ArticleParasites & vectors2016
Development and validation of a climate-based ensemble prediction model for West Nile Virus infection rates in Culex mosquitoes, Suffolk County, New York.
Article in Parasites & vectors, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- A data-parsimonious model for long-term risk assessments of West Nile virus spillover.Scientific reports · 2026Article
- Article
- How technologies are driving digital innovation in mosquito surveillance systems: a global scoping review over the past decade.BMJ public health · 2026Article
- New enemies: contribution of CPathogens and global health · 2025Article
- Using mosquito and arbovirus data to computationally predict West Nile virus in unsampled areas of the Northeast United States.PNAS nexus · 2025Article
- Evaluation of the 2022 West Nile virus forecasting challenge, USA.Parasites & vectors · 2025Article
- Seasonal Bird Migration Could Explain Regional Synchronicity and Amplification in Human West Nile Virus Case Numbers.GeoHealth · 2025Article
- Early warning system of the seasonal west nile virus infection risk in humans in northern greece, 2020-2024.Scientific reports · 2025Article
- Impact of climate change on the global circulation of West Nile virus and adaptation responses: a scoping review.Infectious diseases of poverty · 2024Article
- A Spatially Resolved and Environmentally Informed Forecast Model of West Nile Virus in Coachella Valley, California.GeoHealth · 2023Article
- Assessing the Influence of Climate on the Spatial Pattern of West Nile Virus Incidence in the United States.Environmental health perspectives · 2023Article
- Statistical Tools for West Nile Virus Disease Analysis.Methods in molecular biology (Clifton, N.J.) · 2023Article
- A proposed framework for the development and qualitative evaluation of West Nile virus models and their application to local public health decision-making.PLoS neglected tropical diseases · 2021Review
- Review
- Concurrent assessment of epidemiological and operational uncertainties for optimal outbreak control: Ebola as a case study.Proceedings. Biological sciences · 2019Article
- Spatiotemporal Bayesian modeling of West Nile virus: Identifying risk of infection in mosquitoes with local-scale predictors.The Science of the total environment · 2019Article
- Article
- Key Factors Influencing the Incidence of West Nile Virus in Burleigh County, North Dakota.International journal of environmental research and public health · 2018Article
- Use of temperature to improve West Nile virus forecasts.PLoS computational biology · 2018Article
- Ensemble method for dengue prediction.PloS one · 2018Article
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Authors and funding
3 authors.
Funding
Abstract
backgroundWest Nile Virus (WNV) is an endemic public health concern in the United States that produces periodic seasonal epidemics. Underlying these outbreaks is the enzootic cycle of WNV between mosquito vectors and bird hosts. Identifying the key environmental conditions that facilitate and accelerate this cycle can be used to inform effective vector control.
resultsHere, we model and forecast WNV infection rates among mosquito vectors in Suffolk County, New York using readily available meteorological and hydrological conditions. We first validate a statistical model built with surveillance data between 2001 and 2009 (m09) and specify a set of new statistical models using surveillance data from 2001 to 2012 (m12). This ensemble of new models is then used to make predictions for 2013-2015, and multimodel inference is employed to provide a formal probabilistic interpretation across the disparate individual model predictions. The findings of the m09 and m12 models align; with the ensemble of m12 models indicating an association between warm, dry early spring (April) conditions and increased annual WNV infection rates in Culex mosquitoes.
conclusionsThis study shows that real-time climate information can be used to predict WNV infection rates in Culex mosquitoes prior to its seasonal peak and before WNV spillover transmission risk to humans is greatest.
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