Global pattern of COVID-19 research

  1. Xunzhi Zhu
  2. Qi Jin
  3. Xiyi Jiang
  4. Yuanyuan Dan
  5. Aimin Zhang
  6. Guangming Qiu
  7. Jianlin Lou
  8. Hualong Yu

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Abstract

Since the COVID-19 outbreak began, a large number of studies have been conducted in a short period. However, it is unclear whether countries involved in this crisis have made adequate efforts and allocated resources to cutting-edge SARS-CoV-2 research. We analyzed the dynamics of and professional fields represented by papers about this novel coronavirus published before June 15, 2020. High-infection countries produced more scientific output than low-infection countries, and high-income and upper-middle-income countries were the main contributors. However, the research areas overlapped substantially, indicating a waste of resources. Our findings also suggest that international cooperation among countries is still relatively lacking, and all countries should make better use of their strengths to face the epidemic jointly.

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  1. ScreenIT

    SciScore for 10.1101/2020.07.04.20146530: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    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.
    • Thank you for including a protocol registration statement.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.07.04.20146530v1 on medRxiv