Last I read, the antibody test was not particularly reliable ...
No, the issue with the antibody test is that if the actual incidence in the population of antibodies is very low, then the false positive/negative rates of the test make it difficult to trust the test.
For example, let's say there's a 1.5% prevalence of antibodies in the population, and the antibody test has a 1% false positive rate. As a result, you'll expect roughly a 2.5% positive result when you test that population.
That's problematic. First because if you're making population-level decisions, and 40% of your positive results are false, it's too big of a proportion. But second, if you're one of those people who received a positive antibody test, you only have 60% confidence that you ACTUALLY have antibodies. So personally do you know that you have actually had COVID when that positive test can only tell you with slightly better than a coin flip confidence?
Now, if you have 20% prevalence of antibodies in the population, and the antibody test has a 1% false positive rate, you'll expect to have a 20.8% positive result when you test that population. That's a much smaller error margin. And if you're one of those who was tested and received a positive result, you now have slightly better than 96% confidence that your test revealed actual antibodies and not a false positive.
Of course, that's a complex explanation for a complex phenomenon, and the only thing laypeople took from it was that the tests aren't reliable. And then blame "experts" for not knowing what they're talking about.
