This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 161
Type: Topic Contributed
Date/Time: Monday, August 2, 2010 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics and the Environment
Abstract - #306523
Title: Statistical Challenges in Modeling Wildlife Diseases
Author(s): Jennifer A. Hoeting*+ and Andrew A. Merton and Colleen T. Webb
Companies: Colorado State University and Colorado State University and Colorado State University
Address: Department of Statistics, Fort Collins, CO, 80523-1877,
Keywords: Spatial statistics ; Bayesian statistics ; Disease models ; partial differential equations ; Network models

Modeling infectious diseases in wildlife is challenging for many reasons. While there are well-known mathematical models for disease transmission, some diseases are rare (few positives). In addition, the data can be sparse over time and/or space with missing and correlated observations. Yet there is a great need for risk assessment and surveillance, especially given the possibility for disease spread to humans or the potential economic impact of some diseases. We will discuss how we met some of these statistical challenges in our development of models for two large scale surveillance studies in North America. We developed a new network-modeling framework to assess wildlife movement. We will also describe a Bayesian hierarchical model for disease transmission over time which incorporates a process model for disease dynamics and accommodates multiple data and error sources.

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