For four of the past five years, Carnegie Mellon's forecasting efforts have proven the most accurate of all the research groups participating in the CDC's FluSight Network.
In addition to expanding CMU's existing forecasting research, the new funding will enable CMU to initiate studies on how to best communicate forecast information to the public and to leaders. It will also support efforts to determine how forecasting techniques might apply to pandemics — the rare occasions when a truly novel strain of flu is prevalent around the world.
Roni Rosenfeld, head of CMU's Machine Learning Department and leader of its epidemic forecasting efforts, said the designation of CMU and the University of Massachusetts at Amherst as the first two CDC flu forecasting centers of excellence marks a coming of age for the epidemic forecasting community.
"When the CDC began soliciting flu forecasts, they ran it as an experiment," without funding, Rosenfeld said. But as the usefulness of the forecasts became apparent, the CDC has placed greater reliance on them. "The CDC now routinely includes our forecasting in their messaging to the public and to decision makers."
"In the beginning, we had about 10 groups that voluntarily submitted forecasts," he said. "Now the CDC receives more than 40 forecast submissions. It has become a community and more and more groups are getting involved, which is the real win."