Gerardo Chowell, Forecasting Infectious Disease Epidemics Using Dynamic Modeling: Ebola and Zika as Case Studies - Descripción
Mathematical modeling offers a powerful toolkit to improve our understanding of infectious disease transmission and control. The increasing use of mathematical models for epidemic forecasting has highlighted the importance of designing reliable models that capture the baseline transmission characteristics of specific pathogens and social contexts. More refined models are needed however, in particular to account for variation in the early growth dynamics of real epidemics and generate improved forecasts. I will present recent disease forecasting efforts in the context of Ebola and Zika epidemics and review recent progress on modeling and characterizing early epidemic growth patterns from infectious disease outbreak data.
Gerardo Chowell, Forecasting Infectious Disease Epidemics Using Dynamic Modeling: Ebola and Zika as Case Studies - Biografía
Gerardo Chowell, Ph.D. is a Second Century Initiative Scholar (2CI) and a Professor of Epidemiology and Biostatistics at Georgia State University in Atlanta. He is also a Senior Fellow in the Division of International Epidemiology and Population Studies at the Fogarty International Center, NIH. Dr. Chowell holds a PhD in Biometry from Cornell University. After obtaining his PhD, he was awarded a Director’s Funded Postdoctoral Fellowship to support his mathematical modeling research program at the Theoretical Division of Los Alamos National Laboratory. Dr. Chowell’s academic career has primarily focused on the development and calibration of mathematical and computational models of infectious disease transmission to assess the transmission potential of emerging and re-emerging infectious diseases, generate disease forecasts, quantify the effect of control interventions, and test public health policy. He is currently a member of Editorial Boards of several key journals including BMC Medicine, BMC Infectious Diseases, PLOS ONE, Scientific Reports, Mathematical Biosciences and Engineering, the Journal of Infectious Disease Dynamics, and Infectious Disease Modeling.