Estimating SARS-CoV-2 seroprevalence and epidemiological parameters with uncertainty from serological surveys.

ABSTRACT: Establishing how many people have been infected by SARS-CoV-2 remains an urgent priority for controlling the COVID-19 pandemic. Serological tests that identify past infection can be used to estimate cumulative incidence, but the relative accuracy and robustness of various sampling strategies have been unclear. We developed a flexible framework that integrates uncertainty from test characteristics, sample size, and heterogeneity in seroprevalence across subpopulations to compare estimates from sampling schemes. Using the same framework and making the assumption that seropositivity indicates immune protection, we propagated estimates and uncertainty through dynamical models to assess uncertainty in the epidemiological parameters needed to evaluate public health interventions and found that s

SUBMITTER: Larremore DB 

PROVIDER: S-EPMC7979159 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature