Forecasting the impacts of climate change on Aedes-borne viruses—especially dengue, chikungunya, and Zika—is a key component of public health preparedness. We apply an empirically parameterized model
Real-Time Ensemble Predictions for 2014. For 2014, some of the lowest RMSE scores were for the earliest time periods suggesting predictions could be made early. (XLSX 37Â kb)
Background Aedes-borne diseases pose escalating public health challenges globally, influenced not only by ecological and biological factors but critically by social determinants of health (SDH). In Ir
West Nile virus (WNV) is a leading cause of mosquito-borne disease in the United States. Annual seasonal outbreaks vary in size and location. Predicting where and when higher...
Model-based epidemiological assessment is useful to support decision-making at the beginning of an emerging Aedes-transmitted outbreak. However, early forecasts are generally unreliable as little info