UChicago Scientists Develop Tool to Predict Severity of Flu Season

Did you get your flu shot yet?

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Flu season begins in the U.S. this time of year, and though it’s an annual occurrence, every flu season is different, according to the Centers for Disease Control and Prevention.

Each year, flu vaccines are updated to protect against the influenza viruses that research shows will be most common during the upcoming season. Although public health officials track the spread of flu in order to identify which viruses should be included in each year’s vaccination, it can be difficult to predict how bad a specific flu season will be until people start getting sick.

But a new flu forecasting tool developed by University of Chicago researchers could give public health officials a boost.

UChicago says the tool, which combines data about how the virus spreads with an estimate of how much the current virus evolved compared to recent years, accurately predicted the total number of flu cases for each season in the U.S. from 2002 to 2016 when compared to historical data.

“Combining information about the evolution of the virus with epidemiological data will generate disease forecasts before the season begins, significantly earlier than what is currently possible,” said senior study author Mercedes Pascual, a professor of ecology and evolution at UChicago, in a statement. “You could imagine using our model to make an early prediction about overall severity of the season, and then use other methods to forecast the timing of the outbreak once it begins.”

Each year, four flu strains—H3N2, H1N1 and two B variants—spread seasonally because they evolve just enough to evade human immune systems but not enough to develop into new versions of the virus. If the virus changes drastically, more people get sick because they haven’t been exposed to that particular variation.

Most flu forecasting models don’t factor in the potential for drastic change in the virus. Instead, they’re based on mathematical calculations of how quickly the virus is spreading, which can’t be determined until the flu season is already underway.

Researchers analyzed genetic sequences of the H3N2 virus from past years and compared them to early samples of the current virus that were collected before the season started each year. This allowed researchers to measure how much the virus changed. Adding this information to the new flu forecasting model creates an early estimate of the overall severity of the upcoming flu season because predictions can be made as soon as viruses begin to emerge in the spring and summer, according to a press release.

“Every two or three years, there is a big genetic change in the virus, which can make many more people sick,” said Xiangjun Du, a UChicago postdoctoral fellow who led the study, in a statement. “Without factoring evolution into the model, you cannot capture these peaks in the number of cases.”

The model produced an accurate, real-time prediction for the 2016-17 flu season before it began last fall, according to researchers. As for this year’s flu season, researchers predict it will be better than last year.

“Our analysis for this year showed that the virus is already changing in a significant way,” Pascual said in a statement. “We predict an outbreak that is above average but moderate, not severe, because last year was such a bad season.”

Contact Kristen Thometz: @kristenthometz [email protected] | (773) 509-5452

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