Analysis of an Epidemic Model Incorporating Anxiety Dynamics

Abstract

This study formulates and analyzes a COVID-19 disease contagion model, incorporating a psychological variable over a population considering that infected cases can be confirmed or unreported. Using a system of ordinary differential equations, the model describes the impact of anxiety on the disease progression where the contact parameter is defined as a function of anxiety level. We derive the basic reproduction number $\mathcal{R}_0$ and numerical simulations validate our theoretical results. Our findings provide a qualitative understanding of the interplay between psychological states and epidemiological outcomes, offering a novel framework for future research and potential policymaking applications in epidemic response.