Evidence map›Paper›PMID 42688449›Full record

ArticleFrontiers in microbiology2026

Molecular transmission network analysis of HIV-1 among older adults in Central China: a cross-sectional study in Shaodong City.

Xiaobai Zou, Wei Liu, Jieyu Zhou, Jinghang Zhang, Jie Chen, Jingxin Li, Wenxiu Deng, Huan Chen

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Xiaobai ZouHunan Provincial Center for Disease Control and Prevention, Changsha, Hunan, China.
Wei LiuHunan Provincial Center for Disease Control and Prevention, Changsha, Hunan, China.
Jieyu ZhouHunan Provincial Center for Disease Control and Prevention, Changsha, Hunan, China.
Jinghang ZhangHunan Provincial Center for Disease Control and Prevention, Changsha, Hunan, China.
Jie ChenHunan Provincial Center for Disease Control and Prevention, Changsha, Hunan, China.
Jingxin LiShaoyang Center for Disease Control and Prevention, Shaodong, Hunan, China.
Wenxiu DengShaodong Center for Disease Control and Prevention, Shaoyang, Hunan, China.
Huan ChenHunan Provincial Center for Disease Control and Prevention, Changsha, Hunan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The ageing population poses emerging challenges to HIV prevention, particularly in regions with high proportions of older adults. We conducted a cross-sectional study of 513 newly diagnosed HIV-infected individuals in Shaodong City, Hunan Province, China, between 2021 and 2025, with a focus on individuals aged ≥60 years. Methods: HIV-1 pol sequences were amplified, sequenced, and analyzed for subtype distribution and transmitted drug resistance (TDR). Molecular transmission networks were constructed using a 0.5% genetic distance threshold, and clusters were classified as large (≥10 nodes), medium (5-9 nodes), or small (<5 nodes). Results: CRF85_BC was the predominant subtype (32.55%), and a total of 37 transmission clusters were identified, with the two largest clusters comprising 99 and 19 nodes, respectively. High-risk nodes, defined as those with a transmission network score (TNS) ≥ 0.75 and degree ≥4, were primarily older male farmers engaged in heterosexual commercial sex. The overall TDR prevalence was 10.53%, with NNRTI resistance predominating, and K103N being the most frequent mutation. Conclusion: Our findings indicate that HIV transmission among older adults exhibits substantial clustering, largely driven by commercial sexual activity, and highlight the importance of molecular network analysis for identifying high-risk individuals and guiding targeted prevention interventions. Continuous surveillance of TDR within active clusters is critical for optimizing antiretroviral therapy strategies and mitigating onward transmission.

Indexed as

CRF85_BCheterosexual commercial sexmolecular transmission networkolder adults (60 years and above)transmitted drug resistance

Identifiers

PMID42688449
PMCPMC13534127

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.