There’s no shortage of experts monitoring influenza outbreaks around the globe.

The Centers for Disease Control and Prevention tracks flu activity in the United States year round and produces weekly flu activity reports between the peak months of October to May. Likewise, the World Health Organization constantly gathers epidemiological surveillance data, and releases updates on outbreaks taking place anywhere, anytime.

Still, despite the monitoring and the annual push to administer flu vaccines, influenza still sickens millions of people around the world each year, leading to as many as 500,000 deaths annually. Young children and the elderly in particular are at risk.

But what if we were better at predicting – and preparing for – seasonal flu outbreaks?

That’s the impetus driving a team of researchers trying to show that it is possible to predict the timing and intensity of flu outbreaks in subtropical climates, such as Hong Kong, where flu seasons occur at irregular intervals throughout the year.

The group, which included scientists from Columbia University and the University of Hong Kong, has created a computer model to run various simulations of an outbreak and predict its magnitude and peak, according to a study published Thursday in the journal PLOS Computational Biology.

As a test case, the researchers gathering flu data from dozens of outpatient clinics and lab reports in Hong Kong between 1998 and 2013, then explored whether their system could accurately predict how outbreaks played out during those years. They said the program did remarkably well at predicting the peak of an outbreak several weeks in advance.

That’s not to say it was perfect. Researchers said the accuracy of the predictions varied, depending on the strength of an outbreak and how far in advance they tried to make a prediction. In addition, forecasts for specific strains of influenza proved more reliable than those for overall epidemics, and it was easier to predict the peak and magnitude of an outbreak than exactly when it would begin or how long it might last.

Why does better prediction matter?

“These forecasts provide information at lead times that can be valuable for both the public and heath officials,” Jeffery Shaman, a Columbia environmental health science professor who last year helped develop a computer model to forecast the spread of the Ebola virus, said in an announcement of the findings.

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