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Activity Number: 661 - Statistical Models for Animal Behavior and Population Dynamics
Type: Contributed
Date/Time: Thursday, August 1, 2019 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics and the Environment
Abstract #306375
Title: Combining Animal Movement and Spatial Disease Data for Prediction of Wildlife Disease Spread
Author(s): Sahar Zarmehri* and Ephraim Hanks and Lynn Lin
Companies: Penn State and Pennsylvania State University and Penn State University
Keywords: Infectious disease spread; Animal movement; Spatio-temporal model

In this paper, we build a stochastic disease spread model for binary observations in time and space by combining disease surveillance and animal movement data. We propose a mechanistic Susceptible-Infected-Susceptible (SIS) process that governs the mean disease spread model. We add random noise to Euler approximation of the SIS process to capture extra variations in time and space. To inform spatial rates of transmission, we use host movement data to construct a probability transition matrix (PTM) based on animal movement models. We apply this model to elk serology data of Brucellosis in the Greater Yellowstone Ecosystem (GYE) combined with the GPS data of 1400 collared elk. Because of the asynchrony in data collection, we construct PTM by first fitting a fine resolution movement model to the available GPS data. We then use a computationally-fast approach to construct aggregated PTM in time and space.

Authors who are presenting talks have a * after their name.

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