  Massive research efforts are now underway to develop a cure for HIV
infection, allowing patients to discontinue lifelong combination antiretroviral
therapy (ART). New latency-reversing agents (LRAs) may be able to purge the
persistent reservoir of latent virus in resting memory CD4+ T cells, but the
degree of reservoir reduction needed for cure remains unknown. Here we use a
stochastic model of infection dynamics to estimate the efficacy of LRA needed
to prevent viral rebound after ART interruption. We incorporate clinical data
to estimate population-level parameter distributions and outcomes. Our findings
suggest that approximately 2,000-fold reductions are required to permit a
majority of patients to interrupt ART for one year without rebound and that
rebound may occur suddenly after multiple years. Greater than 10,000-fold
reductions may be required to prevent rebound altogether. Our results predict
large variation in rebound times following LRA therapy, which will complicate
clinical management. This model provides benchmarks for moving LRAs from the
lab to the clinic and can aid in the design and interpretation of clinical
trials. These results also apply to other interventions to reduce the latent
reservoir and can explain the observed return of viremia after months of
apparent cure in recent bone marrow transplant recipients and an
immediately-treated neonate.
