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

这一快速项目将推进对传染病是如何从言语传播的理解，这与当前新冠肺炎大流行中有关社会疏远措施的决策直接相关。在日常交谈中，呼吸道和声道中会产生携带病毒的小液滴。然后，当气流从嘴里流出时，它们被排出到周围环境中。较大的液滴可能会撞击附近的表面，而较小的液滴可能会以气雾剂的形式长时间悬浮在空气中。这两种呼气飞沫都有感染风险。较大的水滴可能会直接落在距离较近的人身上，而较小的气雾化颗粒能够传播更远的距离，并通过吸入呼吸道感染更远的人。目前，语音产生的粒子传播的距离范围，以及由此对近场(近场)和更远(远场)附近的个人构成的感染风险，还不是很清楚。室内环境中长时间说话可能会增加感染风险，空气中的颗粒物可能会随着时间的推移积累并达到更高的浓度，这一点也是未知的。这项研究计划旨在通过对语音进行物理测量并对液滴传输进行数值建模来回答这些问题，以预测受感染说话者的近场和远场感染风险。该项目的目标是确定携带病毒的液滴在语音过程中是如何传播的。特别强调研究在口腔中产生高速空气爆发的特定声音语调(即摩擦音和塞音)，这些语调被假设为推动颗粒在相对较长的距离上传播，并增加近场和远场的感染风险。我们将使用粒子图像测速仪对不同响度的元音、摩擦音和塞音进行持续元音、摩擦音和塞音的实验速度场测量。另外，空气动力学粒度仪将测量由这些相同的话语产生的液滴的尺寸分布。这些数据将用于验证和提供非定常雷诺平均Navier-Stokes计算流体力学模型，该模型采用欧拉-拉格朗日方法来建模和量化液滴动力学。将特定语音的呼气速度场和粒子动力学结合起来，将有助于通过使用SARS-CoV-2病毒的病毒滴度和感染剂量来预测浊音引起的感染风险。将对开放和封闭环境的近场和远场感染风险进行量化，在这些环境中，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积累。还将探索降低室内环境感染风险的缓解策略。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.