Seroprevalence of SARS-CoV-2 specific IgG antibodies in District Srinagar, northern India – A cross-sectional study

  1. S. Muhammad Salim Khan
  2. Mariya Amin Qurieshi
  3. Inaamul Haq
  4. Sabhiya Majid
  5. Arif Akbar Bhat
  6. Sahila Nabi
  7. Nisar Ahmad Ganai
  8. Nazia Zahoor
  9. Auqfeen Nisar
  10. Iqra Nisar Chowdri
  11. Tanzeela Bashir Qazi
  12. Rafiya Kousar
  13. Abdul Aziz Lone
  14. Iram Sabah
  15. Shahroz Nabi
  16. Ishtiyaq Ahmad Sumji
  17. Misbah Ferooz Kawoosa
  18. Shifana Ayoub

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Abstract

Prevalence of IgG antibodies against SARS-CoV-2 infection provides essential information for deciding disease prevention and mitigation measures. We estimate the seroprevalence of SARS-CoV-2 specific IgG antibodies in District Srinagar.

Methods

2906 persons >18 years of age selected from hospital visitors across District Srinagar participated in the study. We tested samples for the presence of SARS-CoV-2 specific IgG antibodies using a chemiluminescent microparticle immunoassay-based serologic test.

Results

Age- and gender-standardized seroprevalence was 3.6% (95% CI 2.9% to 4.3%). Age 30–69 years, a recent history of symptoms of an influenza-like-illness, and a history of being placed under quarantine were significantly related to higher odds of the presence of SARS-CoV-2 specific IgG antibodies. The estimated number of SARS-CoV-2 infections during the two weeks preceding the study, adjusted for test performance, was 32602 with an estimated (median) infection-to-known-case ratio of 46 (95% CI 36 to 57).

Conclusions

The seroprevalence of SARS-CoV-2 specific IgG antibodies is low in the District. A large proportion of the population is still susceptible to the infection. A sizeable number of infections remain undetected, and a substantial proportion of people with symptoms compatible with COVID-19 are not tested.

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  1. Version published to 10.1371/journal.pone.0239303
  2. ScreenIT

    SciScore for 10.1101/2020.09.04.282640: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: We obtained written informed consent from those who agreed to participate.
    IRB: The Institutional Ethics Committee of Government Medical College Srinagar approved the study.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    The SARS-CoV-2 IgG assay uses chemiluminescent microparticle immunoassay (CMIA) technology to detect IgG antibodies to SARS-CoV-2 in human serum and plasma.
    detect IgG
    suggested: None
    The test has a high sensitivity (100%) and specificity (over 99.6%) for the detection of SARS-CoV-2 specific IgG antibodies 17 days after infection [9,10].
    SARS-CoV-2 specific IgG
    suggested: None
    Software and Algorithms
    SentencesResources
    Laboratory procedure: We performed the test med using Fully Automated High Throughput Platform ARCHITECT i1000SR Immunoassay Analyzer by Abbott Laboratories Inc[9].
    Abbott Laboratories
    suggested: None
    Stata version 15.1 (StataCorp. 2017. Stata Statistical Software:
    StataCorp
    suggested: (Stata, RRID:SCR_012763)

    Results from OddPub: Thank you for sharing your data.

    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:
    • No conflict of interest statement was detected. If there are no conflicts, we encourage authors to explicit state so.
    • No funding statement was detected.
    • No protocol registration statement was detected.

    About SciScore

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  3. Version published to 10.1101/2020.09.04.282640 on bioRxiv