I wrote a script to import Wikipedia traffic data for the Influenza page and graph it. (Updates daily)<p>Graph: <a href="http://www.additiveanalytics.com/solutions/flu_tracker" rel="nofollow">http://www.additiveanalytics.com/solutions/flu_tracker</a><p>Inspired by this study published last week: <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1003581#abstract1" rel="nofollow">http://www.ploscompbiol.org/article/info:doi/10.1371/journal...</a><p>The researchers found that Wikipedia page view data provided better real-time reporting on influenza outbreaks when compared to the CDC's data (which has a typical lag of 1-2 weeks) and Google Flu Trends (which had trouble with the 2012-2013 flu season and 2009 H1N1 panic.<p>Graph was done with d3.js.
I was very recently at a conference where some folks presented their work on using Wikipedia for disease tracking - it's considerably more nuanced than just "better than CDC". Large variation by area, disease, etc.<p>Disease surveillance hasn't been well served in the past decade by breathless attempts to replace existing systems with a "Big Data" solution - syndromic surveillance, then Google Flu Trends, then Twitter, now this.<p>Combinations people! Different data streams tell you different things.