Transmission of SARS-CoV-2 associated with cruise ship travel: protocol for a systematic review (Version 1)

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Abstract

Background

Maritime and river travel, including cruise ships, have been implicated with spreading viruses through infected passengers and crew. Given the novelty of the SARS-CoV-2 infection, early cruise ship travel transmission models of spread are based on what is known of the dynamics of other respiratory viral infections. Our objective is to provide a rapid summary and evaluation of relevant data on SARS-CoV-2 transmission aboard cruise ships, report policy implications, and highlight research gaps requiring attention.

Methods

We will search LitCovid, medRxiv, Google Scholar, and the WHO Covid-19 database using COVID-19, SARS-CoV-2, transmission, and cruise ship appropriate synonyms. We will also search the reference lists of included studies for additional relevant studies. We will include studies reporting onboard SARS-CoV-2 transmission from passengers and/or crew to passengers and/or crew. We will consider any potential transmission mode. We will assess study quality based on five criteria and report important findings. The outcome will consist of the onboard cruise ships’ transmission of SARS-CoV-2. We will provide a narrative summary of the data and report the outcomes, including quantitative estimates where feasible and relevant. Where possible, compatible datasets may be pooled for meta-analysis.

Expected results

We will present the evidence in three distinct packages: study description, methodological quality assessment and data extracted. We will summarize the evidence and will draw conclusions as to the quality of the evidence.

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  1. SciScore for 10.1101/2021.10.11.21264724: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    RandomizationStudies can be observational, including case series, ecological, or prospective; or interventional, including randomized trials and clinical reports, outbreak reports, case-control studies, experimental studies, and non-predictive modeling.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Search Strategy: We will search the following electronic databases: LitCovid and the WHO COVID-19 from inception, and medRxiv and Google Scholar databases from January 2020.
    Google Scholar
    suggested: (Google Scholar, RRID:SCR_008878)
    As important new data accumulates, we will produce a report as an individual rapid review and aim to make all our work available by depositing the review findings on the Oxford Research Archive.
    Oxford Research Archive
    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: 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.

    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.