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The well-mixed assumption has been widely used in predicting the spread of infectious diseases in indoor spaces. It is to be expected that a perfect well-mixed state will not be achieved in an indoor space at any reasonable level of ventilation. This work evaluates the well-mixed assumption by comparing the theory with results from large eddy simulations. The robustness of the well-mixed theory is established by comparing at four different levels. The comparison also points out systematic departures in pathogen concentration which can be accurately accounted for with an easily implementable correction factor to quantities such as cumulative exposure time. With the well-mixed model as the baseline, the correction factor can be used to account for additional important problem-specific details. We demonstrate that more accurately accounting for variability in pathogen concentration can help obtain improved estimates for enhanced guidelines of indoor airborne transmission. We further demonstrate that at source-sink separation distances smaller than 5 m, the well-mixed theory on average underestimates the risk of contagion, while for distances larger than about 5 m, the well-mixed theory's prediction, on average, is overly restrictive.


©2022 American Physical Society. Original published version available at

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Physical Review Fluids





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