UMass team working with CDC and other researchers on flu season forecasts


Published: 1/22/2018 3:33:41 PM

Research teams, including one led by biostatistician Nicholas Reich at the University of Massachusetts Amherst, are participating in a national influenza forecasting challenge to try to predict the onset, progress and peaks of regional flu outbreaks to aid prevention and control.

This year, the Reich Lab is leading an effort to improve the forecasting by increasing the collaboration between groups.

“Every year the Centers for Disease Control host a flu forecasting challenge,” Reich said. “It’s the most organized and public effort at forecasting any infectious disease anywhere in the world. This year, we wanted to take it to the next level, so we worked with other teams year-round to develop a way that our models could work together to make a single best forecast for influenza.”

While this flu season has started earlier than usual in the northeastern and southern U.S. according to the most recent data, the forecasts are still showing a fair amount of uncertainty about how big a season it will be.

Reich and colleagues at UMass Amherst’s School of Public Health and Health Sciences collaborate with teams at Carnegie Mellon University in Pittsburgh, Pennsylvania, Columbia University in New York and a group at Los Alamos National Laboratory, in New Mexico, in a group they have dubbed the “FluSight Network.” It issues a new flu season forecast every Monday for public health researchers and practitioners that compares the flu trajectory this year to past years.

To prepare for this flu season, Reich and colleagues develped a system in which each team could compare flu data over the past seven years and evaluate the models used so that they could combine them into a single ensemble forecast. They found that four of their collaborative ensemble methods had higher average scores than any of the individual models. The team is now submitting forecasts from their best performing model and are posting them once a week this season to the CDC’s 2017-18 FluSight Challenge. Reich estimates that there are about 20 teams this year participating in the CDC challenge nationwide, producing about 30 different models. Each model forecasts the onset of the flu season, how it will progress over the coming few weeks, when it will peak, and how intense the peak will be compared to other seasons.

In a heavy flu season, from 5 to 12 percent of doctor’s visits are for influenza-like-illness, and that number varies regionally in the U.S. This metric is one of the key indicators for the CDC of how bad the flu season is, Reich said.

“Certainly for the CDC, there are policy decisions that could be impacted by these forecasts, including the timing of public communication about flu season starting and when to get vaccinated,” he said. “Also, hospitals often try to have enhanced precautions in place during a certain peak period for the disease. If you do that too early, or for too long, you run the risk of individuals getting tired of taking the extra time to comply with the policies.”

Hospital epidemiologists and others responsible for public health decisions do not declare the onset of flu season lightly, Reich said. In hospitals, flu onset — a technical set of symptoms reported to physicians — triggers many extra time-consuming and costly precautions and procedures such as added gloves, masks and gowns, donning and doffing time, special decontamination procedures, increased surveillance and reduced visitor access, for example. There is also health care worker fatigue to consider. Hospitals want to be as effective and efficient as possible in their preparations and response to reduce time and money spent and worker burnout, he said.

“There has been tremendous progress in how we think about infectious disease forecasting in just the last five years,” Reich said. “If you compare that to something like weather forecasting, which has been going on for decades, we’re in the middle of a long process of learning and improvement. Someday we might be able to imagine having a flu forecast on our smart phones that tells us, for example, it’s an early season and I’d better get Mom to the clinic to get her vaccination early this year. We’re close, but that’s not here quite yet.”

The researchers forecasts can be viewed at


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