An integral renewal equation approach to behavioural epidemic models with information index

TL;DR

This paper introduces an integral epidemic model incorporating a memory-based behavioral component called the 'information index', analyzing stability and oscillations influenced by different memory kernels and applying the model to diseases like influenza and SARS.

Contribution

It presents a novel integral model with a memory kernel for behavioral epidemic dynamics, providing stability conditions and demonstrating oscillations with different memory effects.

Findings

Stability is guaranteed with exponential infectivity and weak Erlang memory kernel.

Self-sustained oscillations occur with strong Erlang memory kernel.

Model applied to influenza and SARS, illustrating diverse epidemic behaviors.

Abstract

We propose an integral model describing an epidemic of an infectious disease. The model is behavioural in the sense that the constitutive law for the force of infection includes a distributed delay, called "information index", that describes the opinion-driven human behavioural changes. The information index, in turn, contains a memory kernel to mimic how the individuals maintain memory of the past values of the infection. We obtain sufficient conditions for the endemic equilibrium to be locally stable. In particular, we show that when the infectivity function is represented by an exponential distribution, stability is guaranteed by the weak Erlang memory kernel. However, through numerical simulations, we show that self-sustained oscillations may arise when the memory is more focused in the disease's past history, as exemplified by the strong Erlang kernel. We also show the model solutions in cases of different infectivity functions describing infectious diseases like influenza and SARS.