Reply to post: Re: How will they know it's a false alarm?

NHS tests COVID-19 contact-tracing app that may actually work properly – EU neighbors lent a helping hand

RayG

Re: How will they know it's a false alarm?

6% testing positive for antibodies doesn't necessarily mean 6% exposed - it's a serious over-claim to say 6% antibody positive means 6% have had it.

- The kind of antibodies we test for aren't the only immune mechanism, so there are certainly cases of people having defeated an infection but who would never test positive for those particular antibodies.

- Even for those people who did produce the tested antibodies, the antibody level also falls off over time - so someone who had the disease and their body responded that way five months ago, in March when it was probably much more prevalent than now, might test negative today. This isn't really a "false" negative, but a sensitivity threshold that prevents the test from having an unacceptably high rate of false positives. The body can ramp up production of previous antibodies from incredibly low levels so it doesn't tend to hang on to huge stocks forever.

If the study really meant only 6% ever having had the disease, that would tell us that it probably wasn't very infectious (even if you unsafely assume "lockdown" was highly effective, it was in the country for some time before that). Frankly, that conclusion seems very odd. If instead it were 6% falling into the narrow category of people who had it, and responded with the kind of antibody we can test for, recently enough to show up - that would suggest that rather more than 6% of people have got over it already but maybe it was quite infectious after all. Less qualified conclusions are much harder to draw.

Unfortunately nobody seems to have any solid data on whether people in either of those "had it, but won't show on the antibody survey" categories retain some resistance to catching it again, though it is quite likely. I don't know how prevalent sars-cov-2 is, but I do know (through my work) that there is a serious epidemic of poor-quality scientific papers going on. Symptoms include unverified assumptions in conclusion sections. Read with caution.

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