Network Dynamics and Evolutionary Drivers of HIV Drug Resistance in Eastern China, from 2022 to 2024.

UNLABELLED: The increasing prevalence of HIV drug resistance poses a significant challenge. This study aimed to investigate the epidemiological dynamics and molecular characteristics of pretreatment drug resistance (PDR) and acquired drug resistance in Shaoxing, Eastern China.

METHODS

From 2022 to 2024, 571 newly diagnosed HIV-infected individuals and 119 individuals with antiretroviral treatment failure were enrolled. Molecular transmission networks and Bayesian analysis were employed to identify key drug-resistant clusters and trace their origins.

RESULTS

The overall PDR prevalence was 14.4% (85/571). PDR to non-nucleoside reverse transcriptase inhibitors (NNRTIs) was 9.8% (56/571), significantly higher than to NRTIs (1.1%, 6/571) and PIs (3.7%, 21/571) (χ2 = 50.014, p < 0.001). Molecular network analysis identified large clusters harboring K103N and Q58E resistance mutations within the CRF07_BC subtype. Bayesian analysis estimated their introduction into Shaoxing from Guangdong Province around 2016 and 2017, respectively. Integrated network analysis revealed close linkages between virological failure and newly diagnosed cases, highlighting the role of treatment failure in resistance transmission.

CONCLUSION

Targeted interventions against specific subtypes and transmission clusters, alongside continuous resistance surveillance, are essential to curb the spread of drug-resistant HIV and optimize ART regimens.