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June 21-22, 2021
Agent-Based Models (ABMs) are widely used in epidemiology, with notable applications to Ebola, malaria, and COVID-19. However, the statistical properties of these models are underdeveloped, which makes quantified statements of uncertainty about forecasts difficult. Additionally, there is no standard theory for how to fit parameters in such models, nor how to assess model adequacy. On the other hand, the flexibility and face-validity of ABMs is a powerful tool for conducting “what-if” simulations that can guide public policy. This workshop brings together experts to discuss the capabilities, limitations, and potential pitfalls of ABM use in studying disease spread.
Confirmed speakers/panelists:
Paul Birrell, National Infection Service, UK
Georgiy Bobashev, RTI
Sara Del Valle, Los Alamos National Laboratory
Jonathan Fintzi, NIH
M. Elizabeth Halloran, Fred Hutchinson Cancer Research Center/University of Washington
Mevin Hooten, Colorado State University
Nianqiao (Phyllis) Ju, Harvard University & Purdue University
Chris Krapu, Oak Ridge National Laboratory
Lucy M. Li, The Public Health Company
Jessica Notestine, NCSU
Bruce Rogers, formerly Duke
Toryn Schafer, Cornell University
Simon Spencer, University of Warwick
Anuj Srivastava, Florida State University