Mathematical Analysis of Infectious Disease

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E3: Mathematical Biology".

Deadline for manuscript submissions: closed (20 May 2025) | Viewed by 1616

Special Issue Editors


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Guest Editor
School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an 710049, China
Interests: mathematical biology; bifurcation theory and application; data analysis in public health and medicine

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Guest Editor
Department of Mathematics, University of Miami, Coral Gables, FL 33146, USA
Interests: mathematical biology; differential equations; data fitting; agent-based simulations

Special Issue Information

Dear Colleagues,

Mathematical models are actively evolving and playing increasingly significant roles in understanding disease outbreaks, viral dynamics, and many other phenomena in life science. This Special Issue focuses on mathematical methods and their applications in infectious disease modeling. The topics of interest range from the new development of models and techniques to novel mathematical analyses of existing models. We invite original research related, but not limited to, the following topics:

  1. Mechanism-driven or data-driven models of infectious diseases;
  2. Theoretical analysis of infectious disease models;
  3. Data analysis in the field of disease modelling.

Dr. Xiaodan Sun
Dr. Xi Huo
Guest Editors

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Keywords

  • infectious disease modelling
  • epidemic dynamics
  • data analysis
  • agent-based simulation

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Published Papers (1 paper)

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Research

30 pages, 1195 KiB  
Article
Synergistic Impact of Active Case Detection and Early Hospitalization for Controlling the Spread of Yellow Fever Outbreak in Nigeria: An Epidemiological Modeling and Optimal Control Analysis
by Nawaf L. Alsowait, Mohammed M. Al-Shomrani, Ismail Abdulrashid and Salihu S. Musa
Mathematics 2024, 12(23), 3817; https://doi.org/10.3390/math12233817 - 2 Dec 2024
Viewed by 1107
Abstract
Capturing the factors influencing yellow fever (YF) outbreaks is essential for effective public health interventions, especially in regions like Nigeria, where the disease poses significant health risks. This study explores the synergistic effects of active case detection (ACD) and early hospitalization on controlling [...] Read more.
Capturing the factors influencing yellow fever (YF) outbreaks is essential for effective public health interventions, especially in regions like Nigeria, where the disease poses significant health risks. This study explores the synergistic effects of active case detection (ACD) and early hospitalization on controlling YF transmission dynamics. We develop a dynamic model that integrates vaccination, active case detection, and hospitalization to enhance our understanding of disease spread and inform prevention strategies. Our methodology encompasses mechanistic dynamic modeling, optimal control analysis, parameter estimation, model fitting, and sensitivity analyses to study YF transmission dynamics, ensuring the robustness of control measures. We employ advanced mathematical techniques, including next-generation matrix methods, to accurately compute the reproduction number and assess outbreak transmissibility. Rigorous qualitative analysis of the model reveals two equilibria: disease-free and endemic, demonstrating global asymptotic stability and its impact on overall YF transmission dynamics, significantly affecting control and prevention mechanisms. Furthermore, through sensitivity analysis, we identify crucial parameters of the model that require urgent attention for more effective YF control. Moreover, our results highlight the critical roles of ACD and early hospitalization in reducing YF transmission. These insights provide a foundation for informed decision making and resource allocation in epidemic control efforts, ultimately contributing to the enhancement of public health strategies aimed at mitigating the impact of YF outbreaks. Full article
(This article belongs to the Special Issue Mathematical Analysis of Infectious Disease)
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