[logjammin]

This is a problem of insufficient data. We don't have a denominator, so there's no way to tell if it's more widespread than we thought. In fact there's no good way to tell how widespread it is at all. We have numerators: number of people sick enough to show to up to an ER, or number dead, or whatever, take your pick. But in every fraction we might want, we lack a denominator: total number of people infected.

There's a stuningly simple way to get one: sample randomly from a population of interest in large enough numbers (say e.g. Cook County, home of Chicago, or hell, the entire US) and test everyone for the virus. Voila! You have a representative chunk of your population, an estimate of virus prevalence, and a quantifiable degree of precision about that estimate (SE's for a confidence interval, say). With enough people in your sample, you can have extremely accurate estimates of the spread of Covid in your population of interest. You repeat this process over and over, through time, to track the numbers.

I'm not trivializing this kind of effort: it takes rigorous sampling designs and dozens or hundreds of field workers, among other things. It's intense but very straightforward. Political pollsters (and thousands of researchers in different fields) do it every day.

No one in the US has done this, and no one with any visibility from Fauci on down has even suggested it (that I know of; please correct me). I work in public health, and this is first year, first semester of grad school stuff.

This matters because the public health responses to coronavirus when there's 1% or 10% or 25% or 75% of a population infected all look very different. In short, we may be over- or underreacting to the situation with the measures we currently have in place.

I've been going half crazy wondering what's happening about this for a while now. After the initial fuckup, we now have tests. We have money. We can do this. Why don't we?

(Iceland has done this!)

[oldgradstudent]

> I'm not trivializing this kind of effort: it takes rigorous sampling designs and dozens or hundreds of field workers, among other things. It's intense but very straightforward. Political pollsters (and thousands of researchers in different fields) do it every day.

I am trivializing it, when compared to the cost of stopping down there economy as we've done.

If there a chance the results can restart the economy a bit earlier, it almost doesn't matter how much it will cost.

[a9h74j]

A Stanford MD PhD who had a recent article in the Wall St Journal was interviewed on video[1]. In the video he refers to this very denominator-related test being forthcoming. There are two things I don't understand. First, why did this have to wait for some approved(?) antibody test, rather than being tried with a presumably research-grade test to start?? Second (physicist talking here), to get a rough estimate (to within a factor) whether exposure has already silently _significantly_ spread, why not relax some rigor in the sampling design and just sample 100-1000 geographically-diverse people to get _some_ estimate that could at least speak to the "is exposure already widespread?" question?

[1] https://www.youtube.com/watch?v=-UO3Wd5urg0

[woodandsteel]

My understanding is this hasn't been done yet because we still don't have enough tests for all the people who have symptoms or might have the disease due to circumstances. But the number of available tests is going up very rapidly, so maybe pretty soon we will be able to do that sort of study.

Of course, our stable genius president has been insisting for months that there is no shortage of tests.

By the way, another way to go at this question is to test for antibodies, and that is also being developed very rapidly.