Prevalence of SARS-CoV-2 IgG antibodies and their association with clinical symptoms of COVID-19 in Estonia (KoroSero-EST-1 study)

  1. Piia Jõgi
  2. Hiie Soeorg
  3. Diana Ingerainen
  4. Mari Soots
  5. Freddy Lättekivi
  6. Paul Naaber
  7. Karolin Toompere
  8. Pärt Peterson
  9. Liis Haljasmägi
  10. Eva Žusinaite
  11. Hannes Vaas
  12. Merit Pauskar
  13. Arina Shablinskaja
  14. Katrin Kaarna
  15. Heli Paluste
  16. Kai Kisand
  17. Marje Oona
  18. Riina Janno
  19. Irja Lutsar

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Abstract

No abstract available

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  1. Version published to 10.1016/j.vaccine.2021.07.093
  2. ScreenIT

    SciScore for 10.1101/2020.10.21.20216820: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: All participants and/or their legal guardians provided written informed consent.
    IRB: The study was approved by the Research Ethics Committee of the University of Tartu.
    RandomizationFrom each stratum individuals were randomly identified by Estonian Health Insurance Fund with the aim to include at least 110 participants per age group from both GP practices to achieve desirable precision for the seroprevalence estimates.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Sampling and antibody measurements: Blood samples (3.5 mL) were drawn and stored for 48 hours at +4°C until transported to laboratory, where sera were stored at -30° C until testing in SYNLAB Estonia Central Laboratory in Tallinn or at the research laboratories of the University of Tartu, Estonia. First, all samples were tested by chemiluminescent microparticle immunoassay for detection of IgG against SARS-CoV-2 nucleoprotein (N) (Abbott Architect SARS-CoV-2 IgG with ARCHITECT i2000SR analyzer; Abbott Laboratories, USA) according to the manufacturer’s instructions.
    SARS-CoV-2 nucleoprotein ( N
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    After this, 4×104 Vero E6 cell suspension in 100 μl of VGM per well was added to the wells.
    Vero E6
    suggested: None
    Software and Algorithms
    SentencesResources
    Sampling and antibody measurements: Blood samples (3.5 mL) were drawn and stored for 48 hours at +4°C until transported to laboratory, where sera were stored at -30° C until testing in SYNLAB Estonia Central Laboratory in Tallinn or at the research laboratories of the University of Tartu, Estonia. First, all samples were tested by chemiluminescent microparticle immunoassay for detection of IgG against SARS-CoV-2 nucleoprotein (N) (Abbott Architect SARS-CoV-2 IgG with ARCHITECT i2000SR analyzer; Abbott Laboratories, USA) according to the manufacturer’s instructions.
    Abbott Architect
    suggested: (Abbott ARCHITECT i1000sr System, RRID:SCR_019328)
    Abbott Laboratories
    suggested: None
    Analysis of symptoms: The association between the presence of symptoms and seropositivity was analyzed by multiple correspondence analysis (MCA) using R package FactoMineR.
    FactoMineR
    suggested: (FactoMineR, RRID:SCR_014602)

    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.

    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 10.1101/2020.10.21.20216820v1 on medRxiv