About: Google Trends-based non-English language query data and epidemic diseases: a cross-sectional study of the popular search behaviour in Taiwan

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About: Google Trends-based non-English language query data and epidemic diseases: a cross-sectional study of the popular search behaviour in Taiwan Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Google Trends-based non-English language query data and epidemic diseases: a cross-sectional study of the popular search behaviour in Taiwan
Creator	Suen, Jau-Ling Lin, Chun-Yu Chen, Y.-H Chang, Yu-Wei Chiang, Wei-Lun Gianfredi, Hung, Ling-Chien Reviewer, Vincenza Tsai, Yi-Chang Version 1 -Review, Wang, Wen-Hung
Source	PMC
abstract	OBJECTIVE: This study developed a surveillance system suitable for monitoring epidemic outbreaks and assessing public opinion in non-English-speaking countries. We evaluated whether social media reflects social uneasiness and fear during epidemic outbreaks and natural catastrophes. DESIGN: Cross-sectional study. SETTING: Freely available epidemic data in Taiwan. MAIN OUTCOME MEASURE: We used weekly epidemic incidence data obtained from the Taiwan Centers for Disease Control and online search query data obtained from Google Trends between 4 October 2015 and 2 April 2016. To validate whether non-English query keywords were useful surveillance tools, we estimated the correlation between online query data and epidemic incidence in Taiwan. RESULTS: With our approach, we noted that keywords 感冒 (‘common cold’), 發燒 (‘fever’) and 咳嗽 (‘cough’) exhibited good to excellent correlation between Google Trends query data and influenza incidence (r=0.898, p<0.001; r=0.773, p<0.001; r=0.796, p<0.001, respectively). They also displayed high correlation with influenza-like illness emergencies (r=0.900, p<0.001; r=0.802, p<0.001; r=0.886, p<0.001, respectively) and outpatient visits (r=0.889, p<0.001; r=0.791, p<0.001; r=0.870, p<0.001, respectively). We noted that the query 腸病毒 (‘enterovirus’) exhibited excellent correlation with the number of enterovirus-infected patients in emergency departments (r=0.914, p<0.001). CONCLUSIONS: These results suggested that Google Trends can be a good surveillance tool for epidemic outbreaks, even in Taiwan, the non-English-speaking country. Online search activity indicates that people are concerned about epidemic diseases, even if they do not visit hospitals. This prompted us to develop useful tools to monitor social media during an epidemic because such media usage reflects infectious disease trends more quickly than does traditional reporting.
has issue date	2020-07-05(xsd:dateTime)
bibo:doi	10.1136/bmjopen-2019-034156
bibo:pmid	32624467
has license	cc-by-nc
sha1sum (hex)	26900be3d638c8f0bb614370bdaa664cfdd7a697
schema:url	https://doi.org/10.1136/bmjopen-2019-034156
resource representing a document's title	Google Trends-based non-English language query data and epidemic diseases: a cross-sectional study of the popular search behaviour in Taiwan
has PubMed Central identifier	PMC7337886
has PubMed identifier	32624467
schema:publication	BMJ Open
resource representing a document's body	covid:26900be3d638c8f0bb614370bdaa664cfdd7a697#body_text
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