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Modeling and experimental study of dispersion and deposition of respiratory emissions with implications for disease transmission
The ability to model the dispersion of pathogens in exhaled breath is important for characterizing transmission of the SARS‐CoV‐2 virus and other respiratory pathogens. A Computational Fluid Dynamics (CFD) model of droplet and aerosol emission during exhalations has been developed and for the first...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9111502/ https://www.ncbi.nlm.nih.gov/pubmed/35225395 http://dx.doi.org/10.1111/ina.13000 |
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author | Coldrick, Simon Kelsey, Adrian Ivings, Matthew J. Foat, Timothy G. Parker, Simon T. Noakes, Catherine J. Bennett, Allan Rickard, Helen Moore, Ginny |
author_facet | Coldrick, Simon Kelsey, Adrian Ivings, Matthew J. Foat, Timothy G. Parker, Simon T. Noakes, Catherine J. Bennett, Allan Rickard, Helen Moore, Ginny |
author_sort | Coldrick, Simon |
collection | PubMed |
description | The ability to model the dispersion of pathogens in exhaled breath is important for characterizing transmission of the SARS‐CoV‐2 virus and other respiratory pathogens. A Computational Fluid Dynamics (CFD) model of droplet and aerosol emission during exhalations has been developed and for the first time compared directly with experimental data for the dispersion of respiratory and oral bacteria from ten subjects coughing, speaking, and singing in a small unventilated room. The modeled exhalations consist of a warm, humid, gaseous carrier flow and droplets represented by a discrete Lagrangian particle phase which incorporates saliva composition. The simulations and experiments both showed greater deposition of bacteria within 1 m of the subject, and the potential for a substantial number of bacteria to remain airborne, with no clear difference in airborne concentration of small bioaerosols (<10 μm diameter) between 1 and 2 m. The agreement between the model and the experimental data for bacterial deposition directly in front of the subjects was encouraging given the uncertainties in model input parameters and the inherent variability within and between subjects. The ability to predict airborne microbial dispersion and deposition gives confidence in the ability to model the consequences of an exhalation and hence the airborne transmission of respiratory pathogens such as SARS‐CoV‐2. |
format | Online Article Text |
id | pubmed-9111502 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91115022022-05-17 Modeling and experimental study of dispersion and deposition of respiratory emissions with implications for disease transmission Coldrick, Simon Kelsey, Adrian Ivings, Matthew J. Foat, Timothy G. Parker, Simon T. Noakes, Catherine J. Bennett, Allan Rickard, Helen Moore, Ginny Indoor Air Original Articles The ability to model the dispersion of pathogens in exhaled breath is important for characterizing transmission of the SARS‐CoV‐2 virus and other respiratory pathogens. A Computational Fluid Dynamics (CFD) model of droplet and aerosol emission during exhalations has been developed and for the first time compared directly with experimental data for the dispersion of respiratory and oral bacteria from ten subjects coughing, speaking, and singing in a small unventilated room. The modeled exhalations consist of a warm, humid, gaseous carrier flow and droplets represented by a discrete Lagrangian particle phase which incorporates saliva composition. The simulations and experiments both showed greater deposition of bacteria within 1 m of the subject, and the potential for a substantial number of bacteria to remain airborne, with no clear difference in airborne concentration of small bioaerosols (<10 μm diameter) between 1 and 2 m. The agreement between the model and the experimental data for bacterial deposition directly in front of the subjects was encouraging given the uncertainties in model input parameters and the inherent variability within and between subjects. The ability to predict airborne microbial dispersion and deposition gives confidence in the ability to model the consequences of an exhalation and hence the airborne transmission of respiratory pathogens such as SARS‐CoV‐2. John Wiley and Sons Inc. 2022-02-21 2022-02 /pmc/articles/PMC9111502/ /pubmed/35225395 http://dx.doi.org/10.1111/ina.13000 Text en © 2022 Crown copyright. Indoor Air published by John Wiley & Sons Ltd. This article is published with the permission of the Controller of HMSO and the Queen's Printer for Scotland. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Original Articles Coldrick, Simon Kelsey, Adrian Ivings, Matthew J. Foat, Timothy G. Parker, Simon T. Noakes, Catherine J. Bennett, Allan Rickard, Helen Moore, Ginny Modeling and experimental study of dispersion and deposition of respiratory emissions with implications for disease transmission |
title | Modeling and experimental study of dispersion and deposition of respiratory emissions with implications for disease transmission |
title_full | Modeling and experimental study of dispersion and deposition of respiratory emissions with implications for disease transmission |
title_fullStr | Modeling and experimental study of dispersion and deposition of respiratory emissions with implications for disease transmission |
title_full_unstemmed | Modeling and experimental study of dispersion and deposition of respiratory emissions with implications for disease transmission |
title_short | Modeling and experimental study of dispersion and deposition of respiratory emissions with implications for disease transmission |
title_sort | modeling and experimental study of dispersion and deposition of respiratory emissions with implications for disease transmission |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9111502/ https://www.ncbi.nlm.nih.gov/pubmed/35225395 http://dx.doi.org/10.1111/ina.13000 |
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