Real-time West Nile virus forecasting in 2018
Year: 2019
Type: conference-abstract
Abstract: TPS 751: Farms, antibiotics, infections, Exhibition Hall, Ground floor, August 26, 2019, 3:00 PM - 4:30 PM West Nile virus (WNV) is the most widespread cause of arboviral neurological disease in the world; however, there is considerable inter-annual variation in the number of human cases. As a consequence, effective allocation of public health resources is challenging and often reactive, a circumstance that highlights the need for accurate, real-time forecasts of the burden of disease. Recently, we showed that accurate and reliable predictions of seasonal WNV outbreaks can be made using a mathematical model representing WNV transmission dynamics among mosquitoes and birds, as well as spillover to humans. We then expanded the core model to include environmental forcing (average daily temperature [i.e. climatology] for the region) by accounting for temperature modulation of the extrinsic incubation period. The mathematical model is optimized using a data assimilation method and two observed data streams: mosquito infection rates and reported human WNV cases. These retrospective forecasts were then used to calibrate estimation of real-time forecast expected accuracies for various predicted features: outbreak peak timing, peak magnitude, and total number of infected mosquitoes for the season and the number of human cases in the next 4 weeks and over the season. Weekly forecasts of WNV were generated in real time using this calibrated system for 4 California Counties during the 2018 outbreak season. Overall, the real-time forecasts were able to estimate accurately the peak timing, peak magnitude, and total number of infected mosquitoes for the season in real-time prior to the peak of infected mosquitoes. Forecasts of human WNV cases over the next 4-weeks were able to provide accurate prediction intervals of future observations: the 4-week ahead 50% prediction interval captured 55% of observations. Here we present the models and evaluation of the real-time forecasts.
Source: Environmental Epidemiology
Authors: DeFelice N, Barker C, Shaman J
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $1,200
OpenAlex ID: W2981772273