Seroprevalence of anti-SARS-CoV-2 IgG antibodies in hospitalized patients at a tertiary referral center in North India

  1. Animesh Ray
  2. Komal Singh
  3. Souvick Chattopadhyay
  4. Farha Mehdi
  5. Gaurav Batra
  6. Aakansha Gupta
  7. Ayush Agarwal
  8. M Bhavesh
  9. Shubham Sahni
  10. R Chaithra
  11. Shubham Agarwal
  12. Chitrakshi Nagpal
  13. B H Gagantej
  14. Umang Arora
  15. Kartikeya Kumar Sharma
  16. Ranveer Singh Jadon
  17. Ashish Datt Upadhyay
  18. Neeraj Nischal
  19. Naval K Vikram
  20. Manish Soneja
  21. R M Pandey
  22. Naveet Wig

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Abstract

Background

Seroprevalence of IgG antibodies against SARS-CoV-2 is an important tool to estimate the true extent of infection in a population. However, seroprevalence studies have been scarce in South East Asia including India, which, as of now, carries the third largest burden of confirmed cases in the world. The present study aimed to estimate the seroprevalence of anti-SARS-CoV-2 IgG antibody among hospitalized patients at one of the largest government hospital in India.

Method

This cross-sectional study, conducted at a tertiary care hospital in North India, recruited consecutive patients who were negative for SARS-CoV-2 by RT-PCR or CB-NAAT. Anti-SARS-CoV-2 IgG antibody levels targeting recombinant spike receptor-binding domain (RBD) protein of SARS CoV-2 were estimated in serum sample by the ELISA method.

Results

A total of 212 hospitalized patients were recruited in the study with mean age (±SD) of 41.2 (±15.4) years and 55% male population. Positive serology against SARS CoV-2 was detected in 19.8% patients(95% CI 14.7-25.8). Residency in Delhi conferred a higher frequency of seropositivity 26.5% (95% CI 19.3-34.7) as compared to that of other states 8% (95% CI 3.0-16.4) with p value 0.001. No particular age groups or socio-economic strata showed a higher proportion of seropositivity.

Conclusion

Around, one-fifth of hospitalized patients, who were not diagnosed with COVID-19 before, demonstrated seropositivity against SARS-CoV-2. While there was no significant difference in the different age groups and socio-economic classes; residence in Delhi was associated with increased risk (relative risk of 3.62, 95% CI 1.59-8.21)

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  1. ScreenIT

    SciScore for 10.1101/2020.08.22.20179937: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: After obtaining written consent, 4 ml of blood was drawn, serum was stored at −80°C and was defrosted before testing.
    RandomizationIt was decided to randomly select atleast 60% of the samples positive in RBD ELISA and test them using Euroimmun IgG ELISA for SARS CoV-2 (17) and Zydus Kavach IgG ELISA for SARS CoV-2.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Anti-SARS-CoV-2 IgG antibody was detected using ELISA method, developed and validated “in-house” at the Translational Health Science and Technology Institute (THSTI)
    Anti-SARS-CoV-2 IgG
    suggested: None

    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 study also had some inherent weaknesses. As it was a hospital-based study, the population in the study cohort may not have been truly representative of the population at large. However, the concordance of the seropositivity data with that of the recently conducted sero-surveillance (15) lays credence to the validity of the results. Also since anti-SARS-CoV-2 antibody levels is known to wane over few months, some “exposed” cases might have inadvertently missed in this cross sectional study.

    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

    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 10.1101/2020.08.22.20179937 on medRxiv