Unknown

Dataset Information

0

Ensemble forecast of human West Nile virus cases and mosquito infection rates.


ABSTRACT: West Nile virus (WNV) is now endemic in the continental United States; however, our ability to predict spillover transmission risk and human WNV cases remains limited. Here we develop a model depicting WNV transmission dynamics, which we optimize using a data assimilation method and two observed data streams, mosquito infection rates and reported human WNV cases. The coupled model-inference framework is then used to generate retrospective ensemble forecasts of historical WNV outbreaks in Long Island, New York for 2001-2014. Accurate forecasts of mosquito infection rates are generated before peak infection, and >65% of forecasts accurately predict seasonal total human WNV cases up to 9 weeks before the past reported case. This work provides the foundation for implementation of a statistically rigorous system for real-time forecast of seasonal outbreaks of WNV.

SUBMITTER: DeFelice NB 

PROVIDER: S-EPMC5333106 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

altmetric image

Publications

Ensemble forecast of human West Nile virus cases and mosquito infection rates.

DeFelice Nicholas B NB   Little Eliza E   Campbell Scott R SR   Shaman Jeffrey J  

Nature communications 20170224


West Nile virus (WNV) is now endemic in the continental United States; however, our ability to predict spillover transmission risk and human WNV cases remains limited. Here we develop a model depicting WNV transmission dynamics, which we optimize using a data assimilation method and two observed data streams, mosquito infection rates and reported human WNV cases. The coupled model-inference framework is then used to generate retrospective ensemble forecasts of historical WNV outbreaks in Long Is  ...[more]

Similar Datasets

| S-EPMC5532452 | biostudies-other
| S-EPMC3755645 | biostudies-literature
| S-EPMC3249650 | biostudies-literature
| S-EPMC4091933 | biostudies-literature
| S-EPMC6636212 | biostudies-literature
| S-EPMC7350012 | biostudies-literature
| S-EPMC3485754 | biostudies-literature
2019-09-06 | GSE136342 | GEO
| S-EPMC4111179 | biostudies-literature
| S-EPMC8095553 | biostudies-literature