The outbreak was announced by Wuhan Health Commission (WHC) on Decemon this day, the Chinese Centers for Disease Control and Prevention (China CDC) became involved in the investigation and response. As the outbreak is an isolated rather than recurrent event and the cutoff value to detect an outbreak based on social media and online search behavior is unknown, statistical analyses were not performed. The daily data were plotted according to time for each of the keywords. The keywords mentioned above were also investigated through Baidu Index for Hubei province.

Baidu Index (Baidu Inc) can display how frequently a keyword has been queried over a certain time period in a given region. The corresponding Chinese words were used for all keywords except for “SARS”.īaidu is the dominant Chinese internet search engine. Using WeChat Index, we obtained daily data from November 17, 2019, to February 14, 2020, for keywords related to SARS-CoV-2, such as “SARS,” “Feidian” (SARS in Chinese), “pneumonia,” “fever,” “cough,” “shortness of breath,” “dyspnea,” “fatigue,” “stuffy nose,” “runny nose,” “diarrhea,” “coronavirus,” “novel coronavirus,” and “infection” (raw data in Multimedia Appendix 1). WeChat Index, accessed on the WeChat app, is a publicly available data service that shows how frequently a specific keyword has appeared in posts, subscriptions, and search on WeChat over the previous 90 days. WeChat (called Weixin in China Tencent Inc) is the most popular social media app in China with over 1 billion monthly active users. Internet search queries from Hubei province were also investigated. Herein, we explored whether the SARS-CoV-2 outbreak in China could have been detected earlier through data available on WeChat, a popular Chinese social media app. Technologies using social media, search queries, and other internet resources offer novel and economic approaches for detecting and tracking emerging diseases and such approaches (called infodemiology and infoveillance) have been successfully used in the cases of SARS, influenza, and dengue. Analyzing data on search behaviors provides a new approach for the detection and monitoring of diseases and symptoms. Internet-based search engines are an important source for health information for people from all walks of life.

Details of an event may have been posted about on social media for several days or even months before it was reported through health institutions and official reporting structures. With the popularization of the internet and smartphones, an increasing number of people use social media (eg, Twitter and Facebook) to share information. Due to time and resource constraints, a lack of operational knowledge of reporting systems, and regulations associated with these systems, substantial lags between an outbreak event and its report are common. Traditional surveillance systems typically rely on clinical, virological, and microbiological data submitted by physicians and laboratories.

Early warning systems should be established to prevent or mitigate future disease outbreaks. The outbreak has become a pandemic, with 2.7 million confirmed cases and nearly 200,000 deaths globally as of Ap. Shortly, the cause was identified as a novel coronavirus that resembles severe acute respiratory syndrome (SARS) and it was named SARS-CoV-2.

An outbreak of pneumonia of unknown cause in Wuhan, the capital of Hubei province, China, occurred in December 2019.

Wechat china surveillance