Backward bifurcations and multistationarity

TL;DR

This paper establishes criteria for the existence of multiple positive steady states in epidemiological models, especially around backward bifurcations, and demonstrates multistationarity in a hepatitis C model.

Contribution

It provides a new theorem linking backward bifurcations to multistationarity and applies it to hepatitis C models, extending previous theoretical results.

Findings

Criteria for stable and unstable steady states around bifurcations

Multistationarity demonstrated in hepatitis C model

Comparison with existing models and methods

Abstract

The theory of backward bifurcations provides a criterion for the existence of positive steady states in epidemiological models with parameters where the basic reproductive ratio is less than one. It is often seen in simulations that this phenomenon is accompanied by multistationarity, i.e. the existence of more than one positive steady state, but the latter circumstance is not implied by the general theory. The central result of this paper is a theorem which gives a criterion for the existence of one stable and one unstable positive steady state for parameters where the basic reproductive ratio is less than one. It also gives a criterion for the existence of one stable and one unstable positive steady state in the case that the basic reproductive ratio is greater than one. These steady states arise in a bifurcation. It is shown that in one case, a model for the in-host dynamics of hepatitis C, this result can be used as a basis for showing the existence of parameters for which there are two positive steady states, one of which is stable. Thus, in particular, multistationarity is proved in that case. It is also shown to what extent this theorem can be applied to some other models which have been studied in the literature and what new results can be obtained. In that context the new approach is compared with those previously known.