> Can you provide evidence that every antibody test used in all of the studies above are as inaccurate as you claim? Your 1-word opinion on each of them is useless.
To my knowledge, there are basically no reliable antibody tests, which is the problem. Some are more reliable, but most are terrible, and there are very few places that publish exactly which test they use have, from my reading, used unreliable tests.
The point, which you seem to keep ignoring is that seroprevalence tests aren't reliable. So citing a bunch of them doesn't convince me. You're just citing something which I've already explained isn't reliable.
So let's assume this is true. My understanding is that PCR tests have gotten a bit better since February when that paper was published, but it sets a decent lower bound.
Let's assume the test has a 30% false-negative rate, and a .05% false-positive rate. If 1% of people are infected, and you test everyone, you'll find that (.01 * .70) + (.99 * .0005) = .75% of the population will test positive.
What about 10% of the population? (.1 * .70) + (.9 * .0005) = 7% of the population is infected according to the test. Given that PCR tests are reporting ~1% of the population is infected, we can expect that no more than 2% of the population is infected. And that assumes an incredibly good false-positive rate.
If instead the PCR test has a more reasonable false-positive rate of half a percent, and we assume an underlying 1.5% infection rate, then with a 30% false negative rate, then P(FP|N) > P(FN|P), or in other words, your test would overestimate the true infection rate (to be 1.54%, precisely).
That is to say, when the underlying infection rate is relatively low, false-positives are much more impactful than false negatives, because there are many more chances to be a false positive. This is the base rate fallacy in action.
So the upshot? Even assuming a better than real world[0] false-positive rate of the PCR tests, and a likely worse than real world false-negative rate, the PCR tests show that the true infection rate is still far below what serological tests show.
To my knowledge, there are basically no reliable antibody tests, which is the problem. Some are more reliable, but most are terrible, and there are very few places that publish exactly which test they use have, from my reading, used unreliable tests.
The point, which you seem to keep ignoring is that seroprevalence tests aren't reliable. So citing a bunch of them doesn't convince me. You're just citing something which I've already explained isn't reliable.
> https://www.livescience.com/covid19-coronavirus-tests-false-....
So let's assume this is true. My understanding is that PCR tests have gotten a bit better since February when that paper was published, but it sets a decent lower bound.
Let's assume the test has a 30% false-negative rate, and a .05% false-positive rate. If 1% of people are infected, and you test everyone, you'll find that (.01 * .70) + (.99 * .0005) = .75% of the population will test positive.
What about 10% of the population? (.1 * .70) + (.9 * .0005) = 7% of the population is infected according to the test. Given that PCR tests are reporting ~1% of the population is infected, we can expect that no more than 2% of the population is infected. And that assumes an incredibly good false-positive rate.
If instead the PCR test has a more reasonable false-positive rate of half a percent, and we assume an underlying 1.5% infection rate, then with a 30% false negative rate, then P(FP|N) > P(FN|P), or in other words, your test would overestimate the true infection rate (to be 1.54%, precisely).
That is to say, when the underlying infection rate is relatively low, false-positives are much more impactful than false negatives, because there are many more chances to be a false positive. This is the base rate fallacy in action.
So the upshot? Even assuming a better than real world[0] false-positive rate of the PCR tests, and a likely worse than real world false-negative rate, the PCR tests show that the true infection rate is still far below what serological tests show.
[0]: https://www.medrxiv.org/content/10.1101/2020.04.26.20080911v... suggests that PCR tests have a false-positive rate of ~4%, on average.