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Zonal modeling of air distribution impact on the long-range airborne transmission risk of SARS-CoV-2
A widely used analytical model to quantitatively assess airborne infection risk is the Wells-Riley model which is limited to complete air mixing in a single zone. However, this assumption tends not to be feasible (or reality) for many situations. This study aimed to extend the Wells-Riley model so t...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Author(s). Published by Elsevier Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9420246/ https://www.ncbi.nlm.nih.gov/pubmed/36060304 http://dx.doi.org/10.1016/j.apm.2022.08.027 |
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author | Aganovic, Amar Cao, Guangyu Kurnitski, Jarek Melikov, Arsen Wargocki, Pawel |
author_facet | Aganovic, Amar Cao, Guangyu Kurnitski, Jarek Melikov, Arsen Wargocki, Pawel |
author_sort | Aganovic, Amar |
collection | PubMed |
description | A widely used analytical model to quantitatively assess airborne infection risk is the Wells-Riley model which is limited to complete air mixing in a single zone. However, this assumption tends not to be feasible (or reality) for many situations. This study aimed to extend the Wells-Riley model so that the infection risk can be calculated in spaces where complete mixing is not present. Some more advanced ventilation concepts create either two horizontally divided air zones in spaces as displacement ventilation or the space may be divided into two vertical zones by downward plane jet as in protective-zone ventilation systems. This is done by evaluating the time-dependent distribution of infectious quanta in each zone and by solving the coupled system of differential equations based on the zonal quanta concentrations. This model introduces a novel approach by estimating the interzonal mixing factor based on previous experimental data for three types of ventilation systems: incomplete mixing ventilation, displacement ventilation, and protective zone ventilation. The modeling approach is applied to a room with one infected and one susceptible person present. The results show that using the Wells-Riley model based on the assumption of completely air mixing may considerably overestimate or underestimate the long-range airborne infection risk in rooms where air distribution is different than complete mixing, such as displacement ventilation, protected zone ventilation, warm air supplied from the ceiling, etc. Therefore, in spaces with non-uniform air distribution, a zonal modeling approach should be preferred in analytical models compared to the conventional single-zone Wells-Riley models when assessing long-range airborne transmission risk of infectious respiratory diseases. |
format | Online Article Text |
id | pubmed-9420246 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | The Author(s). Published by Elsevier Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94202462022-08-30 Zonal modeling of air distribution impact on the long-range airborne transmission risk of SARS-CoV-2 Aganovic, Amar Cao, Guangyu Kurnitski, Jarek Melikov, Arsen Wargocki, Pawel Appl Math Model Article A widely used analytical model to quantitatively assess airborne infection risk is the Wells-Riley model which is limited to complete air mixing in a single zone. However, this assumption tends not to be feasible (or reality) for many situations. This study aimed to extend the Wells-Riley model so that the infection risk can be calculated in spaces where complete mixing is not present. Some more advanced ventilation concepts create either two horizontally divided air zones in spaces as displacement ventilation or the space may be divided into two vertical zones by downward plane jet as in protective-zone ventilation systems. This is done by evaluating the time-dependent distribution of infectious quanta in each zone and by solving the coupled system of differential equations based on the zonal quanta concentrations. This model introduces a novel approach by estimating the interzonal mixing factor based on previous experimental data for three types of ventilation systems: incomplete mixing ventilation, displacement ventilation, and protective zone ventilation. The modeling approach is applied to a room with one infected and one susceptible person present. The results show that using the Wells-Riley model based on the assumption of completely air mixing may considerably overestimate or underestimate the long-range airborne infection risk in rooms where air distribution is different than complete mixing, such as displacement ventilation, protected zone ventilation, warm air supplied from the ceiling, etc. Therefore, in spaces with non-uniform air distribution, a zonal modeling approach should be preferred in analytical models compared to the conventional single-zone Wells-Riley models when assessing long-range airborne transmission risk of infectious respiratory diseases. The Author(s). Published by Elsevier Inc. 2022-12 2022-08-28 /pmc/articles/PMC9420246/ /pubmed/36060304 http://dx.doi.org/10.1016/j.apm.2022.08.027 Text en © 2022 The Author(s). Published by Elsevier Inc. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Aganovic, Amar Cao, Guangyu Kurnitski, Jarek Melikov, Arsen Wargocki, Pawel Zonal modeling of air distribution impact on the long-range airborne transmission risk of SARS-CoV-2 |
title | Zonal modeling of air distribution impact on the long-range airborne transmission risk of SARS-CoV-2 |
title_full | Zonal modeling of air distribution impact on the long-range airborne transmission risk of SARS-CoV-2 |
title_fullStr | Zonal modeling of air distribution impact on the long-range airborne transmission risk of SARS-CoV-2 |
title_full_unstemmed | Zonal modeling of air distribution impact on the long-range airborne transmission risk of SARS-CoV-2 |
title_short | Zonal modeling of air distribution impact on the long-range airborne transmission risk of SARS-CoV-2 |
title_sort | zonal modeling of air distribution impact on the long-range airborne transmission risk of sars-cov-2 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9420246/ https://www.ncbi.nlm.nih.gov/pubmed/36060304 http://dx.doi.org/10.1016/j.apm.2022.08.027 |
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