An individual-based model for direct and indirect transmission of chronic wasting disease in free-ranging white-tailed deer

Chronic wasting disease (CWD) is an infectious prion disease that infects members of the Cervidae family (i.e., deer) resulting in widespread ecological, economic, and recreational ramifications. We introduce a spatially explicit individual-based model (IBM) that integrates individual deer movement and behavior with population and disease dynamics to forecast CWD in populations of free-ranging white-tailed deer (Odocoileus virginianus). We use a Susceptible-Exposed-Infectious-Dead (S-E-I-D) epidemiological framework to explore spatiotemporal dynamics of CWD within an agriculturally dominated area in Michigan, USA. The IBM results closely mimicked documented short- and long-term dynamics of white-tailed deer populations and CWD in the Midwestern, USA. We applied pattern-oriented modeling using annual apparent CWD prevalence rates reported by Midwestern state wildlife agencies to validate the disease model. The introduction of a single infected deer to the modeled landscape (93 km2) led to an outbreak of CWD in 100 out of 350 model simulations (29 %); prevalence never exceeded 1.47 % for repetitions where the outbreak ended. For the 100 simulations where disease persisted, the deer population declined by 87 % by year 50 following initial introduction of CWD. Mean (+/- SD) prevalence after 5, 10, 25, and 50 years was 1.1 % (+/- 1.0 %), 3.4 % (+/- 3.3 %), 46.5 % (+/- 18.8 %), and 51.8 % (+/- 18.1 %), respectively, which highly correlated (r = 0.99) with annual CWD prevalence reported in Wisconsin white-tailed deer populations for years 1-21 post initial detection. Combined with a global sensitivity analysis, the IBM indicated that prevalence of CWD at year 20 was most sensitive to harvest rate of yearling and adult female deer and least sensitive to prion shedding rate, prion half-life, and deer group numbers, indicating that deer population parameters were more influential than disease parameters on CWD dynamics. Our IBM serves as a tool to explore and better understand indirect and direct transmission of CWD within free-ranging cervid populations. Users of this model can adjust parameter values to explore how interactions among individual deer and between deer and their environment affect CWD dynamics. This IBM also serves as a framework for applying and assessing spatially and temporally explicit management scenarios.