Flu forecasting tool uses evolution to make earlier predictions

October 25, 2017, University of Chicago Medical Center
Credit: CC0 Public Domain

Each year, public health officials monitor the spread of influenza to identify which flu strains need to go into that year's vaccines and where outbreaks will occur. But it can be difficult to predict how bad a particular flu season will be until people actually start getting sick.

A new flu forecasting tool built by scientists at the University of Chicago aims to make better predictions by combining data about how the virus spreads with an estimate of how much the current virus evolved compared to recent years. Using historical data as a test, the new accurately predicted the total number of cases for each in the U.S. from 2002 to 2016, and produced an accurate, real-time prediction for the 2016-17 season before it started last year.

The researchers say the new model, described this week in Science Translational Medicine, can be used to complement existing forecasting tools that track flu outbreaks in real time by providing an early warning before the season starts.

"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 Mercedes Pascual, PhD, professor of ecology and evolution at UChicago and senior author of the study. "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 influenza strains circulate in the human population: H3N2, H1N1, and two B variants. These viruses spread seasonally each year because of a phenomenon known as antigenic drift. They evolve just enough to evade human immune systems, but not enough to develop into completely new versions of the virus.

If the virus changed a lot, more people get sick because they haven't been exposed to that particular variation. But most flu forecasting models don't factor in this change. Instead, they are based on mathematical calculations of how quickly the virus is spreading—and these projections can't be made until the current season is already underway.

For the new model, Pascual and Xiangjun Du, PhD, a postdoctoral fellow at UChicago who led the study, analyzed genetic sequences from previous years of the H3N2 virus. They then compared them to early samples of the current virus that were collected before the season started each year. This allowed them to create an evolutionary index for the current virus, or a measure of how much it changed. Adding this crucial piece of information to the generates an early estimate of the overall severity of the coming , because they can make a projection as soon as current year's variation of the virus starts to emerge in the spring and summer.

"Every two or three years, there is a big genetic change in the virus, which can make many more people sick," Du said. "Without factoring evolution into the model, you cannot capture these peaks in the number of cases."

The model was built with historical data about the H3N2 virus, although it could be adapted for other strains of flu. The researchers tested its accuracy by seeing how well it predicted past seasons from 2002-2016, including years that weren't used to initially calibrate the tool (the final five from 2011-2016). It generated accurate estimates of the overall number of cases in the U.S. for each year, and produced an accurate forecast for the 2016-17 season before it started last fall.

So, what's in store for this flu season?

"That's the million-dollar question," Pascual said. "Our analysis for this year showed that the is already changing in a significant way. We predict an outbreak that is above average but moderate, not severe, because last year was such a bad season."

The study, "Evolution-informed forecasting of seasonal influenza A (H3N2)," was supported by the University of Chicago. Additional authors include Aaron A. King and Robert J. Woods from the University of Michigan, who were supported by the National Institutes of Health, the National Institute of General Medical Sciences and the National Institute of Allergy and Infectious Diseases.

Explore further: Flu simulations suggest pandemics more likely in spring, early summer

More information: X. Du el al., "Evolution-informed forecasting of seasonal influenza A (H3N2)," Science Translational Medicine (2017). stm.sciencemag.org/lookup/doi/ … scitranslmed.aan5325

Related Stories

Flu simulations suggest pandemics more likely in spring, early summer

October 19, 2017
New statistical simulations suggest that Northern Hemisphere flu pandemics are most likely to emerge in late spring or early summer at the tail end of the normal flu season, according to a new study published in PLOS Computational ...

Experts say flu season could be severe this year

September 22, 2017
If last year's active flu season and this year's severe season in the Southern Hemisphere is any indication of what flu season will look like across the country beginning this fall, then it's important to get vaccinated soon ...

This may not be the 'biggest flu season on record', but it is a big one – here are some possible reasons

August 18, 2017
This year, the number of laboratory-confirmed influenza (flu) virus infections began rising earlier than usual and hit historic highs in some Australian states. If you have been part of any gathering this winter, this is ...

A new approach to predict evolution of influenza viruses can enhance vaccine efficacy

December 7, 2015
New results from a study performed at the University of Helsinki suggest that genomic information from circulating influenza viruses can help in producing more efficient seasonal vaccines. The researchers were able to develop ...

New strategy could yield more precise seasonal flu vaccine

May 23, 2016
During the 2014-15 flu season, the poor match between the virus used to make the world's vaccine stocks and the circulating seasonal virus yielded a vaccine that was less than 20 percent effective.

Recommended for you

Ambitious global virome project could mark end of pandemic era

February 23, 2018
Rather than wait for viruses like Ebola, SARS and Zika to become outbreaks that force the world to react, a new global initiative seeks to proactively identify, prepare for and stop viral threats before they become pandemics.

Forecasting antibiotic resistance with a 'weather map' of local data

February 23, 2018
The resistance that infectious microbes have to antibiotics makes it difficult for physicians to confidently select the right drug to treat an infection. And that resistance is dynamic: It changes from year to year and varies ...

Scientists gain new insight on how antibodies interact with widespread respiratory virus

February 22, 2018
Scientists have found and characterized the activity of four antibodies produced by the human immune system that target an important protein found in respiratory syncytial virus (RSV), according to new research published ...

Study reveals how kidney disease happens

February 22, 2018
Monash researchers have solved a mystery, revealing how certain immune cells work together to instigate autoimmune kidney disease.

Past encounters with the flu shape vaccine response

February 20, 2018
New research on why the influenza vaccine was only modestly effective in recent years shows that immune history with the flu influences a person's response to the vaccine.

Building better tiny kidneys to test drugs and help people avoid dialysis

February 16, 2018
A free online kidney atlas built by USC researchers empowers stem cell scientists everywhere to generate more human-like tiny kidneys for testing new drugs and creating renal replacement therapies.

0 comments

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.