2024•Unpublished venueOpen access

How effective are face coverings in reducing transmission of COVID-19?

Joshua F. Robinson, Ioatzin Rıos de Anda, Fergus J. Moore, Florence K. A. Gregson, Jonathan P. Reid, Lewis Husain, Richard P. Sear, C. Patrick Royall

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Abstract

In the COVID–19 pandemic, billions are wearing face masks, in both health care settings and in public. Which type of mask we should wear in what situation, is therefore important. There are three basic types: cotton, surgical, and respirators (e.g. N95 and similar). All are essentially air filters worn on the face. Here we show that the underlying physics of air filtration ensures particles with diameters ≥ 1 to 3 µm are efficiently filtered out by all three types. However, for particles in the submicrometre range the efficiency depends on the material properties of the masks. For good quality cotton and surgical masks it is in the range 30 to 60%, while it is above 95% for respirators. So air filtration is relatively well understood, however, we have almost no direct evidence on the relative role played by aerosols of differing sizes in disease transmission. Without this data, selecting the correct mask will inevitably involve some guess work. If the virus concentration is assumed independent of aerosol size, then most virus will be in aerosols & 1µm and we expect both surgical masks and multi-layered cotton masks to be effective at reducing the risk of airborne transmission in most settings.

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In the COVID–19 pandemic, billions are wearing face masks, in both health care settings and in public. Which type of mask we should wear in what situation, is therefore important. There are three basic types: cotton, surgical, and respirators (e.g. N95 and similar). All are essentially air filters worn on the face. Here we show that the underlying physics of air filtration ensures particles with diameters ≥ 1 to 3 µm are efficiently filtered out by all three types. However, for particles in the submicrometre range the efficiency depends on the material properties of the masks. For good quality cotton and surgical masks it is in the range 30 to 60%, while it is above 95% for respirators. So air filtration is relatively well understood, however, we have almost no direct evidence on the relative role played by aerosols of differing sizes in disease transmission. Without this data, selecting the correct mask will inevitably involve some guess work. If the virus concentration is assumed independent of aerosol size, then most virus will be in aerosols & 1µm and we expect both surgical masks and multi-layered cotton masks to be effective at reducing the risk of airborne transmission in most settings.

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Available abstract

In the COVID–19 pandemic, billions are wearing face masks, in both health care settings and in public. Which type of mask we should wear in what situation, is therefore important. There are three basic types: cotton, surgical, and respirators (e.g. N95 and similar). All are essentially air filters worn on the face. Here we show that the underlying physics of air filtration ensures particles with diameters ≥ 1 to 3 µm are efficiently filtered out by all three types. However, for particles in the submicrometre range the efficiency depends on the material properties of the masks. For good quality cotton and surgical masks it is in the range 30 to 60%, while it is above 95% for respirators. So air filtration is relatively well understood, however, we have almost no direct evidence on the relative role played by aerosols of differing sizes in disease transmission. Without this data, selecting the correct mask will inevitably involve some guess work. If the virus concentration is assumed independent of aerosol size, then most virus will be in aerosols & 1µm and we expect both surgical masks and multi-layered cotton masks to be effective at reducing the risk of airborne transmission in most settings.

Key concepts: Respirator, Face masks, Coronavirus disease 2019 (COVID-19), Filtration (mathematics), Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Aerosol, Transmission (telecommunications), Range (aeronautics)

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