Bayesian Estimation of the Seroprevalence of Antibodies to SARS-CoV-2

ABSTRACT Accurately estimating the seroprevalence of antibodies to SARS-CoV-2 requires the use of appropriate methods. Bayesian statistics provides a natural framework for considering the variabilities of specificity and sensitivity of the antibody tests, as well as for incorporating prior knowledge of viral infection prevalence. We present a full Bayesian approach for this purpose, and we demonstrate the utility of our approach using a recently published large-scale dataset from the U.S. CDC.