This is v helpful thread from @scienceshared.

One thing missing is positive predictive and negative predictive values (PPV and NPV) that crucially depend on what proportion of people being tested have disease - the prevalence. https://twitter.com/ScienceShared/status/1326563891766243329

Take recent ONS survey - 1.1% of pop infected: PPV is 73%, meaning around 1 in 4 positive tests are false positives
(NPV is 99.7% - if you test -ve, you are)

Test 1000 people: there will be 8 true positives, 3 false positives, 3 false negatives, and 986 true negatives.

If in NW where prevalence is 2.2%, PPV rises to 84% (about 1 in 6 positive tests are false)

BUT in SE, prevalence is 0.5% meaning PPV is 55%, i.e. every other positive result is a false positive.

Of course, PPV will be much higher if you have symptoms, live with a case etc, but otherwise false positives from asymptomatic population screening remain an issue.

So as @ScienceShared says, positive tests in asymptomatic ppl should ideally be repeated or followed up with PCR.

And of course, as @angelaraffle has elegantly described, there are a whole range of reasons for caution and rigorous evaluation to mitigate unintended harm when it comes to population level screening. https://twitter.com/angelaraffle/status/1325870626482106370?s=20