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. 2024 Dec;13(1):2409319.
doi: 10.1080/22221751.2024.2409319. Epub 2024 Sep 30.

Characterizing HIV-1 transmission by genetic cluster analysis among newly diagnosed patients in the China-Myanmar border region from 2020 to 2023

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Characterizing HIV-1 transmission by genetic cluster analysis among newly diagnosed patients in the China-Myanmar border region from 2020 to 2023

Huan Liu et al. Emerg Microbes Infect. 2024 Dec.

Abstract

Cluster analysis of HIV sequence can provide insights into viral transmission patterns in border regions. This study aims to illuminate the HIV-1 subtype distribution and transmission dynamics among newly diagnosed individuals in Dehong prefecture, a region along the China-Myanmar border. Among 948 participants with pol gene sequences, 36 HIV-1 subtypes were identified, with URFs (18.8%, 178/948) being the dominant strain, followed by CRF01_AE (18.5%, 175/948) and CRF07_BC (10.9%, 103/948). Additionally, 287 sequences (30.3%, 287/948) were grouped into 91 clusters, 31 of which contained both Chinese and Burmese individuals. Multivariable logistic regression indicated that men who have sex with men (MSM), CD4 + cell count of 200∼499, and 500 cells/μl and above, and CRF01_AE were risk factors for entering the network. Through the Chord diagram, we found frequent transmission relationships among heterosexual China male group, especially those over 35 years of age. Additionally, the correlation between heterosexual Myanmar female group and heterosexual China male group among cross-risk groups deserved to be emphasized. Furthermore, the network exhibited a growing trend over time, with the largest active transmission cluster identified in Ruili county. In conclusion, the HIV-1 subtype landscape in Dehong has become increasingly complex, and the region has faced risks of transmission from both domestic and international sources. Targeted intervention strategies should be implemented for MSM, heterosexual Chinese middle-aged and elderly men, and heterosexual Burmese young adults to mitigate these risks. These findings provided evidence-based insights for local government to formulate coordinated transnational intervention approaches.

Keywords: HIV-1; cluster analysis; cross-border; molecular epidemiology; subtype.

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Conflict of interest statement

No potential conflict of interest was reported by the author(s).

Figures

Figure 1.
Figure 1.
Flow chart shows the individuals meeting inclusion criteria.
Figure 2.
Figure 2.
Distribution of subtypes by different characteristics. A. subtypes distribution by nationality. B. subtypes distribution by age at diagnosis. C. subtypes distribution by education level. D. subtypes distribution by mode of transmission.
Figure 3.
Figure 3.
Molecular transmission network analysis of HIV-1 among newly diagnosed patients in Dehong from 2020 to 2023.
Figure 4.
Figure 4.
Linkage analysis of different risk groups in the network. Abbreviations: HMF: heterosexual-Myanmar-female,HMM:heterosexual-Myanmar-male, HCF: heterosexual-China-female, HCM: heterosexual-China-male, MSM: men who have sex with men.
Figure 5.
Figure 5.
Analysis of active transmission clusters within the transmission network. Abbreviations: fHeterosexual, heterosexual female; mHeterosexual, heterosexual male.

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