A new system for predicting seasonal peaks of influenza in cities across the U.S., developed by a team of scientists including Dr. Marc Lipsitch of Harvard School of Public Health (HSPH), has won first place out of 11 teams in the Centers for Disease Control and Prevention’s “Predict the Influenza Season Challenge,” along with a prize of $75,000.
Participants in the CDC contest were asked to forecast the timing, peak, and intensity of the 2013-14 flu season using digital data from a variety of sources as well as innovative modeling approaches. From December 2013 through March 2014, teams were required to submit eight biweekly national and regional flu predictions, which the CDC subsequently matched against actual flu outbreak data from around the country.
The winning team, led by Dr. Jeffrey Shaman of the Columbia University Mailman School of Public Health, produced the most accurate and reliable forecasts for about 100 locations around the U.S. They based their predictions on data from Google Flu Trends (which estimates outbreaks based on the number of flu-related search queries), reports of flu-like illnesses, and verified cases of flu. They also incorporated earlier work by Dr. Shaman and Dr. Lipsitch that identified weather conditions, particularly absolute humidity levels, as important drivers of flu transmission. They then fed the data into a mathematical model that was calibrated to produce a more accurate and reliable forecast of national and regional flu activity.