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Insights into the transmission of respiratory infectious diseases through empirical human contact networks
In this study, we present representative human contact networks among Chinese college students. Unlike schools in the US, human contacts within Chinese colleges are extremely clustered, partly due to the highly organized lifestyle of Chinese college students. Simulations of influenza spreading acros...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4985757/ https://www.ncbi.nlm.nih.gov/pubmed/27526868 http://dx.doi.org/10.1038/srep31484 |
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author | Huang, Chunlin Liu, Xingwu Sun, Shiwei Li, Shuai Cheng Deng, Minghua He, Guangxue Zhang, Haicang Wang, Chao Zhou, Yang Zhao, Yanlin Bu, Dongbo |
author_facet | Huang, Chunlin Liu, Xingwu Sun, Shiwei Li, Shuai Cheng Deng, Minghua He, Guangxue Zhang, Haicang Wang, Chao Zhou, Yang Zhao, Yanlin Bu, Dongbo |
author_sort | Huang, Chunlin |
collection | PubMed |
description | In this study, we present representative human contact networks among Chinese college students. Unlike schools in the US, human contacts within Chinese colleges are extremely clustered, partly due to the highly organized lifestyle of Chinese college students. Simulations of influenza spreading across real contact networks are in good accordance with real influenza records; however, epidemic simulations across idealized scale-free or small-world networks show considerable overestimation of disease prevalence, thus challenging the widely-applied idealized human contact models in epidemiology. Furthermore, the special contact pattern within Chinese colleges results in disease spreading patterns distinct from those of the US schools. Remarkably, class cancelation, though simple, shows a mitigating power equal to quarantine/vaccination applied on ~25% of college students, which quantitatively explains its success in Chinese colleges during the SARS period. Our findings greatly facilitate reliable prediction of epidemic prevalence, and thus should help establishing effective strategies for respiratory infectious diseases control. |
format | Online Article Text |
id | pubmed-4985757 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-49857572016-08-22 Insights into the transmission of respiratory infectious diseases through empirical human contact networks Huang, Chunlin Liu, Xingwu Sun, Shiwei Li, Shuai Cheng Deng, Minghua He, Guangxue Zhang, Haicang Wang, Chao Zhou, Yang Zhao, Yanlin Bu, Dongbo Sci Rep Article In this study, we present representative human contact networks among Chinese college students. Unlike schools in the US, human contacts within Chinese colleges are extremely clustered, partly due to the highly organized lifestyle of Chinese college students. Simulations of influenza spreading across real contact networks are in good accordance with real influenza records; however, epidemic simulations across idealized scale-free or small-world networks show considerable overestimation of disease prevalence, thus challenging the widely-applied idealized human contact models in epidemiology. Furthermore, the special contact pattern within Chinese colleges results in disease spreading patterns distinct from those of the US schools. Remarkably, class cancelation, though simple, shows a mitigating power equal to quarantine/vaccination applied on ~25% of college students, which quantitatively explains its success in Chinese colleges during the SARS period. Our findings greatly facilitate reliable prediction of epidemic prevalence, and thus should help establishing effective strategies for respiratory infectious diseases control. Nature Publishing Group 2016-08-16 /pmc/articles/PMC4985757/ /pubmed/27526868 http://dx.doi.org/10.1038/srep31484 Text en Copyright © 2016, The Author(s) 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 Huang, Chunlin Liu, Xingwu Sun, Shiwei Li, Shuai Cheng Deng, Minghua He, Guangxue Zhang, Haicang Wang, Chao Zhou, Yang Zhao, Yanlin Bu, Dongbo Insights into the transmission of respiratory infectious diseases through empirical human contact networks |
title | Insights into the transmission of respiratory infectious diseases through empirical human contact networks |
title_full | Insights into the transmission of respiratory infectious diseases through empirical human contact networks |
title_fullStr | Insights into the transmission of respiratory infectious diseases through empirical human contact networks |
title_full_unstemmed | Insights into the transmission of respiratory infectious diseases through empirical human contact networks |
title_short | Insights into the transmission of respiratory infectious diseases through empirical human contact networks |
title_sort | insights into the transmission of respiratory infectious diseases through empirical human contact networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4985757/ https://www.ncbi.nlm.nih.gov/pubmed/27526868 http://dx.doi.org/10.1038/srep31484 |
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