I will present some deterministic (ODE) models of SARS-CoV-2 infection and discuss yhe state of knowledge about model parameters determined by fitting the model to published longitudinal viral load data obtained from infected individuals. Using this parameterization, one can then introduce antiviral therapy into the model and predict the needed efficacy of therapy to substantially reduce viral load (and presumably symptoms).
Lastly, I will present a stochastic version of the model and use it to calculate the effect of prophylactic treatments of different efficacies on the probability that the introduction of virus leads to extinction rather than establishment of infection.