Effect of moist heat reprocessing of N95 respirators on SARS-CoV-2 inactivation and respirator function

This article has been Reviewed by the following groups

Read the full article See related articles

Discuss this preprint

Start a discussion What are Sciety discussions?

Abstract

No abstract available

Article activity feed

  1. SciScore for 10.1101/2020.05.25.20112615: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    RandomizationWe analyzed fiber morphology with a blinded observer using ImageJ (https://imagej.nih.gov/ij/) in ten randomly selected individual fibers from all quadrants of a representative image of each sample.
    BlindingWe analyzed fiber morphology with a blinded observer using ImageJ (https://imagej.nih.gov/ij/) in ten randomly selected individual fibers from all quadrants of a representative image of each sample.
    Power AnalysisSample size calculations for quantitative respirator fit revealed a required sample size of n=12 to detect a mean fit factor of 120 (pass value 100, mean fit factor of unprocessed mask 190±15) on an alpha level of 0.01 and a power of 0.95 (17).
    Sex as a biological variableFitted respirators were personalized to two blinded test subjects (one male, one female) and underwent thermal disinfection at 0% RH or 50% RH respectively (n=23 each) as outlined above.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    We then titrated the recovered infectious virus particles by standard TCID50 assay using Vero E6 cells as described (5).
    Vero E6
    suggested: RRID:CVCL_XD71)
    Software and Algorithms
    SentencesResources
    We analyzed fiber morphology with a blinded observer using ImageJ (https://imagej.nih.gov/ij/) in ten randomly selected individual fibers from all quadrants of a representative image of each sample.
    ImageJ
    suggested: (ImageJ, RRID:SCR_003070)
    Statistical methods: We conducted statistical analyses using JMP (version 15.1.0, SAS Institute, USA)
    SAS Institute
    suggested: (Statistical Analysis System, RRID:SCR_008567)

    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.