Recognizing the multi-scale, inter-disciplinary 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 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 sub-models, experiments involved to validate those sub-models are discussed. Finally, in the context of preventive measures, respiratory droplet-face mask interactions are described.

认识到 Covid-19 传播动力学的多尺度、跨学科性质，我们讨论了一些最近的进展，这些进展涉及尝试从传染性飞沫和气溶胶的流动物理学以及易感个体之间的接触频率构建疾病传播模型与传染性气溶胶云。这种方法从特定于呼气事件的呼吸液滴大小分布（空气传播/雾化和弹道液滴）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，以及验证这些子模型所涉及的实验。最后，在预防措施的背景下，描述了呼吸飞沫与面罩的相互作用。