Clinical Data on Hospital Environmental Hygiene Monitoring and Medical Staff Protection during the Coronavirus Disease 2019 Outbreak

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Abstract

Background

The outbreak of coronavirus disease 2019 (COVID-19) has placed unprecedented challenges on hospital environmental hygiene and medical staff protection. It is crucial to assess hospital environmental hygiene to understand the most important environmental issues for controlling the spread of COVID-19 in hospitals.

Objective

To detect the presence of COVID-19 in the samples from the area at risk of contamination in the First Hospital of Jilin University.

Methods

Viruses in the air were collected by natural sedimentation and air particle sampler methods. Predetermined environmental surfaces were sampled using swabs at seven o’clock in the morning before disinfection. The real-time reverse-transcription PCR method was used to detect the existence of COVID-19 pathogens.

Results

Viruses could be detected on the surfaces of the nurse station in the isolation area with suspected patients and in the air of the isolation ward with an intensive care patient.

Conclusion

Comprehensive monitoring of hospital environmental hygiene during pandemic outbreaks is conducive to the refinement of hospital infection control. It is of great significance to ensure the safety of medical treatment and the quality of hospital infection control through the monitoring of environmental hygiene.

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  1. SciScore for 10.1101/2020.02.25.20028043: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: This study was approved by the Ethics Committee of the First Hospital of Jilin University (Changchun, China). 2.2 Sampling and Sample Processing: The environmental monitoring methods referenced the hospital sanitation standards (GB15982-2012).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.


    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.