Effect of humidity on the evolution of COVID-19 droplets distribution in extreme in-homogeneous environment

Abstract

We numerically modeled the droplets’ size distribution of sneezing action from the COVID-19 patient, without considering the viral loading of droplets. Thus, we assumed the behavior of COVID-19 droplets same as that of standard water droplets. In this work, we evolved the initial Weibull distribution (typically used for representing the saliva droplets size distribution) using a non-dimensional droplet size distribution equation under extreme in-homogeneous conditions. We varied the environmental humidity contrast according to the range primarily encountered in the world’s major cities. We found bimodal size distribution of droplets for every humidity contrast, previously reported to be a function of Stoke’s number. This bimodal size distribution of droplets is a consistent event in in-homogeneous mixing. The high humidity contrast between the sneezing zone of influence to the environment will have a comparatively long tail of droplets. This long tail of droplets implies that the evaporation time scales will be highly variable and, consequently, significantly impact the transmission of the virus from a COVID-19 patient to a healthy human being. Essentially means that these cities of high humidity contrast will be more prone to high infections.