Advancing Precision Public Health: an implementation science framework for HIV Cluster Detection and Response driven by molecular epidemiology

To align with the UNAIDS 2026–2031 Global AIDS Strategy, this study proposes a paradigm shift from undifferentiated generalized prevention to Precision Public Health (PPH) by constructing an implementation science framework for HIV Cluster Detection and Response (CDR). We synthesize recent advancements in genomic surveillance, specifically evaluating the integration of UMI-NGS and Third-Generation Sequencing (TGS) into public health pipelines. Moving beyond static algorithms, we propose an adaptive, subtype-specific genetic distance threshold approach and the utilization of the effective reproduction number ( Re ) via birth-death skyline models to quantify transmission volatility. High-resolution genomic data should be systematically translated into actionable intelligence. We operationalize the PPH framework through Disease Intervention Specialists (DIS) deploying Data-to-Care models and Enhanced Social Network Strategies (eSNS). A predictive implementation modeling simulation of the rapidly expanding CRF07_BC_N lineage in China projects that DIS-led targeted interventions can achieve a 60% reduction in cluster transmission rates. Concurrently, we embed an indispensable HIV Data Justice ethical structure to mitigate the stigmatization and criminalization risks inherent to Molecular HIV Surveillance (MHS). The proposed framework bridges the critical gap between molecular biology and frontline epidemiology by synchronizing high-resolution genomics, DIS-led targeted field interventions, and robust tiered resource allocation.