A Continuous-Time Markov Chain Model for the Spread of COVID-19

TL;DR

This paper presents a continuous-time Markov chain model to explain COVID-19 spread and control strategies, making complex stochastic process concepts accessible to undergraduate students.

Contribution

It introduces a simplified Markov chain model tailored for educational purposes to illustrate COVID-19 transmission and intervention strategies.

Findings

Model effectively explains virus spread dynamics

Educational tool for stochastic processes in epidemiology

Supports understanding of control measures

Abstract

Since late 2019 the novel coronavirus, also known as COVID-19, has caused a pandemic that persists. This paper shows how a continuous-time Markov chain model for the spread of COVID-19 can be used to explain, and justify to undergraduate students, strategies now being used in attempts to control the virus. The material in the paper is written at the level of students who are taking an introductory course on the theory and applications of stochastic processes.