Dataset Information

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

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 ('common cold'), ('fever') and ('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 ('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.

SUBMITTER: Chang YW

PROVIDER: S-EPMC7337886 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Chang Yu-Wei YW Chiang Wei-Lun WL Wang Wen-Hung WH Lin Chun-Yu CY Hung Ling-Chien LC Tsai Yi-Chang YC Suen Jau-Ling JL Chen Yen-Hsu YH

BMJ open 20200705 7

<h4>Objective</h4>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.<h4>Design</h4>Cross-sectional study.<h4>Setting</h4>Freely available epidemic data in Taiwan.<h4>Main outcome measure</h4>We used weekly epidemic incidence data obtained from the Taiwan Centers for Disease Cont ...[more]

PMID: 32624467

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Project description:BackgroundSince the beginning of the new coronavirus pandemic, there has been much information about the disease and the virus has been in the spotlight, shared and commented upon on the Internet. However, much of this information is infodemics and can interfere with the advancement of the disease and that way that populations act. Thus, Brazil is a country that requires attention, as despite the fact that in almost two years of pandemic it has shown a devastating numbers of deaths and number of cases, and generates false, distorted and malicious news about the pandemic. This work intends to understand the attitudes of the Brazilian population using infodemic queries from the Google Trends search tool and social and income variables.MethodsData from infodemic research carried out on Google Trends, between January 1, 2020 and June 30, 2021, with socioeconomic data, such as income and education, were unified in a single database: standardization and exploratory and multivalued techniques based on grouping were used in the study.ResultsIn the analysis of the search trend of infodemic terms, it is clear that the categories of Prevention and Beliefs should stand out in Brazil, where there is a diverse culture. It is followed by the COVID-19 Treatment category, with treatments that were not those recommended by the authorities. Income transfer programs and information on socioeconomic variables did not have much impact on infodemic surveys, but it was observed that states where President Bolsonaro has more supporters had researched more infodemic information.ConclusionsIn a country as geographically large as Brazil, it is important that political authorities go to great lengths to disseminate reliable information and monitor the infodemic in the media and on the internet. It was concluded that the denial of the pandemic and the influence of political leaders influenced the search for infodemic information, contributing to a disorganization in the control of the disease and prevention measures.

Dataset Information

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

Objective

Design

Setting

Main outcome measure

Results

Conclusions

Publications

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

Similar Datasets

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