  There has been much recent interest in screening populations for an
infectious disease. Here, we present a stochastic-control model, wherein the
optimum screening policy is provably difficult to find, but wherein Thompson
sampling has provably optimal performance guarantees in the form of Bayesian
regret. Thompson sampling seems applicable especially to diseases, for which we
do not understand the dynamics well, such as to the super-spreading COVID-19.
