Google Trends: A Web-Based Tool for Real-Time Surveillance of Disease Outbreaks

Google Flu Trends can detect regional outbreaks of influenza 7–10 days before conventional Centers for Disease Control and Prevention surveillance systems. We describe the Google Trends tool, explain how the data are processed, present examples, and discuss its strengths and limitations. Google Tren...

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Published inClinical infectious diseases Vol. 49; no. 10; pp. 1557 - 1564
Main Authors Carneiro, Herman Anthony, Mylonakis, Eleftherios
Format Journal Article
LanguageEnglish
Published Oxford The University of Chicago Press 15.11.2009
University of Chicago Press
Oxford University Press
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Abstract Google Flu Trends can detect regional outbreaks of influenza 7–10 days before conventional Centers for Disease Control and Prevention surveillance systems. We describe the Google Trends tool, explain how the data are processed, present examples, and discuss its strengths and limitations. Google Trends shows great promise as a timely, robust, and sensitive surveillance system. It is best used for surveillance of epidemics and diseases with high prevalences and is currently better suited to track disease activity in developed countries, because to be most effective, it requires large populations of Web search users. Spikes in search volume are currently hard to interpret but have the benefit of increasing vigilance. Google should work with public health care practitioners to develop specialized tools, using Google Flu Trends as a blueprint, to track infectious diseases. Suitable Web search query proxies for diseases need to be established for specialized tools or syndromic surveillance. This unique and innovative technology takes us one step closer to true real-time outbreak surveillance.
AbstractList Google Flu Trends can detect regional outbreaks of influenza 7–10 days before conventional Centers for Disease Control and Prevention surveillance systems. We describe the Google Trends tool, explain how the data are processed, present examples, and discuss its strengths and limitations. Google Trends shows great promise as a timely, robust, and sensitive surveillance system. It is best used for surveillance of epidemics and diseases with high prevalences and is currently better suited to track disease activity in developed countries, because to be most effective, it requires large populations of Web search users. Spikes in search volume are currently hard to interpret but have the benefit of increasing vigilance. Google should work with public health care practitioners to develop specialized tools, using Google Flu Trends as a blueprint, to track infectious diseases. Suitable Web search query proxies for diseases need to be established for specialized tools or syndromic surveillance. This unique and innovative technology takes us one step closer to true real-time outbreak surveillance.
Google Flu Trends can detect regional outbreaks of influenza 7-10 days before conventional Centers for Disease Control and Prevention surveillance systems. We describe the Google Trends tool, explain how the data are processed, present examples, and discuss its strengths and limitations. Google Trends shows great promise as a timely, robust, and sensitive surveillance system. It is best used for surveillance of epidemics and diseases with high prevalences and is currently better suited to track disease activity in developed countries, because to be most effective, it requires large populations of Web search users. Spikes in search volume are currently hard to interpret but have the benefit of increasing vigilance. Google should work with public health care practitioners to develop specialized tools, using Google Flu Trends as a blueprint, to track infectious diseases. Suitable Web search query proxies for diseases need to be established for specialized tools or syndromic surveillance. This unique and innovative technology takes us one step closer to true real-time outbreak surveillance. [PUBLICATION ABSTRACT]
Author Mylonakis, Eleftherios
Carneiro, Herman Anthony
Author_xml – sequence: 1
  givenname: Herman Anthony
  surname: Carneiro
  fullname: Carneiro, Herman Anthony
  organization: Division of Infectious Diseases, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
– sequence: 2
  givenname: Eleftherios
  surname: Mylonakis
  fullname: Mylonakis, Eleftherios
  email: emylonakis@partners.org
  organization: Division of Infectious Diseases, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
BackLink http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=22121881$$DView record in Pascal Francis
https://www.ncbi.nlm.nih.gov/pubmed/19845471$$D View this record in MEDLINE/PubMed
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Snippet Google Flu Trends can detect regional outbreaks of influenza 7–10 days before conventional Centers for Disease Control and Prevention surveillance systems. We...
Google Flu Trends can detect regional outbreaks of influenza 7-10 days before conventional Centers for Disease Control and Prevention surveillance systems. We...
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SubjectTerms Biological and medical sciences
Data Collection - methods
Disease control
Disease Outbreaks
Disease prevention
Epidemics
Epidemiology
Humans
Infectious diseases
Influenza
Influenza A virus
Influenza, Human - epidemiology
Internet
Medical sciences
Preventive medicine
Search engines
Search terms
Surfing
SURFING THE WEB
Surveillance
Web services
West Nile virus
Title Google Trends: A Web-Based Tool for Real-Time Surveillance of Disease Outbreaks
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