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.
Authors
- Samuel M. Naandam
- Michael Asamani Pobbi (ORCID: https://orcid.org/0000-0001-5687-6528)
- Stephen E. Moore (ORCID: https://orcid.org/0000-0002-5670-4176)
Institutions
- University of Cape Coast (GH)
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