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High correlation of Middle East respiratory syndrome spread with Google search and Twitter trends in Korea
The Middle East respiratory syndrome coronavirus (MERS-CoV) was exported to Korea in 2015, resulting in a threat to neighboring nations. We evaluated the possibility of using a digital surveillance system based on web searches and social media data to monitor this MERS outbreak. We collected the num...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5011762/ https://www.ncbi.nlm.nih.gov/pubmed/27595921 http://dx.doi.org/10.1038/srep32920 |
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author | Shin, Soo-Yong Seo, Dong-Woo An, Jisun Kwak, Haewoon Kim, Sung-Han Gwack, Jin Jo, Min-Woo |
author_facet | Shin, Soo-Yong Seo, Dong-Woo An, Jisun Kwak, Haewoon Kim, Sung-Han Gwack, Jin Jo, Min-Woo |
author_sort | Shin, Soo-Yong |
collection | PubMed |
description | The Middle East respiratory syndrome coronavirus (MERS-CoV) was exported to Korea in 2015, resulting in a threat to neighboring nations. We evaluated the possibility of using a digital surveillance system based on web searches and social media data to monitor this MERS outbreak. We collected the number of daily laboratory-confirmed MERS cases and quarantined cases from May 11, 2015 to June 26, 2015 using the Korean government MERS portal. The daily trends observed via Google search and Twitter during the same time period were also ascertained using Google Trends and Topsy. Correlations among the data were then examined using Spearman correlation analysis. We found high correlations (>0.7) between Google search and Twitter results and the number of confirmed MERS cases for the previous three days using only four simple keywords: “MERS”, “[Image: see text]” (“MERS (in Korean)”), “[Image: see text]” (“MERS symptoms (in Korean)”), and “[Image: see text]” (“MERS hospital (in Korean)”). Additionally, we found high correlations between the Google search and Twitter results and the number of quarantined cases using the above keywords. This study demonstrates the possibility of using a digital surveillance system to monitor the outbreak of MERS. |
format | Online Article Text |
id | pubmed-5011762 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-50117622016-09-12 High correlation of Middle East respiratory syndrome spread with Google search and Twitter trends in Korea Shin, Soo-Yong Seo, Dong-Woo An, Jisun Kwak, Haewoon Kim, Sung-Han Gwack, Jin Jo, Min-Woo Sci Rep Article The Middle East respiratory syndrome coronavirus (MERS-CoV) was exported to Korea in 2015, resulting in a threat to neighboring nations. We evaluated the possibility of using a digital surveillance system based on web searches and social media data to monitor this MERS outbreak. We collected the number of daily laboratory-confirmed MERS cases and quarantined cases from May 11, 2015 to June 26, 2015 using the Korean government MERS portal. The daily trends observed via Google search and Twitter during the same time period were also ascertained using Google Trends and Topsy. Correlations among the data were then examined using Spearman correlation analysis. We found high correlations (>0.7) between Google search and Twitter results and the number of confirmed MERS cases for the previous three days using only four simple keywords: “MERS”, “[Image: see text]” (“MERS (in Korean)”), “[Image: see text]” (“MERS symptoms (in Korean)”), and “[Image: see text]” (“MERS hospital (in Korean)”). Additionally, we found high correlations between the Google search and Twitter results and the number of quarantined cases using the above keywords. This study demonstrates the possibility of using a digital surveillance system to monitor the outbreak of MERS. Nature Publishing Group 2016-09-06 /pmc/articles/PMC5011762/ /pubmed/27595921 http://dx.doi.org/10.1038/srep32920 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Shin, Soo-Yong Seo, Dong-Woo An, Jisun Kwak, Haewoon Kim, Sung-Han Gwack, Jin Jo, Min-Woo High correlation of Middle East respiratory syndrome spread with Google search and Twitter trends in Korea |
title | High correlation of Middle East respiratory syndrome spread with Google search and Twitter trends in Korea |
title_full | High correlation of Middle East respiratory syndrome spread with Google search and Twitter trends in Korea |
title_fullStr | High correlation of Middle East respiratory syndrome spread with Google search and Twitter trends in Korea |
title_full_unstemmed | High correlation of Middle East respiratory syndrome spread with Google search and Twitter trends in Korea |
title_short | High correlation of Middle East respiratory syndrome spread with Google search and Twitter trends in Korea |
title_sort | high correlation of middle east respiratory syndrome spread with google search and twitter trends in korea |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5011762/ https://www.ncbi.nlm.nih.gov/pubmed/27595921 http://dx.doi.org/10.1038/srep32920 |
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