Heads up econofolks: data that are *generated* by testing -- such as, say, indicators of who has a disease or who has antibodies in their blood -- are subject to various false positive / false negatives issues that the data we use in economics usually are not.

More here: https://statmodeling.stat.columbia.edu/2020/04/19/fatal-flaws-in-stanford-study-of-coronavirus-prevalence/

Also, if the goal is to infer rate of X in the population, non-random sampling from that population (especially with selection in based on unobservables) is going to absolutely torpedo that inference in a way it *might* not have for inferring relationship between X and Y say.

which is all to say, the toolbox and set of basic assumptions you're used to in econometrics is NOT a useful guide to this problem. PLEASE STAY HOME INTELLECTUALLY AS WELL AS PHYSICALLY.