Publication Type

Journal Article

Version

publishedVersion

Publication Date

9-2016

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", ("MERS (in Korean)"), ("MERS symptoms (in Korean)"), and ("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.

Discipline

Databases and Information Systems | International and Area Studies | Software Engineering

Research Areas

Data Science and Engineering

Publication

Scientific Reports

Volume

6

First Page

1

Last Page

7

ISSN

2045-2322

Identifier

10.1038/srep32920

Publisher

Nature Research (part of Springer Nature): Fully open access journals / Nature Publishing Group

Additional URL

https://doi.org/10.1038/srep32920

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