ArticleJournal of mathematical biology2024
Three-stage modeling of HIV infection and implications for antiretroviral therapy.
Article in Journal of mathematical biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- CD4 Count and Clinical Outcomes of Mpox in People Living With HIV: A Systematic Review and Meta-Analysis.Health science reports · 2026Review
- Active subspace learning for coarse-grained molecular dynamics.The Journal of chemical physics · 2026Article
- Syphilis Co-Infection Among People Living with HIV in Romania: Epidemiological and Clinical Characteristics in a Single-Center Retrospective Study.Pathogens (Basel, Switzerland) · 2026Article
- Active subspace learning for coarse-grained molecular dynamics.bioRxiv : the preprint server for biology · 2025Article
- Challenges of integrating HIV prevention and treatment in China's border mountain regions: a grounded theory study.BMC infectious diseases · 2025Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
We consider a deterministic model of HIV infection that involves macrophages as a long-term active reservoir to describe all three stages of the disease process: the acute stage, chronic infection, and the transition to AIDS. The proposed model is shown to retain crucial properties, such as the positivity of solutions, regardless of variations in model parameters. A dynamical analysis is performed to identify the local stability properties of the viral clearance steady state. This analysis illustrates how chronically infected macrophages can explain the progression to AIDS and provoke viral explosion, while previous models do not. We further demonstrate that the infected T-cell population, even if not responsible for the majority of new infections that lead to viral explosion, may contribute significantly to the transition amongst the three stages of infection. Moreover, we explore the implications of the model for the administration of antiretroviral therapy (ART) and provide quantitative estimates that emphasize the time sensitive nature of treatment initiation and the level of drug efficacy. Finally, we study the effects of treatment interruption on the disease dynamics predicted by the model and elucidate the influence of both interruption time and duration.
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Registered trials
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