Spatiotemporal transmission of infectious particles in environment: A case study of Covid-19

This study explores the dynamic transmission of infectious particles due to COVID-19 in the environment using a spatiotemporal epidemiological approach. We proposed a novel multi-agent model to simulate the spread of COVID-19 by considering several influencing factors. The model divides the populati...

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Autores principales: Karimian, Hamed, Fan, Qin, Li, Qun, Chen, Youliang, Shi, Juan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10224719/
https://www.ncbi.nlm.nih.gov/pubmed/37247670
http://dx.doi.org/10.1016/j.chemosphere.2023.139065
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author Karimian, Hamed
Fan, Qin
Li, Qun
Chen, Youliang
Shi, Juan
author_facet Karimian, Hamed
Fan, Qin
Li, Qun
Chen, Youliang
Shi, Juan
author_sort Karimian, Hamed
collection PubMed
description This study explores the dynamic transmission of infectious particles due to COVID-19 in the environment using a spatiotemporal epidemiological approach. We proposed a novel multi-agent model to simulate the spread of COVID-19 by considering several influencing factors. The model divides the population into susceptible and infected and analyzes the impact of different prevention and control measures, such as limiting the number of people and wearing masks on the spread of COVID-19. The findings suggest that reducing population density and wearing masks can significantly reduce the likelihood of virus transmission. Specifically, the research shows that if the population moves within a fixed range, almost everyone will eventually be infected within 1 h. When the population density is 50%, the infection rate is as high as 96%. If everyone does not wear a mask, nearly 72.33% of the people will be infected after 1 h. However, when people wear masks, the infection rate is consistently lower than when they do not wear masks. Even if only 25% of people wear masks, the infection rate with masks is 27.67% lower than without masks, which is strong evidence of the importance of wearing a mask. As people's daily activities are mostly carried out indoors, and many super-spreading events of the new crown epidemic also originated from indoor gatherings, the research on indoor epidemic prevention and control is essential. This study provides decision-making support for epidemic preventions and controls and the proposed methodology can be used in other regions and future epidemics.
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spelling pubmed-102247192023-05-30 Spatiotemporal transmission of infectious particles in environment: A case study of Covid-19 Karimian, Hamed Fan, Qin Li, Qun Chen, Youliang Shi, Juan Chemosphere Article This study explores the dynamic transmission of infectious particles due to COVID-19 in the environment using a spatiotemporal epidemiological approach. We proposed a novel multi-agent model to simulate the spread of COVID-19 by considering several influencing factors. The model divides the population into susceptible and infected and analyzes the impact of different prevention and control measures, such as limiting the number of people and wearing masks on the spread of COVID-19. The findings suggest that reducing population density and wearing masks can significantly reduce the likelihood of virus transmission. Specifically, the research shows that if the population moves within a fixed range, almost everyone will eventually be infected within 1 h. When the population density is 50%, the infection rate is as high as 96%. If everyone does not wear a mask, nearly 72.33% of the people will be infected after 1 h. However, when people wear masks, the infection rate is consistently lower than when they do not wear masks. Even if only 25% of people wear masks, the infection rate with masks is 27.67% lower than without masks, which is strong evidence of the importance of wearing a mask. As people's daily activities are mostly carried out indoors, and many super-spreading events of the new crown epidemic also originated from indoor gatherings, the research on indoor epidemic prevention and control is essential. This study provides decision-making support for epidemic preventions and controls and the proposed methodology can be used in other regions and future epidemics. Elsevier Ltd. 2023-09 2023-05-27 /pmc/articles/PMC10224719/ /pubmed/37247670 http://dx.doi.org/10.1016/j.chemosphere.2023.139065 Text en © 2023 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
Karimian, Hamed
Fan, Qin
Li, Qun
Chen, Youliang
Shi, Juan
Spatiotemporal transmission of infectious particles in environment: A case study of Covid-19
title Spatiotemporal transmission of infectious particles in environment: A case study of Covid-19
title_full Spatiotemporal transmission of infectious particles in environment: A case study of Covid-19
title_fullStr Spatiotemporal transmission of infectious particles in environment: A case study of Covid-19
title_full_unstemmed Spatiotemporal transmission of infectious particles in environment: A case study of Covid-19
title_short Spatiotemporal transmission of infectious particles in environment: A case study of Covid-19
title_sort spatiotemporal transmission of infectious particles in environment: a case study of covid-19
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10224719/
https://www.ncbi.nlm.nih.gov/pubmed/37247670
http://dx.doi.org/10.1016/j.chemosphere.2023.139065
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