Results from the second year of a collaborative effort to forecast influenza seasons in the United States

Matthew Biggerstaff, Michael Johansson, David Alper, Logan C. Brooks, Prithwish Chakraborty, David C. Farrow, Sangwon Hyun, Sasikiran Kandula, Craig McGowan, Naren Ramakrishnan, Roni Rosenfeld, Jeffrey Shaman, Rob Tibshirani, Ryan J. Tibshirani, Alessandro Vespignani, Wan Yang, Qian Zhang, Carrie Reed

Accurate forecasts could enable more informed public health decisions. Since 2013, CDC has worked with external researchers to improve influenza forecasts by coordinating seasonal challenges for the United States and the 10 Health and Human Service Regions. Forecasted targets for the 2014-15 challenge were the onset week, peak week, and peak intensity of the season and the weekly percent of outpatient visits due to influenza-like illness (ILI) 1-4 weeks in advance. We used a logarithmic scoring rule to score the weekly forecasts, averaged the scores over an evaluation period, and then exponentiated the resulting logarithmic score. Poor forecasts had a score near 0, and perfect forecasts a score of 1. Five teams submitted forecasts from seven different models. At the national level, the team scores for onset week ranged from <0.01 to 0.41, peak week ranged from 0.08 to 0.49, and peak intensity ranged from <0.01 to 0.17. The scores for predictions of ILI 1-4 weeks in advance ranged from 0.02-0.38 and was highest 1 week ahead. Forecast skill varied by HHS region. Forecasts can predict epidemic characteristics that inform public health actions. CDC, state and local health officials, and researchers are working together to improve forecasts.