Influenza Forecasting Receives Boost from New Computer Model


Researchers at the Mailman School of Public Health at Columbia University are the first to develop a computer model that predicts influenza activity down to the local level.

Predicting the impact of the influenza virus around the world is something health officials grapple with each year, and now, a team of researchers have successfully created an additional resource to aid in the process.

According to a recent press release, researchers from the Mailman School of Public Health at Columbia University have developed a computer model to “predict the onset, duration, and magnitude of influenza outbreaks” down to the local level, and they are “the first to successfully forecast influenza with this level of geographic granularity.”

The researchers utilized data from 52 New York City emergency departments which was provided by the New York City Department of Health and Mental Hygiene. These data were combined with “lab-verified regional flu levels from the Centers for Disease Control and Prevention (CDC)” and information on the “daily population movement within the city,” such as commuter patterns, to forecast influenza activity at the local level.

Given all of these data, the computer model was able to “predict a small uptick in flu activity one week in advance with 82% accuracy; it predicted larger spikes with less accuracy. For severe and ongoing outbreaks, it predicted outbreak duration with 77% accuracy. It could correctly estimate an outbreak's magnitude up to 54% of the time.” The full study and results are published in a recent issue of PLOS Computational Biology.

With the potential for a pandemic influenza outbreak at the “top of mind” for CDC director, Tom Frieden, MD, innovative methods to predict outbreaks and protect individuals are a top priority. The CDC stoked the fires of innovation for advances to improve flu forecasting methods by initiating a contest for the scientific community in 2013. The Department of Environmental Health Sciences at the Mailman School of Public Health at Columbia University was the winner of the CDC’s “Predict the Influenza Season Challenge” to create “innovative approaches to flu forecasting” using digital data that same year.

According to the CDC, “since the competition, [the] CDC has continued to work with contest participants and a few additional groups that subsequently became involved in flu forecasting activities.” Eight external research groups participated in this initiative for the 2015-2016 influenza season.

This past summer, the CDC launched the FluView interactive application, which “shows the distribution by age group of influenza-positive tests by influenza virus type and subtype or lineage” across the country. Users can download data and drill down to view influenza activity on a regional level. In addition, to continue to monitor vaccine effectiveness for the 2016-2017 season, the CDC is “planning multiple studies on the effectiveness of flu shots. These studies measure vaccine effectiveness in preventing laboratory-confirmed influenza among persons 6 months of age and older. A summary of CDC’s latest vaccine effectiveness estimates is available at Seasonal Influenza Vaccine Effectiveness, 2005-2016.”

More information on the 2016-2017 vaccines is available at Prevention and Control of Seasonal Influenza with Vaccines Recommendations of the Advisory Committee on Immunization Practices—United States, 2016—17 Influenza Season.

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