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A Mutation Network Method for Transmission Analysis of Human Influenza H3N2

Characterizing the spatial transmission pattern is critical for better surveillance and control of human influenza. Here, we propose a mutation network framework that utilizes network theory to study the transmission of human influenza H3N2. On the basis of the mutation network, the transmission ana...

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Autores principales: Zhang, Chi, Wang, Yinghan, Chen, Cai, Long, Haoyu, Bai, Junbo, Zeng, Jinfeng, Cao, Zicheng, Zhang, Bing, Shen, Wei, Tang, Feng, Liang, Shiwen, Sun, Caijun, Shu, Yuelong, Du, Xiangjun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7601908/
https://www.ncbi.nlm.nih.gov/pubmed/33022948
http://dx.doi.org/10.3390/v12101125
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author Zhang, Chi
Wang, Yinghan
Chen, Cai
Long, Haoyu
Bai, Junbo
Zeng, Jinfeng
Cao, Zicheng
Zhang, Bing
Shen, Wei
Tang, Feng
Liang, Shiwen
Sun, Caijun
Shu, Yuelong
Du, Xiangjun
author_facet Zhang, Chi
Wang, Yinghan
Chen, Cai
Long, Haoyu
Bai, Junbo
Zeng, Jinfeng
Cao, Zicheng
Zhang, Bing
Shen, Wei
Tang, Feng
Liang, Shiwen
Sun, Caijun
Shu, Yuelong
Du, Xiangjun
author_sort Zhang, Chi
collection PubMed
description Characterizing the spatial transmission pattern is critical for better surveillance and control of human influenza. Here, we propose a mutation network framework that utilizes network theory to study the transmission of human influenza H3N2. On the basis of the mutation network, the transmission analysis captured the circulation pattern from a global simulation of human influenza H3N2. Furthermore, this method was applied to explore, in detail, the transmission patterns within Europe, the United States, and China, revealing the regional spread of human influenza H3N2. The mutation network framework proposed here could facilitate the understanding, surveillance, and control of other infectious diseases.
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spelling pubmed-76019082020-11-01 A Mutation Network Method for Transmission Analysis of Human Influenza H3N2 Zhang, Chi Wang, Yinghan Chen, Cai Long, Haoyu Bai, Junbo Zeng, Jinfeng Cao, Zicheng Zhang, Bing Shen, Wei Tang, Feng Liang, Shiwen Sun, Caijun Shu, Yuelong Du, Xiangjun Viruses Article Characterizing the spatial transmission pattern is critical for better surveillance and control of human influenza. Here, we propose a mutation network framework that utilizes network theory to study the transmission of human influenza H3N2. On the basis of the mutation network, the transmission analysis captured the circulation pattern from a global simulation of human influenza H3N2. Furthermore, this method was applied to explore, in detail, the transmission patterns within Europe, the United States, and China, revealing the regional spread of human influenza H3N2. The mutation network framework proposed here could facilitate the understanding, surveillance, and control of other infectious diseases. MDPI 2020-10-03 /pmc/articles/PMC7601908/ /pubmed/33022948 http://dx.doi.org/10.3390/v12101125 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhang, Chi
Wang, Yinghan
Chen, Cai
Long, Haoyu
Bai, Junbo
Zeng, Jinfeng
Cao, Zicheng
Zhang, Bing
Shen, Wei
Tang, Feng
Liang, Shiwen
Sun, Caijun
Shu, Yuelong
Du, Xiangjun
A Mutation Network Method for Transmission Analysis of Human Influenza H3N2
title A Mutation Network Method for Transmission Analysis of Human Influenza H3N2
title_full A Mutation Network Method for Transmission Analysis of Human Influenza H3N2
title_fullStr A Mutation Network Method for Transmission Analysis of Human Influenza H3N2
title_full_unstemmed A Mutation Network Method for Transmission Analysis of Human Influenza H3N2
title_short A Mutation Network Method for Transmission Analysis of Human Influenza H3N2
title_sort mutation network method for transmission analysis of human influenza h3n2
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7601908/
https://www.ncbi.nlm.nih.gov/pubmed/33022948
http://dx.doi.org/10.3390/v12101125
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