  Within-host models of COVID-19 infection dynamics enable the merits of
different forms of antiviral therapy to be assessed in individual patients. A
stochastic agent-based model of COVID-19 intracellular dynamics is introduced
here, that incorporates essential steps of the viral life cycle targeted by
treatment options. Integration of model predictions with an intercellular ODE
model of within-host infection dynamics, fitted to patient data, generates a
generic profile of disease progression in patients that have recovered in the
absence of treatment. This is contrasted with the profiles obtained after
variation of model parameters pertinent to the immune response, such as
effector cell and antibody proliferation rates, mimicking disease progression
in immunocompromised patients. These profiles are then compared with disease
progression in the presence of antiviral and convalescent plasma therapy
against COVID-19 infections. The model reveals that using both therapies in
combination can be very effective in reducing the length of infection, but
these synergistic effects decline with a delayed treatment start. Conversely,
early treatment with either therapy alone can actually increase the duration of
infection, with infectious virions still present after the decline of other
markers of infection. This suggests that usage of these treatments should
remain carefully controlled in a clinical environment.
