Walter, W. D., B. Hanley, C. E. Them, C. I. Mitchell, J. Kelly, D. Grove, N. Hollingshead, R. C. Abbott, and K. L. Schuler. 2024. Predicting the odds of chronic wasting disease with Habitat Risk software. Spatial and Spatio-temporal Epidemiology 49:100650.
Abstract
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 infection 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 pipeline 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. Software to pre-process environmental data is openly available at doi.org/10.7298/2tt1-yy48, while Habitat Risk software is available at doi.org/10.7298/rcz8-nw50.