Via Nature News & Comment, a fascinating report by Declan Butler: When Google got flu wrong. Excerpt (but read the whole thing):
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.
