Distinguished University Professor of Health Science and Policy
University of Pittsburgh
The objective of the Models and Forecasts Project is to develop the next generation of flexible and high performance simulation methods to model infectious disease epidemics, and further to use these methods to develop a theory and practice of epidemic forecasting. This Project will create key components of an information supply chain: an integrated end-to-end decision support system that leads from data to decisions for effective public health decision-making. The results will provide new approaches for the scientific study of infectious disease transmission dynamics and a flexible framework of preparedness to support rapid decision making for emerging public health threats. The project addresses three specific aims: (1) Develop simulation methods at the population scale that improve our ability to model disease dynamics and to evaluate intervention policies. Advances will include novel multi-scale modeling methods that capture disease dynamics at multiple temporal and spatial scales, combining for the first time in a single framework: (a) models of intra-host course of infection, symptoms, and transmissibility, (b) cognitively plausible models of human health psychology, and (c) population-scale models of transmission. (2) Develop useful translational software tools for the research community and for the community of public health practitioners and educators. Access to user-friendly tools is especially important in state, county and municipal health departments, and adapting MIDAS platforms for use in training and education environments will help create a new generation of public health professionals with a better appreciation for the value of models in making wise public health decisions. (3) Promote the development of systematic methods for improving epidemic forecasting: (a) serve as a clearinghouse for both epidemic forecasters and consumers of epidemic forecasts (local, state and federal agencies, commercial organizations, and the general public); (b) establish common forecasting tasks and curate common datasets; and (c) hold a forecasting workshop to serve all of MIDAS's stakeholders as well as state and local health departments, DHHS, DHS, DoD, and other federal agencies.