Just finished analyzing the info in the link you posted. The person with a post doctorate degree that wrote the article doesn't even understand the difference between false positive and false negative. I worked at a university for over a decade and a lot of professors were incompetent in my opinion.

"These rates may sound low, but when the rate of infection is low, even a small false-positive rate can greatly diminish the reliability of positive test results. For example, consider the scenario diagrammed below, in which 100,000 people are tested, with 1 percent, or 1,000 of them, being infected. If the false-negative rate is 25 percent, a typical estimate from the scientific literature on COVID-19, and the false positive rate is 0.5 percent, a reasonable estimate from our data, then a quarter of the 1,000 samples from infected individuals – that is, 250 samples – will be false negatives, and the rest will be true positives."

Do you see the mistake??? Out of 1,000 positive samples there will be zero false NEGATIVES and 0.5 percent false positive so 5 false positives out of a thousand positives so 995 true positives. What an imbecile! Out of the 100,000 tested, with 25 percent false negative that means around 25,000 people were positive but received a negative result likely due to a low viral load so add that to 995 and it would mean around 25,995 infections out of 100,000 people tested.