I will share our experience of COVID-19 modeling in collaboration with Alberta Health. Simple mathematical models that incorporate human behaviours informed by data, in conjunction with advanced Bayesian-inference-based model calibration algorithms, have proved to be powerful tool for producing reliable long-range projections of the epidemics, as well as retrospective estimations of important quantities such as the fraction of infected populations, and provide dependable modeling results to inform public health decision making.

Bio: Dr. Michael Li is a Professor of Mathematics at the University of Alberta and expert on mathematical theories of epidemic models. His modeling experience includes estimation of HIV incidence and prevalence in China in collaboration with China CDC, TB dynamics on Indigenous communities in Alberta, and predictions for seasonal influenza in collaboration with Alberta Health . He served as the Director of Applied Math institute and leads the Information Research Lab at the University of Alberta. His research interests include . During the COVID-19 pandemic, his research group provided modeling support for Alberta Health.