LAUSR

Introduction: Seasonal influenza is responsible for a high disease burden in the United States and worldwide. Predicting outbreak size in advance can contribute to the timely control of seasonal influenza by informing health care and vaccination planning. Methods: Recently, a process-based model was developed for forecasting incidence dynamics ahead of the season, with the approach validated by several statistical criteria, including an accurate real-time prediction for the past 2016-2017 influenza season before it started. Results: Based on this model and data up to June 2017, a forecast for the upcoming 2017-2018 influenza season is presented here, indicating an above-average, moderately severe, outbreak dominated by the H3N2 subtype. Discussion: The prediction is consistent with surveillance data so far, which already indicate the predominance of H3N2. The forecast for the upcoming 2017-2018 influenza season reinforces the importance of the on-going vaccination campaign.