Year of Publication



Public Health

Date Available


Degree Name

Master of Public Health (M.P.H.)

Committee Chair

Wayne Sanderson, MS, CIH, Ph.D.

Committee Member

Steve Browning, Ph.D., MSPH

Committee Member

W. Jay Christian, PhD

Committee Member

Brent Shelton, PhD


Abstract Background: The rabies virus is a Lyssavirus of the family Rhabdoviridae which affects all mammals and causes progressive encephalomyelitis that is fatal in nearly one hundred percent of untreated cases. In the United States, wildlife act as the primary reservoir for rabies and prevention, surveillance, and control costs remain high. The purpose of this study is to understand the current distribution of wildlife rabies in Central Appalachia, as well as identify any demographic or geographic factors which may affect the risk of human exposure at the county level. Methods: A spatial statistical analysis using StatScan was performed to identify county clusters with apparently high or low rates of raccoon rabies. A Negative Binomial Regression Analysis was then performed to identify potential demographic and geographic factors associated with these varying rates of rabies. Results: 100 North Carolina counties, 118 Virginia counties and independent cities, and 55 West Virginia counties submitted a total of 12,516, 15,556, and 2,642 animals respectively to their state health departments for rabies testing. In North Carolina, raccoons constituted 50% of positive tests, in Virginia, 49%, and in West Virginia 50%. A final model was developed for raccoon rabies rates and then used to model all other species separately. Compared to a those living in West Virginia counties, citizens of North Carolina counties had 1.67 times the risk of exposure (p<.0001) to a rabid raccoon, while citizens of Virginia counties and independent cities have 1.82 times the risk of exposure (p<.0001) to a rabid raccoon. Compared to those counties where farmland makes up less than seventeen percent of total area, citizens of counties with 17-28% farmland have 1.32 times the risk of exposure (p=0.013) to a rabid raccoon, counties with 28-39% farmland have 1.84 times the risk of exposure (<.0001), and counties with 39-100% farmland have 1.64 times the risk of exposure (p=<.0001). Compared to those counties designated non-metropolitan and non-adjacent to a metropolitan area, citizens of counties designated non-metropolitan adjacent to a metropolitan area have 1.56 times the risk of exposure (p=.005) to a rabid raccoon while those in areas designated as metropolitan have 1.41 times the risk of exposure (p=.024). This model did not appear to be the best predictor for rabies exposure from other species. Conclusions: Holding all other factors constant, state, rurality, and percent of area designated as farmland were the best predictors of risk of raccoon rabies exposure. Further expansion of this research is needed to better understand other reservoir species, as well as better identify the effect of the ORV zone in controlling the risk of human exposure to raccoon rabies.

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