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Assessing regional risk of COVID-19 infection from Wuhan via high-speed rail

This paper demonstrates that transportation networks may be used to assess and predict the regional risk of COVID-19 infection from the outbreak. We use China's high-speed rail (HSR) network at the scale of prefecture level to assess, based on a probabilistic risk model, the risk of COVID-19 in...

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Autores principales: Li, Tao, Rong, Lili, Zhang, Anming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8043780/
https://www.ncbi.nlm.nih.gov/pubmed/33867701
http://dx.doi.org/10.1016/j.tranpol.2021.04.009
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author Li, Tao
Rong, Lili
Zhang, Anming
author_facet Li, Tao
Rong, Lili
Zhang, Anming
author_sort Li, Tao
collection PubMed
description This paper demonstrates that transportation networks may be used to assess and predict the regional risk of COVID-19 infection from the outbreak. We use China's high-speed rail (HSR) network at the scale of prefecture level to assess, based on a probabilistic risk model, the risk of COVID-19 infection from Wuhan to the country's 31 province-level regions at the early stage of domestic spread. We find that the high-risk regions are mainly distributed along the southern half of Beijing-Hong Kong HSR line, where a large number of infection cases have been confirmed at the early stage. Furthermore, the two components of the infection risk, namely, the probability (proxied by the region's correlation with Wuhan through HSR) and the impact (proxied by the region's population with mobility), can play different roles in the risk ranking for different regions. For public health administrators, these findings may be used for better decision making, including the preparation of emergency plans and supplies, and the allocation of limited resources, before the extensive spread of the epidemic. Moreover, the administrators should adopt different intervention measures for different regions, so as to better mitigate the epidemic spread according to their own risk scenarios with respect to the probability of occurring and, once occurred, the impact.
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spelling pubmed-80437802021-04-14 Assessing regional risk of COVID-19 infection from Wuhan via high-speed rail Li, Tao Rong, Lili Zhang, Anming Transp Policy (Oxf) Article This paper demonstrates that transportation networks may be used to assess and predict the regional risk of COVID-19 infection from the outbreak. We use China's high-speed rail (HSR) network at the scale of prefecture level to assess, based on a probabilistic risk model, the risk of COVID-19 infection from Wuhan to the country's 31 province-level regions at the early stage of domestic spread. We find that the high-risk regions are mainly distributed along the southern half of Beijing-Hong Kong HSR line, where a large number of infection cases have been confirmed at the early stage. Furthermore, the two components of the infection risk, namely, the probability (proxied by the region's correlation with Wuhan through HSR) and the impact (proxied by the region's population with mobility), can play different roles in the risk ranking for different regions. For public health administrators, these findings may be used for better decision making, including the preparation of emergency plans and supplies, and the allocation of limited resources, before the extensive spread of the epidemic. Moreover, the administrators should adopt different intervention measures for different regions, so as to better mitigate the epidemic spread according to their own risk scenarios with respect to the probability of occurring and, once occurred, the impact. Elsevier Ltd. 2021-06 2021-04-14 /pmc/articles/PMC8043780/ /pubmed/33867701 http://dx.doi.org/10.1016/j.tranpol.2021.04.009 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
Li, Tao
Rong, Lili
Zhang, Anming
Assessing regional risk of COVID-19 infection from Wuhan via high-speed rail
title Assessing regional risk of COVID-19 infection from Wuhan via high-speed rail
title_full Assessing regional risk of COVID-19 infection from Wuhan via high-speed rail
title_fullStr Assessing regional risk of COVID-19 infection from Wuhan via high-speed rail
title_full_unstemmed Assessing regional risk of COVID-19 infection from Wuhan via high-speed rail
title_short Assessing regional risk of COVID-19 infection from Wuhan via high-speed rail
title_sort assessing regional risk of covid-19 infection from wuhan via high-speed rail
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8043780/
https://www.ncbi.nlm.nih.gov/pubmed/33867701
http://dx.doi.org/10.1016/j.tranpol.2021.04.009
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