Specific statistical models are available for estimating the risk that a gathering of N people includes at least one person with COVID-19; other models estimate the influence of airflow and other aspects of building design.
The above depend on local factors: who is likely to be infected, and how many; how much contact (or what “mixing,” as epidemiologists call it) is prevalent in a community; what the local schools are like.
But so much isn't known. We lack consistent regimes of testing, tracing, and isolation. Only 14 states make their tracing data public; So many cases (such a basic number!) are not found or included. And those who aren't included are likely to be in the out-of-the-way corners that are too easy to ignore (underpasses, prisons, streets; entire neighborhoods).
Living under uncertainty is its own psychological trauma, but having at the same time to include in all our calculations considerations of who might be forgotten is a tougher job still, whether we are calculating statistics or merely jotting up risks and benefits on our pads or in our heads.
Yet the forgotten are always closer than one thinks.
