SARS-CoV-2 Seroprevalence in a Rural and Urban Household Cohort during First and Second Waves of Infections, South Africa, July 2020–March 2021

  1. Jackie Kleynhans
  2. Stefano Tempia
  3. Nicole Wolter
  4. Anne von Gottberg
  5. Jinal N. Bhiman
  6. Amelia Buys
  7. Jocelyn Moyes
  8. Meredith L. McMorrow
  9. Kathleen Kahn
  10. F. Xavier Gómez-Olivé
  11. Stephen Tollman
  12. Neil A. Martinson
  13. Floidy Wafawanaka
  14. Limakatso Lebina
  15. Jacques du Toit
  16. Waasila Jassat
  17. Mzimasi Neti
  18. Marieke Brauer
  19. Cheryl Cohen
  20. for the PHIRST-C Group1

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Abstract

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  1. Version published to 10.3201/eid2712.211465
  2. ScreenIT

    SciScore for 10.1101/2021.05.26.21257849: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: The study was approved by the University of the Witwatersrand Human Research Ethics Committee (Reference 150808) and the US Centers for Disease Control and Prevention relied on local clearance (IRB #6840).
    Sex as a biological variablenot detected.
    RandomizationStudy population: We conducted a prospective study on a randomly selected household cohort in a rural (Agincourt, Ehlanzeni District, Mpumalanga Province) and an urban (Jouberton, Dr Kenneth Kaunda District, North West Province) community as part of the PHIRST-C study (a Prospective Household study of SARS-CoV-2, Influenza, and Respiratory Syncytial virus community burden, Transmission dynamics and viral interaction in South Africa).
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data analysis was performed in Stata 14 (StataCorp, College Station, Texas, USA), using six age groups: pre-school (<5 years), primary school (5-12 years), secondary school (13-18 years), young adults (19-34 years), adults (35-59 years) and older adults (≥60 years) who are prioritised for SARS-CoV-2 vaccination.
    StataCorp
    suggested: (Stata, RRID:SCR_012763)

    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.

  3. Version published to 10.1101/2021.05.26.21257849v1 on medRxiv