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

• DOI: 10.48550/arxiv.2309.07146
• Publication Date: 2023-01-01
• Authors: Santiago Rosa; Manuel Pulido; Juan Ruiz; Tadeo Javier Cocucci
• Keywords: Pandemic; Basic reproduction number; Susceptible individual; Ensemble forecasting; Social distance

The COVID-19 pandemic and its multiple outbreaks have challenged governments around the world. Much of epidemiological modeling was based on pre-pandemic contact information population, which changed drastically due to governmental health measures, so called non-pharmaceutical interventions made reduce transmission virus, like social distancing complete lockdown. In this work, we evaluate an ensemble-based data assimilation framework applied a meta-population model infer disease between different population agegroups. We perform set idealized twin-experiments investigate performance possible parameterizations matrix. These experiments show that it is not unambiguously estimate all independent parameters However, under certain parameterizations, matrix in age-compartmental can be estimated. estimated lead increase forecast accuracy agegroups compartments assimilating age-dependent accumulated cases deaths observed Argentina compared single-compartment model, reliable estimations effective reproduction number. forecasting virus may important for accurate prediction diagnosis care demand.