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Use, reuse or discard: quantitatively defined variance in N95 respirator integrity following vaporized hydrogen peroxide decontamination during the COVID-19 pandemic (preprint)
medrxiv; 2020.
Preprint in English | medRxiv | ID: ppzbmed-10.1101.2020.08.18.20177071
ABSTRACT
BackgroundCOVID-19 has stretched the ability of many institutions to supply needed personal protective equipment, especially N95 respirators. N95 decontamination and reuse programs provide one potential solution to this problem. Unfortunately, a comprehensive evaluation of the effects of decontamination on the integrity of various N95 models using a quantitative fit test (QTFT) approach is lacking. Aims1) To investigate the effects of up to eight rounds of vaporized H2O2 (VHP) decontamination on the integrity of N95 respirators currently in use in a hospital setting. 2) To examine if N95 respirators worn by one user can adapt to the face shape of a second user with no compromise of integrity following VHP decontamination. MethodsThe PortaCount Pro+ Respirator Fit Tester Model 8038 was used to quantitatively define the integrity, measured by fit, of N95 respirators following decontamination with VHP. FindingsThere was an observable downward trend in the integrity of Halyard Fluidshield 46727 N95 respirators throughout eight cycles of decontamination with VHP. The integrity of 3M 1870 N95 respirators was significantly reduced after the respirator was worn, decontaminated with VHP, and then quantitatively fit tested on a second user. Furthermore, we uncovered inconsistencies between qualitative fit test and QTFT results that may have strong implications on the fit testing method used by institutions. ConclusionsOur data revealed variability in the integrity of different N95 models after VHP decontamination and exposed potential limitations of N95 decontamination and reuse programs.
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Full text: Available Collection: Preprints Database: medRxiv Main subject: COVID-19 Language: English Year: 2020 Document Type: Preprint

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Full text: Available Collection: Preprints Database: medRxiv Main subject: COVID-19 Language: English Year: 2020 Document Type: Preprint