Chronic wasting disease (CWD) continues to spread through wild cervid herds in North America, rendering surveillance increasingly expensive for wildlife agencies. Although drivers of CWD outbreaks have been studied at herd, outbreak, and even state scales, a comprehensive regional model that predicts locations poised for new infections has never been achieved.
Until now.
Four years in the making, the Surveillance Optimization for Chronic Wasting Disease (SOP4CWD) team followed through on our original idea to use emerging techniques in machine learning with historical CWD surveillance data to make the first-ever comprehensive model predicting CWD across state boundaries.
Published in Scientific Reports, our approach breaks down long-standing barriers to interstate collaboration in wildlife science and pools CWD surveillance data from 16 US state agencies spanning two decades to create the first-ever regional forecast of CWD infection in North America.
Wildlife and public health officials can use the CWD Prediction Web App to investigate where CWD may exist within their jurisdictions to enhance their surveillance efforts.
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The CWD Detection Web App Dashboard
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The image displays when the app predicts the county to be negative for CWD
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The image displays when the app predicts the county to be positive for CWD
The CWD Detection Web App Dashboard
The image displays when the app predicts the county to be negative for CWD
The image displays when the app predicts the county to be positive for CWD
Access the Web App here:
The publication can be found here:
Ahmed MS, Hanley BJ, Mitchell CI, Abbott RA, Hollingshead NA, Booth JG, Guinness J, Jennelle CS, Hodel FH, Gonzalez-Crespo C, Middaugh CR, Ballard JR, Clemons B, Killmaster CH, Harms TM, Caudell JN, Benavidez Westerich KM, McCallen E, Casey C, O'Brien L, Trudeau JK, Steward C, Carstensen M, McKinley WT, Hynes KP, Stevens AE, Miller LA, Cook M, Myers RT, Shaw J, Tonkovich MJ, Kelly JD, Grove DM, Storm DJ, and Schuler KS. 2024. Predicting chronic wasting disease in white-tailed deer at the county scale using machine learning.
Scientific Reports. https://doi.org/10.1038/s41598-024-65002-7
The data can be found here:
Schuler KL, Hanley BJ, Abbott RC, Dayan DB, Hollingshead NA, Ballard JR, Middaugh CR, Cunningham M, Clemons B, Sayler K, Killmaster CH, Harms TM, Ruden RM, Caudell J, Westrich MB, McCallen E, Casey C, O’Brien LM, Trudeau JK, Straka K, Stewart C, Carstensen M, McKinley WT, Hynes KP, Ableman A, Miller LA, Cook M, Myers R, Shaw J, Van de Berg S, Tonkovich MJ, Kelly JD, Grove DM, and Storm DJ. 2024. North American Wildlife Agency CWD Testing and Ancillary Data (2000 – 2022) [Dataset]. Cornell University Library eCommons Repository. https://doi.org/10.7298/7txw-2681.2
Thumbnail image of white-tailed deer by Art Kirsch