Anywhere from 3,000 to 50,000 people die from the flu each year in the U.S. One of the principal challenges for public health officials is to identify the unique shape of a flu season early on. A new study published Thursday by two researchers at Boston Children’s Hospital offers them a shortcut: Wikipedia. By analyzing traffic on 35 of the site’s flu-related pages, David McIver and John Brownstein say they can determine flu levels up to two weeks faster than the Centers for Disease Control and Prevention.
The study will inevitably draw comparisons with Google Flu Trends, which for the past seven years has used data about flu-related search terms to plot outbreaks on a map. (Brownstein and McIver have served as advisers on that project.) Both initiatives claim to be speedier than traditional public health agencies, such as the CDC, based on the assumption that Web searches for flu symptoms come before visits to doctors’ offices. The Google Flu Trends results were seen as a triumph of big data analysis—until the results were shown to be less prescient than initially believed. A paper published last month in Science showed that Google overestimated the prevalence of the flu in 100 of 108 weeks over the 2011-12 flu season.