Speaker
Description
Lyme disease is the most prevalent vector-borne illness in the United States, with incidence rising across Maryland over recent decades. Transmission of Borrelia burgdorferi by Ixodes scapularis ticks is highly sensitive to climatic conditions, making it essential to understand how ongoing and projected warming will shape future disease dynamics. In this presentation, I will introduce a climate-driven epidemiological model developed to investigate the spatiotemporal dynamics of Lyme disease across Maryland. I will describe how the framework integrates fine-scale ecological and epidemiological data with temperature-dependent processes governing tick development, host interactions, and pathogen transmission. I will then present simulation results under current and future warming scenarios, specifically RCP 4.5 and 8.5, highlighting how projected warming influences tick population dynamics, seasonal activity shifts, and the geographic distribution of transmission risk. I will identify regions of heightened vulnerability under each warming scenario and discuss the implications of these spatial shifts for public health planning. Finally, I will evaluate the potential of targeted interventions, including environmental management and rodent-focused tick suppression, to mitigate transmission risk, and I will present coverage thresholds at which such strategies can meaningfully reduce disease persistence. Together, these findings highlight the need for climate-adaptive approaches to vector-borne disease prevention. The modeling framework presented offers a transferable tool for informing evidence-based public health strategies in regions facing similar climate-driven challenges.
