Evidence map›Paper›PMID 41878740›Full record

ArticleFrontiers in microbiology2026

Unraveling HIV-1 spread in Southwest China: a phylogenetic and molecular network approach.

Xianwu Pang, Kailing Tang, Qin He, Jie Ma, Ningye Fang, Haomin Xie, Ge Zhong, Shujia Liang

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. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

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.

Xianwu Pang *Guangxi Key Laboratory for the Prevention and Control of Viral Hepatitis, Guangxi Key Laboratory of AIDS Prevention and Control and Achievement Transformation, Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, China.
Kailing TangGuangxi Key Laboratory for the Prevention and Control of Viral Hepatitis, Guangxi Key Laboratory of AIDS Prevention and Control and Achievement Transformation, Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, China.
Qin HeGuangxi Key Laboratory for the Prevention and Control of Viral Hepatitis, Guangxi Key Laboratory of AIDS Prevention and Control and Achievement Transformation, Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, China.
Jie MaGuangxi Key Laboratory for the Prevention and Control of Viral Hepatitis, Guangxi Key Laboratory of AIDS Prevention and Control and Achievement Transformation, Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, China.
Ningye FangGuangxi Key Laboratory for the Prevention and Control of Viral Hepatitis, Guangxi Key Laboratory of AIDS Prevention and Control and Achievement Transformation, Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, China.
Haomin XieGuangxi Key Laboratory for the Prevention and Control of Viral Hepatitis, Guangxi Key Laboratory of AIDS Prevention and Control and Achievement Transformation, Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, China.
Ge Zhong *Guangxi Key Laboratory for the Prevention and Control of Viral Hepatitis, Guangxi Key Laboratory of AIDS Prevention and Control and Achievement Transformation, Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, China.
Shujia Liang *Guangxi Key Laboratory for the Prevention and Control of Viral Hepatitis, Guangxi Key Laboratory of AIDS Prevention and Control and Achievement Transformation, Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention, Nanning, Guangxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Guangxi is one of the regions most affected by HIV-1 in China, yet the fine-scale transmission dynamics and molecular epidemiology remain incompletely characterized. In this study, we integrated molecular transmission network analysis, phylogenetic inference, and spatial analysis to elucidate HIV-1 dispersal patterns and inform precision public health interventions. We analyzed 10,199 HIV-1 pol sequences collected from all 14 cities in Guangxi, encompassing major subtypes including CRF01_AE, CRF07_BC, CRF08_BC, and CRF55_01B. Molecular networks were constructed using a 1.5% TN93 genetic-distance threshold, and logistic regression was applied to identify factors associated with network clustering. Bayesian phylogenetic and phylogeographic analyses were used to characterize spatiotemporal dissemination patterns. Overall, 75.6% (7,706/10,199) of individuals clustered within molecular networks, with clustering proportions exceeding 60% in every city. Factors independently associated with clustering included viral load >10,000 copies/mL (OR = 1.23, 95% CI: 1.10-1.39), education level of junior high school or below (OR = 1.67, 95% CI: 1.30-2.14), age ≥50 years (OR = 1.38, 95% CI: 1.16-1.63), Zhuang ethnicity (OR = 1.18, 95% CI: 1.08-1.30), and syringe sharing (OR = 1.65, 95% CI: 1.14-2.38). Intercity connections accounted for 48.2% of inferred genetic linkages, with CRF55_01B showing the highest intercity connectivity (60.4%). CRF01_AE displayed the broadest geographic distribution, Nanning and Qinzhou emerged as key connectivity hubs. Phylogeographic analyses suggested that Qinzhou was a major source of dispersal for CRF01_AE and CRF08_BC, whereas Nanning played a central role in the dissemination of CRF07_BC, CRF08_BC, and CRF55_01B. HIV-1 transmission in Guangxi is characterized by high network clustering and pronounced spatial heterogeneity, with distinct hub cities contributing to regional connectivity. These findings provide actionable evidence to support targeted, location-specific HIV prevention and control strategies at both local and regional levels.

Indexed as

HIV-1molecular epidemiologymolecular transmission networksspatial epidemiologytransmission dynamics

Identifiers

PMID41878740
PMCPMC13007254

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Registered trials

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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.