A Discrete SIS Model of Epidemic for a Heterogeneous Population without Discretization of its Continuous Counterpart

In this paper we propose a model of an infectious disease transmission in a heterogeneous population consisting of two different subpopulations: individuals with accordingly low and high susceptibility to an infection. This is a discrete model which was built without discretization of its continuous counterpart. It is not a typical approach. We assume that parameters describing particular processes in each subpopulation have different values. This assumption makes model analysis more complicated comparing to models without this assumption. We investigate conditions for existence and local stability of stationary states. The novelty of this paper lies in presenting the explicit condition concerning stationary states, including stability. We compute the basic reproduction number R0 of the given system, which determines the local stability of the disease-free stationary state. Additionally, we consider a situation when there is no illness transmission in the subpopulation with the low susceptibility. Theoretical result are complemented with numerical simulations in which we fit the model to epidemic data from the Warmian–Masurian province of Poland. These data reflect the case of the tuberculosis epidemic for which the homeless people were treated as a group with the high susceptibility.