Climate-induced expansion of Lyme disease in east central Ohio

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 <i>Ixodes</i>. 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.

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Publication Details

Journal
International Journal of Environmental Health Research
Published
2025-01-29
DOI
https://doi.org/10.1080/09603123.2025.2456966
Citations
3
Primary Topic
Climate Change and Health Impacts
Type
article
Field-Weighted Citation Impact
3.60
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article

Climate-induced expansion of Lyme disease in east central Ohio

Saurav Chakraborty, Joni Downs, Victor Mesev
3 citations
International Journal of Environmental Health Research
Climate Change and Health Impacts
3.60
article

Climate-induced expansion of Lyme disease in east central Ohio

Saurav Chakraborty, Joni Downs, Victor Mesev
article en
3 citations

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 <i>Ixodes</i>. 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.

International Journal of Environmental Health ResearchVol. 35(9)
Florida State University (US), University of South Florida (US), The Ohio State University (US)
Climate action
Openalex Percentile: Top 9%
Climate Change and Health Impacts
3.60
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