SynthesisJournal of acquired immune deficiency syndromes (1999)2025
A Review of Network Models for HIV Spread.
Synthesis in Journal of acquired immune deficiency syndromes (1999), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- From giant components to communities: community-level insights for prioritizing interventions within large clusters of HIV-1 transmission networks.Infectious Disease Modelling · 2027Article
- Modeling the 2022 mpox outbreak with a mechanistic network model.BMC infectious diseases · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
backgroundHIV/AIDS has been a global health crisis for over 4 decades. Network models, which simulate human behavior and intervention impacts, have become an essential tool in guiding HIV prevention strategies and policies. However, no comprehensive survey of network models in HIV research has been conducted. This article fills that gap, offering a summary of past work and future directions to engage more researchers and inform policy related to eliminating HIV.
settingNetwork models explicitly represent interactions between individuals, making them well-suited to study HIV transmission dynamics. Two primary modeling paradigms exist: a mechanistic approach from applied mathematics and a statistical approach from the social sciences. Each has distinct strengths and weaknesses, which should be understood for effective application to HIV research.
methodsWe conducted a systematic review of network models used in HIV research, detailing the model types, populations, interventions, behaviors, datasets, and software used, while identifying potential future research directions.
resultsNetwork models are particularly valuable for studying behaviors central to HIV transmission, such as partner selection and treatment adherence. Unlike traditional models, they focus on individual behaviors, aligning them with clinical practice. However, more accurate network data are needed for better model calibration and actionable insights.
conclusionsThis article serves as a point of reference for HIV researchers interested in applying network models and understanding their limitations. To our knowledge, this is the most comprehensive review of HIV network models to date.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.