Strengthening Chronic Wasting Disease surveillance in captive cervid facilities

What is it about?

Chronic wasting disease (CWD) is a fatal disease that affects members of the deer family, including white-tailed deer, mule deer, elk, and moose. The disease spreads between animals and through contaminated environments, and once it becomes established in a deer population, it is extremely difficult to eliminate. CWD remains one of the greatest challenges facing the future of white-tailed deer management and conservation and, by extension, the North American Model of Wildlife Conservation, which relies heavily on healthy, sustainable deer populations. Captive deer facilities face an especially high risk of CWD because deer are often kept at higher densities, have frequent contact with one another, and are regularly moved between facilities. Early detection of CWD is critical for preventing its spread. However, only a small proportion of deer in a facility are typically tested each year. As a result, when test results come back as “CWD not detected,” it is often unclear whether the herd is truly free of the disease or whether infected deer were simply missed because too few animals were tested. To address this problem, we developed an agent-based model that combines information on herd size, deer demographics, movement histories, and CWD testing records to estimate how likely it is that CWD would have been detected if it were present. The tool helps interpret “CWD not detected” results and identify facilities where the risk of undetected CWD may still be high, allowing surveillance resources to be targeted more effectively.

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Photo by Jessica Cogar on Unsplash

Photo by Jessica Cogar on Unsplash

Why is it important?

A unique aspect of this research was the use of a participatory modeling approach that incorporated both the explicit and experiential knowledge of wildlife biologists, deer managers, and modelers throughout the development and application of the model. Rather than relying solely on theoretical assumptions, the modeling framework was designed in close collaboration with stakeholders to reflect real-world herd management practices, surveillance activities, and decision-making needs. Using data from 23 captive cervid facilities in Texas, we applied our agent-based modeling framework to estimate the probability that CWD would have been detected given each facility’s herd size, deer movement history, and testing records. This approach moves beyond simply reporting whether CWD was detected or not and instead provides a quantitative assessment of the likelihood that infection could have remained undetected. As a result, the framework offers wildlife agencies a practical, data-driven tool for prioritizing surveillance efforts, identifying facilities at higher risk of undetected infection, and supporting more sustainable, equitable, and risk-based CWD surveillance strategies.

Perspectives