2024 : 11 : 22

Mohammad Mehdizadeh

Academic rank: Professor
ORCID:
Education: PhD.
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Faculty: 1
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Research

Title
Stability analysis of a nonlinear malaria transmission epidemic model using an effective numerical scheme
Type
JournalPaper
Keywords
Malaria disease, Reproduction number, Local and global stability, Numerical schemes
Year
2024
Journal Scientific Reports
DOI
Researchers Jian Jun He ، Abeer Aljohani ، Shahbaz Mustafa ، Ali Shokri Shokri ، Mohammad Mehdizadeh ، Herbert Mukalazi

Abstract

Malaria is a fever condition that results from Plasmodium parasites, which are transferred to humans by the attacks of infected female Anopheles mosquitos. The deterministic compartmental model was examined using stability theory of differential equations. The reproduction number was obtained to be asymptotically stable conditions for the disease-free, and the endemic equilibria were determined. More so, the qualitatively evaluated model incorporates time-dependent variable controls which was aimed at reducing the proliferation of malaria disease. The reproduction number R was determined to be an asymptotically stable condition for disease free and endemic equilibria. In this paper, we used various schemes such as Runge–Kutta order 4 (RK-4) and non-standard finite difference (NSFD). All of the schemes produce different results, but the most appropriate scheme is NSFD. This is true for all step sizes. Various criteria are used in the NSFD scheme to assess the local and global stability of disease-free and endemic equilibrium points. The Routh–Hurwitz condition is used to validate the local stability and Lyapunov stability theorem is used to prove the global asymptotic stability. Global asymptotic stability is proven for the disease-free equilibrium when . The endemic equilibrium is investigated for stability when . All of the aforementioned schemes and their effects are also numerically demonstrated. The comparative analysis demonstrates that NSFD is superior in every way for the analysis of deterministic epidemic models. The theoretical effects and numerical simulations provided in this text may be used to predict the spread of infectious diseases.