Suppose we have not yet confirmed an infectious disease of interest in free-ranging wildlife, so where do we even begin to start looking? We start by mapping known risk factors.
For years, the CWHL has worked with the WHP to conduct surveillance for disease outbreaks using the newly published Hazard model. This model hones in on geographical areas around a state or province with disproportionate levels of introduction risk.
Depending on the disease, introduction risks can occur in many forms. Natural risks, such as migrating or dispersing wildlife, can seed new infections. Environmental risks, such as proximity to contaminated sites or within watersheds, may move pathogens around. Or human-based risks, such as the movement of live or dead wildlife from one part of a state or province to another, can inadvertently seed new infections.
The Hazard Model identifies areas where risks have accumulated in time and space, posing a location of disproportionate likelihood that disease will emerge. When no other data are available, we can use this risk map as the basis for our state-wide surveillance strategies.
The Hazard Model was developed in conjunction with wildlife agencies to be sufficiently flexible to specific operational constraints – a welcome capability when organizations may be limited in time or money to surveil for threats that have not yet emerged.
The full publication can be found here:
Schuler, K. L., Hollingshead, N. A., Heerkens, S., Kelly, J. D., Hurst, J. E., Abbott, R. C., Hanley, B. J., Collins, E., & Hynes, K. P. (2025). A “hazard model” using risk-weighted surveillance for first detection of chronic wasting disease. Preventive Veterinary Medicine, 243, 106599. https://doi.org/10.1016/j.prevetmed.2025.106599
The model is immediately available to 22 state wildlife agencies in North America through the SOP4CWD collaboration (sop4cwd.org). The SOP4CWD project, led by the Cornell Wildlife Health Lab, provides a free, automated technological system that enables agencies to manage disease surveillance data and make data-driven decisions to inform conservation outcomes. This new model is autonomously integrated into the CWD Data Warehouse, allowing surveillance savings for research on chronic wasting disease (CWD) to commence immediately.
Code to run the model within the CWD Data Warehouse can be found at the CWHL Git Hub:
