false negatives, meaning that some people who actually have Covid are not being counted. When we put it to Hartley-Brewer that she had misinterpreted explanations of the impact of false positives, she pointed us to other articles that also discussed the impact on random samples of the population, rather than on people who are much more likely to have the virus. There are other signs of real positive results People do not get admitted to hospital by false positives, so if more people are in hospital with Covid, then you can be pretty sure that is due to genuine cases. The same is true of the number of deaths. Dr Birrell says that to be certain cases really are increasing, the daily case count "should always be considered alongside other information sources, such as the hospitalisations or deaths, or the community surveys run by the [ONS or REACT](https://www.bbc.co.uk/news/health-54387057)". Correction 7 October: The piece was corrected to show that 63 out of 1,000 people tested would be true positives if there was a 7% positivity rate and a 0.8% false positive rate. ![Banner image reading 'more about coronavirus'](https://ichef.bbci.co.uk/images/ic/1024x1024/p0hq72jn.png.webp) - SOCIAL DISTANCING: [What are the rules now?](https://www.bbc.co.uk/news/uk-51506729) - SUPPORT BUBBLES: [What are they and who can be in yours?](https://www.bbc.co.uk/news/health-52637354) - SCHOOLS: [What will happen if children catch coronavirus?](https://www.bbc.co.uk/news/education-51643556) - TESTING: [What tests are available?](https://www.bbc.co.uk/news/health-51943612) - LOOK-UP TOOL: [Check cases in your area](https://www.bbc.co.uk/news/uk-51768274) ![Banner](https://ichef.bbci.co.uk/images/ic/1024x1024/p0hq72jn.png.webp) More or Less is on BBC Radio 4 at 09:30 BST on Wednesdays and repeated at 16:30 on Fridays and 20:00 on Sundays. It's also available on [BBC Sounds.](https://www.bbc.co.uk/sounds/series/p02nrss1) ![Presentational grey line](https://ichef.bbci.co.uk/images/ic/1024x1024/p0hq72jn.png.webp) ![Reality Check branding](https://ichef.bbci.co.uk/images/ic/1024x1024/p0hq72jn.png.webp) ![Presentational grey line](https://ichef.bbci.co.uk/images/ic/1024x1024/p0hq72jn.png.webp)
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