An empirical analysis of what people learned about COVID-19 through web search and the impacts on misinformation and attitude towards public health safety guidelines

  1. Ikpe Justice Akpan
  2. Obianuju Genevieve Aguolu
  3. Asuama Akpan

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Abstract

Several people flocked to the Internet to learn about the SARS-CoV-2 and COVID-19 after the outbreak in Wuhan, China, in December 2019. As the novel coronavirus spread rapidly worldwide and was declared a global pandemic, the public rushed to Internet platforms to learn about the outbreak through Google search, online news outlets, and social media platforms. This paper evaluates the public’s web search to learn about the pandemic and the possible impacts on attitude to the public health guidelines. The results highlight four outcomes: First, a significant global population learned about the ongoing pandemic through a web search. Second, there is a direct correlation between learning SARS-CoV-2, COVID-19, and SARS-CoV and searching information on public health measures (wearing a facial mask and social distancing). Third, learning conspiracy theories or misinformation correspond with a lack of interest in gaining knowledge about public health safety guidelines. Also, the initial high interest in learning about Influenza declined as people gained information about SARS-CoV-2 and COVID-19. The results highlight the critical need to promptly sensitize the public about global health concerns using both the Internet platforms and traditional sources, adopt effective health communication strategies, and build trust.

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  1. ScreenIT

    SciScore for 10.1101/2021.02.23.21252323: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Antibodies
    SentencesResources
    Diagnostic testing is performed from respiratory (nose, throat, saliva) and serum samples, using a real-time Reverse Transcriptase Polymerase Chain Reaction (RT-PCR) panel or antibody test.
    Reverse Transcriptase Polymerase Chain Reaction (RT-PCR
    suggested: None
    Software and Algorithms
    SentencesResources
    We use the statistical analysis package called JMP, one of the SAS statistical software packages (Freund & Littell, 1986), and Microsoft Excel to undertake the statistical analyses, including creating the charts, graphs, and computing the correlation matrix.
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

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  2. Version published to 10.1101/2021.02.23.21252323v1 on medRxiv