Dataset Information

Using WeChat, a Chinese Social Media App, for Early Detection of the COVID-19 Outbreak in December 2019: Retrospective Study.

ABSTRACT:

Background

A novel coronavirus, SARS-CoV-2, was identified in December 2019, when the first cases were reported in Wuhan, China. The once-localized outbreak has since been declared a pandemic. As of April 24, 2020, there have been 2.7 million confirmed cases and nearly 200,000 deaths. Early warning systems using new technologies should be established to prevent or mitigate such events in the future.

Objective

This study aimed to explore the possibility of detecting the SARS-CoV-2 outbreak in 2019 using social media.

Methods

WeChat Index is a data service that shows how frequently a specific keyword appears in posts, subscriptions, and search over the last 90 days on WeChat, the most popular Chinese social media app. We plotted daily WeChat Index results for keywords related to SARS-CoV-2 from November 17, 2019, to February 14, 2020.

Results

WeChat Index hits for "Feidian" (which means severe acute respiratory syndrome in Chinese) stayed at low levels until 16 days ahead of the local authority's outbreak announcement on December 31, 2019, when the index increased significantly. The WeChat Index values persisted at relatively high levels from December 15 to 29, 2019, and rose rapidly on December 30, 2019, the day before the announcement. The WeChat Index hits also spiked for the keywords "SARS," "coronavirus," "novel coronavirus," "shortness of breath," "dyspnea," and "diarrhea," but these terms were not as meaningful for the early detection of the outbreak as the term "Feidian".

Conclusions

By using retrospective infoveillance data from the WeChat Index, the SARS-CoV-2 outbreak in December 2019 could have been detected about two weeks before the outbreak announcement. WeChat may offer a new approach for the early detection of disease outbreaks.

SUBMITTER: Wang W

PROVIDER: S-EPMC7572119 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Publications

Using WeChat, a Chinese Social Media App, for Early Detection of the COVID-19 Outbreak in December 2019: Retrospective Study.

Wang Wenjun W Wang Yikai Y Zhang Xin X Jia Xiaoli X Li Yaping Y Dang Shuangsuo S

JMIR mHealth and uHealth 20201005 10

<h4>Background</h4>A novel coronavirus, SARS-CoV-2, was identified in December 2019, when the first cases were reported in Wuhan, China. The once-localized outbreak has since been declared a pandemic. As of April 24, 2020, there have been 2.7 million confirmed cases and nearly 200,000 deaths. Early warning systems using new technologies should be established to prevent or mitigate such events in the future.<h4>Objective</h4>This study aimed to explore the possibility of detecting the SARS-CoV-2 ...[more]

PMID: 32931439

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Dataset Information

Using WeChat, a Chinese Social Media App, for Early Detection of the COVID-19 Outbreak in December 2019: Retrospective Study.

Background

Objective

Methods

Results

Conclusions

Publications

Using WeChat, a Chinese Social Media App, for Early Detection of the COVID-19 Outbreak in December 2019: Retrospective Study.

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