A novel SVIR epidemic model with jumps for understanding the dynamics of the spread of dual diseases

The emergence of multi-disease epidemics presents an escalating threat to global health. In response to this serious challenge, we present an innovative stochastic susceptible-vaccinated-infected-recovered epidemic model that addresses the dynamics of two diseases alongside intricate vaccination strategies. Our novel model undergoes a comprehensive exploration through both theoretical and numerical analyses. The stopping time concept, along with appropriate Lyapunov functions, allows us to explore the possibility of a globally positive solution. Through the derivation of reproduction numbers associated with the stochastic model, we establish criteria for the potential extinction of the diseases. The conditions under which one or both diseases may persist are explained. In the numerical aspect, we derive a computational scheme based on the Milstein method. The scheme will not only substantiate the theoretical results but also facilitate the examination of the impact of parameters on disease dynamics. Through examples and simulations, we have a crucial impact of varying parameters on the system's behavior.

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Publication Details

Journal
Chaos An Interdisciplinary Journal of Nonlinear Science
Published
2024-09-01
DOI
https://doi.org/10.1063/5.0175352
Citations
17
Primary Topic
Mathematical and Theoretical Epidemiology and Ecology Models
Type
article
Field-Weighted Citation Impact
9.23

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article

A novel SVIR epidemic model with jumps for understanding the dynamics of the spread of dual diseases

Hasib Khan, Jungang Wang, Yufeng Nie, Abdulwasea Alkhazzan et al.
17 citations
Chaos An Interdisciplinary Journal of Nonlinear Science
Mathematical and Theoretical Epidemiology and Ecology Models
9.23
article

A novel SVIR epidemic model with jumps for understanding the dynamics of the spread of dual diseases

Hasib Khan, Jungang Wang, Yufeng Nie, Abdulwasea Alkhazzan, Jehad Alzabut
article en
17 citations

Abstract

The emergence of multi-disease epidemics presents an escalating threat to global health. In response to this serious challenge, we present an innovative stochastic susceptible-vaccinated-infected-recovered epidemic model that addresses the dynamics of two diseases alongside intricate vaccination strategies. Our novel model undergoes a comprehensive exploration through both theoretical and numerical analyses. The stopping time concept, along with appropriate Lyapunov functions, allows us to explore the possibility of a globally positive solution. Through the derivation of reproduction numbers associated with the stochastic model, we establish criteria for the potential extinction of the diseases. The conditions under which one or both diseases may persist are explained. In the numerical aspect, we derive a computational scheme based on the Milstein method. The scheme will not only substantiate the theoretical results but also facilitate the examination of the impact of parameters on disease dynamics. Through examples and simulations, we have a crucial impact of varying parameters on the system's behavior.

Chaos An Interdisciplinary Journal of Nonlinear ScienceVol. 34(9)
Shaheed Benazir Bhutto University (PK), Prince Sultan University (SA), Sana'a University (YE), Northwestern Polytechnical University (CN), Ostim Technical University (TR)
Fundamental Research Funds for the Central Universities
Good health and well-being
Openalex Percentile: Top 2%
Mathematical and Theoretical Epidemiology and Ecology Models
9.23
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