Cumulative incidence of SARS-CoV-2 and associated risk factors among healthcare workers: a cross-sectional study in the Eastern Cape, South Africa

  1. David Stead
  2. Oladele Vincent Adeniyi
  3. Mandisa Singata-Madliki
  4. Shareef Abrahams
  5. Joanne Batting
  6. Eloise Jelliman
  7. Andrew Parrish

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Abstract

This study assesses the cumulative incidence of SARS-CoV-2 infection among healthcare workers (HCWs) during South Africa’s first wave and examines the associated demographic, health-related and occupational risk factors for infection.

Methods

Multistage cluster sampling was used in a cross-sectional study to recruit 1309 HCWs from two academic hospitals in the Eastern Cape, South Africa over 6 weeks in November and December 2020. Prior test results for SARS-CoV-2 PCR and participants’ characteristics were recorded while a blood sample was drawn for detection of IgG antibodies against SARS-CoV-2 nucleocapsid protein. The primary outcome measure was the SARS-CoV-2 cumulative incidence rate, defined as the combined total of positive results for either PCR or IgG antibodies, divided by the total sample. The secondary outcome was significant risk factors associated with infection.

Results

Of the total participants included in the analysis (n=1295), the majority were women (81.5%), of black race (78.7%) and nurses (44.8%). A total of 390 (30.1%) HCWs had a positive SARS-CoV-2 PCR result and SARS-CoV-2 antibodies were detected in 488 (37.7%), yielding a cumulative incidence of 47.2% (n=611). In the adjusted logistic regression model, being overweight (adjusted OR (aOR)=2.15, 95% CI 1.44 to 3.20), obese (aOR=1.37, 95% CI 1.02 to 1.85) and living with HIV (aOR=1.78, 95% CI 1.38 to 2.08) were independently associated with SARS-CoV-2 infection. There was no significant difference in infection rates between high, medium and low COVID-19 exposure working environments.

Conclusions

The high SARS-CoV-2 cumulative incidence in the cohort was surprising this early in the epidemic and probably related to exposure both in and outside the hospitals. To mitigate the impact of SARS-CoV-2 among HCWs, infection prevention and control strategies should target community transmission in addition to screening for HIV and metabolic conditions.

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  1. Version published to 10.1136/bmjopen-2021-058761
  2. ScreenIT

    SciScore for 10.1101/2021.11.08.21265966: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: Ethical Considerations: The Walter Sisulu University Ethics Committee granted approval for the implementation of the study (Reference: 087/2020), as well as the Eastern Cape Provincial Department of Health and local hospitals ethics committee.
    Consent: Each participant provided written informed consent for the study.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power AnalysisThere was no sample size calculation performed, but rather as many staff recruited as possible within the budgeted time frame for the study.
    Cell Line AuthenticationAuthentication: Certain comorbidities (diabetes, hypertension, HIV, Tuberculosis, Chronic kidney disease, heart disease, Asthma/Chronic obstructive pulmonary disease, liver disease, cancer, pregnancy) or immunosuppressive therapy, that have been shown to increase the risk of acquiring SARS-CoV-2 were explored in the questionnaire.2,8,13,15,19 A prior SARS-CoV-2 diagnosis was self-reported by the participants and validated through the OHS personnel database in each hospital.

    Table 2: Resources

    Antibodies
    SentencesResources
    All blood samples were tested for the IgG antibodies against SARS-CoV-2 nucleocapsid protein by the National Health Laboratory Services in accordance with standard protocols.
    SARS-CoV-2 nucleocapsid protein
    suggested: None
    To link the results of SARS-CoV-2 PCR tests recorded on the OHS databases with the SARS-CoV-2 IgG antibody tests, while maintaining confidentiality, a unique identifying number was used to encode the participants’ details (names, date of birth and area of work) in the research register, which was accessible only to the investigators.
    SARS-CoV-2 IgG
    suggested: None
    The proportion of HCWs with either a SARS-CoV-2 PCR diagnosis or positive IgG antibodies, or both, were reckoned as cumulative incidence in the study.
    positive IgG
    suggested: None
    Software and Algorithms
    SentencesResources
    e measures: Serum samples were analysed on an Abbott ARCHITECT i1000SR instrument using the Abbott SARS-CoV-2 IgG assay in accordance with the manufacturer’s instructions.
    Abbott
    suggested: (Abbott, RRID:SCR_010477)
    Data analysis: Data were exported from the REDCap® online database for analysis using the IBM SPSS version 25.0 software (IBM SPSS, Chicago, Illinois) after cross-checking for completeness and accuracy.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    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 10.1101/2021.11.08.21265966 on medRxiv