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Striving to be the fittest: Quantitative P2/N95 respirator fit test results among hospital staff during the COVID-19 pandemic

  • Melanie (Meilun) Zhang
  • , Liam Hackett
  • , Jesse Smith
  • , Zoe Pritchard
  • , Matthew Casey
  • , Caitlin Low
  • , Paul Buntine

Research output: Contribution to journal › Article › Research › peer-review

Abstract

Objective: To provide fit rates for specific P2/N95 respirators and compare these results by age, sex, clean-shaven status, and fit tester experience. Design: Exploratory audit involving secondary analysis of existing quantitative fit testing data. Setting: In response to the COVID-19 pandemic, healthcare services across Australia implemented respiratory protection protocols. This study details healthcare workers' (HCWs) fit testing results from a large Victorian public health service. Participants: Fit-tested employees of a large tertiary public health network. Methods: Fit rates for ten individual P2/N95 respirators were calculated, and the effect of age, sex, clean-shaven status, and fit tester experience was examined via logistic regression. Results: 4593 employees were included, with 97.98% successfully fitting at least one respirator. Males were found to have significantly increased odds of achieving fit success compared to females (OR 11.61 95%CI 1.60-84.10). Fit rates dropped by 4% with each 1-year age increase (OR 0.96 95%CI 0.94-0.98). Clean-shaven individuals were also more likely to achieve a fit compared to non-clean-shaved individuals (OR 79.23 95%CI 10.21-614.62). More experienced fit testers also yielded significantly higher fit rates (OR 3.95, 95%CI 2.34-6.67). Conclusions: 98% of staff achieved a successful fitting of at least one respirator, with three-panel flat fold models (Industree Trident, 3M Aura 9320A+, and 3M Aura 1870+) performing the most consistently. An individual's ability to achieve a successful fit was associated with; male sex, younger age, clean-shaven status, and fit tester experience.

Original languageEnglish
Article numbere233
Number of pages8
JournalAntimicrobial Stewardship and Healthcare Epidemiology
Volume3
Issue number1
DOIs
Publication statusPublished - 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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