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10.2196/18831

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32540844!7333795!32540844
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suck abstract from ncbi


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pmid32540844      J+Med+Internet+Res 2020 ; 22 (7): e18831
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  • Mapping of Health Literacy and Social Panic Via Web Search Data During the COVID-19 Public Health Emergency: Infodemiological Study #MMPMID32540844
  • Xu C; Zhang X; Wang Y
  • J Med Internet Res 2020[Jul]; 22 (7): e18831 PMID32540844show ga
  • BACKGROUND: Coronavirus 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. OBJECTIVE: The aim of this paper is to analyze web search data volumes related to COVID-19 in China. METHODS: We 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). RESULTS: The 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." 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.
  • |*Betacoronavirus[MESH]
  • |Anxiety/*epidemiology[MESH]
  • |COVID-19[MESH]
  • |China/epidemiology[MESH]
  • |Coronavirus Infections/*epidemiology/virology[MESH]
  • |Disease Outbreaks[MESH]
  • |Facilities and Services Utilization[MESH]
  • |Health Literacy/*statistics & numerical data[MESH]
  • |Humans[MESH]
  • |Internet/*statistics & numerical data[MESH]
  • |Pandemics[MESH]
  • |Pneumonia, Viral/*epidemiology/virology[MESH]
  • |Public Health/*statistics & numerical data[MESH]
  • |SARS-CoV-2[MESH]


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