Speaker
Description
Abstract: Lyme disease, the most prevalent vector-borne disease in the United States, has been expanding across Maryland, with rising temperatures accelerating its spread. Transmission of Borrelia burgdorferi by Ixodes scapularis ticks is highly sensitive to climatic variables. This study develops a climate-driven epidemiological model to investigate the spatiotemporal dynamics of Lyme disease in Maryland. Integrating fine-scale ecological data with temperature-dependent vector-host interactions, we assess the impact of climate change on tick population dynamics, seasonal activity shifts, and transmission intensity under Representative Concentration Pathways (RCP 4.5 and 8.5). Results project substantial expansion of Lyme disease across Maryland counties, driven by increased tick activity and host population growth. We find significant increases in disease incidence, basic reproduction number (R₀), and infected nymphal density, with the most pronounced effects in Central and Western Maryland under RCP 8.5. Spatial analyses reveal a northward shift of high-risk zones. Further analysis demonstrates that environmental clearance and rodent-targeted tick suppression can reduce transmission risk, with R₀ declining significantly when intervention compliance exceeds 50%. These findings emphasize the need for climate-adaptive vector management and provide a framework for evidence-based Lyme disease prevention.
