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

Nat Commun. 2017 Feb 24;8:14592. doi: 10.1038/ncomms14592.

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.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Animals
  • Culicidae / virology*
  • Disease Outbreaks*
  • Epidemiological Monitoring
  • Female
  • Forecasting / methods
  • Humans
  • Models, Biological
  • Mosquito Vectors / virology*
  • Retrospective Studies
  • Seasons
  • United States / epidemiology
  • West Nile Fever / epidemiology*
  • West Nile Fever / transmission
  • West Nile Fever / virology
  • West Nile virus / pathogenicity*