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Dynamic model of respiratory infectious disease transmission in urban public transportation systems

During the epidemics of respiratory infectious diseases, the use of public transportation increases the risk of disease transmission. Therefore, we established a dynamic model to provide an in-depth understanding of the mechanism of epidemic spread via this route. We designed a computer program to m...

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Autores principales: Guo, Zuiyuan, Xiao, Guangquan, Wang, Yayu, Li, Sidong, Du, Jianhong, Dai, Botao, Gong, Lili, Xiao, Dan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10034446/
https://www.ncbi.nlm.nih.gov/pubmed/36967891
http://dx.doi.org/10.1016/j.heliyon.2023.e14500
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author Guo, Zuiyuan
Xiao, Guangquan
Wang, Yayu
Li, Sidong
Du, Jianhong
Dai, Botao
Gong, Lili
Xiao, Dan
author_facet Guo, Zuiyuan
Xiao, Guangquan
Wang, Yayu
Li, Sidong
Du, Jianhong
Dai, Botao
Gong, Lili
Xiao, Dan
author_sort Guo, Zuiyuan
collection PubMed
description During the epidemics of respiratory infectious diseases, the use of public transportation increases the risk of disease transmission. Therefore, we established a dynamic model to provide an in-depth understanding of the mechanism of epidemic spread via this route. We designed a computer program to model a rail transit system including four transit lines in a small town in which assumed 70% of the residents commute via these trams in weekdays and the remaining residents take the tram at random. The model could identify the best travel route for each passenger and the specific passengers onboard when the tram passed through each station, and simulate the dynamic spread of a respiratory pathogen as the passengers used the rail transit system. Based on the program operating, we estimated that all residents in the town were ultimately infected, including 86.6% who were infected due to the public transportation system. The remaining individuals were infected at home. As the infection rate increased, the number of infected individuals increased more rapidly. Reducing the frequency of trams, driving private cars or riding bicycles, showing nucleic acid certificates and wearing masks for passengers, etc., are effective measures for the prevention of the spread of epidemic diseases.
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spelling pubmed-100344462023-03-24 Dynamic model of respiratory infectious disease transmission in urban public transportation systems Guo, Zuiyuan Xiao, Guangquan Wang, Yayu Li, Sidong Du, Jianhong Dai, Botao Gong, Lili Xiao, Dan Heliyon Research Article During the epidemics of respiratory infectious diseases, the use of public transportation increases the risk of disease transmission. Therefore, we established a dynamic model to provide an in-depth understanding of the mechanism of epidemic spread via this route. We designed a computer program to model a rail transit system including four transit lines in a small town in which assumed 70% of the residents commute via these trams in weekdays and the remaining residents take the tram at random. The model could identify the best travel route for each passenger and the specific passengers onboard when the tram passed through each station, and simulate the dynamic spread of a respiratory pathogen as the passengers used the rail transit system. Based on the program operating, we estimated that all residents in the town were ultimately infected, including 86.6% who were infected due to the public transportation system. The remaining individuals were infected at home. As the infection rate increased, the number of infected individuals increased more rapidly. Reducing the frequency of trams, driving private cars or riding bicycles, showing nucleic acid certificates and wearing masks for passengers, etc., are effective measures for the prevention of the spread of epidemic diseases. Elsevier 2023-03-11 /pmc/articles/PMC10034446/ /pubmed/36967891 http://dx.doi.org/10.1016/j.heliyon.2023.e14500 Text en © 2023 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Research Article
Guo, Zuiyuan
Xiao, Guangquan
Wang, Yayu
Li, Sidong
Du, Jianhong
Dai, Botao
Gong, Lili
Xiao, Dan
Dynamic model of respiratory infectious disease transmission in urban public transportation systems
title Dynamic model of respiratory infectious disease transmission in urban public transportation systems
title_full Dynamic model of respiratory infectious disease transmission in urban public transportation systems
title_fullStr Dynamic model of respiratory infectious disease transmission in urban public transportation systems
title_full_unstemmed Dynamic model of respiratory infectious disease transmission in urban public transportation systems
title_short Dynamic model of respiratory infectious disease transmission in urban public transportation systems
title_sort dynamic model of respiratory infectious disease transmission in urban public transportation systems
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10034446/
https://www.ncbi.nlm.nih.gov/pubmed/36967891
http://dx.doi.org/10.1016/j.heliyon.2023.e14500
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