Malaria and COVID-19 co-dynamics: A mathematical model and optimal control
S Y Tchoumi1, M L Diagne2, H Rwezaura3
1Department of Mathematics and Computer Sciences ENSAI, University of NGaoundere, P.O. Box 455 Ngaoundere, Cameroon.
Applied Mathematical Modelling
|July 7, 2021
Summary
This study models malaria and COVID-19 co-dynamics, finding that combined prevention strategies are more effective than single measures for mitigating disease spread. Mathematical analysis supports concurrent interventions for better public health outcomes.
Area of Science:
- Epidemiology
- Mathematical Biology
- Public Health
Background:
- Malaria remains a significant global health issue, particularly in tropical regions.
- The COVID-19 pandemic presents complex challenges, exacerbating existing health crises.
- Co-infection dynamics between malaria and COVID-19 require urgent investigation.
Purpose of the Study:
- To develop and analyze a mathematical model for the co-dynamics of malaria and COVID-19.
- To investigate the stability of disease-free and endemic equilibria for both diseases.
- To derive and analyze optimal control strategies for mitigating co-infection.
Main Methods:
- Formulation of a mathematical model incorporating epidemiological features of malaria and COVID-19.
- Analysis of sub-models for individual disease dynamics and stability of equilibria.
- Application of Pontryagin's Maximum Principle for optimal control derivation.
Main Results:
- The COVID-19 sub-model exhibits globally asymptotically stable equilibria.
- The malaria sub-model may display backward bifurcation under specific conditions.
- The dual model equilibria are locally stable, with global stability potentially limited by backward bifurcation.
Conclusions:
- Concurrent application of malaria and COVID-19 protective measures is more effective than single interventions.
- Mathematical modeling provides insights into optimal control strategies for co-endemic diseases.
- Integrated public health strategies are crucial for managing complex disease outbreaks.
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