2018-02-08 - Chris Groendyke - Bayesian Inference for Contact Network Models using Epidemic Data

I will discuss how network models can be used to study the spread of epidemics through a population, and in turn what epidemics can tell us about the structure of this population. I apply a Bayesian methodology to data from a disease presumed to have spread across a contact network in a population in order to perform inference on the parameters of the underlying network and disease models. Using a simulation study, I will discuss the strengths, weaknesses, and limitations of this type of these models, and the data required for this type of inference. Finally, I will describe an analysis of an actual measles epidemic that spread through the town of Hagelloch, Germany, in 1861 and share the conclusions it allows us to make regarding the population structure.
Robert Morris University
Feb 8, 2018