To characterize COVID-19 transmission dynamics in each of the 15 most populous metropolitan statistical areas (MSAs) in United States, we constructed a compartmental model accounting for effects of multiple distinct periods of non-pharmaceutical interventions by adding consideration of vaccination and mutation variants. For each MSA, we used Bayesian inference to calibrate region-specific models for consistency with daily reports of confirmed cases. This online learning approach enables early identification of new trends despite considerable variability in case reporting. In this talk, I will present the compartmental model and Bayesian uncertainty quantification in parameter estimates and forecasts.
Math Bio Seminar
November 18, 2022
11:30 AM - 12:30 PM, Arizona time
WXLR A309 and Virtual via Zoom
Those joining remotely can use the link: https://asu.zoom.us/j/7048540230
Department of Mathematics
Northern Arizona University