Department of Infection Management, Nanjing Drum Tower Hospital, Nanjing, China.
Children's Hospital of Nanjing Medical University, Nanjing, China.
JMIR Public Health Surveill. 2024 May 29;10:e56593. doi: 10.2196/56593.
The 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.
This 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.
We 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.
A 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.
The 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.
HIV-1 分子网络是一种创新性工具，利用基因序列来了解传播属性，并补充社会和性网络研究。虽然以前的研究集中在静态网络特征上，但最近研究对动态特征的强调提高了我们对实时变化的理解，为有针对性的干预措施和有效分配公共卫生资源提供了见解。
本研究旨在识别 HIV-1 分子传播网络中发生的动态变化，并分析驱动 HIV-1 分子网络动态变化的主要影响因素。
我们分析并比较了基线和观察终点之间特定时间段内分子网络的动态变化。通过单变量分析和多变量分析确定影响 HIV-1 分子网络动态变化的主要因素。
从 1013 个标本中成功扩增了 955 个 HIV-1 聚合酶片段；CRF01_AE 和 CRF07_BC 是主要的亚型，分别占标本的 40.8%（n=390）和 33.6%（n=321）。通过对基本和终端分子网络的分析和比较，发现 144 个序列构成静态分子网络，487 个序列构成动态分子网络。多变量分析的结果表明，作为学生、流动人口、汉族、偶尔或多次性伴侣、肛交和单身的职业、汉族、偶尔或多次性伴侣、肛交和单身是 HIV-1 分子网络动态变化的独立危险因素，比值比（OR；95%CI）值分别为 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）和 2.10（1.25-3.54）。与双性恋相比，异性恋和同性恋似乎表现出保护作用，OR 值分别为 0.12（95%CI 0.05-0.32）和 0.26（95%CI 0.11-0.64）。此外，国家八项评分和性教育经验也被确定为 HIV-1 分子网络动态变化的保护因素，OR 值分别为 0.12（95%CI 0.05-0.32）和 0.26（95%CI 0.11-0.64）。
HIV-1 分子网络分析显示，静态网络中有 144 个序列，动态网络中有 487 个序列。多变量分析显示，学生职业、流动人口、汉族和危险性行为是动态变化的独立危险因素，而异性恋和同性恋与双性恋相比具有保护作用。国家八项评分和性教育经验较高也是保护因素。识别 HIV 动态分子网络为正在发生动态变化的个体特征提供了有价值的见解。这些发现有助于更好地了解 HIV-1 传播动态，并为有针对性的预防策略提供信息。
