I found this snippet which describes what I've been trying to say.
Although I’m currently a practicing attorney, in a prior career I was a researcher and a published statistical data analyst with the Washington University School of Medicine. I have a master’s degree in public health. And I have grave concerns about the numbers that the State of Illinois (and other states) are using to make decisions about closing down large facets of our economy. The so-called “positivity rate” doesn’t tell us the full story about what is happening in the community with this disease.
As a quick example, if 100 people are tested for COVID-19 right now, it is extremely likely that they are being tested because they are sick, or because they have recently been in close contact with someone who has tested positive. If 6 of those people test positive (a 6% “positivity rate”) or 8 test positive, (an 8% “positivity rate”), does that tell us what the rate of positive tests are in the community? No. Because it is very possible – even probable – that the folks being tested are more likely to have a positive test result. Again, they may have felt sick or have been in close proximity to someone who is. So of course the percent with a positive result can be higher than in the general population. In science, this is called “selection bias,” or “ascertainment bias.” More thorough definitions of selection and ascertainment bias can be found online. One researcher described exactly this problem in a very recently-published article. “A crude measure of population prevalence [of COVID-19] is the fraction of positive tests at any given date. However, this is subject to large ascertainment bias since tests are typically only ordered from symptomatic cases, whereas a large proportion of infected might show little to no symptoms…”