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Contact network analysis of Covid-19 in tourist areas——Based on 333 confirmed cases in China

The spread of infectious diseases is highly related to the structure of human networks. Analyzing the contact network of patients can help clarify the path of virus transmission. Based on confirmed cases of COVID-19 in two major tourist provinces in southern China (Hainan and Yunnan), this study ana...

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Autores principales: Yang, Zhangbo, Song, Jingen, Gao, Shanxing, Wang, Hui, Du, Yingfei, Lin, Qiuyue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8670701/
https://www.ncbi.nlm.nih.gov/pubmed/34905566
http://dx.doi.org/10.1371/journal.pone.0261335
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author Yang, Zhangbo
Song, Jingen
Gao, Shanxing
Wang, Hui
Du, Yingfei
Lin, Qiuyue
author_facet Yang, Zhangbo
Song, Jingen
Gao, Shanxing
Wang, Hui
Du, Yingfei
Lin, Qiuyue
author_sort Yang, Zhangbo
collection PubMed
description The spread of infectious diseases is highly related to the structure of human networks. Analyzing the contact network of patients can help clarify the path of virus transmission. Based on confirmed cases of COVID-19 in two major tourist provinces in southern China (Hainan and Yunnan), this study analyzed the epidemiological characteristics and dynamic contact network structure of patients in these two places. Results show that: (1) There are more female patients than males in these two districts and most are imported cases, with an average age of 45 years. Medical measures were given in less than 3 days after symptoms appeared. (2) The whole contact network of the two areas is disconnected. There are a small number of transmission chains in the network. The average values of degree centrality, betweenness centrality, and PageRank index are small. Few patients have a relatively high contact number. There is no superspreader in the network.
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spelling pubmed-86707012021-12-15 Contact network analysis of Covid-19 in tourist areas——Based on 333 confirmed cases in China Yang, Zhangbo Song, Jingen Gao, Shanxing Wang, Hui Du, Yingfei Lin, Qiuyue PLoS One Research Article The spread of infectious diseases is highly related to the structure of human networks. Analyzing the contact network of patients can help clarify the path of virus transmission. Based on confirmed cases of COVID-19 in two major tourist provinces in southern China (Hainan and Yunnan), this study analyzed the epidemiological characteristics and dynamic contact network structure of patients in these two places. Results show that: (1) There are more female patients than males in these two districts and most are imported cases, with an average age of 45 years. Medical measures were given in less than 3 days after symptoms appeared. (2) The whole contact network of the two areas is disconnected. There are a small number of transmission chains in the network. The average values of degree centrality, betweenness centrality, and PageRank index are small. Few patients have a relatively high contact number. There is no superspreader in the network. Public Library of Science 2021-12-14 /pmc/articles/PMC8670701/ /pubmed/34905566 http://dx.doi.org/10.1371/journal.pone.0261335 Text en © 2021 Yang et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Yang, Zhangbo
Song, Jingen
Gao, Shanxing
Wang, Hui
Du, Yingfei
Lin, Qiuyue
Contact network analysis of Covid-19 in tourist areas——Based on 333 confirmed cases in China
title Contact network analysis of Covid-19 in tourist areas——Based on 333 confirmed cases in China
title_full Contact network analysis of Covid-19 in tourist areas——Based on 333 confirmed cases in China
title_fullStr Contact network analysis of Covid-19 in tourist areas——Based on 333 confirmed cases in China
title_full_unstemmed Contact network analysis of Covid-19 in tourist areas——Based on 333 confirmed cases in China
title_short Contact network analysis of Covid-19 in tourist areas——Based on 333 confirmed cases in China
title_sort contact network analysis of covid-19 in tourist areas——based on 333 confirmed cases in china
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8670701/
https://www.ncbi.nlm.nih.gov/pubmed/34905566
http://dx.doi.org/10.1371/journal.pone.0261335
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