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How well do masks prevent the spread of aerosol particles?

Why is mask wearing so important to preventing the spread of viruses?

As a result of the global SARS-CoV-2 pandemic, mask wearing has become increasingly commonplace across the globe. One of the primary benefits attributed to mask wearing is that it prevents the onward transmission of the virus – that is, people who are already infected with coronavirus are less likely to infect others if they are wearing a mask. Opponents of mask wearing point to the absence of high quality evidence supporting this assertion. This is technically accurate. For ethical and logistical reasons, there are no high-quality experimental studies demonstrating the impact of masks on preventing the spread of SARS-CoV-2. 

In the absence of COVID-specific evidence, the scientific community must instead rely on more generalised mechanistic studies to demonstrate the benefits of mask wearing. A study published in Nature Scientific Reports represents an interesting addition to the growing body of such mechanistic evidence (1). 

The study examines the effectiveness of a variety of mask types at reducing aerosol particle emission during a number of activities. To carry out these tests, the research team recruited 10 participants, four female and six male, across a variety of age brackets. An aerodynamic particle sizer (APS) was set up inside a HEPA-filtered laminar flow hood. The HEPA-filter minimises background particulate matter, while the APS is capable of identifying and counting particles between 0.3 and 20µm in size. A funnel was placed at an opening in the flow hood and connected to the APS.

Participants were then asked to place their mouths in front of the funnel and to complete a variety of expiratory tasks such as speaking coughing etc. These activities were repeated with each mask type and in the absence of any mask. A microphone placed next to the funnel recorded the duration and intensity of actions like talking and coughing. The mask types used included surgical masks, N95 respirators, vented KN95 respirators, and a variety of homemade cloth masks.

Wearing surgical masks or KN95 vented respirators resulted in a significant reduction in particle emission while breathing, coughing, and speaking. However, a slight increase in particle emission was observed in participants wearing single or double layer cotton t-shirt masks. The authors conclude that this increase is not in fact due to expiratory particles and instead the result of particulate matter from the mask itself. Cotton is a friable cellulosic fibre meaning it can be worn away by shear forces. The proposed explanation for the unexpected results here is that expiratory forces result in cotton particulate matter becoming dislodged and being detected by the APS, rather than cotton-based masks resulting in an increase in expiratory droplets.

Interestingly, one of the study participants was considered a “superemitter” as his particle emission during coughing was two orders of magnitude above the average. Surgical masks and KN95 respirators remained effective even when dealing with this “superemitter”. The audio recording device confirmed that when wearing masks, people talk more loudly but do not cough more loudly.

Overall the study raises some interesting results. The results of tests using surgical and medical grade masks confirm the effectiveness of these masks at reducing droplet emission. However, the results of tests using the homemade masks, particularly the cotton masks, raise some further questions. Research is needed to confirm the hypothesis that the observed increase in particle emission when wearing these masks is due to fabric particles. But it is also important to explore whether these fabric particles might contain viral material.

Written by Michael McCarthy

1. Asadi S, Cappa CD, Barreda S, Wexler AS, Bouvier NM, Ristenpart WD. Efficacy of masks and face coverings in controlling outward aerosol particle emission from expiratory activities. Sci Rep. 2020;10(1):15665.

Image by cromaconceptovisual from Pixabay 



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