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A computational framework for transmission risk assessment of aerosolized particles in classrooms
Infectious airborne diseases like the recent COVID-19 pandemic render confined spaces high-risk areas. However, in-person activities like teaching in classroom settings and government services are often expected to continue or restart quickly. It becomes important to evaluate the risk of airborne di...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer London
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9884603/ https://www.ncbi.nlm.nih.gov/pubmed/36742376 http://dx.doi.org/10.1007/s00366-022-01773-9 |
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author | Tan, Kendrick Gao, Boshun Yang, Cheng-Hau Johnson, Emily L. Hsu, Ming-Chen Passalacqua, Alberto Krishnamurthy, Adarsh Ganapathysubramanian, Baskar |
author_facet | Tan, Kendrick Gao, Boshun Yang, Cheng-Hau Johnson, Emily L. Hsu, Ming-Chen Passalacqua, Alberto Krishnamurthy, Adarsh Ganapathysubramanian, Baskar |
author_sort | Tan, Kendrick |
collection | PubMed |
description | Infectious airborne diseases like the recent COVID-19 pandemic render confined spaces high-risk areas. However, in-person activities like teaching in classroom settings and government services are often expected to continue or restart quickly. It becomes important to evaluate the risk of airborne disease transmission while accounting for the physical presence of humans, furniture, and electronic equipment, as well as ventilation. Here, we present a computational framework and study based on detailed flow physics simulations that allow straightforward evaluation of various seating and operating scenarios to identify risk factors and assess the effectiveness of various mitigation strategies. These scenarios include seating arrangement changes, presence/absence of computer screens, ventilation rate changes, and presence/absence of mask-wearing. This approach democratizes risk assessment by automating a key bottleneck in simulation-based analysis—creating an adequately refined mesh around multiple complex geometries. Not surprisingly, we find that wearing masks (with at least 74% inward protection efficiency) significantly reduced transmission risk against unmasked and infected individuals. While the use of face masks is known to reduce the risk of transmission, we perform a systematic computational study of the transmission risk due to variations in room occupancy, seating layout and air change rates. In addition, our findings on the efficacy of face masks further support use of face masks. The availability of such an analysis approach will allow education administrators, government officials (courthouses, police stations), and hospital administrators to make informed decisions on seating arrangements and operating procedures. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00366-022-01773-9. |
format | Online Article Text |
id | pubmed-9884603 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer London |
record_format | MEDLINE/PubMed |
spelling | pubmed-98846032023-01-30 A computational framework for transmission risk assessment of aerosolized particles in classrooms Tan, Kendrick Gao, Boshun Yang, Cheng-Hau Johnson, Emily L. Hsu, Ming-Chen Passalacqua, Alberto Krishnamurthy, Adarsh Ganapathysubramanian, Baskar Eng Comput Original Article Infectious airborne diseases like the recent COVID-19 pandemic render confined spaces high-risk areas. However, in-person activities like teaching in classroom settings and government services are often expected to continue or restart quickly. It becomes important to evaluate the risk of airborne disease transmission while accounting for the physical presence of humans, furniture, and electronic equipment, as well as ventilation. Here, we present a computational framework and study based on detailed flow physics simulations that allow straightforward evaluation of various seating and operating scenarios to identify risk factors and assess the effectiveness of various mitigation strategies. These scenarios include seating arrangement changes, presence/absence of computer screens, ventilation rate changes, and presence/absence of mask-wearing. This approach democratizes risk assessment by automating a key bottleneck in simulation-based analysis—creating an adequately refined mesh around multiple complex geometries. Not surprisingly, we find that wearing masks (with at least 74% inward protection efficiency) significantly reduced transmission risk against unmasked and infected individuals. While the use of face masks is known to reduce the risk of transmission, we perform a systematic computational study of the transmission risk due to variations in room occupancy, seating layout and air change rates. In addition, our findings on the efficacy of face masks further support use of face masks. The availability of such an analysis approach will allow education administrators, government officials (courthouses, police stations), and hospital administrators to make informed decisions on seating arrangements and operating procedures. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00366-022-01773-9. Springer London 2023-01-30 /pmc/articles/PMC9884603/ /pubmed/36742376 http://dx.doi.org/10.1007/s00366-022-01773-9 Text en © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Article Tan, Kendrick Gao, Boshun Yang, Cheng-Hau Johnson, Emily L. Hsu, Ming-Chen Passalacqua, Alberto Krishnamurthy, Adarsh Ganapathysubramanian, Baskar A computational framework for transmission risk assessment of aerosolized particles in classrooms |
title | A computational framework for transmission risk assessment of aerosolized particles in classrooms |
title_full | A computational framework for transmission risk assessment of aerosolized particles in classrooms |
title_fullStr | A computational framework for transmission risk assessment of aerosolized particles in classrooms |
title_full_unstemmed | A computational framework for transmission risk assessment of aerosolized particles in classrooms |
title_short | A computational framework for transmission risk assessment of aerosolized particles in classrooms |
title_sort | computational framework for transmission risk assessment of aerosolized particles in classrooms |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9884603/ https://www.ncbi.nlm.nih.gov/pubmed/36742376 http://dx.doi.org/10.1007/s00366-022-01773-9 |
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