High prevalence of SARS-CoV-2 antibodies in pets from COVID-19+ households

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Abstract

In a survey of household cats and dogs of laboratory-confirmed COVID-19 patients, we found a high seroprevalence of SARS-CoV-2 antibodies, ranging from 21% to 53%, depending on the positivity criteria chosen. Seropositivity was significantly greater among pets from COVID-19+ households compared to those with owners of unknown status. Our results highlight the potential role of pets in the spread of the epidemic.

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  1. SciScore for 10.1101/2020.09.22.307751: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: From May 11 to 22, 384 patients were contacted and 84 reported owning dogs and/or cats. 34 gave us their informed consent to sample their pets.
    IACUC: Sampling of animals for this study was approved by VetAgro Sup ethical committee (approval number n°2031).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Prepandemic (including non SARS-CoV2 coronaviruses positive) sera from France were used as negative controls, and anti-SARS-CoV-2 RBD antibody was used as positive control.
    anti-SARS-CoV-2 RBD
    suggested: None
    10μg of three recombinant SARS-CoV-2 antigens (nucleoprotein, spike subunit 1 and spike subunit 2) were used to capture specific serum antibodies, whereas a recombinant human protein (O6-methylguanine DNA methyltransferase) was used as a control antigen in the assay.
    antigens (nucleoprotein, spike subunit 1
    suggested: None
    spike subunit 2
    suggested: (Thermo Fisher Scientific Cat# MA5-29983, RRID:AB_2785782)

    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.

    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.