<i>Ov</i> CWD: An agent‐based modeling framework for informing chronic wasting disease management in white‐tailed deer populations
Aniruddha Belsare, Chad M. Stewart
Abstract
Abstract 1. Wildlife diseases are gathering attention worldwide due to their public health and economic or conservation impacts, and consequently, wildlife agencies are increasingly being tasked with disease surveillance and management responsibilities. 2. Wildlife disease surveillance and management is challenging primarily due to complex processes of host population dynamics, some of which are inherently stochastic in nature. Individual heterogeneity in pathogen transmission further complicates our understanding of wildlife disease systems. 3. Agent‐based models can incorporate stochasticity as well as individual heterogeneities and facilitate a better understanding of epidemiological processes in wildlife disease systems. Such an understanding is critical for designing and implementing effective disease control strategies. 4. We have developed a customizable agent‐based modeling framework ( Ov CWD) that incorporates nonrandom and heterogeneous aspects of an emerging host–pathogen system (chronic wasting disease [CWD] in white‐tailed deer). Models in this framework link white‐tailed deer demography and behavior with CWD transmission dynamics. Insights gained from model explorations can help us better understand CWD spread in regional deer populations. 5. We illustrate Ov CWD application by deriving CWD outbreak probabilities for Montcalm County (Michigan, USA) deer population using alternate harvest strategies. The focus is on preemptive harvest strategies that can be implemented before CWD is detected in a population (pre‐establishment phase). 6. Ov CWD provides a defensible decision‐making context for designing locally relevant CWD control strategies. Ov CWD can be readily adapted for simulating CWD in other cervid species as well as for simulating other cervid disease systems.