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Relating quanta conservation and compartmental epidemiological models of airborne disease outbreaks in buildings
We investigate the underlying assumptions and limits of applicability of several documented models for outbreaks of airborne disease inside buildings by showing how they may each be regarded as special cases of a system of equations which combines quanta conservation and compartmental epidemiologica...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10575980/ https://www.ncbi.nlm.nih.gov/pubmed/37833394 http://dx.doi.org/10.1038/s41598-023-44527-3 |
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author | Wood, Samuel G. A. Craske, John Burridge, Henry C. |
author_facet | Wood, Samuel G. A. Craske, John Burridge, Henry C. |
author_sort | Wood, Samuel G. A. |
collection | PubMed |
description | We investigate the underlying assumptions and limits of applicability of several documented models for outbreaks of airborne disease inside buildings by showing how they may each be regarded as special cases of a system of equations which combines quanta conservation and compartmental epidemiological modelling. We investigate the behaviour of this system analytically, gaining insight to its behaviour at large time. We then investigate the characteristic timescales of an indoor outbreak, showing how the dilution rate of the space, and the quanta generation rate, incubation rate and removal rate associated with the illness may be used to predict the evolution of an outbreak over time, and may also be used to predict the relative performances of other indoor airborne outbreak models. The model is compared to a more commonly used model, in which it is assumed the environmental concentration of infectious aerosols adheres to a quasi-steady-state, so that the the dimensionless quanta concentration is equal to the the infectious fraction. The model presented here is shown to approach this limit exponentially to within an interval defined by the incubation and removal rates. This may be used to predict the maximum extent to which a case will deviate from the quasi steady state condition. |
format | Online Article Text |
id | pubmed-10575980 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-105759802023-10-15 Relating quanta conservation and compartmental epidemiological models of airborne disease outbreaks in buildings Wood, Samuel G. A. Craske, John Burridge, Henry C. Sci Rep Article We investigate the underlying assumptions and limits of applicability of several documented models for outbreaks of airborne disease inside buildings by showing how they may each be regarded as special cases of a system of equations which combines quanta conservation and compartmental epidemiological modelling. We investigate the behaviour of this system analytically, gaining insight to its behaviour at large time. We then investigate the characteristic timescales of an indoor outbreak, showing how the dilution rate of the space, and the quanta generation rate, incubation rate and removal rate associated with the illness may be used to predict the evolution of an outbreak over time, and may also be used to predict the relative performances of other indoor airborne outbreak models. The model is compared to a more commonly used model, in which it is assumed the environmental concentration of infectious aerosols adheres to a quasi-steady-state, so that the the dimensionless quanta concentration is equal to the the infectious fraction. The model presented here is shown to approach this limit exponentially to within an interval defined by the incubation and removal rates. This may be used to predict the maximum extent to which a case will deviate from the quasi steady state condition. Nature Publishing Group UK 2023-10-13 /pmc/articles/PMC10575980/ /pubmed/37833394 http://dx.doi.org/10.1038/s41598-023-44527-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Wood, Samuel G. A. Craske, John Burridge, Henry C. Relating quanta conservation and compartmental epidemiological models of airborne disease outbreaks in buildings |
title | Relating quanta conservation and compartmental epidemiological models of airborne disease outbreaks in buildings |
title_full | Relating quanta conservation and compartmental epidemiological models of airborne disease outbreaks in buildings |
title_fullStr | Relating quanta conservation and compartmental epidemiological models of airborne disease outbreaks in buildings |
title_full_unstemmed | Relating quanta conservation and compartmental epidemiological models of airborne disease outbreaks in buildings |
title_short | Relating quanta conservation and compartmental epidemiological models of airborne disease outbreaks in buildings |
title_sort | relating quanta conservation and compartmental epidemiological models of airborne disease outbreaks in buildings |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10575980/ https://www.ncbi.nlm.nih.gov/pubmed/37833394 http://dx.doi.org/10.1038/s41598-023-44527-3 |
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