CROI 2025 Abstract eBook

Abstract eBook

Poster Abstracts

(n=227; median=8; IQR: 6–11), yet had higher annual growth (median=5; IQR: 4–8 vs. median=1; IQR: 1–2) and grew to include 10–110 persons. Age, transmission category, region, and early infection were similar across clusters (Table). Conclusions: Sexual transmission clusters are common and vary in growth after detection; over one third had continued rapid growth. Our analysis did not identify predictors of cluster growth. Exploration of other factors (e.g., the level of response, HIV testing and its impact on cluster growth, and social determinants of health) might reveal important differences to further guide prioritization and response.

1156 Evolution of HIV-1 A6 Clusters in Poland Following Full-Scale Armed Conflict in Ukraine Karol Serwin 1 , Kaja Mielczak 1 , Anna Urbańska 1 , Bogusz Aksak-Wąs 1 , Piotr Ząbek 2 , Ewa Siwak 2 , Iwona Cielniak 2 , Paweł Jakubowski 3 , Monika Bociąga-Jasik 4 , Bartosz Szetela 5 , Malwina Karasińska-Cieślak 1 , Magdalena Witak-Jędra 1 , Milosz Parczewski 1 1 Pomeranian Medical University, Szczecin, Poland, 2 Medical University of Warsaw, Warsaw, Poland, 3 Pomeranian Hospitals, Gdańsk, Poland, 4 Jagiellonian University, Kraków, Poland, 5 Wrocław Medical University, Wrocław, Poland Background: One of the fastest-growing HIV-1 epidemics is the A6 sub subtype, which has dominated countries of the Former Soviet Union. In Poland, the HIV-1 A6 prevalence has been increasing for over a decade, boosted after 2022 by the extensive influx of individuals from Ukraine. Our goal was to assess the changes in phylogenetic clustering patterns and cluster growth of HIV A6 in Poland between 2020 and 2024. Methods: We created a dataset of 14,007 unique HIV-1 pol gene fragments of sub-subtype A6 from publicly available sequence databases and included 2,089 sequences from Poland sampled between 1996 and 2024. The dataset was divided into three data points: up to 2020, 2022, and 2024. We defined a cluster as a sample introduced into Poland, representing a local transmission chain with a distinct entry point. Time-calibration of the maximum-likelihood phylogenetic trees and discrete phylogeographic inference were performed to evaluate distinct clusters Results: The number of A6 Polish clusters has increased from 74 in 2020 to 105 in 2022 and 191 in 2024. Median cluster sizes were 2 (2–306, n=628), 2 (2–457, n=939), and 2 (2–655, n=1499), respectively. These clusters comprised nearly all sequences from individuals born in Poland, with the proportion growing from 88.1% in 2020 to 90.5% in 2024. The fraction of females in clusters increased notably from 9.0% (n=28) in the 2020-2022 period to 19.6% (n=110; p<0.001) in the two following years, driven mainly by foreign-born women. The number of non-clustered (singleton) sequences increased significantly from 21.9% (n=87) to 35.5% (n=307; p<0.001), and the proportion of singletons surged from 70.5% in 2020 to 75.8% in 2024. The share of migrants among non-clustered sequences increased from 80.5% (n=70) in the first two years of the study to 90.2% (n=279; p<0.01) in the most recent two years. We noted a substantial rise in virus introductions into the country, with 120 cases in the period of two years before 2022 and 399 importations in the following two years Conclusions: The number and size of A6 clusters in Poland have increased, including those involving female sequences. Several of the large male dominated clusters continue to drive the spread of domestic infections and national A6 epidemic is propelled by infections from war related migration. Containing the growth and number of clusters presents a healthcare challenge, especially as resources are constrained by the need to support the large influx of individuals from abroad

Poster Abstracts

1155 Changing Clustering Rates in the Rhode Island HIV-1 Epidemic

Vlad Novitsky 1 , Jon Steingrimsson 1 , August Guang 1 , Casey Dunn 2 , Fizza Gillani 1 , Joel Hague 1 , John Fulton 1 , Thomas Bertrand 3 , Lila Bhattarai 3 , Meghan MacAskill 3 , Utpala Bandy 3 , Joseph Hogan 1 , Rami Kantor 1 1 Brown University, Providence, RI, USA, 2 Yale University, New Haven, CT, USA, 3 Rhode Island Department of Health, Providence, RI, USA Background: Tracking changes over time in proportions and characteristics of persons living with HIV who are part of molecular clusters (clustering rates), has potential to provide valuable insights into HIV transmission dynamics and help guide targeted public health interventions for prevention. Methods: We monitored clustering rates patterns and changes over time among key populations in the statewide HIV-1 epidemic in Rhode Island from 1991 to 2023. Partial HIV-1 pol sequences were grouped by year of HIV diagnosis, and molecular clusters were identified in cumulative annual phylogenies. Mann-Kendall statistics were used to estimate trends in clustering rates over time in newly-diagnosed and prevalent HIV infections, and among key populations defined by selected socio-demographic characteristics and transmission risk factors. Results: By the end of 2023, 2,630 persons with sequences represented the statewide Rhode Island HIV-1 epidemic. Overall, clustering rates increased from 7% in 1991 to 46% in 2023, correlating with cumulative sequence increase. Specifically, clustering rates increased significantly over time more among newly-diagnosed persons compared to prevalent infections mostly since 1998 (Figure), males versus others since 2009, people >40 years at HIV diagnosis versus others since 2005, MSM versus non-MSM since 2009, Whites versus others since 2005, persons with mental illness versus those without it since 2013, persons with HIV-1 subtype B versus non-B since 2013, and US-born versus foreign-born persons since 2007. Crossovers and divergence patterns in clustering rates identified over time among some groups further characterized clustering trend dynamics. Conclusions: Monitoring HIV molecular clustering rates over three decades in a statewide epidemic revealed evolving trends and diverse patterns among key populations over time, suggesting a gradual shift toward a more localized HIV-1 epidemic in Rhode Island. Findings emphasize the importance of tracking clustering rates to guide targeted interventions and prevent new transmissions.

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