Infectious diseases continue to cause significant domestic and global burden in epidemic and pandemic years. The occurrence of several pandemics in the last 20 years (influenza, Ebola, COVID-19, monkeypox) has shown the importance of computational modeling to understand transmission patterns, project the impact of interventions, and guide decision-making. The section of computational epidemiology and modeling of infectious diseases at DIEPS, FIC, NIH aims to answer critical questions about pathogen transmission, immunity, severity and risk factors, mobility and contacts, and vaccine benefits. We apply a variety of statistical and mathematical approaches to epidemiological information collected at different scales (from households to countries). Created in 2000, our focus has historically been on respiratory viruses, particularly influenza and respiratory syncytial virus, and expanded over the years to include a variety of pandemic threats (Ebola, MERS, SARS and COVID19) and endemic pathogens (antimicrobial resistance).
Current projects include research on the US COVID-19 and influenza
scenario modeling hubs, patterns of infection and immunity to SARS-CoV-2 in
South African cohorts, modeling the resurgence of endemic pathogens in the post-COVID19 period, respiratory virus surveillance and immunity
in the Seattle area, mobility and COVID-19 transmission, sero-epidemiology, and excess mortality.
Contact