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

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.

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Publication Details

Journal
Applied Mathematics in Science and Engineering
Published
2025-03-19
DOI
https://doi.org/10.1080/27690911.2025.2478041
Citations
3
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
2.74
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article

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

Samuel M. Naandam, Michael Asamani Pobbi, Stephen E. Moore
3 citations
Applied Mathematics in Science and Engineering
COVID-19 epidemiological studies
2.74
article

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

Samuel M. Naandam, Michael Asamani Pobbi, Stephen E. Moore
article en
3 citations

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.

Applied Mathematics in Science and EngineeringVol. 33(1)
University of Cape Coast (GH)
Zero hunger
Openalex Percentile: Top 12%
COVID-19 epidemiological studies
2.74
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Mathematical modelling and analysis of stochastic malaria and COVID-19 co-infection model — Samuel M. Naandam, Michael Asamani Pobbi, et al. · Applied Mathematics in Science and Engineering (2025) | TGRS Research Map | TGRS