Evidence map›Paper›PMID 38810253›Full record

ArticleJMIR public health and surveillance2024

Exploring Dynamic Changes in HIV-1 Molecular Transmission Networks and Key Influencing Factors: Cross-Sectional Study.

Yan He, Ying Tang, Qun Hua, Xin Li, You Ge, Yangyang Liu, Rong Tang, Ye Tian, Wei Li

Abstract read
In one paragraph

Article in JMIR public health and surveillance, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

9 authors.

Yan He *Department of Infection Management, Nanjing Drum Tower Hospital, Nanjing, China.ORCID 0000-0003-0912-3755
Ying Tang *Children's Hospital of Nanjing Medical University, Nanjing, China.ORCID 0009-0003-6000-5516
Qun Hua *Children's Hospital of Nanjing Medical University, Nanjing, China.ORCID 0000-0003-3524-8180
Xin LiNanjing Municipal Center for Disease Control and Prevention, Nanjing, China.ORCID 0000-0002-3343-8012
You GeSchool of Public Health, Southeast University, Nanjing, China.ORCID 0000-0003-4497-7916
Yangyang LiuSchool of Public Health, Southeast University, Nanjing, China.ORCID 0000-0003-4344-4034
Rong TangNanjing Qixia District Center for Disease Control and Prevention, Nanjing, China.ORCID 0009-0006-4456-8660
Ye TianChildren's Hospital of Nanjing Medical University, Nanjing, China.ORCID 0000-0001-7763-5600
Wei LiChildren's Hospital of Nanjing Medical University, Nanjing, China.ORCID 0000-0003-0769-5805

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe HIV-1 molecular network is an innovative tool, using gene sequences to understand transmission attributes and complementing social and sexual network studies. While previous research focused on static network characteristics, recent studies' emphasis on dynamic features enhances our understanding of real-time changes, offering insights for targeted interventions and efficient allocation of public health resources.

objectiveThis study aims to identify the dynamic changes occurring in HIV-1 molecular transmission networks and analyze the primary influencing factors driving the dynamics of HIV-1 molecular networks.

methodsWe analyzed and compared the dynamic changes in the molecular network over a specific time period between the baseline and observed end point. The primary factors influencing the dynamic changes in the HIV-1 molecular network were identified through univariate analysis and multivariate analysis.

resultsA total of 955 HIV-1 polymerase fragments were successfully amplified from 1013 specimens; CRF01_AE and CRF07_BC were the predominant subtypes, accounting for 40.8% (n=390) and 33.6% (n=321) of the specimens, respectively. Through the analysis and comparison of the basic and terminal molecular networks, it was discovered that 144 sequences constituted static molecular networks, and 487 sequences contributed to the formation of dynamic molecular networks. The findings of the multivariate analysis indicated that the factors occupation as a student, floating population, Han ethnicity, engagement in occasional or multiple sexual partnerships, participation in anal sex, and being single were independent risk factors for the dynamic changes observed in the HIV-1 molecular network, and the odds ratio (OR; 95% CIs) values were 2.63 (1.54-4.47), 1.83 (1.17-2.84), 2.91 (1.09-7.79), 1.75 (1.06-2.90), 4.12 (2.48-6.87), 5.58 (2.43-12.80), and 2.10 (1.25-3.54), respectively. Heterosexuality and homosexuality seem to exhibit protective effects when compared to bisexuality, with OR values of 0.12 (95% CI 0.05-0.32) and 0.26 (95% CI 0.11-0.64), respectively. Additionally, the National Eight-Item score and sex education experience were also identified as protective factors against dynamic changes in the HIV-1 molecular network, with OR values of 0.12 (95% CI 0.05-0.32) and 0.26 (95% CI 0.11-0.64), respectively.

conclusionsThe HIV-1 molecular network analysis showed 144 sequences in static networks and 487 in dynamic networks. Multivariate analysis revealed that occupation as a student, floating population, Han ethnicity, and risky sexual behavior were independent risk factors for dynamic changes, while heterosexuality and homosexuality were protective compared to bisexuality. A higher National Eight-Item score and sex education experience were also protective factors. The identification of HIV dynamic molecular networks has provided valuable insights into the characteristics of individuals undergoing dynamic alterations. These findings contribute to a better understanding of HIV-1 transmission dynamics and could inform targeted prevention strategies.

Indexed as

HIV-1HIV InfectionsAdultCross-Sectional StudiesFemaleHumansMaleMiddle Ageddynamicdynamic alterationdynamic alterationsgene distanceheterosexualHIVHIV-1homosexualinfectioninfluence factorsmolecular networkmolecular transmission networkNanjingreal-time analysisrisk factortransmission

Identifiers

PMID38810253
PMCPMC11170051

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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.