ArticleProceedings of the National Academy of Sciences of the United States of America2005
HIV dynamics with multiple infections of target cells.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
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Who cites it
46 citing papers in PubMed.
- A Darwinian model for the evolution of drug resistance to long-acting PrEP during an early HIV infection.PloS one · 2026Article
- Antiviral capacity of the early CD8 T-cell response is predictive of natural control of SIV infection: Learning in vivo dynamics using ex vivo data.PLoS computational biology · 2024Article
- Modeling dynamics of acute HIV infection incorporating density-dependent cell death and multiplicity of infection.PLoS computational biology · 2024Article
- Incorporating Intracellular Processes in Virus Dynamics Models.Microorganisms · 2024Review
- The role of tunneling nanotubes during early stages of HIV infection and reactivation: implications in HIV cure.NeuroImmune pharmacology and therapeutics · 2023Review
- Semi-infectious particles contribute substantially to influenza virus within-host dynamics when infection is dominated by spatial structure.Virus evolution · 2023Article
- Superinfection exclusion: A viral strategy with short-term benefits and long-term drawbacks.PLoS computational biology · 2022Article
- Article
- Evolution during primary HIV infection does not require adaptive immune selection.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- A hybrid stochastic-deterministic approach to explore multiple infection and evolution in HIV.PLoS computational biology · 2021Article
- Pre-existing resistance in the latent reservoir can compromise VRC01 therapy during chronic HIV-1 infection.PLoS computational biology · 2020Article
- Article
- Effect of synaptic cell-to-cell transmission and recombination on the evolution of double mutants in HIV.Journal of the Royal Society, Interface · 2020Article
- Within-host infectious disease models accommodating cellular coinfection, with an application to influenza.Virus evolution · 2019Article
- Multiple infection of cells changes the dynamics of basic viral evolutionary processes.Evolution letters · 2019Article
- Number of infection events per cell during HIV-1 cell-free infection.Scientific reports · 2017Article
- HIV Cell-to-Cell Spread Results in Earlier Onset of Viral Gene Expression by Multiple Infections per Cell.PLoS pathogens · 2016Article
- Cell-to-Cell Spread of HIV and Viral Pathogenesis.Advances in virus research · 2016Review
- Modeling multiple infection of cells by viruses: Challenges and insights.Mathematical biosciences · 2015Article
- Modeling the acute and chronic phases of Theiler murine encephalomyelitis virus infection.Journal of virology · 2013Article
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2 authors.
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Abstract
The high incidence of multiple infections of cells by HIV sets the stage for rapid HIV evolution by means of recombination. Yet how HIV dynamics proceeds with multiple infections remains poorly understood. Here, we present a mathematical model that describes the dynamics of viral, target cell, and multiply infected cell subpopulations during HIV infection. Model calculations reproduce several experimental observations and provide key insights into the influence of multiple infections on HIV dynamics. We find that the experimentally observed scaling law, that the number of cells coinfected with two distinctly labeled viruses is proportional to the square of the total number of infected cells, can be generalized so that the number of triply infected cells is proportional to the cube of the number of infected cells, etc. Despite the expectation from Poisson statistics, we find that this scaling relationship only holds under certain conditions, which we predict. We also find that multiple infections do not influence viral dynamics when the rate of viral production from infected cells is independent of the number of times the cells are infected, a regime expected when viral production is limited by cellular rather than viral factors. This result may explain why extant models, which ignore multiple infections, successfully describe viral dynamics in HIV patients. Inhibiting CD4 down-modulation increases the average number of infections per cell. Consequently, altering CD4 down-modulation may allow for an experimental determination of whether viral or cellular factors limit viral production.
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