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Prediction of respiratory droplets evolution for safer academic facilities planning amid COVID-19 and future pandemics: A numerical approach
Airborne dispersion of the novel SARS-CoV-2 through the droplets produced during expiratory activities is one of the main transmission mechanisms of this virus from one person to another. Understanding how these droplets spread when infected humans with COVID-19 or other airborne infectious diseases...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9107331/ http://dx.doi.org/10.1016/j.jobe.2022.104593 |
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author | Quiñones, Jhon J. Doosttalab, Ali Sokolowski, Steven Voyles, Richard M. Castaño, Victor Zhang, Lucy T. Castillo, Luciano |
author_facet | Quiñones, Jhon J. Doosttalab, Ali Sokolowski, Steven Voyles, Richard M. Castaño, Victor Zhang, Lucy T. Castillo, Luciano |
author_sort | Quiñones, Jhon J. |
collection | PubMed |
description | Airborne dispersion of the novel SARS-CoV-2 through the droplets produced during expiratory activities is one of the main transmission mechanisms of this virus from one person to another. Understanding how these droplets spread when infected humans with COVID-19 or other airborne infectious diseases breathe, cough or sneeze is essential for improving prevention strategies in academic facilities. This work aims to assess the transport and fate of droplets in indoor environments using Computational Fluid Dynamics (CFD). This study employs unsteady Reynolds-Averaged Navier-Stokes (URANS) simulations with the Euler-Lagrange approach to visualize the location of thousands of droplets released in a respiratory event and their size evolution. Furthermore, we assess the dispersion of coughing, sneezing, and breathing saliva droplets from an infected source in a classroom with air conditioning and multiple occupants. The results indicate that the suggested social distancing protocol is not enough to avoid the transmission of COVID-19 since small saliva droplets ( ≤ 12 μm) can travel in the streamwise direction up to 4 m when an infected person coughs and more than 7 m when sneezes. These droplets can reach those distances even when there is no airflow from the wind or ventilation systems. The number of airborne droplets in locations close to the respiratory system of a healthy person increases when the relative humidity of the indoor environment is low. This work sets an accurate, rapid, and validated numerical framework reproducible for various indoor environments integrating qualitative and quantitative data analysis of the droplet size evolution of respiratory events for a safer design of physical distancing standards and air cleaning technologies. |
format | Online Article Text |
id | pubmed-9107331 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91073312022-05-16 Prediction of respiratory droplets evolution for safer academic facilities planning amid COVID-19 and future pandemics: A numerical approach Quiñones, Jhon J. Doosttalab, Ali Sokolowski, Steven Voyles, Richard M. Castaño, Victor Zhang, Lucy T. Castillo, Luciano Journal of Building Engineering Article Airborne dispersion of the novel SARS-CoV-2 through the droplets produced during expiratory activities is one of the main transmission mechanisms of this virus from one person to another. Understanding how these droplets spread when infected humans with COVID-19 or other airborne infectious diseases breathe, cough or sneeze is essential for improving prevention strategies in academic facilities. This work aims to assess the transport and fate of droplets in indoor environments using Computational Fluid Dynamics (CFD). This study employs unsteady Reynolds-Averaged Navier-Stokes (URANS) simulations with the Euler-Lagrange approach to visualize the location of thousands of droplets released in a respiratory event and their size evolution. Furthermore, we assess the dispersion of coughing, sneezing, and breathing saliva droplets from an infected source in a classroom with air conditioning and multiple occupants. The results indicate that the suggested social distancing protocol is not enough to avoid the transmission of COVID-19 since small saliva droplets ( ≤ 12 μm) can travel in the streamwise direction up to 4 m when an infected person coughs and more than 7 m when sneezes. These droplets can reach those distances even when there is no airflow from the wind or ventilation systems. The number of airborne droplets in locations close to the respiratory system of a healthy person increases when the relative humidity of the indoor environment is low. This work sets an accurate, rapid, and validated numerical framework reproducible for various indoor environments integrating qualitative and quantitative data analysis of the droplet size evolution of respiratory events for a safer design of physical distancing standards and air cleaning technologies. Elsevier Ltd. 2022-08-15 2022-05-14 /pmc/articles/PMC9107331/ http://dx.doi.org/10.1016/j.jobe.2022.104593 Text en © 2022 Elsevier Ltd. All rights reserved. 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 Quiñones, Jhon J. Doosttalab, Ali Sokolowski, Steven Voyles, Richard M. Castaño, Victor Zhang, Lucy T. Castillo, Luciano Prediction of respiratory droplets evolution for safer academic facilities planning amid COVID-19 and future pandemics: A numerical approach |
title | Prediction of respiratory droplets evolution for safer academic facilities planning amid COVID-19 and future pandemics: A numerical approach |
title_full | Prediction of respiratory droplets evolution for safer academic facilities planning amid COVID-19 and future pandemics: A numerical approach |
title_fullStr | Prediction of respiratory droplets evolution for safer academic facilities planning amid COVID-19 and future pandemics: A numerical approach |
title_full_unstemmed | Prediction of respiratory droplets evolution for safer academic facilities planning amid COVID-19 and future pandemics: A numerical approach |
title_short | Prediction of respiratory droplets evolution for safer academic facilities planning amid COVID-19 and future pandemics: A numerical approach |
title_sort | prediction of respiratory droplets evolution for safer academic facilities planning amid covid-19 and future pandemics: a numerical approach |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9107331/ http://dx.doi.org/10.1016/j.jobe.2022.104593 |
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