Incorporating genomic sequences into infectious disease transmission modeling to improve the forecasting and analysis

The recent COVID-19 pandemic has highlighted the growing importance of infectious disease forecasting and analysis. An accurate and robust predictive model can empower public health leaders to make timely decisions on social distancing and vaccination policies, thereby reducing the number of infections and severe cases. However, the emergence of new variants and subvariants of SARS-CoV-2 virus has significantly altered the immunity to, transmissibility and virulence of the virus in a short time, making the number of cases, hospitalizations and deaths difficult to model and predict. We aim to develop a mathematical transmission model that incorporates genomics data to better project epidemics and model infectious disease transmission and control.