People need to look up Bayes' theorem. if a test is 99% sensitive and 99% specific, and the population sick is 1%, what is the probability that a person who tested positive is actually sick? The number is 1 out of 2.
So what happens is that when the % of sick people is really low, the false positives are very high.
I looked at the numbers yesterday. If the actual sick is 2%, the positive will be slightly more than 60%. Now, if the sick is 5%, then the test will be correct more than 90% of the time.
If I had to guess, not many sick people out there. I don't buy the 2 to 5%.