Data Sheet 1_Molecular transmission network analysis of newly diagnosed HIV-1 infections in Ningbo from 2018–2022.docx

IntroductionUnderstanding molecular transmission patterns is critical for HIV prevention designed with key populations. This study aimed to characterize the molecular epidemiology, transmission networks, and underlying factors associated with HIV-1 transmission in Ningbo during 2018–2022.
MethodsWe analyzed data from 1,409 newly diagnosed people living with HIV who had successful genotyping. A maximum likelihood phylogenetic tree was constructed, and transmission clusters were identified using 1.3% distance and 0.9 bootstrap values. Multivariate logistic regression was applied to identify factors associated with clustered, large clusters (≥10 nodes) and fast-growing clusters.
ResultsMolecular analysis revealed 11 distinct HIV-1 subtypes and some unique recombinant forms (URFs), with CRF07_BC (41.6%) and CRF01_AE (33.2%) as the most prevalent. CRF07_BC consistently tended to form larger, more densely connected clusters, whereas CRF01_AE networks primarily exhibited sparse, fragmented distributions. Molecular transmission network analysis identified 9 large clusters and 12 fast-growing clusters. HIV-1 subtypes were associated with the large clusters and fast-growing clusters. CRF07_BC formed larger clusters (aOR = 7.80, 95%CI: 4.70–13.49) and fast-growing clusters (aOR = 6.02, 95%CI: 3.80–9.78) compared to CRF01_AE. Temporally, the molecular transmission networks (MTNs) expanded rapidly in 2020–2021.
ConclusionThis study elucidates the MTNs of HIV-1 in Ningbo, highlighting the role of subtype diversity and demographic traits in shaping transmission networks. Continuous monitoring of HIV-1 molecular subtypes among key populations may serve as feasible and focused prevention strategies to curb HIV transmission.