Risk assessment using a fluid-mechanics informed statistical framework for short and long-term exposure for indoor airborne viral transmission

The risk of airborne viral contagion in indoor spaces can be greatly mitigated or aggravated by the quality of the ventilation system. Theoretical models [1] have been used extensively to predict the spread of infectious diseases in such settings. This work is aimed at providing a statistical framework to act as an improvement on the well-mixed theory by leveraging LES and RANS simulations of fluid flow and droplet nuclei dispersal in multiple room and ventilation configurations. The developed framework provides a simple multiplicative correction factor, that accounts for the roles of separation distance and filtration efficiency, to quantify the deviation of the simulations from the theory [2,3].

The framework is then used to provide guidelines for short and long-term occupancy in indoor spaces. The effect of factors such as separation distance, time of exposure and size of the indoor space on increasing or decreasing the probability of infection is relatively well understood. The contradictory effects of increasing flow rate on turbulent dispersion and rate of removal of droplet nuclei lead to a worst-case ACH for relatively short exposure times (under 30 minutes). The statistical framework is used to quantify this worst-case ACH for differing separation distances, filter efficiencies, and exposure times. For long-term exposure (more than an hour), the general guideline of operating at as high an ACH as possible is still applicable. For such scenarios, the role of the parameters mentioned above is used to provide guidelines for occupancy as a function of the cumulative exposure time.



References:

[1] M. Z. Bazant and J. W. Bush, A guideline to limit indoor airborne transmission of COVID-19, Proceedings of the National Academy of Sciences 118 (2021).

[2] J.S. Salinas, K.A. Krishnaprasad, N. Zgheib, and S. Balachandar, Improved guidelines of indoor airborne transmission taking into account departure from the well-mixed assumption, Physical Review Fluids 7, 064309 (2022).

[3] K.A. Krishnaprasad, J.S. Salinas, N. Zgheib, and S. Balachandar, Fluid mechanics of air recycling and filtration for indoor airborne transmission, Physics of Fluids 35, 013344 (2023).