  The rapid emergence and the disastrous impact of the severe acute respiratory
syndrome coronavirus 2 (SARS-CoV-2) pandemic on public health, societies, and
economies around the world has created an urgent need for understanding the
pathways critical for virus transmission. Airborne virus transmission by
asymptomatic SARS-CoV-2-infected individuals is considered to be a major
contributor to the spread of SARS-CoV-2 and social distancing and wearing of
face masks in public have been implemented as countermeasures in many
countries. However, a comprehensive risk assessment framework for the airborne
transmission of SARS-CoV-2 incorporating realistic assumptions on the
filtration of infectious aerosols (IAs) by face masks is not available yet. In
particular, in most end-to-end models for airborne virus transmission, it is
neglected that the stochastic spread of IAs through imperfectly fitted face
masks depends on the dynamics of the breathing of the wearer. In this paper, we
consider airborne virus transmission from an infected but asymptomatic person
to a healthy person, both wearing imperfectly fitted face masks, in an indoor
environment. By framing the end-to-end virus transmission as a Molecular
Communications (MC) system, we obtain a statistical description of the number
of IAs inhaled by the healthy person subject to the respective configurations
of the face masks of both persons. We demonstrate that the exhalation and
inhalation air flow dynamics have a significant impact on the stochastic
filtering of IAs by the face masks. Furthermore, we show that the fit of the
face mask of the infected person can highly impact the infection probability.
We conclude that the proposed MC model may contribute a valuable assessment
tool to fight the spread of SARS-CoV-2 as it encompasses the randomness of the
transmission process and enables comprehensive risk analysis beyond statistical
averages.
