Sero-prevalence of anti-SARS-CoV-2 antibodies in Chattogram Metropolitan Area, Bangladesh

  1. Jahan Ara
  2. Md. Sirazul Islam
  3. Md. Tarek Ul Quader
  4. Anan Das
  5. F. M. Yasir Hasib
  6. Mohammad Saiful Islam
  7. Tazrina Rahman
  8. Seemanta Das
  9. M.A. Hassan Chowdhury
  10. Goutam Buddha Das
  11. Sharmin Chowdhury

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Abstract

Background

Seroprevalence studies of coronavirus disease 2019 (COVID-19) assess the degree of undetected transmission in the community. Different groups, such as healthcare workers (HCWs), garment workers, and others, are deemed vulnerable due to their workplace hazards and immense responsibility.

Purpose

The present study was conducted to estimate the seroprevalence of anti-SARS-CoV-2 antibody (IgG) and its association with different explanatory variables. Further, the antibody was quantified to assess the increasing or decreasing trend over different intervention periods and according to other factors.

Methodology

This cross-sectional study observed health workers - doctor, nurse, hospital staff, etc. in and outpatients (non-COVID-19) and garments workers of Chattogram metropolitan area (CMA, N=748) from randomly selected six government and private hospitals and two garment factories. Study subjects were included upon written consent, fulfilling specific inclusion criteria. Venous blood was collected following standard aseptic methods. Qualitative and quantitative ELISA was used to identify and quantify antibodies (IgG) in serum samples. Descriptive, univariable, and multivariable statistical analysis was performed.

Results

Overall seroprevalence was estimated as 66.99% (95% CI: 63.40%-70.40%). Seroprevalence among HCWs, in and outpatients, and garments workers were 68.99 % (95% CI: 63.8%-73.7%), 81.37 % (95% CI: 74.7%-86.7%), and 50.56 % (95% CI: 43.5%-57.5%), respectively. Seroprevalence was 44.47 % (95% CI: 38.6%-50.4%) in the non-vaccinated population while it was significantly ( p <0.001) higher in the population receiving the first dose (61.66 %, 95% CI: 54.8%-68.0%) and both (first and second) doses of vaccine (100%, 95% CI: 98.4%-100%). The mean titer of the antibody was estimated as 255.46 DU/ml and 159.08 DU/ml in the population with both doses and one dose of vaccine, respectively, compared to 53.71 DU/ml of the unvaccinated population. A decreasing trend in the titer of antibodies with increasing time after vaccination was observed.

Conclusions

Seroprevalence and mean antibody titer varied according to different factors in this study. The second dose of vaccine significantly increased the seroprevalence and titer, which decreased to a certain level over time. Although antibody was produced following natural infection, the mean titer was relatively low compared to antibody after vaccination. This study emphasizes the role of the vaccine in antibody production. Based on the findings, interventions like continuing extensive mass vaccination of the leftover unvaccinated population and bringing the mass population with a second dose under a third dose campaign might be planned.

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  1. ScreenIT

    SciScore for 10.1101/2022.02.09.22270717: (What is this?)

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

    Table 1: Rigor

    EthicsConsent: We interviewed participants to collect information after receiving written consent.
    Field Sample Permit: Baseline blood collection and processing: Heparinized blood specimens (6mL) were collected and transported to the clinical pathology laboratory (CPL) of Chattogram Veterinary and Animal Sciences University (CVASU) within three hours of collection.
    Sex as a biological variablenot detected.
    RandomizationFrom each stratum, six hospitals were randomly selected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Serological test examination: Antibody was determined by a commercial qualitative assay using COVID-19 IgG ELISA test (Beijing Kewei Clinical Diagnostic Reagent Inc., China; Ref: 601340) as per the manufacturer’s instructions.
    COVID-19 IgG
    suggested: None
    The effects of different potential explanatory variables on the binary outcome - presence/absence of anti-SARS-CoV-2 antibody, was evaluated using univariable and followed by multivariable logistic regression models.
    anti-SARS-CoV-2
    suggested: None
    Software and Algorithms
    SentencesResources
    STATA-IC 13 (StataCorp, California, USA) and GraphPad Prism 7.00 for Windows (GraphPad Software, La Jolla, California, USA) were used for statistical analyses and visualization.
    StataCorp
    suggested: (Stata, RRID:SCR_012763)
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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:
    Our study has several limitations, such as the fact that we only collected samples from hospitals and the garment industry, but the results would be more representative of the community if we included other groups. We could not compare immunological responses produced by different COVID-19 vaccine brands at the same post-vaccination interval since distinct COVID-19 vaccines were licensed and supplied to CMA at different times. We did not reveal the type and name of COVID-19 vaccines, whereas a sufficient fraction was not covered under the vaccination program, and we were concerned about an infodemic.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    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.

  2. Version published to 10.1101/2022.02.09.22270717 on medRxiv