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  • Using Google Trends for Influenza Surveillance in South China

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    86628_1.pdf (417.0Kb)
    Author(s)
    Kang, Min
    Zhong, Haojie
    He, Jianfeng
    Rutherford, Shannon
    Yang, Fen
    Griffith University Author(s)
    Rutherford, Shannon
    Yang, Fuwen
    Year published
    2013
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    Abstract
    Background: Google Flu Trends was developed to estimate influenza activity in many countries; however there is currently no Google Flu Trends or other Internet search data used for influenza surveillance in China. Methods and Findings: Influenza surveillance data from 2008 through 2011 were obtained from provincial CDC influenzalike illness and virological surveillance systems of Guangdong, a province in south China. Internet search data were downloaded from the website of Google Trends. Pearson's correlation coefficients with 95% confidence intervals (95% CI) were calculated to compare surveillance data and internet ...
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    Background: Google Flu Trends was developed to estimate influenza activity in many countries; however there is currently no Google Flu Trends or other Internet search data used for influenza surveillance in China. Methods and Findings: Influenza surveillance data from 2008 through 2011 were obtained from provincial CDC influenzalike illness and virological surveillance systems of Guangdong, a province in south China. Internet search data were downloaded from the website of Google Trends. Pearson's correlation coefficients with 95% confidence intervals (95% CI) were calculated to compare surveillance data and internet search trends. The correlation between CDC ILI surveillance and CDC virus surveillance was 0.56 (95% CI: 0.43, 0.66). The strongest correlation was between the Google Trends term of Fever and ILI surveillance with a correlation coefficient of 0.73 (95% CI: 0.66, 0.79). When compared with influenza virological surveillance, the Google Trends term of Influenza A had the strongest correlation with a correlation coefficient of 0.64 (95% CI: 0.43, 0.79) in the 2009 H1N1 influenza pandemic period. Conclusions: This study shows that Google Trends in Chinese can be used as a complementary source of data for influenza surveillance in south China. More research in the future should develop new models using search trends in Chinese language to estimate local disease activity and detect early signals of outbreaks.
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    Journal Title
    PloS One
    Volume
    8
    Issue
    1
    DOI
    https://doi.org/10.1371/journal.pone.0055205
    Copyright Statement
    © 2013 Kang et al. This is an Open Access article distributed under the terms of the Creative Commons Attribution License CCAL. (http://www.plos.org/journals/license.html)
    Subject
    Health informatics and information systems
    Publication URI
    http://hdl.handle.net/10072/54748
    Collection
    • Journal articles

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