Chaudhuri Swetaprovo, Saha Abhishek, Basu Saptarshi
Institute for Aerospace Studies, University of Toronto, Toronto, ON M3H 5T6, Canada.
Department of Mechanical and Aerospace Engineering, University of California San Diego, La Jolla, CA 92093, USA.
Curr Opin Colloid Interface Sci. 2021 Aug;54:101462. doi: 10.1016/j.cocis.2021.101462. Epub 2021 May 1.
Recognizing the multiscale, interdisciplinary nature of the Covid-19 transmission dynamics, we discuss some recent developments concerning an attempt to construct a disease spread model from the flow physics of infectious droplets and aerosols and the frequency of contact between susceptible individuals with the infectious aerosol cloud. Such an approach begins with the exhalation event-specific, respiratory droplet size distribution (both airborne/aerosolized and ballistic droplets), followed by tracking its evolution in the exhaled air to estimate the probability of infection and the rate constants of the disease spread model. The basic formulations and structure of submodels, experiments involved to validate those submodels, are discussed. Finally, in the context of preventive measures, respiratory droplet-face mask interactions are described.
认识到新冠病毒传播动力学的多尺度、跨学科性质，我们讨论了一些近期的进展，这些进展涉及尝试从传染性飞沫和气溶胶的流体物理学以及易感个体与传染性气溶胶云之间的接触频率构建疾病传播模型。这种方法从特定呼气事件的呼吸道飞沫大小分布（包括空气传播/气溶胶化飞沫和弹道飞沫）开始，然后跟踪其在呼出空气中的演变，以估计感染概率和疾病传播模型的速率常数。讨论了子模型的基本公式和结构，以及用于验证这些子模型的实验。最后，在预防措施的背景下，描述了呼吸道飞沫与口罩的相互作用。
