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Using molecular network analysis to understand current HIV-1 transmission characteristics in an inland area of Yunnan, China
HIV-1 molecular surveillance provides a new approach to explore transmission risks and targeted interventions. From January to June 2021, 663 newly reported HIV-1 cases were recruited in Zhaotong City, Yunnan Province, China. The distribution characteristics of HIV-1 subtypes and HIV-1 molecular net...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10540185/ https://www.ncbi.nlm.nih.gov/pubmed/37462024 http://dx.doi.org/10.1017/S0950268823001140 |
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author | Cao, Rui Lei, Shouxiong Chen, Huichao Ma, Yanling Dai, Jie Dong, Lijuan Jin, Xiaomei Yang, Min Sun, Pengyan Wang, Yawen Zhang, Yuying Jia, Manhong Chen, Min |
author_facet | Cao, Rui Lei, Shouxiong Chen, Huichao Ma, Yanling Dai, Jie Dong, Lijuan Jin, Xiaomei Yang, Min Sun, Pengyan Wang, Yawen Zhang, Yuying Jia, Manhong Chen, Min |
author_sort | Cao, Rui |
collection | PubMed |
description | HIV-1 molecular surveillance provides a new approach to explore transmission risks and targeted interventions. From January to June 2021, 663 newly reported HIV-1 cases were recruited in Zhaotong City, Yunnan Province, China. The distribution characteristics of HIV-1 subtypes and HIV-1 molecular network were analysed. Of 542 successfully subtyped samples, 12 HIV-1 strains were identified. The main strains were CRF08_BC (47.0%, 255/542), CRF01_AE (17.0%, 92/542), CRF07_BC (17.0%, 92/542), URFs (8.7%, 47/542), and CRF85_BC (6.5%, 35/542). CRF08_BC was commonly detected among Zhaotong natives, illiterates, and non-farmers and was mostly detected in Zhaoyang County. CRF01_AE was frequently detected among married and homosexual individuals and mostly detected in Weixin and Zhenxiong counties. Among the 516 pol sequences, 187 (36.2%) were clustered. Zhaotong natives, individuals aged ≥60 years, and illiterate individuals were more likely to be found in the network. Assortativity analysis showed that individuals were more likely to be genetically associated when stratified by age, education level, occupation, and reporting area. The genetic diversity of HIV-1 reflects the complexity of local HIV epidemics. Molecular network analyses revealed the subpopulations to focus on and the characteristics of the risk networks. The results will help optimise local prevention and control strategies. |
format | Online Article Text |
id | pubmed-10540185 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cambridge University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-105401852023-09-30 Using molecular network analysis to understand current HIV-1 transmission characteristics in an inland area of Yunnan, China Cao, Rui Lei, Shouxiong Chen, Huichao Ma, Yanling Dai, Jie Dong, Lijuan Jin, Xiaomei Yang, Min Sun, Pengyan Wang, Yawen Zhang, Yuying Jia, Manhong Chen, Min Epidemiol Infect Original Paper HIV-1 molecular surveillance provides a new approach to explore transmission risks and targeted interventions. From January to June 2021, 663 newly reported HIV-1 cases were recruited in Zhaotong City, Yunnan Province, China. The distribution characteristics of HIV-1 subtypes and HIV-1 molecular network were analysed. Of 542 successfully subtyped samples, 12 HIV-1 strains were identified. The main strains were CRF08_BC (47.0%, 255/542), CRF01_AE (17.0%, 92/542), CRF07_BC (17.0%, 92/542), URFs (8.7%, 47/542), and CRF85_BC (6.5%, 35/542). CRF08_BC was commonly detected among Zhaotong natives, illiterates, and non-farmers and was mostly detected in Zhaoyang County. CRF01_AE was frequently detected among married and homosexual individuals and mostly detected in Weixin and Zhenxiong counties. Among the 516 pol sequences, 187 (36.2%) were clustered. Zhaotong natives, individuals aged ≥60 years, and illiterate individuals were more likely to be found in the network. Assortativity analysis showed that individuals were more likely to be genetically associated when stratified by age, education level, occupation, and reporting area. The genetic diversity of HIV-1 reflects the complexity of local HIV epidemics. Molecular network analyses revealed the subpopulations to focus on and the characteristics of the risk networks. The results will help optimise local prevention and control strategies. Cambridge University Press 2023-07-18 /pmc/articles/PMC10540185/ /pubmed/37462024 http://dx.doi.org/10.1017/S0950268823001140 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited. |
spellingShingle | Original Paper Cao, Rui Lei, Shouxiong Chen, Huichao Ma, Yanling Dai, Jie Dong, Lijuan Jin, Xiaomei Yang, Min Sun, Pengyan Wang, Yawen Zhang, Yuying Jia, Manhong Chen, Min Using molecular network analysis to understand current HIV-1 transmission characteristics in an inland area of Yunnan, China |
title | Using molecular network analysis to understand current HIV-1 transmission characteristics in an inland area of Yunnan, China |
title_full | Using molecular network analysis to understand current HIV-1 transmission characteristics in an inland area of Yunnan, China |
title_fullStr | Using molecular network analysis to understand current HIV-1 transmission characteristics in an inland area of Yunnan, China |
title_full_unstemmed | Using molecular network analysis to understand current HIV-1 transmission characteristics in an inland area of Yunnan, China |
title_short | Using molecular network analysis to understand current HIV-1 transmission characteristics in an inland area of Yunnan, China |
title_sort | using molecular network analysis to understand current hiv-1 transmission characteristics in an inland area of yunnan, china |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10540185/ https://www.ncbi.nlm.nih.gov/pubmed/37462024 http://dx.doi.org/10.1017/S0950268823001140 |
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