Researchers report the results of 16 teams of dengue virus epidemic forecasters, who used a variety of data and predictive models to forecast the severity of dengue over 8 seasons in Peru and Puerto Rico; the results showed that the teams' prediction skill was strong late in the season and weak early in the season and provide a framework for continually refining future epidemic forecasting, according to the authors.
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Article #19-09865: "An open challenge to advance probabilistic forecasting for dengue epidemics," by Michael A. Johansson et al.
MEDIA CONTACT: Michael A. Johansson, Centers for Disease Control and Prevention, Atlanta, GA; tel: 404-639-3286; email: media@cdc.gov
Proceedings of the National Academy of Sciences