RAPID: Speech as a modality for airborne transport of virus-laden droplets in the COVID-19 pandemic

此RAPID项目将促进对传染病如何通过说话传播的理解，这与当前COVID-19大流行中有关社交距离措施的决策直接相关。在正常的交谈中，呼吸道和声道中会产生携带病毒的小飞沫。然后，随着气流离开口腔，它们被排入周围环境。较大的液滴可能会撞击附近的表面，而较小的液滴可能会作为气溶胶长时间悬浮在空气中。这两种类型的呼气飞沫都有感染的风险。较大的液滴可能直接落在非常接近的人身上，而较小的雾化颗粒能够传播更长的距离，并通过吸入呼吸道感染更远的人。目前，人们还不太清楚语音产生的颗粒传播的距离范围，以及由此产生的对直接（近场）和更远（远场）附近的个人造成的感染风险。由于室内环境中长时间讲话，空气中的颗粒物可能会随着时间的推移而积累并达到更高的浓度，因此感染风险增加的可能性也尚不清楚。该研究计划旨在回答这些问题，通过对语音进行物理测量，并结合液滴传输的数值模拟，预测受感染者近场和远场的感染风险。该项目的目标是确定携带病毒的液滴如何在语音中传播。特别强调的是研究特定的声乐语调，产生高速爆发的空气在嘴（即，摩擦音和爆破音），其被假设为在相对长的距离上推进颗粒并增加近场和远场两者中的感染风险。实验速度场测量的人口射流将获得持续元音，摩擦音和爆破音，在不同的响度水平使用粒子图像测速。另外，空气动力学颗粒尺寸光谱法将测量由这些相同的话语产生的液滴尺寸分布。这些数据将被用来验证和通知非定常雷诺平均纳维尔-斯托克斯计算流体动力学模型，采用欧拉-拉格朗日方法来建模和量化液滴动力学。耦合呼气速度场和粒子动力学的特定语音发音将有助于预测感染风险所产生的有声语音通过使用病毒滴度水平和感染剂量的SARS-CoV-2病毒。将量化开放和密闭环境的近场和远场感染风险，其中与通风、颗粒沉降和病毒灭活率相关的竞争时间尺度将影响稳态颗粒累积。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This RAPID project will advance the understanding of how infectious diseases are spread from speaking, which is directly relevant to informing decisions regarding social distancing measures in the current COVID-19 pandemic. During regular conversation, small virus-laden droplets are generated in the respiratory and vocal tract. They are then expelled into the surrounding environment as airflow exits the mouth. Larger droplets may impact surfaces in the immediate vicinity, while smaller ones may stay suspended in the air as aerosols for long periods of time. Both types of expiratory droplets pose an infection risk. Larger droplets may land directly on individuals that are in close proximity, while smaller aerosolized particles are capable of traveling longer distances and infecting people much farther away by being inhaled into the respiratory tract. Currently, the range of distances that particles travel when produced by speech, and the resulting infection risk posed to individuals in the immediate (near field) and more distant (far field) vicinity, is not well understood. The potential for increased infection risk due to prolonged speech in indoor environments, where airborne particles may accumulate over time and reach higher concentrations, is also not known. This research proposal aims to answer these questions by performing physical measurements of speech in tandem with numerical modeling of droplet transport to predict infection risks in both the near and far field of an infected speaker.The goal of this project is to determine how virus-laden droplets are spread during speech. Particular emphasis is placed on investigating specific vocal intonations that produce high velocity bursts of air at the mouth (i.e., fricatives and plosives), which are hypothesized to propel particles over relatively long distances and increase infection risk in both the near and far field. Experimental velocity field measurements of the human mouth jet will be acquired using particle image velocimetry for sustained vowels, fricatives, and plosives, at varying levels of loudness. Separately, aerodynamic particle size spectrometry will measure the droplet size distributions generated by these same utterances. These data will be used to validate and inform an unsteady Reynolds-averaged Navier-Stokes computational fluid dynamics model that adopts an Eulerian-Lagrangian approach to model and quantify droplet dynamics. Coupling the expiratory velocity fields and particle dynamics for specific speech utterances will facilitate predicting the infection risk arising from voiced speech by using viral titer levels and infectious doses for the SARS-CoV-2 virus. Near and far field infection risks will be quantified for both open and confined surroundings, where the competing times scales associated with ventilation, particle settling, and virus inactivation rates, will influence the steady-state particle accumulation. Mitigation strategies to decrease infection risk in indoor environments will also be explored.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.