article · Franklin Open
Malaria remains a major mosquito-borne disease causing fever, chills, and headaches, managed primarily through blood testing and antimalarial medications. Mathematical models provide valuable tools for evaluating prevention and eradication strategies. This research establishes a deterministic compartmental framework consisting of susceptible, latent, infected, and recovered populations to evaluate transmission patterns and the impact of enlightened therapy. The basic reproduction number is derived alongside disease-free and endemic equilibrium states. Using Lyapunov functions, Laplace transformations, and software simulations, the stability and reliability of the model are confirmed. Additionally, the approach integrates Caputo fractional-order derivatives to assess how varying derivative orders influence disease dynamics and intervention outcomes, presenting visual simulations to aid public health planning.
Malaria places an enormous health burden on populations, particularly across Africa. By incorporating fractional-order mathematics and therapy interventions into epidemic modelling, public health planners can gain clearer theoretical insight into disease transmission thresholds. These mathematical assessments help health authorities understand how education and medical therapies together influence potential eradication pathways.
The research is early-stage theoretical modelling, offering mathematical frameworks and simulation data rather than a commercial product. It could potentially inform epidemiological simulation software used by public health bodies, academic researchers, and healthcare policy planners designing intervention programmes. However, moving this work toward applied planning tools would require extensive calibration with real-world clinical and field data.
AI-generated from the published abstract. Always read the original work before citing.
This paper examines malaria, a prevalent mosquito-borne disease in Africa that causes fever, chills, and headaches. Diagnosis involves blood tests, and treatment primarily relies on antimalarial drugs. Mathematical modeling is crucial for disease prevention and eradication strategies. The study uses deterministic models to analyze global malaria transmission patterns, focusing on enlightened therapy's effectiveness as a control measure. Four compartmental models depict susceptible, latent, infected, and recovered populations, exploring various disease spread scenarios while ensuring model stability and reliability. Epidemiological principles identify disease-free and endemic equilibria, calculating the basic reproduction number. Stability analysis utilizes Lyapunov functions, supported by Laplace transformation and MAPLE18 simulations for solution derivation. Furthermore, the study investigates the impact of fractional-order derivatives on transmission dynamics and control strategies, analyzing the effects of increasing fractional derivative orders using graphical representations. This research provides insights valuable for public health initiatives and malaria eradication efforts, emphasizing the role of Caputo fractional derivatives in refining malaria control strategies and elucidating the findings for a broader readership appeal.
This page summarises published work. The authoritative version sits with the publisher.
DOI: 10.1016/j.fraope.2024.100147
Is something wrong with this record? Report it or request removal.
Discussion
Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.
No discussion yet. Open the first thread.
New to MARATTO™? Create a free account.
