Susceptible-Infected-Susceptible dynamics with mitigation in connection of infected population

TL;DR

This paper introduces a modified SIS epidemic model incorporating a mitigation factor to simulate reduced participation of infected individuals, analyzing its effects on disease spread within scale-free networks.

Contribution

It presents a novel SIS model with a mitigation factor affecting infected individuals' connectivity, providing analytical insights on its impact on epidemic dynamics.

Findings

Mitigation reduces the prevalence of infection in the network.

Analytical results show how mitigation influences epidemic thresholds.

Comparison highlights differences between original and mitigated models.

Abstract

The susceptible-infected-susceptible epidemic model is analyzed through a degree-based mean-field approach. In this work, a mitigation factor is introduced in the probability of finding an infected individual following an edge. This modification simulates situations where the infected population reduces its participation in the dynamics of disease propagation, as may happen with the seclusion or hospitalization of infected individuals. A detailed investigation of this new model and its comparison to the original one (without the mitigation factor) was performed on the Barab\'asi-Albert network, where some important results were analytically accessible.