Carl Heneghan

How many Covid diagnoses are false positives?

Picture credit: Getty

Test, test, test said the WHO. And globally, that’s what everyone did: tests have detected more than 14 million cases of Sars-CoV-2 so far. The thinking goes: turn up, have your test, and if positive, you must have the disease. But that’s far from the truth. When virus levels in the population are very low, the chances of a test accurately detecting Covid-19 could be even less than 50 per cent – for reasons that are not widely understood.

There are two issues about tests to get your head around. The first is the sensitivity of the test: the proportion of people who test positive, out of the population who have the virus. The second measure, specificity, is about the proportion of people who test negative, out of the population who should have tested negative. Finding out the actual values of these two measures is tricky. The Office for National Statistics admits they do not ‘know the true sensitivity and specificity of the test because Covid-19 is a new virus’.

There are two issues about tests to get your head around: sensitivity and specificity

Estimates suggest that roughly 80 per cent of infected people will have a positive test (the sensitivity). Based on the latest data, specificity may be as high as 99.9 per cent for those who test negative. I think this is a bit high, but let’s run with it for now.

To unravel the confusion, let’s think about what happens when the virus level is low – which it is in Britain at the moment. The latest ONS estimate is that about 0.04 per cent, or one in 2,300 people, had the virus at any point between 6 and 12 July. But for ease of calculation, let’s imagine the real infection level is higher: that 1 in 1,000 of us have the virus.

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