[Question] How can we extrapolate the true prevalence of a disease, given available information?

Note: a similar question got more attention here so maybe check that out.

The motivation here is COVID-19, but I think there are useful general models in the area.

I’ve made a lot of risk assessment models over the last week, most of which depend on knowing the true infection rate of a population. That’s difficult to pin down at the best of times, but especially in the case of COVID-19. In the country I’m most familiar with, the US, there simply aren’t enough tests performed to provide good prevalence information. This post is for models extrapolating the true prevalence of a disease from information you have on hand.

This is an exploration thread, so don’t worry about it not being rigorous or defensible enough. I’ll be posting my own as an example in the answers section.