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

RAPID：在 COVID-19 大流行中，语音是携带病毒的飞沫通过空气传播的一种方式

• 批准号: 2029548
• 负责人: Byron Erath
• 金额: $ 19.94万
• 依托单位: Clarkson University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-05-01 至 2021-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2029548&HistoricalAwards=false
• 关键词: RAPID; Speech; modality; airborne; transport

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.

这个快速的项目将促进对传染病如何从说话中传播的理解，这与告知有关当前Covid-19-19的大流行中社会疏远措施的决定直接相关。在常规对话中，在呼吸道和声带中产生了富含病毒的小滴。然后，随着气流出口，它们被驱逐到周围环境中。较大的液滴可能会影响附近附近的表面，而较小的液滴可能会长时间作为气溶胶悬挂在空气中。两种类型的呼气液滴都构成感染风险。较大的液滴可能直接落在处于近距离接近的个体上，而较小的雾化颗粒能够通过被吸入呼吸道的距离更长的距离并感染更远的人。当前，颗粒在语音产生时传播的距离范围以及对即时（近场）和更遥远（远场）附近的个体带来的感染风险尚不清楚。在室内环境中延长的语音导致感染风险增加的可能性，在室内环境中，空中颗粒可能会随着时间的流逝而积聚并达到较高的浓度。该研究建议旨在通过与液滴运输的数值建模进行语音测量来回答这些问题，以预测感染扬声器的近距离和远处的感染风险。该项目的目的是确定在语音期间如何散布病毒的液滴。特别强调研究特定的声音语调，这些音调在口腔（即摩擦剂和plosives）上产生高速速度的空气爆发，这些声音被认为可以推动相对较长的距离颗粒，并在近距离和远处增加感染风险。将使用粒子图像速度测定法获得持续的元音，摩擦剂和plosives的实验速度场测量，以不同的响度。另外，空气动力学粒径光谱法将测量这些相同话语产生的液滴尺寸分布。这些数据将用于验证和告知不稳定的雷诺平均Navier-Stokes计算流体动力学模型，该模型采用Eulerian-Lagrangian方法来建模和量化液滴动力学。耦合呼气速度场和特定语音话语的粒子动力学将有助于预测通过使用病毒滴度水平和SARS-COV-2病毒的病毒滴度水平和感染性剂量引起的言语引起的感染风险。近距离和远处感染的风险将在开放和约束环境中进行量化，在这种环境中，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粒子的积累。还将探讨降低室内环境中感染风险的缓解策略。该奖项反映了NSF的法定任务，并且使用基金会的知识分子优点和更广泛的影响审查标准，被认为值得通过评估来获得支持。

项目成果

Host-to-host airborne transmission as a multiphase flow problem for science-based social distance guidelines

• DOI: 10.1016/j.ijmultiphaseflow.2020.103439
• 发表时间: 2020-09-04
• 期刊: International Journal of Multiphase Flow
• 影响因子: 3.8
• 作者: Balachandar S;Zaleski S;Soldati A;Ahmadi G;Bourouiba L
• 通讯作者: Bourouiba L

Significance of Vocal Tract Geometrical Variations and Loudness on Airflow and Droplet Dispersion in a Two-Dimensional Representation of [F]

[F] 二维表示中声带几何变化和响度对气流和液滴扩散的意义

• DOI: 10.1115/fedsm2021-65485
• 发表时间: 2021
• 期刊: The American Society of Mechanical Engineers Fluids Engineering Division Summer Meeting
• 作者: Mofakham, Amir A.;Helenbrook, Brian T.;Ahmed, Tanvir;Erath, Byron D.;Ferro, Andrea R.;Brown, Deborah M.;Ahmadi, Goodarz
• 通讯作者: Ahmadi, Goodarz

Aerosols Transport, Dispersion and Deposition- Applications to Transmission of COVID-19

气溶胶传输、分散和沉积 - 在 COVID-19 传播中的应用

• DOI: 10.5185/vpoam.2021.0187
• 发表时间: 2021
• 期刊: Video Proceedings of Advanced Materials
• 作者: Ahmadi, Goodarz

Variability in expiratory trajectory angles during consonant production by one human subject and from a physical mouth model: Application to respiratory droplet emission

• DOI: 10.1111/ina.12908
• 发表时间: 2021-07-23
• 期刊: INDOOR AIR
• 影响因子: 5.8
• 作者: Ahmed, Tanvir;Wendling, Hannah E.;Erath, Byron D.
• 通讯作者: Erath, Byron D.