Abstract
Purpose: Our purpose was to model the transport and fate of respiratory cles in the vocal tract during phonation and to determine the size of parthat can be emitted if generated at the level of glottis or below. The COVpandemic and associated discussion on airborne transmission has led to need to understand particle emission during respiratory activities and its mecnisms. Computational fluid dynamics (CFD) simulations can model partitransport inside the airways, as in vivo measurements remain challenging. Method: CFD (large eddy) simulations were used to analyze airflow patternthe vocal tract and the motion of particles (1–100 μm) introduced from the of glottis. The effect of airflow velocity was evaluated. Results: In the model, the upper airway filtered the large particles, allowing particles < 10 μm to exit the mouth. The cutoff size for filtration depends oflow velocity and Stokes number of particles, which describes a particle’s dency to follow the flow. The results indicate that the cutoff size decrewhen the flow rate increases. Conclusions: We demonstrated that the largest particles (> 5–10 μm) forbelow the pharynx may adhere to airway walls due to the complex anatomy vocal tract. We propose that the primary deposition mechanism is the inabilitthese particles to change direction at locations where the flow turns. The retherefore suggest that infections in lower airways may transmit primarily via sparticles. This should be considered when planning suitable protective measures.
| Original language | English |
|---|---|
| Pages (from-to) | 3107-3118 |
| Number of pages | 12 |
| Journal | Journal of Speech, Language, and Hearing Research |
| Volume | 68 |
| Issue number | 7 |
| DOIs | |
| Publication status | Published - Jul 2025 |
| MoE publication type | A1 Journal article-refereed |
Funding
This study was funded by Business Finland, the Helsinki University Hospital Co-Innovation fund, Grant 4793/31/ 2021, under the E3 Excellence in Pandemic Response project. Additionally, A.T. would like to express gratitude for funding received from the Finnish Cultural Foundation (Grant 00201112), the Finnish Medical Foundation sr (Grant 5412), and the Finnish Otorhinolaryngology— Head and Neck Surgery Foundation (Grant 20220043). E.S. acknowledges funding from Finska Läkaresällska-pet, Tuberkuloosin vastustamissäätiö, Tampereen tuber-kuloosisäätiö, and the Jalmari and Rauha Ahokas Foundation. V.V. acknowledges the Academy of Finland (presently the Research Council of Finland) for its financial support (Grant 335516). D.I. acknowledges financial support from the Research Council of Finland (Grant 354620). The computational resources for this study were provided by CSC Finnish – IT Center for Science. The funders had no role in the study design, data analysis, interpretation, or writing of the report. This study was funded by Business Finland, the Helsinki University Hospital Co-Innovation fund, Grant 4793/31/ 2021, under the E3 Excellence in Pandemic Response project. Additionally, A.T. would like to express gratitude for funding received from the Finnish Cultural Foundation (Grant 00201112), the Finnish Medical Foundation sr (Grant 5412), and the Finnish Otorhinolaryngology— Head and Neck Surgery Foundation (Grant 20220043). E.S. acknowledges funding from Finska Läkaresällskapet, Tuberkuloosin vastustamissäätiö, Tampereen tuberkuloosisäätiö, and the Jalmari and Rauha Ahokas Foundation. V.V. acknowledges the Academy of Finland (presently the Research Council of Finland) for its financial support (Grant 335516). D.I. acknowledges financial support from the Research Council of Finland (Grant 354620). The computational resources for this study were provided by CSC Finnish – IT Center for Science. The funders had no role in the study design, data analysis, interpretation, or writing of the report.
Keywords
- Hydrodynamics
- Humans
- Vocal Cords/physiology
- Mouth/physiology
- Computer Simulation
- COVID-19/transmission
- Phonation/physiology
- Models, Biological
- Particle Size
- SARS-CoV-2