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Google Flu Trends--the initial application of big data in public health / 中华预防医学杂志
Chinese Journal of Preventive Medicine ; (12): 581-584, 2015.
Article in Chinese | WPRIM | ID: wpr-270035
ABSTRACT
Google Flu Trends (GFT) was the first application of big data in the public health field. GFT was open online in 2009 and attracted worldwide attention immediately. However, GFT failed catching the 2009 pandemic H1N1 and kept overestimating the intensity of influenza-like illness in the 2012-2014 season in the United States. GFT model has been updated for three times since 2009, making its prediction bias controlled. Here, we summarized the mechanism GFT worked, the strategy GFT used to update, and its influence on public health.
Subject(s)
Full text: Available Index: WPRIM (Western Pacific) Main subject: United States / Population Surveillance / Public Health / Disease Outbreaks / Statistics as Topic / Internet / Influenza, Human / Influenza A Virus, H1N1 Subtype Type of study: Prognostic study / Screening study Limits: Humans Country/Region as subject: North America Language: Chinese Journal: Chinese Journal of Preventive Medicine Year: 2015 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Main subject: United States / Population Surveillance / Public Health / Disease Outbreaks / Statistics as Topic / Internet / Influenza, Human / Influenza A Virus, H1N1 Subtype Type of study: Prognostic study / Screening study Limits: Humans Country/Region as subject: North America Language: Chinese Journal: Chinese Journal of Preventive Medicine Year: 2015 Type: Article