ArticleThe Science of the total environment2019
Spatiotemporal Bayesian modeling of West Nile virus: Identifying risk of infection in mosquitoes with local-scale predictors.
Article in The Science of the total environment, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- Article
- Risk assessment of West Nile fever in equines in Europe based on an ecological niche model.BMC veterinary research · 2026Article
- A data-parsimonious model for long-term risk assessments of West Nile virus spillover.Scientific reports · 2026Article
- The evolution of public health statistical modeling approaches and how to advance their incorporation into modern arboviral surveillance.Journal of medical entomology · 2026Article
- Land and climate suitability for West Nile virus in Atlantic archipelagos guided by historical data from Europe.Communications biology · 2026Article
- Spatio-temporal modelling of COVID-19 infection and associated risk factors in Dakar, Senegal.PLOS global public health · 2026Article
- Climate and landscape drivers of a mosquito-borne pathogen in an iconic game bird in the eastern and upper midwestern USA.Scientific reports · 2025Article
- Validating a Bayesian Spatio-Temporal Model to Predict La Crosse Virus Human Incidence in the Appalachian Mountain Region, USA.Microorganisms · 2025Article
- A parsimonious Bayesian predictive model for forecasting new reported cases of West Nile disease.Infectious Disease Modelling · 2024Article
- Demographic and zoological drivers of infectome diversity in companion cats with ascites.mSystems · 2024Article
- Spatial distribution and environmental correlations of Culex pipiens pallens (Diptera: Culicidae) in Haidian district, Beijing.Journal of medical entomology · 2024Article
- Impact of climate change on the global circulation of West Nile virus and adaptation responses: a scoping review.Infectious diseases of poverty · 2024Article
- Forecasting freshwater cyanobacterial harmful algal blooms for Sentinel-3 satellite resolved U.S. lakes and reservoirs.Journal of environmental management · 2024Article
- Two-step light gradient boosted model to identify human west nile virus infection risk factor in Chicago.PloS one · 2024Article
- Interactive effects of climate, land use and soil type onOne health (Amsterdam, Netherlands) · 2023Article
- Seasonal dynamics of the wild rodent faecal virome.Molecular ecology · 2023Article
- Mapping the abundance of endemic mosquito-borne diseases vectors in southern Quebec.BMC public health · 2023Article
- Investigating the impact of environmental factors on West Nile virus human case prediction in Ontario, Canada.Frontiers in public health · 2023Article
- The utility of a Bayesian predictive model to forecast neuroinvasive West Nile virus disease in the United States of America, 2022.PloS one · 2023Article
- Synthesis of Two Decades of US EPA's Ecosystem Services Research to Inform Environmental, Community, and Sustainability Decision Making.Sustainability · 2021Article
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2 authors.
Funding
Abstract
Monitoring and control of West Nile virus (WNV) presents a challenge to state and local vector control managers. Models of mosquito presence and viral incidence have revealed that variations in mosquito autecology and land use patterns introduce unique dynamics of disease at the scale of a county or city, and that effective prediction requires locally parameterized models. We applied Bayesian spatiotemporal modeling to West Nile surveillance data from 49 mosquito trap sites in Nassau County, New York, from 2001 to 2015 and evaluated environmental and sociological predictors of West Nile virus incidence in Culex pipiens-restuans. A Bayesian spike-and-slab variable selection algorithm was used to help select influential independent variables. This method can be used to identify locally-important predictors. The best model predicted West Nile positives well, with an Area Under Curve (AUC) of 0.83 on holdout data. The temporal trend was nonlinear and increased throughout the year. The spatial component identified increased West Nile incidence odds in the northwestern portion of the county, with lower odds in wetlands on the south shore of Long Island. High Normalized Difference Vegetation Index (NDVI) areas, wetlands, and areas of high urban development had negative associations with WNV incidence. In this study we demonstrate a method for improving spatiotemporal models of West Nile virus incidence for decision making at the county and community scale, which empowers disease and vector control organizations to prioritize and evaluate prevention efforts.
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