ORCID ID
Graduation Date
Spring 5-10-2025
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Programs
Epidemiology
First Advisor
David Brett-Major
Abstract
Lyme disease is the most common vector-borne disease in North America. This dissertation examines (1) how crowd-sourced compares to active vector surveillance and whether they are associated with Lyme disease, (2) how ecological factors relate to tick abundance and whether they can predict high disease years, and (3) estimated health and economic burden of Lyme disease and savings when interventions are applied. Tick abundance data from active and passive surveillance were compared and tested for association with Lyme disease in the first aim. We found differences in tick life-stage, species, and seasonality. Tick observations were positively correlated with Lyme disease. Observed differences in outputs suggest differences between tick populations and human encounters. These findings signal an opportunity for early identification of high disease years through integrated surveillance that informs the conduct of disease surveillance. In the second aim, we used logistic regression and gradient boosting machine learning to examine relationships between environment and tick abundance and high disease years. Several factors were found to predict tick abundance. Palmer Drought Severity Index, soil moisture, Snow Water Equivalent, days below 0°F, degree days, small mammal count and mouse ratio were all highly predictive of high Lyme disease burden. Environmental factors predict tick abundance best in the same and subsequent year, and high disease burden two years in advance. Monitoring environmental factors provides opportunities for public health intervention through prediction of tick abundance and higher Lyme disease incidence. In the third aim, Monte Carlo simulations were used to estimate the health and economic burden of Lyme disease and prevented burden when prevention interventions are implemented. We found on average 8,436 Lyme disease cases annually. High-incidence years saw >3,700 more cases than low-incidence, with costs for patients and society exceeding $2 million. Public health education before high-incidence years could reduce Lyme disease cases by 390 to 787, saving $1.2 million in societal costs. Simulation modeling demonstrates Lyme disease's significant impact on individuals and society. Annual forecasting-triggered public health intervention programs could reduce cost and burden.
Recommended Citation
Angell, Kathleen E., "From Vector to Consequence: Integrating Vector Surveillance, Environmental Drivers, and Public Health Impact into Lyme Disease Risk Management" (2025). Theses & Dissertations. 915.
https://digitalcommons.unmc.edu/etd/915
Comments
2025 Copyright, the authors