In this work, we estimate the probability of an infected person infecting another person in the vicinity by coughing in the context of COVID-19. The analysis relies on the experimental data of Simha and Rao [“Universal trends in human cough airflows at large distances,” Phys. Fluids 32, 081905 (2020)] and similarity analysis of Agrawal and Bhardwaj [“Reducing chances of COVID-19 infection by a cough cloud in a closed space,” Phys. Fluids 32, 101704 (2020)] to determine the variation of the concentration of infected aerosols with some distance from the source. The analysis reveals a large probability of infection within the volume of the cough cloud and a rapid exponential decay beyond it. The benefit of using a mask is clearly brought out through a reduction in the probability of infection. The increase in the probability of transmission by a super-spreader is also quantified for the first time. At a distance of 1 m, the probability of infection from a super-spreader is found to be 185% larger than a normal person. Our results support the current recommendation of maintaining a 2 m distance between two people. The analysis is enough to be applied to the transmission of other diseases by coughing, while the probability of transmission of COVID-19 due to other respiratory events can be obtained using our proposed approach.

中文翻译：

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正常人和超级传播者咳嗽引起COVID-19感染的可能性

在这项工作中，我们通过在COVID-19的情况下咳嗽来估计被感染者感染附近另一个人的可能性。该分析基于Simha和Rao的实验数据[“人类远距离咳嗽气流的普遍趋势”，Phys。流体32，081905（2020）]和阿格拉瓦尔和巴德瓦杰[的相似性分析物理学“由咳嗽云在一个封闭的空间，降低COVID-19感染机会”。流体32，101704（2020）]来确定受感染气雾剂的浓度在距源头一定距离处的变化。分析表明，在咳嗽云内有很大的感染可能性，而在咳嗽云之外迅速呈指数衰减。降低感染几率显然带出了使用口罩的好处。超级扩展器传输的可能性的增加也首次被量化。在1 m的距离处，发现从超级传播者感染的可能性比正常人大185％。我们的结果支持目前建议两个人之间保持2 m的距离。该分析足以通过咳嗽应用于其他疾病的传播，