Neutralizing antibody responses to SARS-CoV-2: A population based seroepidemiological analysis

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Abstract

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  1. SciScore for 10.1101/2021.12.28.21268472: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: A p-value < 0.05 was considered statistically significant The study was approved by the Institutional Ethics Committee, Maulana
    Consent: Electronic and informed consent was obtained from all the study participants.
    Sex as a biological variablenot detected.
    RandomizationThe samples for screening were selected through computer-based simple random sampling method.
    Blindingnot detected.
    Power AnalysisThis sample size was adequate at 95% confidence levels with 1.2% absolute precision levels.

    Table 2: Resources

    Antibodies
    SentencesResources
    The sVNT kit detects circulating neutralizing anti SARS-CoV-2 antibodies through immune system response either after COVID-19 infection or vaccination.
    anti SARS-CoV-2
    suggested: None
    These antibodies prevent the interaction between the ACE2 human cell surface receptor and the receptor binding domain (RBD) of the SARS-CoV-2 spike glycoprotein [
    SARS-CoV-2 spike glycoprotein [
    suggested: None
    Software and Algorithms
    SentencesResources
    Data were analysed with IBM SPSS Statistics for Windows, Version 25.0.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    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.