Inference and Forecast of Infectious Disease Spatial Temporal Dynamics

Inference and Forecast of Infectious Disease Spatial Temporal Dynamics Dr. Wan Yang (Columbia University, Mailman School of Public Health) Abstract: The spatial temporal dynamics of infectious diseases reflect disease transmission patterns and underlying mechanisms. Infectious disease modeling can help improve this understanding and make prediction toaid intervention and control planning. This talk will present two such examples using spatial network models in conjunction with Bayesian inference methods. In the first, we develop a meta-population network model inference system to reconstruct the transmission network of Ebola among districts across Sierra Leone during the recent 2014-2016 Ebola epidemic. In the second, we apply a similar model-inference framework to forecast influenza epidemics in boroughs and neighborhoods within New York City. Dept. of Epidemiology and Biostatistics Graduate School of Public Health and Health Policy The City University of New York 55 W. 125th Street, Room 543 NY, NY 10027