An annual influenza season forecasting challenge issued by the US Centers for Disease Control provides unique insight into epidemic forecasting, according to a study published in the journal Scientific Reports.
An annual influenza season forecasting challenge issued by the US Centers for Disease Control provides unique insight into epidemic forecasting, according to a study published in the journal Scientific Reports.
The study, conducted by a large team of researchers, including biocomplexity scientist Matteo Convertino of Japan’s Hokkaido University, analyzed the forecasts of 14 predictive models submitted by 11 teams to the US-based Centers for Disease Control and Prevention (CDC) as part of its 2015-2016 influenza season forecasting challenge.
The CDC launched the annual challenge in 2013, encouraging academics and private industry researchers to forecast the timing, peak, and intensity of the flu season in the US. Previous efforts were directed toward forecasting Dengue fever. The general aim of the challenge is to improve influenza forecasting in order to better inform public health responses to seasonal epidemics and future pandemics.
Results from analyses of the submissions of the 2015-16 season show that forecasting skill, measured using a logarithmic score, was generally highest among the teams and their models for seasonal peak intensity and short-term forecasts, but was generally low for timing of season onset and peak week.
Read more at Hokkaido University
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