Quantitative fit testing of filtering face-piece respirators during the COVID-19 pandemic reveals anthropometric deficits in most respirators available in Iran

J Environ Health Sci Eng. 2021 Apr 15;19(1):805-817. doi: 10.1007/s40201-021-00648-3. eCollection 2021 Jun.

Abstract

Purpose: Frontline health care workers (HCWs) must wear a standard N95 or FFP2 respirator during worldwide pandemics of respiratory diseases including COVID-19 to protect against airborne infectious pathogens when performing care activities. This study aimed to quantitatively investigate the fit of most of the common FFRs used during the COVID-19 pandemic in Iran.

Methods: A total of 37 volunteers were fit tested in 20 selected FFRs in a randomized order. The selected FFRs were underwent quantitative fit testing by PortaCount® model 8038. To determine the effects of face sizes on respirator fit, the participants' facial dimensions were measured using a digital caliper.

Results: The rate of passing fit tests for the studied FFRs were surprisingly low with 11 out of 20 FFRs having less than 10% passing fit tests and the best performers having only 43% and 27% passing fit tests (brands 2 and 20, respectively). Cup-shaped respirators provided significantly greater fit than the vertical flat-fold ones (p < 0.001). A significantly different FFs were found among the respirator brands (F = 13.60, p < 0.001).

Conclusion: Overall, unacceptably low fit factors were obtained from the studied FFRs. The main reasons for this are suspected to single size and style for each studied FFR. It confirms the importance and requirement of the proper respirator selection in that way fitted optimally into facial dimensions, appropriate usage, and properly performing the fit testing procedure. A unique fit test panel should be developed to guide respirator wearers in selecting the appropriate FFR for their specific face sizes.

Keywords: Coronavirus (COVID-19). Filtering face-piece respirators. Quantitative fit test. Respiratory protection program. Respirator characteristics. Subject features.