When Google got flu wrong

US outbreak foxes a leading web-based method for tracking seasonal flu

When influenza hit early and hard in the United States this year, it quietly claimed an unacknowledged victim: one of the cutting-edge techniques being used to monitor the outbreak. A comparison with traditional surveillance data showed that Google Flu Trends, which estimates prevalence from flu-related Internet searches, had drastically overestimated peak flu levels. The glitch is no more than a temporary setback for a promising strategy, experts say, and Google is sure to refine its algorithms. But as flu-tracking techniques based on mining of web data and on social media proliferate, the episode is a reminder that they will complement, but not substitute for, traditional epidemiological surveillance networks.
“It is hard to think today that one can provide disease surveillance without existing systems,” says Alain-Jacques Valleron, an epidemiologist at the Pierre and Marie Curie University in Paris, and founder of France’s Sentinelles monitoring network. “The new systems depend too much on old existing ones to be able to live without them,” he adds.
This year’s US flu season started around November and seems to have peaked just after Christmas, making it the earliest flu season since 2003. It is also causing more serious illness and deaths than usual, particularly among the elderly, because, just as in 2003, the predominant strain this year is H3N2 — the most virulent of the three main seasonal flu strains.
Traditional flu monitoring depends in part on national networks of physicians who report cases of patients with influenza-like illness (ILI) — a diffuse set of symptoms, including high fever, that is used as a proxy for flu. That estimate is then refined by testing a subset of people with these symptoms to determine how many have flu and not some other infection.
With its creation of the Sentinelles network in 1984, France was the first country to computerize its surveillance. Many countries have since developed similar networks — the US system, overseen by the Centers for Disease Control and Prevention (CDC) in Atlanta, Georgia, includes some 2,700 health-care centres that record about 30 million patient visits annually.
But the near-global coverage of the Internet and burgeoning social-media platforms such as Twitter have raised hopes that these technologies could open the way to easier, faster estimates of ILI, spanning larger populations.
The mother of these new systems is Google’s, launched in 2008. Based on research by Google and the CDC, it relies on data mining records of flu-related search terms entered in Google’s search engine, combined with computer modelling. Its estimates have almost exactly matched the CDC’s own surveillance data over time — and it delivers them several days faster than the CDC can. The system has since been rolled out to 29 countries worldwide, and has been extended to include surveillance for a second disease, dengue.

By Declan Butler
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