A system dynamics model to understand the integrated ecological and human dimensions of managing chronic wasting disease

Chronic wasting disease (CWD) presents an ongoing challenge for managing deer populations and sustaining recreational opportunities across North America. Existing disease models rarely capture the complex interplay among disease dynamics, host ecology, and socio-economic factors. We developed a comprehensive system dynamics (SD) model that integrates demographic, epidemiological, ecological, and socio-economic processes within a single model to more fully characterize the complex network of causal feedbacks throughout the system. The model was calibrated using a Bayesian approach that incorporates prior knowledge to generate interpretable outcomes despite sparse data. To estimate the joint posterior distribution of parameters, we leveraged time series of deer abundance, harvest composition, genetic profiles, CWD surveillance, and hunter demographics and behavior. Model outputs reproduced key system behaviors, including observed CWD prevalence trends, deer population dynamics, and hunter license purchasing patterns. Predictions were most sensitive to parameters governing initial population size and recruitment. While model outputs generally aligned with observed data, discrepancies in early CWD detection and overestimation of hunter reactivation highlight data and modelling limitations. Results suggest indirect transmission and moderate density-dependence in transmission are necessary to explain observed prevalence, and CWD-driven population-level genetic shifts may also influence transmission and progression. The SD approach enabled estimation of difficult-to-measure parameters and identified actionable leverage points for management, such as prioritizing increased antlerless harvest among existing hunters over recruiting new hunters. This integrated modelling approach provides a flexible foundation for adaptive wildlife disease management and emphasizes the value of unifying biological and human dimensions to support effective, evidence-based policy.