ArticleScience advances2022
Deep learning and social network analysis elucidate drivers of HIV transmission in a high-incidence cohort of people who inject drugs.
Article in Science advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
What it found
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Incidence of HIV and hepatitis C virus among people who inject drugs, and associations with age and sex or gender: a global systematic review and meta-analysis.The lancet. Gastroenterology & hepatology · 2023Pooled it
- From giant components to communities: community-level insights for prioritizing interventions within large clusters of HIV-1 transmission networks.Infectious Disease Modelling · 2027Article
- What, how, and when matters: acceptability and preferences for HIV pre-exposure prophylaxis among people who inject drugs in New Delhi, India.AIDS and behavior · 2026Article
- AI-Driven Approaches for the Detection, Classification, and Surveillance of Viral Pathogens: Current Advances, Challenges, and Future Directions.Pathogens (Basel, Switzerland) · 2026Review
- Geometric deep learning enables high-fidelity network imputation for HIV transmission modeling.Communications medicine · 2026Article
- Evaluating spatially targeted HIV interventions and harm reduction services among people who inject drugs in a high-burden setting.Nature communications · 2026Article
- Evaluating Spatially Targeted HIV Interventions and Harm Reduction Services Among People Who Inject Drugs in a High-Burden Setting.medRxiv : the preprint server for health sciences · 2026Article
- Network-based strategies to combat HCV: Examining social and spatial drivers of transmission among PWID in New Delhi.Journal of viral hepatitis · 2024Article
- Injection network drivers of HIV prevention service utilization among people who inject drugs: results of a community-based sociometric network cohort in New Delhi, India.Journal of the International AIDS Society · 2024Article
- Network centrality and HIV prevention service use among people who inject drugs: Findings from a sociometric network cohort in New Delhi, India.Addiction (Abingdon, England) · 2024Observational
- FAD: Fine-Grained Adversarial Detection by Perturbation Intensity Classification.Entropy (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
Globally, people who inject drugs (PWID) experience some of the fastest-growing HIV epidemics. Network-based approaches represent a powerful tool for understanding and combating these epidemics; however, detailed social network studies are limited and pose analytical challenges. We collected longitudinal social (injection partners) and spatial (injection venues) network information from 2512 PWID in New Delhi, India. We leveraged network analysis and graph neural networks (GNNs) to uncover factors associated with HIV transmission and identify optimal intervention delivery points. Longitudinal HIV incidence was 21.3 per 100 person-years. Overlapping community detection using GNNs revealed seven communities, with HIV incidence concentrated within one community. The injection venue most strongly associated with incidence was found to overlap six of the seven communities, suggesting that an intervention deployed at this one location could reach the majority of the sample. These findings highlight the utility of network analysis and deep learning in HIV program design.
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Registered trials
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