North American Wildlife Agency CWD Testing and Ancillary Data (2000 – 2022)

Collections
CVM Research
Author
Schuler, Krysten L.
Hanley, Brenda J.
Abbott, Rachel C.
Dayan, David B.
Hollingshead, Nicholas A.
Ballard, Jennifer R.
Middaugh, Christopher R.
Cunningham, Mark
Clemons, Bambi
Sayler, Katherine
Kelly, James D.
Killmaster, Charlie H.
Harms, Tyler M.
Ruden, Rachel M.
Caudell, Joe
Westrich, Michelle Benavidez
McCallen, Emily
Casey, Christine
O’Brien, Lindsey M.
Trudeau, Jonathan K.
Straka, Kelly
Stewart, Chad
Carstensen, Michelle
McKinley, William T.
Hynes, Kevin P.
Ableman, Ashley
Miller, Landon A.
Cook, Merril
Myers, Ryan
Shaw, Jonathan
Van de Berg, Sarah
Tonkovich, Michael J.
Grove, Daniel M.
Storm, Daniel J.
Abstract

The North American Wildlife Agency CWD Testing and Ancillary Data (2000-2022) dataset (“Dataset”) represents epidemiological, population, ecological, and anthropogenic data related to chronic wasting disease (CWD) surveillance in white-tailed deer (Odocoileus virginianus) in 16 US states (“Administrative Areas”) in North America. The data are summarized at the “Sub-Administrative Area” level. For most state wildlife agencies, counties or equivalent units within Administrative Areas serve as sub-administrative area. While the overall time-period represented by the Dataset spans the years 2000 through 2022, data availability varies by wildlife agency. Administrative Areas and associated wildlife agencies represented in the Dataset include Arkansas (Arkansas Game and Fish Commission), Florida (Florida Fish and Wildlife Conservation Commission), Georgia (Georgia Department of Natural Resources), Indiana (Indiana Department of Natural Resources), Iowa (Iowa Department of Natural Resources), Kentucky (Kentucky Department of Fish and Wildlife Resources), Maryland (Maryland Department of Natural Resources), Michigan (Michigan Department of Natural Resources), Minnesota (Minnesota Department of Natural Resources), Mississippi (Mississippi Department of Wildlife, Fisheries, and Parks), New York (New York State Department of Environmental Conservation), North Carolina (North Carolina Wildlife Resources Commission), Ohio (Ohio Department of Natural Resources), Tennessee (Tennessee Wildlife Resources Agency), Virginia (Virginia Department of Wildlife Resources), and Wisconsin (Wisconsin Department of Natural Resources). This dataset is intended for use in regional models to determine risk factors that can be used to predict locations of CWD incidence in white-tailed deer at the sub-administrative unit level. Version 2 (the current version) of the Dataset corrects errors present in Version 1 of the Dataset (Them et al. 2023). For Version 2, the original data sources were re-examined and re-processed to ensure the highest level of fidelity and accuracy possible. Data processing scripts were revised for improved precision and data quality and are available in a related repository (Hollingshead et al. 2024). All data and scripts were assessed for accuracy and consistency using a thorough QAQC process completed by internal and external collaborators.

Description
Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

The findings and conclusions in this material are those of the authors and do not necessarily represent the views of the U.S. Fish and Wildlife Service.
Sponsorship
Data collection was funded in part by Arkansas’s Wildlife Restoration funds, State of Florida State Game Trust Fund Deer Management Program; Georgia’s Wildlife and Sport Fish Restoration Program; Indiana Department of Natural Resources and Fish and Wildlife # F18AF00484, W38R05 White-tailed Deer Management, F20AF10029-00, Monitoring Wildlife Populations and Health W-51-R-01, F21AF02467-01, Monitoring Wildlife Populations and Health W-51-R-02; Iowa’s Fish and Wildlife Trust Fund and Iowa’s award of the U. S. Fish and Wildlife Service Wildlife and Sport Fish Restoration Program; Maryland’s award of the U. S. Fish and Wildlife Service Wildlife and Sport Fish Restoration Program, #W-61-R-29; Minnesota Department of Natural Resources; New York’s Wildlife Health Unit and New York’s award for Federal Aid Wildlife Restoration Grant #W-178-R; North Carolina’s award for Federal Aid in Wildlife Restoration; Ohio’s award for the Wildlife Restoration Grant # F20AF12094; Tennessee’s award for the Wildlife Restoration Program; Virginia’s Pittman-Roberston Federal Aid; Wisconsin’s award for the Federal Aid in Wildlife Restoration; Multistate Conservation Grant Program # F21AP00722-01. The Michigan Disease Initiative # RC109358, Alabama Department of Conservation and Natural Resources, Florida Fish and Wildlife Conservation Commission, Tennessee Wildlife Resources Agency, and New York State Department of Environmental Conservation contributed funding to the overall project. This Project was funded by a Multistate Conservation Grant # F23AP00488-00, a program funded form the Wildlife and Sport Fish Restoration Program, and jointly managed by the U.S. Fish and Wildlife Service and the Association of Fish and Wildlife Agencies.
Date Issued
2024-05-06
Keywords
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Related To
Hollingshead, N., & Dayan, D. B. (2024). North American Wildlife Agency CWD Testing and Ancillary Data (2000 – 2022) Scripts. Cornell University Library eCommons Repository. https://doi.org/10.7298/3B45-4E62
Related Publication(s)
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
Link(s) to Related Publication(s)
Rights
Attribution 4.0 International
Rights URI
Type
dataset

Version History

Now showing 1 - 2 of 2
VersionDateSummary
2*
 2024-05-06 15:45:22
More data sources were added and previously used data sources were re-processed to improve accuracy and completeness.
1
 2023-09-22 10:41:26
* Selected version