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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.

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