High correlation of Middle East respiratory syndrome spread with Google search and Twitter trends in Korea
High correlation of Middle East respiratory syndrome spread with Google search and Twitter trends in Korea
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DOI：
10.1038/srep32920
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发表时间：
2016-09-06
影响因子：
4.6
通讯作者：
Jo, Min-Woo
中科院分区：
文献类型：
--
作者：
Shin, Soo-Yong;Seo, Dong-Woo;Jo, Min-Woo
中东呼吸综合征冠状病毒（MERS-CoV）于2015年出口到韩国，对邻国造成威胁。我们评估了使用基于网络搜索和社交媒体数据的数字监控系统来监控MERS疫情的可能性。我们使用韩国政府MERS门户网站收集了2015年5月11日至2015年6月26日期间每日实验室确诊的MERS病例和隔离病例的数量。同一时期通过Google搜索和Twitter观察到的每日趋势也使用Google Trends和Topsy确定。然后使用斯皮尔曼相关分析检查数据之间的相关性。我们发现谷歌搜索和Twitter结果与前三天确诊的MERS病例数之间的相关性很高（>0.7），仅使用四个简单的关键词：“MERS”，（“MERS（韩语）”），（“MERS症状（韩语）”）和（“MERS医院（韩语）”）。此外，我们发现谷歌搜索和Twitter结果与使用上述关键词的隔离病例数量之间存在高度相关性。这项研究证明了使用数字监测系统来监测MERS爆发的可能性。
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.