SARS-CoV-2 IgG seroprevalence in blood donors located in three different federal states, Germany, July 2020 to June 2021 – a follow-up

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Abstract

Seroprevalence studies can contribute to better assess the actual incidence of infection. Since long-term data for Germany are lacking, we determined seroprevalence of IgG-antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 3,759 regular blood donors in three German federal states between July 2020 and June 2021. The IgG seroprevalence was 5.48% (95% confidence interval (CI): 4.77–6.25) overall, ranging from 5.15% (95% CI: 3.73–6.89) in Lower Saxony to 5.62% (95% CI: 4.57–6.84) in North Rhine Westphalia.

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  1. SciScore for 10.1101/2022.02.11.22270833: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    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: We detected the following sentences addressing limitations in the study:
    It should be emphasized that the preselection of blood donors as study cohort is accompanied by limitations regarding representation of the population: Blood donors are between 18 and 65 years-old, young healthy adults are usually overrepresented and other groups (e.g. children, HIV/HCV/HBV-infected patients, older people with underlying conditions, institutionalised people) are excluded or underrepresented. Nevertheless, our findings suggest that there are a large number of unrecorded cases throughout the whole one-year study period. As mentioned in other studies [14], our data therefore reinforces, that longitudinal seroprevalence studies are helpful to better assess the actual incidence of infection within the respectively considered region.

    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.