title: [Google Flu Trends--the initial application of big data in public health].
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.
authors: National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
authors: Xiaohui
authors: X
authors: Zou
authors: National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
authors: Wenfei
authors: W
authors: Zhu
authors: National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
authors: Lei
authors: L
authors: Yang
authors: National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; Email: yshu@cnic.org.cn.
authors: Yuelong
authors: Y
authors: Shu
mesh_terms: D004196:Disease Outbreaks; D006801:Humans; D053118:Influenza A Virus, H1N1 Subtype; D007251:Influenza, Human; D020407:Internet; D011159:Population Surveillance; D011634:Public Health; D013223:Statistics as Topic; D014481:United States