Computational Model Library

Displaying 5 of 5 results chronic wasting disease clear filters

Peer reviewed INOvCWD

Aniruddha Belsare | Published Wednesday, June 01, 2022 | Last modified Wednesday, July 10, 2024

INOvCWD is a spatially-explicit, agent-based model designed to simulate the spread of chronic wasting disease (CWD) in Indiana’s white-tailed deer populations.

Peer reviewed MOOvPOP

Aniruddha Belsare Matthew Gompper Joshua J Millspaugh | Published Monday, April 10, 2017 | Last modified Tuesday, May 12, 2020

MOOvPOP is designed to simulate population dynamics (abundance, sex-age composition and distribution in the landscape) of white-tailed deer (Odocoileus virginianus) for a selected sampling region.

Peer reviewed MOOvPOPsurveillance

Aniruddha Belsare Matthew Gompper Joshua J Millspaugh | Published Tuesday, April 04, 2017 | Last modified Tuesday, May 12, 2020

MOOvPOPsurveillance was developed as a tool for wildlife agencies to guide collection and analysis of disease surveillance data that relies on non-probabilistic methods like harvest-based sampling.

Peer reviewed MIOvCWD

Aniruddha Belsare | Published Friday, December 13, 2019

MIOvCWD is a spatially-explicit, agent-based model designed to simulate the spread of chronic wasting disease (CWD) in Michigan’s white-tailed deer populations. CWD is an emerging prion disease of North American cervids (white-tailed deer Odocoileus virginianus, mule deer Odocoileus hemionus, and elk Cervus elaphus) that is being actively managed by wildlife agencies in most states and provinces in North America, including Michigan. MIOvCWD incorporates features like deer population structure, social organization and behavior that are particularly useful to simulate CWD dynamics in regional deer populations.

Peer reviewed MIOvPOPsurveillance

Aniruddha Belsare | Published Monday, April 13, 2020

MIOvPOPsurveillance is set up to simulate harvest-based chronic wasting disease (CWD) surveillance of white-tailed deer (Odocoileus virginianus) populations in select Michigan Counties. New regions can be readily added, also the model can be readily adapted for other disease systems and used for informed-decision making during planning and implementation stages of disease surveillance in wildlife and free-ranging species.

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