SARS-CoV-2 Antibody Seroprevalence in Industry Workers in Split-Dalmatia and Šibenik-Knin County, Croatia

  1. Ivan Jerković
  2. Toni Ljubić
  3. Željana Bašić
  4. Ivana Kružić
  5. Nenad Kunac
  6. Joško Bezić
  7. Arijana Vuko
  8. Alemka Markotić
  9. Šimun Anđelinović

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Abstract

To examine seroprevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies in industry workers population sample.

Methods:

From 23 to April 28, 2020, we conducted serological testing for antibodies (Immunoglobulin G (IgG) and Immunoglobulin M (IgM)) on 1494 factory employees living in the Split-Dalmatia and Šibenik-Knin County (Croatia).

Results:

We detected antibodies in 1.27% of participants (95% confidence interval [CI] 0.77–1.98%). In Split facility 13/1316 (0.99%, 95% CI 0.53–1.68%) of participants were tested positive, of which 13/1079 (1.20%, 95% CI 0.64–2.05%) of those living outside the facility and 0/237 (0%, 95% CI 0–1.26%) of those living inside the facility. In Knin facility, 6/178 (3.37%, 95% CI 1.25–7.19%) participants were tested positive for antibodies.

Conclusions:

The study showed relatively small SARS-CoV-2 antibody seroprevalence in the DIV Group population sample.

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  1. Version published to 10.1097/jom.0000000000002020
  2. ScreenIT

    SciScore for 10.1101/2020.05.11.20095158: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Antibodies
    SentencesResources
    The test is intended for the rapid immunochromatographic qualitative detection of IgG and IgM antibodies to SARS-CoV-2 in whole human blood, serum, and plasma samples.
    IgM
    suggested: None
    For this calculation, we used the test performance data specified by the manufacturer and assumed that in the sample of 2000 people, that was the expected size of the study sample, one per cent of participants would have IgG, and one per cent of participants would have IgM antibodies against SARS-CoV-2.
    SARS-CoV-2
    suggested: None
    With the parameters stated above, we estimated that 20.22% of the sample tested positive for IgG could really have IgG antibodies, while 0.1% of the sample tested negative would have IgG antibodies.
    have IgG
    suggested: None
    Software and Algorithms
    SentencesResources
    To calculate two-sided 95% CI, Clopper-Pearson exact method in RStudio (version 1.2.5033, RStudio, Inc., Boston, MA, USA) and package GenBinomApps (https://CRAN.R-project.org/package=GenBinomApps) were used.
    RStudio
    suggested: (RStudio, RRID:SCR_000432)

    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:
    The major limitation of the study was the characteristics of serological immunoassay tests, which are currently not sufficiently explored and validated [18]. In our case, the most pronounced drawback of the test reflected in the fact that RT-PCR confirmed two of six IgM positive cases (33%), which was not reported in previous serological studies [20-22]. However, due to the generally low incidence of the disease, this result was not unexpected [26]. Specifically, as previously mentioned in our estimation (see Methods section), we could expect that 26.39% of individuals with positive test results would truly have IgM antibodies. However, it does not imply that people tested negative truly have IgM antibodies, as our previous calculations estimated that it would be the case only in 0.05%, i.e., in no more than one individual within our overall sample. To further explain test inconsistencies, other factors should also be considered. Firstly, most of the tests are still not validated, and, as in our case, only manufacturer data about test performance is available. Along with test performance indicators, test manufacturer also stressed that samples with higher heterophile antibodies or rheumatoid factor could affect the test result [25]. Secondly, WHO stated that serological tests, in general, could be susceptible to cross-reaction with other frequent infections, like human coronaviruses causing common cold [28]. Nonetheless, despite their limitations, these tests can still be a v...

    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

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  3. Version published to 10.1101/2020.05.11.20095158 on medRxiv