Analyzing Smoothness and Dynamics in an SEIR$^{\text{T}}$R$^{\text{P}}$D Endemic Model with Distributed Delays

TL;DR

This paper investigates an advanced SEIR model with distributed delays, revealing smoothness properties, boundedness, and non-negativity of solutions, and demonstrates how continuous models can be approximated by discrete lag models for disease dynamics analysis.

Contribution

It introduces a class of delay kernels with compact support and proves solution smoothness and boundedness, enhancing understanding of infectious disease models with distributed delays.

Findings

Solutions possess a smoothing property under mild conditions.

Boundedness and non-negativity of solutions are established.

Numerical simulations show discrete lag models approximate the continuous model.

Abstract

This article explores the properties of an SEIR$^{\text{T}}$R$^{\text{P}}$D endemic model expressed through delay-differential equations with distributed delays for latency and temporary immunity. Our research delves into the variability of latent periods and immunity durations across diseases, in particular, we introduce a class of delays defined by continuous integral kernels with compact support. The main result of the paper is a kind of smoothening property which the solution function posesses under mild conditions of the system parameter functions. Also, boundedness and non-negativity is proved. Numerical simulations indicates that the continuous model can be approximated with a discrete lag endemic models. The study contributes to understanding infectious disease dynamics and provides insights into the numerical approximation of exact solution for different delay scenarios.