Projecting lyme disease risk in the United States: A machine learning approach integrating environmental, socioeconomic and vector factors

Projecting lyme disease risk in the United States: A machine learning approach integrating environmental, socioeconomic and vector factors

Objective: Lyme disease, caused by Borrelia burgdorferi and transmitted by blacklegged ticks (Ixodes species), is the most common vector-borne disease in the United States. Its spatiotemporal dynamics are influenced by environmental and socioeconomic factors, yet the impacts of the COVID-19 pandemic...

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Bibliographic Details
Main Authors: Yan-Qun Sun, Xiao-Yan Zhu, Tian-Ci Fan, Tian Ma, Hong-Han Ge, Rui-Fang Shi, Xu Wang, Wei Li, Jie-Yun Yin, Ye Tian
Format: Article
Language:English
Published: Elsevier 2025-12-01
Series:One Health
Subjects:
Lyme disease
Blacklegged ticks
COVID-19 pandemic
Machine learning
Online Access:http://www.sciencedirect.com/science/article/pii/S2352771425001478
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http://www.sciencedirect.com/science/article/pii/S2352771425001478

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