Google Flu Trends--the initial application of big data in public health.
- Author:
Xiaohui ZOU
1
;
Wenfei ZHU
1
;
Lei YANG
1
;
Yuelong SHU
2
;
Email: YSHU@CNIC.ORG.CN.
Author Information
1. National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
2. National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
- Publication Type:Journal Article
- MeSH:
Disease Outbreaks;
Humans;
Influenza A Virus, H1N1 Subtype;
Influenza, Human;
Internet;
Population Surveillance;
Public Health;
Statistics as Topic;
United States
- From:
Chinese Journal of Preventive Medicine
2015;49(6):581-584
- CountryChina
- Language:Chinese
-
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.
