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Background: Characterizing HIV clustering rates and their trends over time can improve understanding a local epidemic and enhance its control., Methods: Leveraging an academic-public health partnership in Rhode Island, we explored longitudinal dynamics of statewide clustering rates among key populations from 1991 to 2023. Partial HIV-1 pol sequences were grouped by year of HIV-1 diagnosis. Molecular clusters were identified in cumulative annual phylogenies. Overall clustering rates, and clustering rates of newly diagnosed and prevalent infections, and of specific sociodemographic characteristics of key populations over time were determined. Mann-Kendall statistics were used to estimate clustering rate trends and relationships among groups., Results: By the end of 2023, 2630 individuals with sequences represented the statewide epidemic in Rhode Island. Overall clustering rates increased from 7% in 1991 to 46% in 2023, correlating with cumulative sequence increase. Clustering rates of newly diagnosed and prevalent infections significantly increased over time, higher in newly diagnosed individuals since the early 2000s. Increases were also observed among groups defined by gender, age, transmission risks, race, mental illness, HIV-1 subtypes, and country of birth, with some crossovers and divergence patterns over time., Conclusion: Exploring dynamics of HIV clustering rates over three decades in a statewide HIV-1 epidemic expanded its characterization and provided insight into its evolving changes. These dynamics may indicate a gradual shift towards a more concentrated and localized HIV-1 epidemic, highlighting important opportunities for targeted interventions to effectively prevent new HIV transmissions., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Background: Human immunodeficiency virus type 1 (HIV-1) acquired drug resistance (ADR) compromises antiretroviral therapy (ART)., Methods: We aggregated all HIV-1 protease-reverse transcriptase-integrase sequences over 2004-2021 at the largest HIV center in Rhode Island and evaluated ADR extent, trends, and impact using Stanford Database tools. Trends were measured with Mann-Kendall statistic, and multivariable regressions evaluated resistance predictors., Results: Sequences were available for 914 ART-experienced persons. Overall ADR to any drug decreased from 77% to 49% (-0.66 Mann-Kendall statistic); nucleoside reverse transcriptase inhibitors 65% to 32%, nonnucleoside reverse transcriptase inhibitors 53% to 43%, and protease inhibitors 28% to 7% (2004-2021), and integrase strand transfer inhibitors 16% to 13% (2017-2021). Multiclass resistance decreased from 44% to 12% (2-class) and 12% to 6% (3-class). In 2021, 94% had at least one 3-drug or 2-drug one-pill-once-daily (OPOD) option. Males and those exposed to more ART regimens were more likely to have ≥2-class resistance, and higher regimen exposure was also associated with fewer OPOD options., Conclusions: Comprehensive analyses within a densely-sampled HIV epidemic over 2004-2021 demonstrated decreasing ADR. Continued ADR monitoring is important to maintain ART success, particularly with rising INSTI use in all lines of therapy and 2-drug and long-acting formulations., Competing Interests: Potential conflicts of interest . All authors: No reported conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (© The Author(s) 2024. Published by Oxford University Press on behalf of Infectious Diseases Society of America. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Molecular HIV cluster data can guide public health responses towards ending the HIV epidemic. Currently, real-time data integration, analysis, and interpretation are challenging, leading to a delayed public health response. We present a comprehensive methodology for addressing these challenges through data integration, analysis, and reporting. We integrated heterogeneous data sources across systems and developed an open-source, automatic bioinformatics pipeline that provides molecular HIV cluster data to inform public health responses to new statewide HIV-1 diagnoses, overcoming data management, computational, and analytical challenges. We demonstrate implementation of this pipeline in a statewide HIV epidemic and use it to compare the impact of specific phylogenetic and distance-only methods and datasets on molecular HIV cluster analyses. The pipeline was applied to 18 monthly datasets generated between January 2020 and June 2022 in Rhode Island, USA, that provide statewide molecular HIV data to support routine public health case management by a multi-disciplinary team. The resulting cluster analyses and near-real-time reporting guided public health actions in 37 phylogenetically clustered cases out of 57 new HIV-1 diagnoses. Of the 37, only 21 (57%) clustered by distance-only methods. Through a unique academic-public health partnership, an automated open-source pipeline was developed and applied to prospective, routine analysis of statewide molecular HIV data in near-real-time. This collaboration informed public health actions to optimize disruption of HIV transmission.

Objectives: Molecular epidemiology is a powerful tool to characterize HIV epidemics and prioritize public health interventions. Typically, HIV clusters are assumed to have uniform patterns over time. We hypothesized that assessment of cluster evolution would reveal distinct cluster behavior, possibly improving molecular epidemic characterization, towards disrupting HIV transmission., Design: Retrospective cohort., Methods: Annual phylogenies were inferred by cumulative aggregation of all available HIV-1 pol sequences of individuals with HIV-1 in Rhode Island (RI) between 1990 and 2020, representing a statewide epidemic. Molecular clusters were detected in annual phylogenies by strict and relaxed cluster definition criteria, and the impact of annual newly-diagnosed HIV-1 cases to the structure of individual clusters was examined over time., Results: Of 2153 individuals, 31% (strict criteria) - 47% (relaxed criteria) clustered. Longitudinal tracking of individual clusters identified three cluster types: normal, semi-normal and abnormal. Normal clusters (83-87% of all identified clusters) showed predicted growing/plateauing dynamics, with approximately three-fold higher growth rates in large (15-18%) vs. small (∼5%) clusters. Semi-normal clusters (1-2% of all clusters) temporarily fluctuated in size and composition. Abnormal clusters (11-16% of all clusters) demonstrated collapses and re-arrangements over time. Borderline values of cluster-defining parameters explained dynamics of non-normal clusters., Conclusions: Comprehensive tracing of molecular HIV clusters over time in a statewide epidemic identified distinct cluster types, likely missed in cross-sectional analyses, demonstrating that not all clusters are equal. This knowledge challenges current perceptions of consistent cluster behavior over time and could improve molecular surveillance of local HIV epidemics to better inform public health strategies., (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.)