Mathematical modelling and analysis of stochastic malaria and COVID-19 co-infection model

Abstract

In this article, we construct and analyse a stochastic mathematical model to study the co-infection dynamics of malaria and COVID-19 in a population. We derive the basic reproduction number associated with the disease-free equilibrium of the stochastic system using a Lyapunov function and establish conditions for its stability. Specifically, we calculate the threshold parameters for malaria-only [Formula: see text] COVID-19-only [Formula: see text], and co-infection [Formula: see text] models at the disease-free equilibrium using the next-generation matrix method. We further determine the conditions for stochastic stability in malaria-only, COVID-19-only, and co-infection scenarios. Moreover, we investigate the sufficient conditions for disease extinction and persistence based on the reproductive numbers. Finally, we utilize the Euler–Maruyama numerical scheme to simulate the co-infection dynamics and support the theoretical findings.

Keywords

• Stochastic model
• Gaussian distribution
• global stability
• local stability
• 37N25
• 60H10