Abstract
ABSTRACT The geographical distribution of Lyme disease has been attributed to changes in Earth’s climate and associated distribution of its vector, ticks of the genus Ixodes. This study focuses on the impact of climatic and meteorological conditions on Lyme disease transmission in East Central Ohio, an emerging hotspot of cases. Using county-level data from 2001 to 2023, we analyzed the relationship between Lyme disease cases and temperature, precipitation, and the Southern Oscillation Index (SOI) using a distributed lag nonlinear model (DLNM). Results show that warmer winter temperatures, higher precipitation, and negative SOI values (El Niño conditions) were significantly associated with increased Lyme disease incidence and displayed delayed effects of 6 to18 months. These findings suggest that climate change, with its potential to bring milder winters and increased spring and summer rainfall, may further exacerbate Lyme disease cases in Ohio.
Published Version
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