Affiliation:
1. U.S. Geological Survey, Eastern Ecological Science Center (Patuxent Wildlife Research Center), SO Conte Anadromous Fish Research Lab Turners Falls Massachusetts USA
2. Rubenstein School of Environment and Natural Resources University of Vermont Burlington Vermont USA
3. Department of Zoology & Physiology University of Wyoming Laramie Wyoming USA
4. U.S. Fish and Wildlife Service East Lansing Michigan USA
5. U.S. Fish and Wildlife Service, Branch of SSA Science Support Fort Collins Colorado USA
Abstract
AbstractWildlife disease management decisions often require rapid responses to situations that are fraught with uncertainty. By recognizing that management is implemented to achieve specific objectives, resource managers and science partners can identify an analysis technique and develop a monitoring plan to evaluate management effectiveness. For emerging infectious diseases, objectives may take several distinct forms, dependent on the perceived stage of disease emergence (i.e., pre‐epidemic, early outbreak, mid‐epidemic, and endemic), the expected rate of spread, and the anticipated effect of the disease on host populations. Identifying modeling techniques and metrics that are linked to management objectives will require early and consistent communication between managers and science partners. We link modeling approaches that can be used to forecast and evaluate the performance of intervention strategies with a range of disease management objectives. Our aim is to help scientists recognize alternative modeling approaches which may better align with different forms of disease management objectives, and to help managers evaluate the relevance of proposed modeling approaches to their specified objectives for disease management. Recognizing that disease management objectives can take different forms, and thus require different modeling approaches, can help wildlife disease response teams (i.e., natural resource managers, scientists, and stakeholders working collaboratively) better prepare and respond to disease threats.