An expert-elicited approach to inform proactive risk assessments for chronic wasting disease in white-tailed deer

One of the most rational and successful ways to mitigate the effects of wildlife disease is to perform proactive management efforts that can either prevent disease prior to first exposure or detect and eradicate disease prior to its establishment. However, estimating the risk of wildlife disease in new locations is often challenged by a lack of tractable linkages between known or presumed disease hazards and comprehensive risk of introduction and spread. In this study, we present a low-cost approach that estimated comprehensive risk of chronic wasting disease (CWD) in Michigan, United States, based on the localized knowledge of experts and the use of existing datasets. We controlled for sources of expert bias, avoided group conflict that may challenge qualitative risk assessments, and generated estimates of risk that aligned with known positives and can be used in targeted surveillance and mitigation efforts. We found that 97% of CWD detections fell within high risk counties, with only 3 out of 117 cases (3%) falling in counties at low risk. Furthermore, we found coherence between indirect expert-elicited risk estimates and direct hazard rankings, suggesting that an indirect approach maximized expert knowledge sharing while controlling for sources of potential bias. Lastly, our approach required limited time commitment from group participants and thus, represented a low-cost decision-making approach. Taken together, our study may provide an opportunity to mount proactive wildlife disease management in a way that has often been promoted but rarely accomplished.