Novel Spatial Profiles of Population Distribution of Two Diffusive SIS Epidemic Models with Mass Action Infection Mechanism and Small Movement Rate for the Infected Individuals

TL;DR

This study investigates the spatial distribution of populations in two SIS epidemic models with small movement rates, revealing how susceptible and infected populations concentrate or spread based on risk functions and population dynamics.

Contribution

It provides new insights into the spatial profiles of populations in reaction-diffusion SIS models with small movement rates, considering both constant and variable total populations.

Findings

Susceptible population converges to a positive constant at risk minimums.

Infected population concentrates at high-risk points or intervals.

Results depend on the risk function's behavior and smoothness.

Abstract

In this paper, we are concerned with two SIS epidemic reaction-diffusion models with mass action infection mechanism of the form $SI$, and study the spatial profile of population distribution as the movement rate of the infected individuals is restricted to be small. For the model with a constant total population number, our results show that the susceptible population always converges to a positive constant which is indeed the minimum of the associated risk function, and the infected population either concentrates at the isolated highest-risk points or aggregates only on the highest-risk intervals once the highest-risk locations contain at least one interval. In sharp contrast, for the model with a varying total population number which is caused by the recruitment of the susceptible individuals and death of the infected individuals, our results reveal that the susceptible population converges to a positive function which is non-constant unless the associated risk function is constant, and the infected population may concentrate only at some isolated highest-risk points, or aggregate at least in a neighborhood of the highest-risk locations or occupy the whole habitat, depending on the behavior of the associated risk function and even its smoothness at the highest-risk locations. Numerical simulations are performed to support and complement our theoretical findings.