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.

Forecasting the spatial transmission of influenza in the United States

“…Similar model-data assimilation frameworks have been successfully used to forecast the local epidemic trajectory for a number of infectious diseases (13)(14)(15)(16)26). During model training, the state variables and parameters in the dynamical model are repeatedly calibrated by available observations; a forecast is then generated by integrating the optimized model into the future.…”

Counteracting structural errors in ensemble forecast of influenza outbreaks

“…In our work, we often use a simple ordinary differential equation (ODE) model to depict the underlying dynamics governing the disease transmission process 50 . Similar ODE models have produced satisfactory forecasts for a number of infectious diseases 4 , 5 , 10 , 14 , 15 .…”

“…Recent efforts have produced a number of forecasting systems for a range of infectious diseases 2 , 3 , including influenza 4 – 9 , dengue fever 10 , Ebola 11 – 13 , respiratory syncytial virus 14 , and West Nile virus 15 . Validated through retrospective forecasts of historical outbreaks, these techniques have demonstrated the feasibility of epidemiological forecast in real-time.…”

Modeling and Surveillance of Reporting Delays of Mosquitoes and Humans Infected With West Nile Virus and Associations With Accuracy of West Nile Virus Forecasts

“…In a recent study, 12 , 13 we showed that accurate and reliable forecasts of WNV outbreaks can be made using WNV surveillance data and a mathematical model representing the transmission dynamics of WNV among mosquitoes and birds, as well as spillover to humans. This model system was able to retrospectively forecast mosquito infection rates prior to the week of mosquito peak infection and to forecast accurately the seasonal total number of human WNV cases prior to when the majority of cases were reported.…”