Estimation of the fraction of COVID-19 infected people in U.S. states and countries worldwide.

ABSTRACT: Since the beginning of the coronavirus disease 2019 (COVID-19) pandemic, daily counts of confirmed cases and deaths have been publicly reported in real-time to control the virus spread. However, substantial undocumented infections have obscured the true size of the currently infected population, which is arguably the most critical number for public health policy decisions. We developed a machine learning framework to estimate time courses of actual new COVID-19 cases and current infections in all 50 U.S. states and the 50 most infected countries from reported test results and deaths. Using published epidemiological parameters, our algorithm optimized slowly varying daily ascertainment rates and a time course of currently infected cases each day. Severe under-ascertainment of COVID-19 cases

SUBMITTER: Noh J 

PROVIDER: S-EPMC7869996 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature