Can Twitter predict disease outbreaks?BMJ 2012; 344 doi: http://dx.doi.org/10.1136/bmj.e2353 (Published 17 May 2012) Cite this as: BMJ 2012;344:e2353
- Connie St Louis, director, science journalism MA1,
- Gozde Zorlu, freelance journalist2
- 1City University, London, UK
- Correspondence to: C St Louis
In March 2011 the most powerful earthquake and tsunami in Japan’s history caused horrifying devastation on the country’s northeastern coast. Along with a massive loss of life, the entire infrastructure of the region was destroyed: buildings were crushed and telephone lines were down. However, the mobile internet was still available, and resourceful doctors decided to use Twitter to inform chronically ill patients where they could obtain essential medicines. In a letter to the Lancet Yuichi Tamura and Keiichi Fukuda, cardiologists at Keio University School of Medicine in Tokyo, wrote: “We were able to notify displaced patients via Twitter on where to acquire medications. These ‘tweets’ immediately spread through patients’ networks, and consequently most could attend to their essential treatments.”1
Today the success of Twitter continues unabated, with over 500 million accounts and more than half of active users signing in every day. And it’s not just Twitter. The use of social media has quadrupled in the past five years: Facebook has more than 800 million active users, and WordPress, one of the most popular blogging platforms, holds over 15 million blogs.
Use of social media by doctors to communicate with patients raises a multitude of ethical conundrums, particularly verification of identity. But the medical potential of this untapped source of data is beginning to be recognised. Infectious disease experts and computer scientists are working together to use this open data to improve disease surveillance.
Public health agencies rely on traditional methods of surveillance to monitor outbreaks of disease. These include collection of diagnostic information from doctors and laboratory reporting of test results. Although this way of gathering data is very accurate, it can take a long time to identify …
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