Evidence map›Paper›PMID 40503661›Full record

ArticleThe Journal of infectious diseases2025

Newly Diagnosed Individuals in Molecular HIV-1 Clusters in Rhode Island Over 3 Decades.

Vlad Novitsky, Jon Steingrimsson, August Guang, Fizza S Gillani, Joel Hague, John Fulton, Aditya Khanna, Thomas Bertrand, Meghan MacAskill, Joseph Hogan and 1 more

Abstract read
In one paragraph

Article in The Journal of infectious diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Vlad NovitskyDepartment of Medicine, Alpert Medical School of Brown University.ORCID 0000-0002-4279-9071
Jon SteingrimssonDepartment of Medicine, Alpert Medical School of Brown University.ORCID 0000-0003-2116-9377
August GuangDepartment of Medicine, Alpert Medical School of Brown University.ORCID 0000-0003-4974-1873
Fizza S GillaniDepartment of Medicine, Alpert Medical School of Brown University.
Joel HagueDepartment of Medicine, Alpert Medical School of Brown University.ORCID 0000-0003-4687-6756
John FultonDepartment of Medicine, Alpert Medical School of Brown University.ORCID 0000-0002-7114-8390
Aditya KhannaDepartment of Medicine, Alpert Medical School of Brown University.ORCID 0000-0003-1049-3374
Thomas BertrandRhode Island Department of Health, Providence.
Meghan MacAskillRhode Island Department of Health, Providence.
Joseph HoganDepartment of Medicine, Alpert Medical School of Brown University.
Rami KantorDepartment of Medicine, Alpert Medical School of Brown University.ORCID 0000-0003-3659-1108

Funding

Translational ScienceP30AI042853 · NIAID · MIRIAM HOSPITAL · PI CURT G BECKWITH, DEBBIE M. CHENG · 1998 to 2026
$51.7M
Real Time Phylogeny and Contact Tracing to Disrupt HIV TransmissionR01AI136058 · NIAID · MIRIAM HOSPITAL · PI KANTOR, RAMI · 2018 to 2022
$3.4M
Real Time Phylogeny and Contact Tracing to Disrupt HIV TransmissionR37AI136058 · NIAID · MIRIAM HOSPITAL · PI Rami Kantor · 2025 to 2026
$1.5M
HIV Drug Resistance, Monitoring and TransmissionK24AI134359 · NIAID · MIRIAM HOSPITAL · PI Rami Kantor · 2018 to 2026
$1.3M
NIAID NIH HHS K24 AI134359NIAID NIH HHS P30 AI042853NIAID NIH HHS R01 AI136058NIAID NIH HHS R37 AI136058NIH HHS K24AI134359NIH HHS P30AI42853NIH HHS R01AI136058
6 · The paper itself

Abstract

backgroundCharacterizing clustering rates of people with HIV in high-risk populations can offer insights on the HIV epidemic, enhancing efforts to control its spread.

methodsWe investigated longitudinal dynamics of clustering rates among individuals newly diagnosed with HIV-1. Data were extracted from the medical records of all people with HIV in Rhode Island with available viral sequences. Partial pol sequences were grouped by HIV diagnosis year, and clusters were identified in annual phylogenies. Clustering trends were estimated within 11 sociodemographic variables with the Mann-Kendall statistic. Associations with clustering propensity and changes over time were tested via generalized linear mixed effects models.

resultsHIV-1 sequences from 2630 individuals representing the statewide epidemic were analyzed across 33 annual datasets (1991-2023). Over this period, a continuous increase in clustering rates among newly diagnosed individuals was observed despite decreasing diagnoses over the last decade. Significant upward trends in clustering were seen among newly diagnosed men who have sex with men, males, the 21- to 40-year age group, non-Hispanic or Latino people, White persons, those with subtype B, and US-born individuals but not among people who inject drugs, females, and incarcerated individuals. Analyses of relative associations between groups within variables corroborated these results.

conclusionsAnalyses focusing on molecular HIV clusters among newly diagnosed people in a statewide epidemic over 3 decades revealed significant evolving trends among those at highest risk of HIV transmission, patterns not seen in the overall population. These findings inform the design and development of targeted public health interventions aimed at high-risk populations to curb HIV spread.

Indexed as

HIV-1HIV InfectionsAdolescentAdultCluster AnalysisFemaleHumansLongitudinal StudiesMaleMiddle AgedPhylogenyRhode IslandRisk FactorsYoung Adulthigh-risk populationsmolecular HIV clustersnewly diagnosed individualssociodemographic characteristicstransmission factors

Identifiers

PMID40503661
PMCPMC12455327

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