Digital Epidemiology: Using Wikipedia and Twitter to Change the Way We Respond to Epidemics

Map generated by more than 250 million public tweets with high-resolution location information, March 2011 – January 2012. Inset shows greater Los Angeles area. Brightness of color corresponds to geographic density of tweets. doi:10.1371/journal.pcbi.1002616.g001 Source: plos.org
Map generated by more than 250 million public tweets with high-resolution location information, March 2011 – January 2012. Inset shows greater Los Angeles area. Brightness of color corresponds to geographic density of tweets. doi:10.1371/journal.pcbi.1002616.g001
Source: plos.org

There is a segment of the research community known as digital epidemiology that is taking advantage of raw data that is openly available. Here are some examples from an article on plos.org:

“A system to forecast 28 days in advance where influenza will strike hardest based on localized Wikipedia searches

A basis for predicting which communities will see more cases of flu resulting from vaccination decisions as revealed by geographically-based Twitter sentiments.”

Read more at: http://blogs.plos.org/plos/2015/01/researchers-changing-way-respond-epidemics-wikipedia-twitt/

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Dave Bove

Innovation Lover, Singer, Actor, Songwriter, Guitarist (poor one), Artist, Computer Geek, and Jolly (sometimes) Rancher...

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