A minimal model for adaptive SIS epidemics

TL;DR

This paper introduces a minimal adaptive SIS epidemic model using a system of ODEs that accounts for dynamic contact networks influenced by disease prevalence, providing insights into endemic equilibria and stability without oscillations.

Contribution

It presents a novel planar ODE model incorporating adaptive contact networks based on disease prevalence, with explicit reproduction number and stability analysis.

Findings

Explicit basic reproduction number derived

Existence of at least one endemic equilibrium proven

Limit cycles are shown not to exist in the model

Abstract

The interplay between disease spreading and personal risk perception is of key importance for modelling the spread of infectious diseases. We propose a planar system of ordinary differential equations (ODEs) to describe the co-evolution of a spreading phenomenon and the average link density in the personal contact network. Contrary to standard epidemic models,we assume that the contact network changes based on the current prevalence of the disease in the population, i.e.\ it adapts to the current state of the epidemic. We assume that personal risk perception is described using two functional responses: one for link-breaking and one for link-creation. The focus is on applying the model to epidemics, but we highlight other possible fields of application. We derive an explicit form for the basic reproduction number and guarantee the existence of at least one endemic equilibrium, for all possible functional responses. Moreover, we show that for all functional responses, limit cycles do not exist.