Literature DB >> 18954267

Using internet searches for influenza surveillance.

Philip M Polgreen1, Yiling Chen, David M Pennock, Forrest D Nelson.   

Abstract

The Internet is an important source of health information. Thus, the frequency of Internet searches may provide information regarding infectious disease activity. As an example, we examined the relationship between searches for influenza and actual influenza occurrence. Using search queries from the Yahoo! search engine ( http://search.yahoo.com ) from March 2004 through May 2008, we counted daily unique queries originating in the United States that contained influenza-related search terms. Counts were divided by the total number of searches, and the resulting daily fraction of searches was averaged over the week. We estimated linear models, using searches with 1-10-week lead times as explanatory variables to predict the percentage of cultures positive for influenza and deaths attributable to pneumonia and influenza in the United States. With use of the frequency of searches, our models predicted an increase in cultures positive for influenza 1-3 weeks in advance of when they occurred (P < .001), and similar models predicted an increase in mortality attributable to pneumonia and influenza up to 5 weeks in advance (P < .001). Search-term surveillance may provide an additional tool for disease surveillance.

Entities:  

Mesh:

Year:  2008        PMID: 18954267     DOI: 10.1086/593098

Source DB:  PubMed          Journal:  Clin Infect Dis        ISSN: 1058-4838            Impact factor:   9.079


  166 in total

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2.  Predicting consumer behavior with Web search.

Authors:  Sharad Goel; Jake M Hofman; Sébastien Lahaie; David M Pennock; Duncan J Watts
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3.  Accurate estimation of influenza epidemics using Google search data via ARGO.

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Review 4.  Early detection of disease outbreaks using the Internet.

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Authors:  Daniel B Neill; Karl A Soetebier
Journal:  Emerg Health Threats J       Date:  2011-12-06

6.  Twitter improves influenza forecasting.

Authors:  Michael J Paul; Mark Dredze; David Broniatowski
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8.  "Google flu trends" and emergency department triage data predicted the 2009 pandemic H1N1 waves in Manitoba.

Authors:  Mohammad Tufail Malik; Abba Gumel; Laura H Thompson; Trevor Strome; Salaheddin M Mahmud
Journal:  Can J Public Health       Date:  2011 Jul-Aug

9.  Eliciting Disease Data from Wikipedia Articles.

Authors:  Geoffrey Fairchild; Sara Y Del Valle; Lalindra De Silva; Alberto M Segre
Journal:  Proc Int AAAI Conf Weblogs Soc Media       Date:  2015-05

10.  Web queries as a source for syndromic surveillance.

Authors:  Anette Hulth; Gustaf Rydevik; Annika Linde
Journal:  PLoS One       Date:  2009-02-06       Impact factor: 3.240

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