Cargando…
Modeling epidemic spread in transportation networks: A review
The emergence of novel infectious diseases has become a serious global problem. Convenient transportation networks lead to rapid mobilization in the context of globalization, which is an important factor underlying the rapid spread of infectious diseases. Transportation systems can cause the transmi...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Periodical Offices of Chang'an University. Publishing services by Elsevier B.V. on behalf of Owner.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7833723/ http://dx.doi.org/10.1016/j.jtte.2020.10.003 |
_version_ | 1783642128691232768 |
---|---|
author | Li, Jian Xiang, Tao He, Linghui |
author_facet | Li, Jian Xiang, Tao He, Linghui |
author_sort | Li, Jian |
collection | PubMed |
description | The emergence of novel infectious diseases has become a serious global problem. Convenient transportation networks lead to rapid mobilization in the context of globalization, which is an important factor underlying the rapid spread of infectious diseases. Transportation systems can cause the transmission of viruses during the epidemic period, but they also support the reopening of economies after the epidemic. Understanding the mechanism of the impact of mobility on the spread of infectious diseases is thus important, as is establishing the risk model of the spread of infectious diseases in transportation networks. In this study, the basic structure and application of various epidemic spread models are reviewed, including mathematical models, statistical models, network-based models, and simulation models. The advantages and limitations of model applications within transportation systems are analyzed, including dynamic characteristics of epidemic transmission and decision supports for management and control. Lastly, research trends and prospects are discussed. It is suggested that there is a need for more in-depth research to examine the mutual feedback mechanism of epidemics and individual behavior, as well as the proposal and evaluation of intervention measures. The findings in this study can help evaluate disease intervention strategies, provide decision supports for transport policy during the epidemic period, and ameliorate the deficiencies of the existing system. |
format | Online Article Text |
id | pubmed-7833723 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Periodical Offices of Chang'an University. Publishing services by Elsevier B.V. on behalf of Owner. |
record_format | MEDLINE/PubMed |
spelling | pubmed-78337232021-01-26 Modeling epidemic spread in transportation networks: A review Li, Jian Xiang, Tao He, Linghui Journal of Traffic and Transportation Engineering (English Edition) Review Article The emergence of novel infectious diseases has become a serious global problem. Convenient transportation networks lead to rapid mobilization in the context of globalization, which is an important factor underlying the rapid spread of infectious diseases. Transportation systems can cause the transmission of viruses during the epidemic period, but they also support the reopening of economies after the epidemic. Understanding the mechanism of the impact of mobility on the spread of infectious diseases is thus important, as is establishing the risk model of the spread of infectious diseases in transportation networks. In this study, the basic structure and application of various epidemic spread models are reviewed, including mathematical models, statistical models, network-based models, and simulation models. The advantages and limitations of model applications within transportation systems are analyzed, including dynamic characteristics of epidemic transmission and decision supports for management and control. Lastly, research trends and prospects are discussed. It is suggested that there is a need for more in-depth research to examine the mutual feedback mechanism of epidemics and individual behavior, as well as the proposal and evaluation of intervention measures. The findings in this study can help evaluate disease intervention strategies, provide decision supports for transport policy during the epidemic period, and ameliorate the deficiencies of the existing system. Periodical Offices of Chang'an University. Publishing services by Elsevier B.V. on behalf of Owner. 2021-01-05 /pmc/articles/PMC7833723/ http://dx.doi.org/10.1016/j.jtte.2020.10.003 Text en © 2021 The Authors 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 | Review Article Li, Jian Xiang, Tao He, Linghui Modeling epidemic spread in transportation networks: A review |
title | Modeling epidemic spread in transportation networks: A review |
title_full | Modeling epidemic spread in transportation networks: A review |
title_fullStr | Modeling epidemic spread in transportation networks: A review |
title_full_unstemmed | Modeling epidemic spread in transportation networks: A review |
title_short | Modeling epidemic spread in transportation networks: A review |
title_sort | modeling epidemic spread in transportation networks: a review |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7833723/ http://dx.doi.org/10.1016/j.jtte.2020.10.003 |
work_keys_str_mv | AT lijian modelingepidemicspreadintransportationnetworksareview AT xiangtao modelingepidemicspreadintransportationnetworksareview AT helinghui modelingepidemicspreadintransportationnetworksareview |