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Activity Number: 577 - Statistical Models in Ecology
Type: Contributed
Date/Time: Wednesday, July 31, 2019 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistics and the Environment
Abstract #304360 Presentation
Title: Integrating Spatial-Capture Recapture Models into Spatially Explict Disease Simulations
Author(s): Robin Russell* and Daniel Walsh and Tonie Rocke and Martin Grunnill
Companies: US Geological Survey and US Geological Survey and US Geological Survey and US Geological Survey and University of Wisconsin
Keywords: spatial modeling; disease dynamics; capture-recapture models; wildlife; agent-based models

Modeling wildlife disease is complex, particularly because observing contacts and/or estimating contact rates is difficult. Spatial-capture recapture models estimate the density of animals and approximate locations or “activity center” of individuals based on traditional mark recapture data where the locations of traps have been recorded. This information can be used to estimate the relative frequency of contacts and the potential identity of interacting individuals to help inform disease transmission models. We demonstrate this application using mark-recapture data sets from a large scale study field-testing an oral sylvatic plague vaccine on prairie dogs (Cynomys spp.). We develop an agent-based, spatially-explicit model of plague transmission and integrate estimates of average animal movements from spatial-capture recapture models to parameterize contact rates between individuals. We present results from multiple species of prairie dogs and demonstrate how differences in density and movement affect contact rates and influence the dynamics of plague transmission (number of survivors, speed of transmission, probability of colony extinction).

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

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