Transmission matrix parameter estimation of COVID-19 evolution with age compartments using ensemble-based data assimilation.

ABSTRACT: The COVID-19 pandemic, with its multiple outbreaks, has posed significant challenges for governments worldwide. Much of the epidemiological modeling relied on pre-pandemic contact information of the population to model the virus transmission between population age groups. However, said interactions underwent drastic changes due to governmental health measures, referred to as non-pharmaceutical interventions. These interventions, from social distancing to complete lockdowns, aimed to reduce transmission of the virus. This work proposes taking into account the impact of non-pharmaceutical measures upon social interactions among different age groups by estimating the time dependence of these interactions in real time based on epidemiological data. This is achieved by using a time-dependent tr

SUBMITTER: Rosa S 

PROVIDER: S-EPMC12036932 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature