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Identifiability and Interacting Scales in Modeling Disease Dynamics

Tuesday, April 7, 2015
12:00 AM
411 West Hall

Disease dynamics involve interacting factors at multiple scales, and modeling these processes can involve working with a wide range of (sometimes incomplete) data sets. I will discuss identifiability and parameter estimation of disease transmission models, and examine how these issues are affected when incorporating processes and data from a range of scales (from cellular to environmental). I will highlight examples from some of our recent work, including applications to cholera, human papillomavirus (HPV), and influenza transmission on social networks.

Marisa Eisenberg, Assistant Professor Epidemiology, SPH, University of Michigan