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Using Google Trends for Influenza Surveillance in South China
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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3555864/ https://www.ncbi.nlm.nih.gov/pubmed/23372837 http://dx.doi.org/10.1371/journal.pone.0055205 |
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author | Kang, Min Zhong, Haojie He, Jianfeng Rutherford, Shannon Yang, Fen |
author_facet | Kang, Min Zhong, Haojie He, Jianfeng Rutherford, Shannon Yang, Fen |
author_sort | Kang, Min |
collection | PubMed |
description | 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 influenza-like 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. |
format | Online Article Text |
id | pubmed-3555864 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-35558642013-01-31 Using Google Trends for Influenza Surveillance in South China Kang, Min Zhong, Haojie He, Jianfeng Rutherford, Shannon Yang, Fen PLoS One Research Article 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 influenza-like 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. Public Library of Science 2013-01-25 /pmc/articles/PMC3555864/ /pubmed/23372837 http://dx.doi.org/10.1371/journal.pone.0055205 Text en © 2013 Kang et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Kang, Min Zhong, Haojie He, Jianfeng Rutherford, Shannon Yang, Fen Using Google Trends for Influenza Surveillance in South China |
title | Using Google Trends for Influenza Surveillance in South China |
title_full | Using Google Trends for Influenza Surveillance in South China |
title_fullStr | Using Google Trends for Influenza Surveillance in South China |
title_full_unstemmed | Using Google Trends for Influenza Surveillance in South China |
title_short | Using Google Trends for Influenza Surveillance in South China |
title_sort | using google trends for influenza surveillance in south china |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3555864/ https://www.ncbi.nlm.nih.gov/pubmed/23372837 http://dx.doi.org/10.1371/journal.pone.0055205 |
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