A viral co-infection model with general infection rate in deterministic and stochastic environments.

In this paper, we present a model of infection in which a virus can simultaneously infect two types of target cells. The model has a general form of infection rates in deterministic and stochastic settings, incorporating bilinear infection rates, saturated incidences and half-saturated incidences. In the deterministic case, we investigate the existence and stability of infection-free steady state and infection steady state, respectively. Considering that the infection rate coefficient is affected by random noise, we built the corresponding stochastic model using the Ornstein–Uhlenbeck process. In the stochastic case, by constructing suitable Lyapunov functions, we established sufficient conditions for the stationary distribution and extinction of the model, respectively. In addition, the covariance matrix in the probability density function of the model near the infection steady state is determined. Finally, we consider the three most common forms of virus infection and perform comprehensive numerical simulations to support our theoretical results. • A viral co-infection model with general infection rate in deterministic and stochastic environments is developed. • We derive steady states and asymptotic stability for the deterministic model. • We obtain sufficient conditions for the stationary distribution and extinction of the stochastic model, respectively. • We conduct extensive numerical simulations to illustrate the effect of different infection functions. [ABSTRACT FROM AUTHOR]