SARS-CoV-2 seroprevalence in the city of Hyderabad, India in early 2021

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Abstract

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  1. SciScore for 10.1101/2021.07.18.21260555: (What is this?)

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

    Table 1: Rigor

    EthicsField Sample Permit: Data collection and ethics approvals: Data were collected by 15 field teams and 3 lab teams.
    Consent: An informed written individual consent was taken from all participants.
    Sex as a biological variableThus, a total of around 100 households were sampled from every ward, including all consenting and available males and females aged ≥10 years from each household.
    RandomizationSampling procedure: About 30 wards were selected using a simple random sampling technique from the list of 150 wards in the GHMC area.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    However, the IgG antibody test results were shared with each individual for their information.
    IgG
    suggested: None
    Antibody titre assays and measurement: The samples were tested for total SARS-CoV-2 antibodies via electrochemiluminescence immunoassay using Elecsys Anti-SARS-Cov2 kit (Roche Cobas E411) based on a recombinant protein representing the nucleocapsid (N) antigen for antibody determination, as per manufacturer’s protocol.
    total SARS-CoV-2
    suggested: None
    Anti-SARS-Cov2
    suggested: None
    Software and Algorithms
    SentencesResources
    Data was analysed and visualised using SPSS v.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)
    22 and ggplot2.
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)

    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:
    An important caveat to note is that antibody testing kits used in seroprevalence surveys aren’t very sensitive, nor are they all uniform and direct comparisons of results from different studies should be interpreted cautiously. We found gender-specific differences in seropositivity levels as also documented by some of the above-mentioned serosurveys in India. Females appear to generate better protective antibody responses than do males following vaccination against influenza, yellow fever, dengue, and several other viruses [11]. Differential exposure and susceptibility, and behavioural and immunological divergence between the genders have been cited to account for higher seroprevalence found in other surveys in the country. A recent review looking at global seroprevalence rates concluded that in most other countries, however, males had a slightly higher seropositivity than females, or there was no difference found between the genders [12]. Though we found no correlation with any known comorbidities some difference in seroprevalence was seen with smoking, which causes the upregulation of ACE-2 receptor [13]. Most of the survey subjects appeared to be asymptomatic for the known COVID-19 symptoms prevalent in the first wave of infections, and were likely unaware of their infected status. It is unclear whether genetic and/or environmental and behavioural differences contribute to any of the observed differences among individuals. Larger studies in these target groups are needed f...

    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.