Input for Habitat Risk Software

Chronic wasting disease (CWD) is a transmissible spongiform encephalopathy that was first detected in captive cervids in Colorado, United States (US) in 1967, but has since spread into free-ranging white-tailed deer (Odocoileus virginianus) populations across the US and Canada. In some areas, the disease is considered endemic in wild deer populations, and governmental wildlife agencies have employed epidemiological models to understand long-term environmental risk. However, continued rapid spread of CWD into new regions of the continent has underscored the need for extension of these models into broader tools applicable for wide use by wildlife agencies. Additionally, efforts to semi-automate models will facilitate access of technical scientific methods to broader audiences. We introduce software (Habitat Risk) designed to link a previously published epidemiological model with spatially referenced environmental and disease testing data enabling agency personnel to make up-to-date, localized, data-driven predictions regarding the odds of CWD detection in surrounding areas after an outbreak is discovered. Habitat Risk requires pre-processing publicly available environmental datasets and standardization of disease testing (surveillance) data, after which an autonomous computational workflow terminates in a user interface that displays an interactive map of disease risk. We demonstrated the use of the Habitat Risk software with surveillance data of white-tailed deer from Tennessee, US. This data release includes the data inputs necessary to run the 1st script of the Habitat Risk Software which includes a .csv and preprocessed spatial layers described in Mitchell et al. 2021 but provided here for ease of running the example and surveillance disease testing data (included here). Data included in the .csv are not true locations of samples, rather modified data to be used solely for purposes of running through the R-code Mitchell, C., Walter, W. D., Hollingshead, N., & Schuler, K. 2021. Processing of Geospatial Data for the Habitat Risk Software [Software]. Cornell University Library eCommons Repository. https://doi.org/10.7298/2tt1-yy48

Data and Resources

Field Value
accessLevel public
bureauCode {010:12}
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catalog_@id https://ddi.doi.gov/usgs-data.json
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catalog_describedBy https://project-open-data.cio.gov/v1.1/schema/catalog.json
identifier http://datainventory.doi.gov/id/dataset/usgs-64de6780d34e5f6cd5535071
metadata_type geospatial
modified 2023-08-31T00:00:00Z
old-spatial -90.3000, 34.9800, -86.5723, 36.6508
publisher U.S. Geological Survey
resource-type Dataset
source_datajson_identifier true
source_hash fe62c81d1e94c88e1047c36b2c94b15501097fbb466bc3b462f2468263827901
source_schema_version 1.1
spatial {"type": "Polygon", "coordinates": [[[-90.3000, 34.9800], [-90.3000, 36.6508], [ -86.5723, 36.6508], [ -86.5723, 34.9800], [-90.3000, 34.9800]]]}
theme {geospatial}
Groups
  • AmeriGEOSS
  • National Provider
  • North America
Tags
  • AmeriGEO
  • AmeriGEOSS
  • CKAN
  • GEO
  • GEOSS
  • National
  • North America
  • United States
  • biota
  • surveillance
  • usgs-64de6780d34e5f6cd5535071
isopen False
license_id notspecified
license_title License not specified
maintainer William D Walter
maintainer_email wwalter@usgs.gov
metadata_created 2025-09-24T23:21:34.807350
metadata_modified 2025-09-24T23:21:34.807363
notes Chronic wasting disease (CWD) is a transmissible spongiform encephalopathy that was first detected in captive cervids in Colorado, United States (US) in 1967, but has since spread into free-ranging white-tailed deer (Odocoileus virginianus) populations across the US and Canada. In some areas, the disease is considered endemic in wild deer populations, and governmental wildlife agencies have employed epidemiological models to understand long-term environmental risk. However, continued rapid spread of CWD into new regions of the continent has underscored the need for extension of these models into broader tools applicable for wide use by wildlife agencies. Additionally, efforts to semi-automate models will facilitate access of technical scientific methods to broader audiences. We introduce software (Habitat Risk) designed to link a previously published epidemiological model with spatially referenced environmental and disease testing data enabling agency personnel to make up-to-date, localized, data-driven predictions regarding the odds of CWD detection in surrounding areas after an outbreak is discovered. Habitat Risk requires pre-processing publicly available environmental datasets and standardization of disease testing (surveillance) data, after which an autonomous computational workflow terminates in a user interface that displays an interactive map of disease risk. We demonstrated the use of the Habitat Risk software with surveillance data of white-tailed deer from Tennessee, US. This data release includes the data inputs necessary to run the 1st script of the Habitat Risk Software which includes a .csv and preprocessed spatial layers described in Mitchell et al. 2021 but provided here for ease of running the example and surveillance disease testing data (included here). Data included in the .csv are not true locations of samples, rather modified data to be used solely for purposes of running through the R-code Mitchell, C., Walter, W. D., Hollingshead, N., & Schuler, K. 2021. Processing of Geospatial Data for the Habitat Risk Software [Software]. Cornell University Library eCommons Repository. https://doi.org/10.7298/2tt1-yy48
num_resources 2
num_tags 11
title Input for Habitat Risk Software