It seems that influenza is a popular target for internet-based research; perhaps because it’s so common and well-known that population trends can be picked up accurately this way.

Five scientists, and one from the CDC, have published evidence in Nature1 that Google search terms are accurate ways of measuring influenza epidemics.  Their influenza tool is available at (and has an explanation of the techniques involved).  Their accuracy seems pretty decent, as the figure below shows — red traces are CDC-recorded cases, black is the cases as predicted from Google searches.  

Google influenza searches
A comparison of model estimates for the mid-Atlantic region (black) against CDC-reported ILI percentages (red)1

There are a surprising number of on-line maps for influenza and avian influenza, although as though far as I know they’re all much more descriptive (all based on reported cases) than Google’s version, which is (sort of) predictive.  For example, there’s the avian influenza outbreak map, various maps from the WHO , and the CDC’s set of maps.  (There’s also Bird Flu Breaking Newswhich occasionally links to my posts, but the site seems to be broken; too bad, because if I remember correctly, it had an interesting variant on maps that was conceptually related to Google’s — showing where new discussion on avian flu was located.)  

  1. Jeremy Ginsberg, Matthew H. Mohebbi, Rajan S. Patel, Lynnette Brammer, Mark S. Smolinski, Larry Brilliant (2009). Detecting influenza epidemics using search engine query data Nature, 457 (7232), 1012-1014 DOI: 10.1038/nature07634[][]