Differences in SARS-CoV-2 infections during the first and second wave of SARS-CoV-2 between six ethnic groups in Amsterdam, the Netherlands: A population-based longitudinal serological study

  1. Liza Coyer
  2. Anders Boyd
  3. Janke Schinkel
  4. Charles Agyemang
  5. Henrike Galenkamp
  6. Anitra D.M. Koopman
  7. Tjalling Leenstra
  8. Yvonne T.H.P. van Duijnhoven
  9. Eric P. Moll van Charante
  10. Bert-Jan H. van den Born
  11. Anja Lok
  12. Arnoud Verhoeff
  13. Aeilko H. Zwinderman
  14. Suzanne Jurriaans
  15. Karien Stronks
  16. Maria Prins

Reviewed by

Read the full article See related articles

Discuss this preprint

Start a discussion What are Sciety discussions?

Listed in

Log in to save this article

Abstract

No abstract available

Article activity feed

  1. Version published to 10.1016/j.lanepe.2021.100284
  2. ScreenIT

    SciScore for 10.1101/2021.07.21.21260956: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: Ethical approval for the HELIUS study was obtained from the Academic Medical Center Ethical Review Board.
    Consent: All participants provided written informed consent.
    Sex as a biological variablenot detected.
    RandomizationA random sample of persons, stratified by ethnic origin, was taken from the municipality register of Amsterdam and subjects were invited to participate.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    All analyses were conducted using Stata 15·1 (StataCorp, College Station, TX, USA) and the msm package17 in R version 3·5·2 (Vienna, Austria).
    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: We detected the following sentences addressing limitations in the study:
    Nevertheless, there are several limitations. First, our study might be subject to selection bias. Participants in our substudy might have been more concerned about their health compared to non-participants. Second, LTFU differed between ethnic groups, and was higher in participants with lower socio-economic status. We were unable to directly control for differential LTFU, but our sensitivity analysis suggests the impact of LTFU on our results was limited. Third, exposure variables were collected after infection and may have been different at the time of infection, depending on restrictions in place. Fourth, while we included many potential exposures and correlates of infection in our analysis, some might have been missed, such as preventive behaviours (e.g. wearing masks, keeping distance) during activities. In conclusion, ethnic differences in SARS-CoV-2 infection became apparent during the second wave of infection in the Netherlands and incidence was higher in ethnic minority groups compared to those of Dutch origin. Targeted prevention efforts following the first wave might not have been sufficient to prevent these disparities. Focus should be placed on reaching high vaccine coverage in all ethnic groups, alongside improvement of other targeted prevention strategies addressing the needs of individuals within these groups.

    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 10.1101/2021.07.21.21260956 on medRxiv