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