The basic error presented here is the assumption that all PCR tests are run on a random population sample of the UK, for which the prevalence is 1/1000 This is inaccuratepic.twitter.com/5otBWj16Gn
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The basic error presented here is the assumption that all PCR tests are run on a random population sample of the UK, for which the prevalence is 1/1000 This is inaccuratepic.twitter.com/5otBWj16Gn
Most PCR tests in the UK (and everywhere) are run on the SUSPICION of COVID-19 In other words, it's a SELECTED POPULATION with a HIGHER PREVALENCE
We can see this in the % positive of COVID-19 tests run in the UK. While it's relatively low now, it is still above 1% (i.e. >1/100 tests run come back positive)pic.twitter.com/nozHjsCgaE
In other words, we EXPECT the rate of true positives to be FAR HIGHER in those receiving PCR tests than in the general population BY DESIGN So the central premise of the article is completely flawed
I'd say it's not unlikely that there are 10-20% false positives, depending on the population sampled, but since many/most people who get a positive PCR test are re-tested it's largely a non-issue in terms of the statistics
Anyway @MichaelYeadon3, probably worth correcting the factual mistakes in your piece, they are currently rather glaring
Oh, and some more on PCR tests and the actual rate of false positives from @MackayIMhttps://virologydownunder.com/and-another-thing-on-false-positives/ …
I should also clarify that, as has been pointed out to me, 10-20% false positives for PCR testing of COVID-19 is unlikely except in areas of vanishingly low prevalence where enormous community testing is taking place. In the UK, it's probably closer to 0%
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