Multi-phase simulation of infected respiratory cloud transmission in air

In the face of the increasing death toll of the COVID-19 global pandemic, countries around the world have instituted restrictive measures to mitigate the serious effects of the pandemic. Human-to-human transmission of COVID-19 occurs primarily through large droplets that are expelled with sufficient momentum to come in direct contact with the recipients’ mouth. Therefore, the physics of flow is central to transmission of COVID-19. Respiratory infections increase the frequency of violent expiration, including coughing and sneezing that are particularly effective in dispersing virus-carrying droplets. Moreover, the high viral load in droplets of asymptomatic hosts that are expelled during respiratory activities is contributing to the rapid growth of the COVID-19 global pandemic. The present study uses 2D smoothed-particle-hydrodynamics multi-phase simulations of the fluid dynamics of violent expiratory events in order to obtain a deeper understanding of the multi-phase nature of respiratory clouds, which can help determine separation distances from an infected person needed to minimize respiratory transmission. Our results indicate that there are three phases of jet cloud flow: the first is dominated by no-buoyancy jet-like dynamics characterized by a high speed, the second is dominated by negative buoyancy, and the third is dominated by gravity that deflects the cloud downward. Moreover, two modes of jet behavior that differ in dilution have been identified to be a function of distance from the human mouth. This work is of direct relevance to studies on the spread of COVID-19 and similar outbreaks in the future.

Abstract licence: CC BY

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.