Functional Differential Equations and Epidemiological Modelling, 2nd Edition

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Difference and Differential Equations".

Deadline for manuscript submissions: 1 June 2025 | Viewed by 2454

Special Issue Editor


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Guest Editor
Department of Mathematics, Sun Yat-sen University, Guangzhou 510275, China
Interests: functional analysis; functional differential equations; ordinary differential equation; fuzzy logic
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Special Issue Information

Dear Colleagues,

This Special Issue is a continuation of the previous successful Special Issue “Functional Differential Equations and Epidemiological Modelling” in the MDPI journal Mathematics.

Overview:

Functional differential equations play a major role in mathematical modeling. Over the past few years, the world has faced a major challenge from rapidly spreading and deathly infectious diseases. These infectious diseases have infected and even killed millions of people all over the world. It is important to note that statistics (numbers of infected and deaths) provided by nations around the globe cannot offer a true numerical figure, because it is not possible to confirm if reported cases are cases unless verified, and there are undoubtedly other unknown infected individuals. Humans, on their part, as they have the goal of managing the world in which they live, have taken drastic steps to strike back to avoid the spread of these epidemics. To date, countless data have been collected in different countries, showing the number of deaths and recoveries in the literature. Mathematical models may be useful if they are capable of replicating the observed facts, including the evaluation of the proposed models with experimental or collected data. If mathematical simulations are in strong compliance with experimental results, the future can be predicted. These steps give rise to research with many objectives.

This Special Issue aims at providing a specific opportunity to review the stability strategies for deadly diseases through modeling with functional applications. It will bring together researchers in relevant areas to discuss the latest progress, new research methodologies, and potential research topics. All original papers related to modeling and their application for optimization and control are welcome. The Special Issue will focus on, but is not limited to, the following topics:

 Topics

  • Theory and applications of functional differential equations;
  • Functional differential equations;
  • Differential equations;
  • Stochastic differential equations;
  • Fractional differential equations;
  • Deterministic and stochastic models of infectious diseases;
  • Fractional models of infectious diseases;
  • Review performance of mathematical models with delay equations with functional applications;
  • Theoretical, computational, and realistic nature of infectious disease models;
  • Review of the effect of new fractal differential and integral operators for modelling infectious diseases/sources;
  • Chaos theory for biological problems with functional application.

Prof. Dr. Yongjin Li
Guest Editor

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Published Papers (2 papers)

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Research

15 pages, 744 KiB  
Article
Differential Equations and Applications to COVID-19
by Tierry Mitonsou Hounkonnou and Laure Gouba
Mathematics 2024, 12(17), 2738; https://doi.org/10.3390/math12172738 - 2 Sep 2024
Viewed by 1042
Abstract
This paper focuses on the application of the Verhulst logistic equation to model in retrospect the total COVID-19 cases in Senegal during the period from April 2022 to April 2023. Our predictions for April 2023 are compared with the real COVID-19 data for [...] Read more.
This paper focuses on the application of the Verhulst logistic equation to model in retrospect the total COVID-19 cases in Senegal during the period from April 2022 to April 2023. Our predictions for April 2023 are compared with the real COVID-19 data for April 2023 to assess the accuracy of the model. The data analysis is conducted using Python programming language, which allows for efficient data processing and prediction generation. Full article
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12 pages, 273 KiB  
Article
The Convergence and Boundedness of Solutions to SFDEs with the G-Framework
by Rahman Ullah, Faiz Faizullah and Quanxin Zhu
Mathematics 2024, 12(2), 279; https://doi.org/10.3390/math12020279 - 15 Jan 2024
Viewed by 942
Abstract
Generally, stochastic functional differential equations (SFDEs) pose a challenge as they often lack explicit exact solutions. Consequently, it becomes necessary to seek certain favorable conditions under which numerical solutions can converge towards the exact solutions. This article aims to delve into the convergence [...] Read more.
Generally, stochastic functional differential equations (SFDEs) pose a challenge as they often lack explicit exact solutions. Consequently, it becomes necessary to seek certain favorable conditions under which numerical solutions can converge towards the exact solutions. This article aims to delve into the convergence analysis of solutions for stochastic functional differential equations by employing the framework of G-Brownian motion. To establish the goal, we find a set of useful monotone type conditions and work within the space Cr((,0];Rn). The investigation conducted in this article confirms the mean square boundedness of solutions. Furthermore, this study enables us to compute both LG2 and exponential estimates. Full article
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