article · Healthcare Analytics
Mathematical modelling provides insights into how malaria and COVID-19 interact when both diseases circulate simultaneously. Using a fractional-order framework based on the Atangana-Baleanu derivative, the dynamics of co-infection across humans and mosquitoes are described across different disease stages. Mathematical analysis confirms that unique solutions exist for the model and defines the basic reproduction number to assess epidemic thresholds. Stability analyses explore both disease-free and endemic states for individual infections and their combined presence. Computational simulations, carried out using an approximate polynomial interpolation technique, demonstrate the impact of interventions. The findings show that implementing preventive measures against either condition lowers the likelihood of developing the other disease upon initial infection, ultimately demonstrating that combined control efforts can substantially suppress transmission towards extinction.
When two major infectious diseases overlap, understanding their interaction is critical for public health planning. This theoretical model clarifies how tackling one disease reduces vulnerability to the other. By demonstrating that preventive measures yield compounding benefits across both malaria and COVID-19, the work provides an analytical foundation to help health authorities design coordinated intervention strategies in regions facing dual disease burdens.
The work represents early-stage theoretical and computational research. It could potentially inform public health software developers, healthcare analysts, and epidemiologists seeking to incorporate co-infection dynamics into disease forecasting tools. However, the abstract does not indicate any direct product development, clinical validation, or immediate commercialisation pathway.
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This study proposes a fractional-order mathematical model for malaria and COVID-19 co-infection using the Atangana-Baleanu Derivative. We explain the various stages of the diseases together in humans and mosquitoes, and we also establish the existence and uniqueness of the fractional order co-infection model solution using the fixed point theorem. We conduct the qualitative analysis along with an epidemic indicator, the basic reproduction number R0 of this model. We investigate the global stability at the disease and endemic free equilibrium of the malaria-only, COVID-19-only, and co-infection models. We run different simulations of the fractional-order co-infection model using a two-step Lagrange interpolation polynomial approximate method with the aid of the Maple software package. The results reveal that reducing the risk of malaria and COVID-19 by taking preventive measures will reduce the risk factor for getting COVID-19 after contracting malaria and will also reduce the risk factor for getting malaria after contracting COVID-19 even to the point of extinction.
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DOI: 10.1016/j.health.2023.100210
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