Abstract
BackgroundCoronavirus disease (COVID-19) is a type of pneumonia caused by a novel coronavirus that was discovered in 2019. As of May 6, 2020, 84,407 cases and 4643 deaths have been confirmed in China. The Chinese population has expressed great concern since the COVID-19 outbreak. Meanwhile, an average of 1 billion people per day are using the Baidu search engine to find COVID-19–related health information.ObjectiveThe aim of this paper is to analyze web search data volumes related to COVID-19 in China.MethodsWe conducted an infodemiological study to analyze web search data volumes related to COVID-19. Using Baidu Index data, we assessed the search frequencies of specific search terms in Baidu to describe the impact of COVID-19 on public health, psychology, behaviors, lifestyles, and social policies (from February 11, 2020, to March 17, 2020).ResultsThe search frequency related to COVID-19 has increased significantly since February 11th. Our heat maps demonstrate that citizens in Wuhan, Hubei Province, express more concern about COVID-19 than citizens from other cities since the outbreak first occurred in Wuhan. Wuhan citizens frequently searched for content related to “medical help,” “protective materials,” and “pandemic progress.” Web searches for “return to work” and “go back to school” have increased eight-fold compared to the previous month. Searches for content related to “closed community and remote office” have continued to rise, and searches for “remote office demand” have risen by 663% from the previous quarter. Employees who have returned to work have mainly engaged in the following web searches: “return to work and prevention measures,” “return to work guarantee policy,” and “time to return to work.” Provinces with large, educated populations (eg, Henan, Hebei, and Shandong) have been focusing on “online education” whereas medium-sized cities have been paying more attention to “online medical care.”ConclusionsOur findings suggest that web search data may reflect changes in health literacy, social panic, and prevention and control policies in response to COVID-19.
Highlights
In December 2019, a severe public health emergency was induced by the outbreak of a novel coronavirus, which has since been named coronavirus disease (COVID-19) by the World Health Organization (WHO) [1]
Despite China’s active response in combating this outbreak, a proportion of the Chinese population has remained afraid, which may seriously affect progress in controlling and preventing future outbreaks. This phenomenon is striking on the internet and within social media, and investigating COVID-19–related health literacy and social panic via these platforms may yield important insights
Taking the COVID-19 outbreak as an example, spurious information disseminated via social media by nonexpert individuals has included false claims on how to kill the COVID-19 virus, for example, by drinking alcohol, smoking, aromatherapy, essential balms, use of a hair dryer, or taking a hot bath [2]
Summary
In December 2019, a severe public health emergency was induced by the outbreak of a novel coronavirus, which has since been named coronavirus disease (COVID-19) by the World Health Organization (WHO) [1]. Since the first-level response by government officials to COVID-19 across China’s provinces and cities, governmentally imposed social isolation has provided the Chinese population with ample time to search online for the latest COVID-19–related news [2]. At the time of the COVID-19 outbreak, we found that the number of searches for COVID-19 had increased exponentially, despite the fact that its incidence and mortality rates were much lower than those of some noncommunicable diseases, such as cancer. This phenomenon is worthy of further attention and discussion. Objective: The aim of this paper is to analyze web search data volumes related to COVID-19 in China. Employees who have returned to work have mainly engaged in the following web searches: “return to work and prevention measures,” “return to work guarantee policy,” and “time to return to work.” Provinces with large, educated populations (eg, Henan, Hebei, and Shandong) have been focusing on “online education” whereas medium-sized cities have been paying more attention to “online medical care.” Conclusions: Our findings suggest that web search data may reflect changes in health literacy, social panic, and prevention and control policies in response to COVID-19
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