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Fluid dynamics of COVID-19 airborne infection suggests urgent data for a scientific design of social distancing
The COVID-19 pandemic is largely caused by airborne transmission, a phenomenon that rapidly gained the attention of the scientific community. Social distancing is of paramount importance to limit the spread of the disease, but to design social distancing rules on a scientific basis the process of di...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7773744/ https://www.ncbi.nlm.nih.gov/pubmed/33380739 http://dx.doi.org/10.1038/s41598-020-80078-7 |
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author | Rosti, M. E. Olivieri, S. Cavaiola, M. Seminara, A. Mazzino, A. |
author_facet | Rosti, M. E. Olivieri, S. Cavaiola, M. Seminara, A. Mazzino, A. |
author_sort | Rosti, M. E. |
collection | PubMed |
description | The COVID-19 pandemic is largely caused by airborne transmission, a phenomenon that rapidly gained the attention of the scientific community. Social distancing is of paramount importance to limit the spread of the disease, but to design social distancing rules on a scientific basis the process of dispersal of virus-containing respiratory droplets must be understood. Here, we demonstrate that available knowledge is largely inadequate to make predictions on the reach of infectious droplets emitted during a cough and on their infectious potential. We follow the position and evaporation of thousands of respiratory droplets by massive state-of-the-art numerical simulations of the airflow caused by a typical cough. We find that different initial distributions of droplet size taken from literature and different ambient relative humidity lead to opposite conclusions: (1) most versus none of the viral content settles in the first 1–2 m; (2) viruses are carried entirely on dry nuclei versus on liquid droplets; (3) small droplets travel less than [Formula: see text] versus more than [Formula: see text] . We point to two key issues that need to be addressed urgently in order to provide a scientific foundation to social distancing rules: (I1) a careful characterisation of the initial distribution of droplet sizes; (I2) the infectious potential of viruses carried on dry nuclei versus liquid droplets. |
format | Online Article Text |
id | pubmed-7773744 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-77737442021-01-07 Fluid dynamics of COVID-19 airborne infection suggests urgent data for a scientific design of social distancing Rosti, M. E. Olivieri, S. Cavaiola, M. Seminara, A. Mazzino, A. Sci Rep Article The COVID-19 pandemic is largely caused by airborne transmission, a phenomenon that rapidly gained the attention of the scientific community. Social distancing is of paramount importance to limit the spread of the disease, but to design social distancing rules on a scientific basis the process of dispersal of virus-containing respiratory droplets must be understood. Here, we demonstrate that available knowledge is largely inadequate to make predictions on the reach of infectious droplets emitted during a cough and on their infectious potential. We follow the position and evaporation of thousands of respiratory droplets by massive state-of-the-art numerical simulations of the airflow caused by a typical cough. We find that different initial distributions of droplet size taken from literature and different ambient relative humidity lead to opposite conclusions: (1) most versus none of the viral content settles in the first 1–2 m; (2) viruses are carried entirely on dry nuclei versus on liquid droplets; (3) small droplets travel less than [Formula: see text] versus more than [Formula: see text] . We point to two key issues that need to be addressed urgently in order to provide a scientific foundation to social distancing rules: (I1) a careful characterisation of the initial distribution of droplet sizes; (I2) the infectious potential of viruses carried on dry nuclei versus liquid droplets. Nature Publishing Group UK 2020-12-30 /pmc/articles/PMC7773744/ /pubmed/33380739 http://dx.doi.org/10.1038/s41598-020-80078-7 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Rosti, M. E. Olivieri, S. Cavaiola, M. Seminara, A. Mazzino, A. Fluid dynamics of COVID-19 airborne infection suggests urgent data for a scientific design of social distancing |
title | Fluid dynamics of COVID-19 airborne infection suggests urgent data for a scientific design of social distancing |
title_full | Fluid dynamics of COVID-19 airborne infection suggests urgent data for a scientific design of social distancing |
title_fullStr | Fluid dynamics of COVID-19 airborne infection suggests urgent data for a scientific design of social distancing |
title_full_unstemmed | Fluid dynamics of COVID-19 airborne infection suggests urgent data for a scientific design of social distancing |
title_short | Fluid dynamics of COVID-19 airborne infection suggests urgent data for a scientific design of social distancing |
title_sort | fluid dynamics of covid-19 airborne infection suggests urgent data for a scientific design of social distancing |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7773744/ https://www.ncbi.nlm.nih.gov/pubmed/33380739 http://dx.doi.org/10.1038/s41598-020-80078-7 |
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