Molecular transmission network analysis of newly diagnosed HIV-1 infections in Ningbo from 2018-2022

Understanding 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.

We 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.

Molecular 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.

This 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.