Tropes

Nature 04407.txt

#When Google got flu wrong 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 overestimated drastically 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 refined then 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 developed since 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 launched Google s 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 matched almost exactly 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. Sources: Google Flu Trends (www. google. org/flutrends; CDC; Flu Near Yougoogle Flu Trends has continued to perform remarkably well, and researchers in many countries have confirmed that its ILI estimates are accurate. But the latest US flu season seems to have confounded its algorithms. Its estimate for the Christmas national peak of flu is almost double the CDC s (see Fever peaks), and some of its state data show even larger discrepancies. It is not the first time that a flu season has tripped Google up. In 2009, Flu Trends had to tweak its algorithms after its models badly underestimated ILI in the United states at the start of the H1n1 (swine flu) pandemic###a glitch attributed to changes in people s search behaviour as a result of the exceptional nature of the pandemic (S. Cook et al. PLOS ONE 6, e23610; 2011). ) Google would not comment on thisyear s difficulties. But several researchers suggest that the problems may be due to widespread media coverage of this year s severe US flu season, including the declaration of a public-health emergency by New york state last month. The press reports may have triggered many flu-related searches by people who were not ill. Few doubt that Google Flu will bounce back after its models are refined, however.""You need to be constantly adapting these models, they don t work in a vacuum, says John Brownstein, an epidemiologist at Harvard Medical school in Boston, Massachusetts.""You need to recalibrate them every year. Brownstein is one of many researchers trying to harness the power of the web to establish sentinel networks made up not of physicians, but of ordinary citizens who volunteer to report when they or someone in their family are experiencing symptoms of ILI. Flu Near You, a system run by the Healthmap initiative co-founded by Brownstein at Boston Children s Hospital, was launched in 2011 and now has 46,000 participants, covering 70,000 people. SLIDESHOW France's Sentinelles'network of doctors reporting cases of influenza-like illness has produced a clear picture of how the 2012-13#flu season has evolved. Sentinelles UMR-S 707 Inserm, UPMCSENTINELLES, UMR-S 707 Inserm, UPMCSENTINELLES, UMR-S 707 Inserm, UPMCSENTINELLES, UMR-S 707 Inserm, UPMCSENTINELLES , UMR-S 707 Inserm, UPMCSENTINELLES, UMR-S 707 Inserm, UPMCSENTINELLES, UMR-S 707 Inserm, UPMCSENTINELLES, UMR-S 707 Inserm, UPMCSENTINELLES , UMR-S 707 Inserm, UPM C

< Back - Next >