Tracking the transmission dynamics of COVID-19 with a time-varying coefficient state-space model.

ABSTRACT: The spread of COVID-19 has been greatly impacted by regulatory policies and behavior patterns that vary across counties, states, and countries. Population-level dynamics of COVID-19 can generally be described using a set of ordinary differential equations, but these deterministic equations are insufficient for modeling the observed case rates, which can vary due to local testing and case reporting policies and nonhomogeneous behavior among individuals. To assess the impact of population mobility on the spread of COVID-19, we have developed a novel Bayesian time-varying coefficient state-space model for infectious disease transmission. The foundation of this model is a time-varying coefficient compartment model to recapitulate the dynamics among susceptible, exposed, undetected infectious,

SUBMITTER: Keller JP 

PROVIDER: S-EPMC9111166 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature