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Molecular transmission network analysis of newly diagnosed HIV-1 infections in Nanjing from 2019 to 2021

Authors :
Hongjie Shi
Xin Li
Sainan Wang
Xiaoxiao Dong
Mengkai Qiao
Sushu Wu
Rong Wu
Xin Yuan
Jingwen Wang
Yuanyuan Xu
Zhengping Zhu
Source :
BMC Infectious Diseases, Vol 24, Iss 1, Pp 1-14 (2024)
Publication Year :
2024
Publisher :
BMC, 2024.

Abstract

Abstract Objective The objective of this study was to conduct a comprehensive analysis of the molecular transmission networks and transmitted drug resistance (TDR) patterns among individuals newly diagnosed with HIV-1 in Nanjing. Methods Plasma samples were collected from newly diagnosed HIV patients in Nanjing between 2019 and 2021. The HIV pol gene was amplified, and the resulting sequences were utilized for determining TDR, identifying viral subtypes, and constructing molecular transmission network. Logistic regression analyses were employed to investigate the epidemiological characteristics associated with molecular transmission clusters. Results A total of 1161 HIV pol sequences were successfully extracted from newly diagnosed individuals, each accompanied by reliable epidemiologic information. The analysis revealed the presence of multiple HIV-1 subtypes, with CRF 07_BC (40.57%) and CRF01_AE (38.42%) being the most prevalent. Additionally, six other subtypes and unique recombinant forms (URFs) were identified. The prevalence of TDR among the newly diagnosed cases was 7.84% during the study period. Employing a genetic distance threshold of 1.50%, the construction of the molecular transmission network resulted in the identification of 137 clusters, encompassing 613 nodes, which accounted for approximately 52.80% of the cases. Multivariate analysis indicated that individuals within these clusters were more likely to be aged ≥ 60, unemployed, baseline CD4 cell count ≥ 200 cells/mm3, and infected with the CRF119_0107 (P

Details

Language :
English
ISSN :
14712334
Volume :
24
Issue :
1
Database :
Directory of Open Access Journals
Journal :
BMC Infectious Diseases
Publication Type :
Academic Journal
Accession number :
edsdoj.7dff9facbfc4f9e801b78a4b16cbda7
Document Type :
article
Full Text :
https://doi.org/10.1186/s12879-024-09337-6