An age-structured epidemic model with vaccination

TL;DR

This paper develops an age-structured COVID-19 epidemic model incorporating vaccination, analyzes its stability, and applies it to real-world data to evaluate control strategies and the impact of age-specific factors.

Contribution

It introduces a novel age-structured epidemic model with vaccination, providing stability analysis and real-world application to assess intervention effectiveness.

Findings

Disease-free equilibrium is stable when R0 < 1

Vaccination and age structure significantly influence epidemic dynamics

Model accurately predicts case trends in Shijiazhuang

Abstract

In this article, we construct an age-structured model for COVID-19 with vaccination and analyze it from multiple perspectives. We derive the unique disease-free equilibrium point and the basic reproduction number $ \mathscr{R}_0 $, then we show that the disease-free equilibrium is locally asymptotically stable when $ \mathscr{R}_0 < 1 $, while is unstable when $ \mathscr{R}_0 > 1 $. We also work out endemic equilibrium points and reveal the stability. We use sensitivity analysis to explore how parameters influence $ \mathscr{R}_0 $. Sensitivity analysis helps us develop more targeted strategies to control epidemics. Finally, this model is used to discuss the cases in Shijiazhuang, Hebei Province at the beginning of 2021. We compare reported cases with the simulation to evaluate the measures taken by Shijiazhuang government. Our study shows how age structure, vaccination and drastic containment measures can affect the epidemic.