Face Mask Fit Hacks: Improving the Fit of KN95 Masks and Surgical Masks with Fit Alteration Techniques

Abstract

The COVID-19 pandemic has drawn unprecedented attention to the use of masks and fabric face coverings to prevent the spread of respiratory viruses, such as SARS-CoV-2. The fit of a mask has been identified as one the primary factors in determining the effectiveness of masks. If substantial gaps exist between the mask and the wearers face, air may take the path of least resistance through gaps and avoid filtration, both during inhalation and exhalation. A number of techniques, referred to as fit hacks have emerged to improve the fit of face masks. In this paper we test a variety of fit hacks on surgical masks and KN95 masks to compare their effectiveness. We identify fit hacks which greatly improved the fit of masks, and thus their effectiveness.