Stochastic resetting antiviral therapies prevent drug resistance development

We study minimal mean-field models of viral drug resistance development in which the efficacy of a therapy is described by a one-dimensional stochastic resetting process with mixed reflecting-absorbing boundary conditions. We derive analytical expressions for the mean survival time for the virus to develop complete resistance to the drug. We show that the optimal therapy resetting rates that achieve a minimum and maximum mean survival times undergo a second- and first-order phase transition-like behaviour as a function of the therapy efficacy drift. We illustrate our results with simulations of a population dynamics model of HIV-1 infection.