Effectiveness of Covid-19 Vaccines against the SARS-COV-2-Delta (B.1.617.2) in China-A Real World Study

  1. Xinge Ma
  2. Jianfeng Han
  3. Hongxia Li
  4. Chang Liu

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Abstract

Background

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) delta (B.1.617.2) variant is highly transmissible and has contributed to a surge in cases globally. This study aimed to explore the potential of vaccines against SARS-CoV-2 delta (B.1.617.2) variant in China.

Methods

In this real-world study, all data were extracted from Xi’an Chest Hospital. Confirmed cases infected with Delta VOC with exact date of positive viral testing were included for analysis. Patients meeting the study criteria were divided into unvaccinated and partially vaccinated (one dose), full vaccinated (two doses), and booster vaccination of COVID-19.

Results

A total of 455 cases were enrolled in this study. Proportion of severe and critical cases in full vaccinated cases (1.82%) and cases with booster vaccination (1.35%) of COVID-19 were much lower than that of unvaccinated and partially vaccinated cases (8.16%). In addition, cases with booster vaccination (12.78 days) and full vaccinated cases (12.59 days) showed shorter duration of viral shedding than that in unvaccinated and partially vaccinated cases (13.87 days).

Conclusion

This is the first real world study indicating that Covid-19 vaccines showed much powerful effectiveness against the SARS-COV-2-Delta (B.1.617.2) in China, including lowing the proportion of severe illness and shorting the virus shedding time.

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  1. ScreenIT

    SciScore for 10.1101/2022.02.07.22270490: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: This study was approved by the local institutional research and ethics committee (XJTU1AF2022LSK-001).
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot 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.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    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 10.1101/2022.02.07.22270490 on medRxiv