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Assessing the Influence of Climate on the Spatial Pattern of West Nile Virus Incidence in the United States.
Gorris, Morgan E; Randerson, James T; Coffield, Shane R; Treseder, Kathleen K; Zender, Charles S; Xu, Chonggang; Manore, Carrie A.
Afiliación
  • Gorris ME; Information Systems and Modeling, Los Alamos National Laboratory, Los Alamos, New Mexico, USA.
  • Randerson JT; Center for Nonlinear Studies, Los Alamos National Laboratory, Los Alamos, New Mexico, USA.
  • Coffield SR; Department of Earth System Science, University of California, Irvine, Irvine, California, USA.
  • Treseder KK; Department of Earth System Science, University of California, Irvine, Irvine, California, USA.
  • Zender CS; Department of Ecology and Evolutionary Biology, University of California, Irvine, Irvine, California, USA.
  • Xu C; Department of Earth System Science, University of California, Irvine, Irvine, California, USA.
  • Manore CA; Earth and Environmental Sciences Division, Los Alamos National Laboratory, Los Alamos, New Mexico, USA.
Environ Health Perspect ; 131(4): 47016, 2023 04.
Article en En | MEDLINE | ID: mdl-37104243
BACKGROUND: West Nile virus (WNV) is the leading cause of mosquito-borne disease in humans in the United States. Since the introduction of the disease in 1999, incidence levels have stabilized in many regions, allowing for analysis of climate conditions that shape the spatial structure of disease incidence. OBJECTIVES: Our goal was to identify the seasonal climate variables that influence the spatial extent and magnitude of WNV incidence in humans. METHODS: We developed a predictive model of contemporary mean annual WNV incidence using U.S. county-level case reports from 2005 to 2019 and seasonally averaged climate variables. We used a random forest model that had an out-of-sample model performance of R2=0.61. RESULTS: Our model accurately captured the V-shaped area of higher WNV incidence that extends from states on the Canadian border south through the middle of the Great Plains. It also captured a region of moderate WNV incidence in the southern Mississippi Valley. The highest levels of WNV incidence were in regions with dry and cold winters and wet and mild summers. The random forest model classified counties with average winter precipitation levels <23.3mm/month as having incidence levels over 11 times greater than those of counties that are wetter. Among the climate predictors, winter precipitation, fall precipitation, and winter temperature were the three most important predictive variables. DISCUSSION: We consider which aspects of the WNV transmission cycle climate conditions may benefit the most and argued that dry and cold winters are climate conditions optimal for the mosquito species key to amplifying WNV transmission. Our statistical model may be useful in projecting shifts in WNV risk in response to climate change. https://doi.org/10.1289/EHP10986.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Fiebre del Nilo Occidental / Virus del Nilo Occidental Tipo de estudio: Incidence_studies / Prognostic_studies / Risk_factors_studies Límite: Animals / Humans País/Región como asunto: America do norte Idioma: En Revista: Environ Health Perspect Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
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XML
PubMed Links
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Fiebre del Nilo Occidental / Virus del Nilo Occidental Tipo de estudio: Incidence_studies / Prognostic_studies / Risk_factors_studies Límite: Animals / Humans País/Región como asunto: America do norte Idioma: En Revista: Environ Health Perspect Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos