Using Contact Networks and Mortality Patterns to Estimate Epidemiological Process Parameters

• Activity Number: 288
• Type: Contributed
• Date/Time: Tuesday, August 5, 2014 : 8:30 AM to 10:20 AM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Kezia Manlove*+
• Companies: Penn State
• Keywords: infectious disease ; mechanistic model ; approximate Bayesian computation ; social network analysis ; survival analysis

Abstract

Advances in social network analysis and parameter estimation for mechanistic process models are changing the way that scientists study infectious disease. Although classic epidemiological models assumed that populations mix homogeneously, recent work shows that epidemic size is partially determined by heterogeneity in host mixing. Here we studied how the homogeneity assumption impacts parameter estimation for a bighorn sheep population with recurrent juvenile disease. First, we constructed contact networks for 46 birth cohorts, and used variance decomposition to quantify how host contact structures, year-specific, and population-specific factors contribute to epidemic severity. Greater than 92.5% of the variation was attributed to contact structures. We then generated approximate posterior distributions for two parameters related to epidemic spread, 1) number of outbreak starting points, and 2) disease-induced mortality rate. A comparison of posteriors from homogeneous and network-based contact structures suggested that failing to account for contact heterogeneity led to biased parameter estimates, and substantially changed perceptions about the system's epidemiological process.