Quantification of leakage of sub-micron aerosols through surgical masks and facemasks for pediatric use

Abstract

ABSTRACTSurgical respirators, surgical masks (SMs), and facemasks for pediatric use (FPUs) are routinely used in the U.S. healthcare industry as personal protective equipment (PPE) against infectious diseases. While N95s including surgical respirators have been routinely studied, SMs and FPUs have not received as much attention, particularly in the context of aerosolized threats. This is because SMs and PFUs are not designed to protect against sub-micron aerosols. However, with the possibility of new or re-emerging airborne diseases or bio-aerosol weapons lingering, combined with the limited availability of respirators and logistical issues associated with fit-testing millions, the general adult and pediatric populations may elect to wear SMs and FPUs, respectively, in the case of a pandemic or a bio-terrorist attack. When a person dons a PPE, gaps are created between the wearer's face and the PPE, and aerosols leaking through these gaps can be an important contributor to the risk of infection compared to filtered aerosols. To understand and quantify the contribution of leakage of aerosols through gaps, with particular emphasis on SMs and FPUs, this study investigated leakage of charge-neutralized, polydispersed, dried sodium-chloride aerosols across different brands of PPE. Different breathing rates, aerosol particle sizes, and gap sizes were considered. A few major findings of this study were: (a) leakage, is not a strong function of sub-micron aerosol size; (b) for the same gap size, leakage of aerosols through surgical respirators can often be higher than in SMs and FPUs; and (c) as the gap size increases, the increase in leakage through surgical respirators is higher compared for SMs and FPUs, implying that some SMs and FPUs that possess electret layers may be preferable to N95s that have not been fit-tested. The results obtained can also be used to explain conflicting findings from clinical studies on the effectiveness of SMs when compared to N95s and can be input into risk-assessment models to determine the increase in infection rate resulting from deployment of PPE under less-than-ideal conditions.