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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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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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. |
format | Online Article Text |
id | pubmed-10034446 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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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