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Integrated travel network model for studying epidemics: Interplay between journeys and epidemic
The ease of travelling between cities has contributed much to globalization. Yet, it poses a threat on epidemic outbreaks. It is of great importance for network science and health control to understand the impact of frequent journeys on epidemics. We stress that a new framework of modelling that tak...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4466778/ https://www.ncbi.nlm.nih.gov/pubmed/26073191 http://dx.doi.org/10.1038/srep11401 |
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author | Ruan, Zhongyuan Wang, Chaoqing Ming Hui, Pak Liu, Zonghua |
author_facet | Ruan, Zhongyuan Wang, Chaoqing Ming Hui, Pak Liu, Zonghua |
author_sort | Ruan, Zhongyuan |
collection | PubMed |
description | The ease of travelling between cities has contributed much to globalization. Yet, it poses a threat on epidemic outbreaks. It is of great importance for network science and health control to understand the impact of frequent journeys on epidemics. We stress that a new framework of modelling that takes a traveller’s viewpoint is needed. Such integrated travel network (ITN) model should incorporate the diversity among links as dictated by the distances between cities and different speeds of different modes of transportation, diversity among nodes as dictated by the population and the ease of travelling due to infrastructures and economic development of a city, and round-trip journeys to targeted destinations via the paths of shortest travel times typical of human journeys. An example is constructed for 116 cities in China with populations over one million that are connected by high-speed train services and highways. Epidemic spread on the constructed network is studied. It is revealed both numerically and theoretically that the traveling speed and frequency are important factors of epidemic spreading. Depending on the infection rate, increasing the traveling speed would result in either an enhanced or suppressed epidemic, while increasing the traveling frequency enhances the epidemic spreading. |
format | Online Article Text |
id | pubmed-4466778 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-44667782015-06-18 Integrated travel network model for studying epidemics: Interplay between journeys and epidemic Ruan, Zhongyuan Wang, Chaoqing Ming Hui, Pak Liu, Zonghua Sci Rep Article The ease of travelling between cities has contributed much to globalization. Yet, it poses a threat on epidemic outbreaks. It is of great importance for network science and health control to understand the impact of frequent journeys on epidemics. We stress that a new framework of modelling that takes a traveller’s viewpoint is needed. Such integrated travel network (ITN) model should incorporate the diversity among links as dictated by the distances between cities and different speeds of different modes of transportation, diversity among nodes as dictated by the population and the ease of travelling due to infrastructures and economic development of a city, and round-trip journeys to targeted destinations via the paths of shortest travel times typical of human journeys. An example is constructed for 116 cities in China with populations over one million that are connected by high-speed train services and highways. Epidemic spread on the constructed network is studied. It is revealed both numerically and theoretically that the traveling speed and frequency are important factors of epidemic spreading. Depending on the infection rate, increasing the traveling speed would result in either an enhanced or suppressed epidemic, while increasing the traveling frequency enhances the epidemic spreading. Nature Publishing Group 2015-06-15 /pmc/articles/PMC4466778/ /pubmed/26073191 http://dx.doi.org/10.1038/srep11401 Text en Copyright © 2015, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Ruan, Zhongyuan Wang, Chaoqing Ming Hui, Pak Liu, Zonghua Integrated travel network model for studying epidemics: Interplay between journeys and epidemic |
title | Integrated travel network model for studying epidemics: Interplay between journeys and epidemic |
title_full | Integrated travel network model for studying epidemics: Interplay between journeys and epidemic |
title_fullStr | Integrated travel network model for studying epidemics: Interplay between journeys and epidemic |
title_full_unstemmed | Integrated travel network model for studying epidemics: Interplay between journeys and epidemic |
title_short | Integrated travel network model for studying epidemics: Interplay between journeys and epidemic |
title_sort | integrated travel network model for studying epidemics: interplay between journeys and epidemic |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4466778/ https://www.ncbi.nlm.nih.gov/pubmed/26073191 http://dx.doi.org/10.1038/srep11401 |
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