Abstract
It remains unclear why HIV persists in most untreated individuals, and why a small minority of individuals can control the virus, either spontaneously or after an early treatment. Striking differences have been discovered between patient cohorts in CD4 + T-cell avidity but not in CD8 + T-cell avidity. The present work has the aim to explain the diverse outcome of infection and identify the key virological and immunological parameters predicting the outcome. A mathematical model informed by these experiments and taking into account the details of HIV virology is developed. The model predicts an arms race between viral dissemination and the proliferation of HIV-specific CD4 + helper cells leading to one of two states: a low-viremia state (controller) or a high-viremia state (progressor). Helper CD4 + cells with a higher avidity favor virus control. The parameter segregating spontaneous and posttreatment controllers is the infectivity difference between activated and resting CD4 + T cells. The model is shown to have a better connection to experiment than a previous model based on T-cell 'exhaustion'. Using the model informed by patient data, the timing of antiretroviral therapy can be optimized.
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