A simple mathematical model for estimating the risk of airborne transmission of a respiratory infection such as COVID-19, is presented. The model employs basic concepts from fluid dynamics and incorporates the known scope of factors involved in the airborne transmission of such diseases. Simplicity in the mathematical form of the model is by design, so that it can serve not only as a common basis for scientific inquiry across disciplinary boundaries, but , also be understandable by a broad audience outside science and academia. The model is used to assess the protection from transmission afforded by face coverings made from a variety of fabrics. In addition, the reduction in transmission associated with physical distancing between the host and susceptible as well as the level of physical activity  of the host and /or the susceptible in enhancing transmission risk, is also examined .
A mathematical model for estimating the risk of airborne transmission of a respiratory infection such as COVID-19, is presented. The model employs basic concepts from fluid dynamics and incorporates the known scope of factors involved in the airborne transmission of such diseases. Simplicity in the mathematical form of the model is by design, so that it can serve not only as a common basis for scientific inquiry across disciplinary boundaries, but also be understandable by a broad audience outside science and academia. The caveats and limitations of the model are discussed in detail. The model is used to assess the protection from transmission afforded by face coverings made from a variety of fabrics. The reduction in transmission risk associated with increased physical distance between the host and susceptible is also quantified by coupling the model with available data on scalar dispersion in canonical flows. Finally, the effect of the level of physical activity (or exercise intensity) of the host and the susceptible in enhancing transmission risk, is also assessed .
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simple
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model
caveats and limitations of the model are discussed in detail. The model
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associated with physical distancing
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as well as the
is also quantified by coupling the model with available data on scalar dispersion in canonical flows. Finally, the effect of the
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(or exercise intensity)
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/or
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examined
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