Fifteen-Month Follow-Up of Anti-Spike Receptor-Binding Domain SARS-CoV-2 Antibodies among Healthcare Workers in Boston, MA

  1. Maura C Dodge
  2. Manisha Cole
  3. Elizabeth R Duffy
  4. Martha M Werler
  5. Yachana Kataria

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

Background

Boston Medical Center (BMC) is a safety net hospital in Boston, and from the initial wave of COVID-19 there has been an overwhelming concern about the exposure of healthcare workers (HCWs) to SARS-CoV-2.

Methods

We conceived a study to follow a cohort of BMC HCWs, beginning in July 2020 and continuing for 15 months, collecting survey data and serum samples at approximately 3-month intervals. Serum samples were analyzed using the Abbott Architect i2000 for SARS-CoV-2 antibodies (anti-spike1-Receptor Binding Domain IgG and anti-nucleoprotein IgG). Positive anti-n IgG results were used, in addition to reverse transcription-PCR results, for identifying cases of infection. History of COVID-19 and vaccination status were confirmed, where possible, using electronic medical records. Participants were grouped according to vaccination and infection status in September 2021 for analysis of anti-s IgG trends.

Results

A majority of HCWs remain well above the positivity threshold for anti-spike IgG antibodies for up to 11 months post-vaccination and 15 months post-infection, regardless of combinations and permutations of vaccination and infection. Those with COVID-19 infection before vaccination had significantly higher median serum antibody concentrations in comparison to HCWs with no prior infection at each follow-up time point.

Conclusions

These findings further support what is known regarding the decline in serum antibody concentrations following natural infection and vaccination, adding knowledge of serum antibody levels for up to 15 months post- infection and 11 months post-vaccination.

Article activity feed

  1. Version published to 10.1093/jalm/jfac056
  2. ScreenIT

    SciScore for 10.1101/2022.03.18.22272553: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: This study was approved by the Institutional Review Board at BMC (8).
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    The Abbott anti-s IgG (quant) assay became available after the initial time point and bio-banked serum samples were used to examine serum antibody concentrations for the prior timepoints.
    anti-s IgG
    suggested: None
    Software and Algorithms
    SentencesResources
    Questionnaires were collected and managed in REDCap electronic data capture tools hosted at Boston University, CTSI 1UL1TR001430 (6,7).
    REDCap
    suggested: (REDCap, RRID:SCR_003445)
    Samples from all timepoints were analyzed for SARS-CoV-2 anti-spike-1 RBD IgG II (quantitative) and anti-nucleoprotein IgG (qualitative) in the clinical pathology laboratory at BMC using the Abbott Architect i2000sr, using IgG II (quantitative) and IgG (qualitative) assays, respectively (Abbott Laboratories, Abbott Park, IL) following manufacturer’s specifications.
    Abbott Architect
    suggested: (Abbott ARCHITECT i1000sr System, RRID:SCR_019328)
    Abbott Laboratories
    suggested: None
    Statistical analyses were run using Statistical Analysis Software version 9.4 (SAS Institute, Cary, NC).
    Statistical Analysis
    suggested: (Statistical Analysis System, RRID:SCR_008567)
    SAS Institute
    suggested: (Statistical Analysis System, RRID:SCR_008567)

    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 10.1101/2022.03.18.22272553v1 on medRxiv