CWD Surveillance Tools Released

CWD Surveillance Tools Released

Thanks to multiple national funding sources and numerous agency, NGO, and academic partnerships, the next generation of CWD information and quantitative surveillance tools were recently rolled out to assist wildlife management agencies in the long fight against Chronic Wasting Disease (CWD). In parallel and in partnership, the CWD Alliance along with the Cornell Wildlife Health Lab at Cornell University and Boone and Crockett Quantitative Wildlife Center at Michigan State University spent nearly two years creating state-of-the-art web-based applications to help state and provincial wildlife management agencies use and manage their data in novel ways that better support their CWD management goals. The CWD Alliance and the Cornell Team rolled out the results of their respective projects in a joint webinar late last month titled “CWD Tools, Maps, and More Showcase.”

white-tailed deer

Focused primarily on CWD policy, regulation, and public-facing information, the CWD Alliance presented three ArcGIS – Esri maps that synthesize and spatially organize CWD information relevant to public stakeholders. Touted as the first of many more applications to come, these interactive maps and web-based tools allow users to easily navigate the complex suite of state and provincial carcass transportation regulations, laws affecting the baiting or feeding of cervids (deer, elk, and moose), and the use of cervid-derived substances. Additionally, this collection of applications includes a map of CWD presence in North America at both county and game management scales that is more accurate and representative of surveillance data than any North American CWD map ever developed.

“The challenge with presenting CWD-related information has always been a three-part problem: accuracy, timeliness, and usability,” stated Matt Dunfee, the coordinator of the CWD Alliance. “We, along with many other organizations, have struggled with providing all three of these characteristics in the information and data we present.”

Dunfee and his collaborators (who include agency CWD experts as well as communications consultant firm DJ Case & Associates) believe they have developed a way to serve as that reliable source of CWD information by essentially letting the owners of that information—state and provincial wildlife agencies—have unique access to edit and manage the very data used to populate these new mapping applications.

“Every CWD management agency will be given the opportunity to obtain their own ArcGIS hub account that will allow them to securely access and update their data at any time,” Dunfee continued. “We will be there to help remind them to update their content, and make sure everything looks good on the front end.” All of the CWD Alliance’s new tools will be hosted on the CWD Alliance website pending their approval by state and provincial wildlife agencies.

But CWD policy and regulation information is not well suited to answer other questions that plague agencies tasked with finding and managing CWD in wild populations. Questions like, where should CWD surveillance efforts be focused, how much sampling is enough to determine if disease prevalence is increasing or decreasing, and what does an efficient and effective disease surveillance plan look like? For these and many other CWD surveillance roadblocks, Cornell and Michigan State University have implemented the Surveillance Optimization Project for Chronic Wasting Disease (SOP4CWD).

According to Dr. Krysten Schuler, the project lead for SOP4CWD, the project collaborators are “applying methods from mathematical modeling and data science to address the challenges of disease surveillance, merging analytical techniques including risk weighting, Bayesian modeling, and geospatial analysis with machine learning algorithms to aggregate surveillance data, mathematically explore and rank alternative sampling strategies, and generate summary reports and recommendations for state agencies to target surveillance efforts and enhance early detection.” All of these analytical tools and approaches have been integrated into a comprehensive CWD surveillance, modeling, and management application that takes the form of “a user-friendly interface for agency personnel that allows managers and field staff to explore sampling strategies, track progress to sampling goals, and provide data summaries and reports in real time during the hunting season.”

Currently, 22 US states and one Canadian province have joined SOP4CWD, and Dr. Schuler has encouraged all other state and provincial wildlife agencies from eastern North America to join the project by integrating their data. “The more partners we have, the stronger and better the outcomes of this effort will be,” said Schuler. Agencies interested in becoming a part of SOP4CWD should contact the Cornell Wildlife Health Lab ( for information on how to join. Additional information about the project can be found at

According to both Dunfee and Schuler, these projects were developed by a systematic, scientific approach to identifying agency CWD data-sharing and surveillance management needs, preferences, and barriers. Data from multiple national surveys and assessments conducted by the Association of Fish and Wildlife Agencies, the CWD Alliance, DJ Case & Associates, and national CWD experts were used to identify the specific wildlife management agency challenges to managing CWD and guide the choice of the solutions engineered by the project collaborators.

Photo Credit
Florida Fish and Wildlife Service, Flickr
September 15, 2021