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韩国国家流感监测数据与谷歌趋势之间的相关性。

Correlation between national influenza surveillance data and google trends in South Korea.

作者信息

Cho Sungjin, Sohn Chang Hwan, Jo Min Woo, Shin Soo-Yong, Lee Jae Ho, Ryoo Seoung Mok, Kim Won Young, Seo Dong-Woo

机构信息

Department of Emergency Medicine, University of Ulsan, College of Medicine, Asan Medical Center, Seoul, South Korea.

出版信息

PLoS One. 2013 Dec 5;8(12):e81422. doi: 10.1371/journal.pone.0081422. eCollection 2013.

Abstract

BACKGROUND

In South Korea, there is currently no syndromic surveillance system using internet search data, including Google Flu Trends. The purpose of this study was to investigate the correlation between national influenza surveillance data and Google Trends in South Korea.

METHODS

Our study was based on a publicly available search engine database, Google Trends, using 12 influenza-related queries, from September 9, 2007 to September 8, 2012. National surveillance data were obtained from the Korea Centers for Disease Control and Prevention (KCDC) influenza-like illness (ILI) and virologic surveillance system. Pearson's correlation coefficients were calculated to compare the national surveillance and the Google Trends data for the overall period and for 5 influenza seasons.

RESULTS

The correlation coefficient between the KCDC ILI and virologic surveillance data was 0.72 (p<0.05). The highest correlation was between the Google Trends query of H1N1 and the ILI data, with a correlation coefficient of 0.53 (p<0.05), for the overall study period. When compared with the KCDC virologic data, the Google Trends query of bird flu had the highest correlation with a correlation coefficient of 0.93 (p<0.05) in the 2010-11 season. The following queries showed a statistically significant correlation coefficient compared with ILI data for three consecutive seasons: Tamiflu (r = 0.59, 0.86, 0.90, p<0.05), new flu (r = 0.64, 0.43, 0.70, p<0.05) and flu (r = 0.68, 0.43, 0.77, p<0.05).

CONCLUSIONS

In our study, we found that the Google Trends for certain queries using the survey on influenza correlated with national surveillance data in South Korea. The results of this study showed that Google Trends in the Korean language can be used as complementary data for influenza surveillance but was insufficient for the use of predictive models, such as Google Flu Trends.

摘要

背景

在韩国,目前尚无利用互联网搜索数据(包括谷歌流感趋势)的症状监测系统。本研究的目的是调查韩国国家流感监测数据与谷歌趋势之间的相关性。

方法

我们的研究基于一个公开可用的搜索引擎数据库——谷歌趋势,使用了2007年9月9日至2012年9月8日期间的12个与流感相关的查询词。国家监测数据来自韩国疾病控制与预防中心(KCDC)的流感样疾病(ILI)和病毒学监测系统。计算皮尔逊相关系数,以比较整个时间段以及5个流感季节的国家监测数据和谷歌趋势数据。

结果

KCDC的ILI与病毒学监测数据之间的相关系数为0.72(p<0.05)。在整个研究期间,谷歌趋势中H1N1的查询与ILI数据之间的相关性最高,相关系数为0.53(p<0.05)。与KCDC的病毒学数据相比,在2010 - 11季节,谷歌趋势中禽流感的查询相关性最高,相关系数为0.93(p<0.05)。以下查询词与ILI数据相比,连续三个季节显示出具有统计学意义的相关系数:达菲(r = 0.59、0.86、0.90,p<0.05)、新型流感(r = 0.64、0.43、0.70,p<0.05)和流感(r = 0.68、0.43、0.77,p<0.05)。

结论

在我们的研究中,我们发现使用流感调查的某些查询词的谷歌趋势与韩国的国家监测数据相关。本研究结果表明,韩语的谷歌趋势可作为流感监测的补充数据,但不足以用于谷歌流感趋势等预测模型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/08da/3855287/e1b6c747d25f/pone.0081422.g001.jpg

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