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Impacts of social distancing on the spread of infectious diseases with asymptomatic infection: A mathematical model
Social distancing can be divided into two categories: spontaneous social distancing adopted by the individuals themselves, and public social distancing promoted by the government. Both types of social distancing have been proved to suppress the spread of infectious disease effectively. While previou...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7833012/ https://www.ncbi.nlm.nih.gov/pubmed/33518834 http://dx.doi.org/10.1016/j.amc.2021.125983 |
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author | Huang, He Chen, Yahong Yan, Zhijun |
author_facet | Huang, He Chen, Yahong Yan, Zhijun |
author_sort | Huang, He |
collection | PubMed |
description | Social distancing can be divided into two categories: spontaneous social distancing adopted by the individuals themselves, and public social distancing promoted by the government. Both types of social distancing have been proved to suppress the spread of infectious disease effectively. While previous studies examined the impact of each social distancing separately, the simultaneous impacts of them are less studied. In this research, we develop a mathematical model to analyze how spontaneous social distancing and public social distancing simultaneously affect the outbreak threshold of an infectious disease with asymptomatic infection. A communication-contact two-layer network is constructed to consider the difference between spontaneous social distancing and public social distancing. Based on link overlap of the two layers, the two-layer network is divided into three subnetworks: communication-only network, contact-only network, and overlapped network. Our results show that public social distancing can significantly increase the outbreak threshold of an infectious disease. To achieve better control effect, the subnetwork of higher infection risk should be more targeted by public social distancing, but the subnetworks of lower infection risk shouldn’t be overlooked. The impact of spontaneous social distancing is relatively weak. On the one hand, spontaneous social distancing in the communication-only network has no impact on the outbreak threshold of the infectious disease. On the other hand, the impact of spontaneous social distancing in the overlapped network is highly dependent on the detection of asymptomatic infection sources. Moreover, public social distancing collaborates with infection detection on controlling an infectious disease, but their impacts can’t add up perfectly. Besides, public social distancing is slightly less effective than infection detection, because infection detection can also promote spontaneous social distancing. |
format | Online Article Text |
id | pubmed-7833012 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-78330122021-01-26 Impacts of social distancing on the spread of infectious diseases with asymptomatic infection: A mathematical model Huang, He Chen, Yahong Yan, Zhijun Appl Math Comput Article Social distancing can be divided into two categories: spontaneous social distancing adopted by the individuals themselves, and public social distancing promoted by the government. Both types of social distancing have been proved to suppress the spread of infectious disease effectively. While previous studies examined the impact of each social distancing separately, the simultaneous impacts of them are less studied. In this research, we develop a mathematical model to analyze how spontaneous social distancing and public social distancing simultaneously affect the outbreak threshold of an infectious disease with asymptomatic infection. A communication-contact two-layer network is constructed to consider the difference between spontaneous social distancing and public social distancing. Based on link overlap of the two layers, the two-layer network is divided into three subnetworks: communication-only network, contact-only network, and overlapped network. Our results show that public social distancing can significantly increase the outbreak threshold of an infectious disease. To achieve better control effect, the subnetwork of higher infection risk should be more targeted by public social distancing, but the subnetworks of lower infection risk shouldn’t be overlooked. The impact of spontaneous social distancing is relatively weak. On the one hand, spontaneous social distancing in the communication-only network has no impact on the outbreak threshold of the infectious disease. On the other hand, the impact of spontaneous social distancing in the overlapped network is highly dependent on the detection of asymptomatic infection sources. Moreover, public social distancing collaborates with infection detection on controlling an infectious disease, but their impacts can’t add up perfectly. Besides, public social distancing is slightly less effective than infection detection, because infection detection can also promote spontaneous social distancing. Elsevier Inc. 2021-06-01 2021-01-17 /pmc/articles/PMC7833012/ /pubmed/33518834 http://dx.doi.org/10.1016/j.amc.2021.125983 Text en © 2021 Elsevier Inc. 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 Huang, He Chen, Yahong Yan, Zhijun Impacts of social distancing on the spread of infectious diseases with asymptomatic infection: A mathematical model |
title | Impacts of social distancing on the spread of infectious diseases with asymptomatic infection: A mathematical model |
title_full | Impacts of social distancing on the spread of infectious diseases with asymptomatic infection: A mathematical model |
title_fullStr | Impacts of social distancing on the spread of infectious diseases with asymptomatic infection: A mathematical model |
title_full_unstemmed | Impacts of social distancing on the spread of infectious diseases with asymptomatic infection: A mathematical model |
title_short | Impacts of social distancing on the spread of infectious diseases with asymptomatic infection: A mathematical model |
title_sort | impacts of social distancing on the spread of infectious diseases with asymptomatic infection: a mathematical model |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7833012/ https://www.ncbi.nlm.nih.gov/pubmed/33518834 http://dx.doi.org/10.1016/j.amc.2021.125983 |
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