  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. FFP2, N95 and similar). All are essentially air
filters worn on the face. Air filtration is relatively well understood,
however, we have almost no direct evidence on the relative role played by
aerosol particles of differing sizes in disease transmission. But if the virus
concentration is assumed independent of aerosol particle size, then most virus
will be in particles > 1 $\mu$m. We develop a model that predicts surgical
masks are effective at reducing the risk of airborne transmission because the
filtering material most surgical masks use is highly effective at filtering
particles with diameters > 1 $\mu$m. However, surgical masks are significantly
less effective than masks of FFP2, N95 and similar standards, mostly due to the
poor fit of surgical masks. Earlier work found that ~30% of the air bypasses a
surgical mask and is not filtered. This highlights the fact that standards for
surgical masks do not specify how well the mask should fit, and so are not
adequate for protection against COVID-19.
