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 in | Clinical infectious diseases Vol. 49; no. 10; pp. 1557 - 1564 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Oxford
The University of Chicago Press
15.11.2009
University of Chicago Press Oxford University Press |
Subjects | |
Online Access | Get full text |
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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. |
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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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Title | Google Trends: A Web-Based Tool for Real-Time Surveillance of Disease Outbreaks |
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