High correlation of Middle East respiratory syndrome spread with Google search and Twitter trends in Korea
Open Access
- 6 September 2016
- journal article
- Published by Springer Science and Business Media LLC in Scientific Reports
- Vol. 6 (1), 32920
- https://doi.org/10.1038/srep32920
Abstract
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”, “"Equation missing"” (“MERS (in Korean)”), “"Equation missing"” (“MERS symptoms (in Korean)”), and “"Equation missing"” (“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.This publication has 25 references indexed in Scilit:
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