A prospective study of asymptomatic SARS-CoV-2 infection among individuals involved in academic research under limited operations during the COVID-19 pandemic

This article has been Reviewed by the following groups

Read the full article See related articles

Abstract

Early in the pandemic, transmission risk from asymptomatic infection was unclear, making it imperative to monitor infection in workplace settings. Further, data on SARS-CoV-2 seroprevalence within university populations has been limited.

Methods

We performed a longitudinal study of University research employees on campus July-December 2020. We conducted questionnaires on COVID-19 risk factors, RT-PCR testing, and SARS-CoV-2 serology using an in-house spike RBD assay, laboratory-based Spike NTD assay, and standard nucleocapsid platform assay. We estimated prevalence and cumulative incidence of seroconversion with 95% confidence intervals using the inverse of the Kaplan-Meier estimator.

Results

910 individuals were included in this analysis. At baseline, 6.2% (95% CI 4.29–8.19) were seropositive using the spike RBD assay; four (0.4%) were seropositive using the nucleocapsid assay, and 44 (4.8%) using the Spike NTD assay. Cumulative incidence was 3.61% (95% CI: 2.04–5.16). Six asymptomatic individuals had positive RT-PCR results.

Conclusions

Prevalence and incidence of SARS-CoV-2 infections were low; however, differences in target antigens of serological tests provided different estimates. Future research on appropriate methods of serological testing in unvaccinated and vaccinated populations is needed. Frequent RT-PCR testing of asymptomatic individuals is required to detect acute infections, and repeated serosurveys are beneficial for monitoring subclinical infection.

Article activity feed

  1. SciScore for 10.1101/2021.11.17.21266367: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: Ethical Approval: This study was approved by the Institutional Review Board at the University of North Carolina at Chapel Hill.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Similar procedures were conducted at month 1 and 3 with one exception: at month 1, participants were provided a Tasso device (Tasso, Inc., Seattle, WA, USA) for self-administered blood collection (30-80 μl), which they could take home and return at a later time to test for SARS-CoV-2 antibodies.
    SARS-CoV-2
    suggested: None
    The first was the commercially available Abbott SARS-CoV-2 assay (Abbott, Chicago, IL, USA) to detect IgG antibodies to nucleocapsid antigen using a chemiluminescent microparticle immunoassay (CMIA), which had received an EUA.
    detect IgG
    suggested: None
    The CMIA provides qualitative detection of SARS-CoV-2 IgG antibodies on the Abbott Architect instrument.
    SARS-CoV-2 IgG
    suggested: None
    The assay plate was washed, then a cocktail of horseradish peroxidase-conjugated secondary Goat Anti-Human IgG, IgA, and IgM secondary antibodies was used to measure antigen-specific total Ig.
    Anti-Human IgG
    suggested: None
    IgM
    suggested: None
    antigen-specific total Ig.
    suggested: None
    Software and Algorithms
    SentencesResources
    Using primers based on the Respiratory Diagnostic Clinic assay and human RNA control primers, amplicons were amplified and then quantified using a ThermoFisher QuantStudio 7 system.
    ThermoFisher QuantStudio
    suggested: (Primer Express Software, RRID:SCR_017376)
    The first was the commercially available Abbott SARS-CoV-2 assay (Abbott, Chicago, IL, USA) to detect IgG antibodies to nucleocapsid antigen using a chemiluminescent microparticle immunoassay (CMIA), which had received an EUA.
    Abbott
    suggested: (Abbott, RRID:SCR_010477)

    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.