TY - JOUR T1 - An agent-based framework for improving wildlife disease surveillance: A case study of chronic wasting disease in Missouri white-tailed deer JF - bioRxiv DO - 10.1101/478610 SP - 478610 AU - Aniruddha V. Belsare AU - Matthew E. Gompper AU - Barbara Keller AU - Jason Sumners AU - Lonnie Hansen AU - Joshua J. Millspaugh Y1 - 2018/01/01 UR - http://biorxiv.org/content/early/2018/11/29/478610.abstract N2 - Epidemiological surveillance for important wildlife diseases often relies on samples obtained from hunter-harvested animals. A problem, however, is that although convenient and cost-effective, hunter-harvest samples are not representative of the population due to heterogeneities in disease distribution and biased sampling. We developed an agent-based modeling framework that simulates spatial and demographic heterogeneities in disease distribution as well as hunter harvest sampling, thereby facilitating population-specific sample size calculations for prompt detection of disease. Application of this framework is illustrated using the example of chronic wasting disease (CWD) surveillance in Missouri’s white-tailed deer (Odocoileus virginianus) population. We show how confidence in detecting CWD is grossly overestimated under the unrealistic, but standard, assumptions that sampling effort and disease are randomly and independently distributed. We then provide adjusted sample size recommendations based on more realistic assumptions. Wildlife agencies can use these open-access models to design their CWD surveillance. Furthermore, these models can be readily adapted to other regions and other wildlife disease systems. ER -