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Author ORCID Identifier

https://orcid.org/0009-0000-1354-0311

Date Available

5-1-2026

Year of Publication

2026

Document Type

Master's Thesis

Degree Name

Master of Epidemiology (MS EPI)

College

Public Health

Department/School/Program

Epidemiology

Faculty

Wayne T. Sanderson

Faculty

Amanda Ellis

Abstract

This ecological study examined county-level environmental, landscape, and host-related predictors of Lyme disease incidence across Kentucky, Virginia, and West Virginia from 2000-2019. Lyme disease is an emerging public health concern in the Appalachian region, where geographic expansion and shifting ecological conditions may influence disease risk.

Lyme disease case rates (per 10,000 population) were analyzed in relation to climate variables, land cover metrics, host density measures, and rurality using publicly available data sources. Descriptive and regression analyses were conducted to evaluate associations between candidate predictors and disease incidence.

Substantial geographic variation in Lyme disease incidence was observed, with higher case rates in Virginia and West Virginia and consistently lower rates in Kentucky. Deer density emerged as the most consistent predictor of Lyme disease incidence, while temperature and precipitation were inversely associated with case rates. Landscape variables showed variable associations across states.

Several limitations may impact the interpretation of these findings, including the use of aggregate data and potential underreporting or misclassification of Lyme disease cases. Despite these limitations, the results suggest that Lyme disease risk in the Appalachian region is influenced by host availability, environmental conditions, and regional ecological differences. These findings highlight the need for improved surveillance and targeted public health strategies and interventions in emerging risk areas.

Digital Object Identifier (DOI)

https://doi.org/10.13023/etd.2026.228

Archival?

Archival

Funding Information

The author and this work were supported by a traineeship from the Central Appalachian Regional Education and Research Center (CARERC) as part of the occupational epidemiology core (PHS grant number 6T42OH010278-12M010). Funds were awarded directly to author for the 2025-26 academic year.

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