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Influence of transportation network on transmission heterogeneity of COVID-19 in China
In this paper, we propose a novel approach to model spatial heterogeneity for epidemic spreading, which combines the relevance of transport proximity in human movement and the excellent estimation accuracy of deep neural network. We apply this model to investigate the effects of various transportati...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8169317/ https://www.ncbi.nlm.nih.gov/pubmed/34092940 http://dx.doi.org/10.1016/j.trc.2021.103231 |
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author | Lu, Jing Lin, Anrong Jiang, Changmin Zhang, Anming Yang, Zhongzhen |
author_facet | Lu, Jing Lin, Anrong Jiang, Changmin Zhang, Anming Yang, Zhongzhen |
author_sort | Lu, Jing |
collection | PubMed |
description | In this paper, we propose a novel approach to model spatial heterogeneity for epidemic spreading, which combines the relevance of transport proximity in human movement and the excellent estimation accuracy of deep neural network. We apply this model to investigate the effects of various transportation networks on the heterogeneous propagation of COVID-19 in China. We further apply it to predict the development of COVID-19 in China in two scenarios, i.e., i) assuming that different types of traffic restriction policies are conducted and ii) assuming that the epicenter of the COVID-19 outbreak is in Beijing, so as to illustrate the potential usage of the model in generating various policy insights to help the containment of the further spread of COVID-19. We find that the most effective way to prevent the coronavirus from spreading quickly and extensively is to control the routes linked to the epicenter at the beginning of the pandemic. But if the virus has been widely spread, setting restrictions on hub cities would be much more efficient than imposing the same travel ban across the whole country. We also show that a comprehensive consideration of the epicenter location is necessary for disease control. |
format | Online Article Text |
id | pubmed-8169317 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-81693172021-06-02 Influence of transportation network on transmission heterogeneity of COVID-19 in China Lu, Jing Lin, Anrong Jiang, Changmin Zhang, Anming Yang, Zhongzhen Transp Res Part C Emerg Technol Article In this paper, we propose a novel approach to model spatial heterogeneity for epidemic spreading, which combines the relevance of transport proximity in human movement and the excellent estimation accuracy of deep neural network. We apply this model to investigate the effects of various transportation networks on the heterogeneous propagation of COVID-19 in China. We further apply it to predict the development of COVID-19 in China in two scenarios, i.e., i) assuming that different types of traffic restriction policies are conducted and ii) assuming that the epicenter of the COVID-19 outbreak is in Beijing, so as to illustrate the potential usage of the model in generating various policy insights to help the containment of the further spread of COVID-19. We find that the most effective way to prevent the coronavirus from spreading quickly and extensively is to control the routes linked to the epicenter at the beginning of the pandemic. But if the virus has been widely spread, setting restrictions on hub cities would be much more efficient than imposing the same travel ban across the whole country. We also show that a comprehensive consideration of the epicenter location is necessary for disease control. Elsevier Ltd. 2021-08 2021-06-02 /pmc/articles/PMC8169317/ /pubmed/34092940 http://dx.doi.org/10.1016/j.trc.2021.103231 Text en © 2021 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 Lu, Jing Lin, Anrong Jiang, Changmin Zhang, Anming Yang, Zhongzhen Influence of transportation network on transmission heterogeneity of COVID-19 in China |
title | Influence of transportation network on transmission heterogeneity of COVID-19 in China |
title_full | Influence of transportation network on transmission heterogeneity of COVID-19 in China |
title_fullStr | Influence of transportation network on transmission heterogeneity of COVID-19 in China |
title_full_unstemmed | Influence of transportation network on transmission heterogeneity of COVID-19 in China |
title_short | Influence of transportation network on transmission heterogeneity of COVID-19 in China |
title_sort | influence of transportation network on transmission heterogeneity of covid-19 in china |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8169317/ https://www.ncbi.nlm.nih.gov/pubmed/34092940 http://dx.doi.org/10.1016/j.trc.2021.103231 |
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