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Influenza: Detecting epidemics early (AOP)
DOI: 10.1038/nature07634
A computational model based on web search queries can provide real-time surveillance of influenza-like illnesses, replicating patterns observed in data from the US Centers for Disease Control and Prevention. The application ‘Google Flu Trends’, launched last week, attracted a great deal of attention and the research behind the tool is published online in Nature today.
Seasonal influenza epidemics cause tens of millions of respiratory illnesses and between 250,000 and 500,000 deaths worldwide each year. Jeremy Ginsberg and colleagues used data from large numbers of Google search queries to track influenza-like illness in the United States. The frequency of certain searches is correlated with physician visits where a patient presents with influenza-like symptoms, making it possible to estimate accurately the current weekly levels of influenza activity with only a day lag time, compared with one to two weeks for traditional methods.
The authors believe that the data will be most useful as a means to spur further investigation and collection of direct disease activity.
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Jeremy Ginsberg (Google Inc. San Francisco, CA, USA)
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The paper is freely available. Please link to it here: http://www.nature.com/nature/journal/vaop/ncurrent/full/nature07634.html
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