» Articles » PMID: 36695355

Not All Clusters Are Equal: Dynamics of Molecular HIV-1 Clusters in a Statewide Rhode Island Epidemic

Abstract

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.

Citing Articles

Dynamics of clustering rates in the Rhode Island HIV-1 epidemic.

Novitsky V, Steingrimsson J, Guang A, Dunn C, Howison M, Gillani F AIDS. 2024; 39(2):105-114.

PMID: 39527774 PMC: 11717628. DOI: 10.1097/QAD.0000000000004062.


Prospective Evaluation of Routine Statewide Integration of Molecular Epidemiology and Contact Tracing to Disrupt Human Immunodeficiency Virus Transmission.

Kantor R, Steingrimsson J, Fulton J, Novitsky V, Howison M, Gillani F Open Forum Infect Dis. 2024; 11(10):ofae599.

PMID: 39474444 PMC: 11521326. DOI: 10.1093/ofid/ofae599.


Integrating HIV Cluster Analysis in Everyday Public Health Practice: Lessons Learned From a Public Health--Academic Partnership.

Fulton J, Novitsky V, Gillani F, Guang A, Steingrimsson J, Khanna A J Acquir Immune Defic Syndr. 2024; 97(1):48-54.

PMID: 39116331 PMC: 11310557. DOI: 10.1097/QAI.0000000000003469.


An Automated Bioinformatics Pipeline Informing Near-Real-Time Public Health Responses to New HIV Diagnoses in a Statewide HIV Epidemic.

Howison M, Gillani F, Novitsky V, Steingrimsson J, Fulton J, Bertrand T Viruses. 2023; 15(3).

PMID: 36992446 PMC: 10058263. DOI: 10.3390/v15030737.