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A New Stochastic Split-Step θ-Nonstandard Finite Difference Method for the Developed SVIR Epidemic Model with Temporary Immunities and General Incidence Rates

In this paper, an SVIR epidemic model with temporary immunities and general incidence rates is constructed and analyzed. By utilizing Lyapunov functions, we prove the existence and uniqueness of the positive global solution of the constructed model, as well as the sufficient conditions of extinction...

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Autores principales: Alkhazzan, Abdulwasea, Wang, Jungang, Nie, Yufeng, Hattaf, Khalid
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9610737/
https://www.ncbi.nlm.nih.gov/pubmed/36298547
http://dx.doi.org/10.3390/vaccines10101682
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author Alkhazzan, Abdulwasea
Wang, Jungang
Nie, Yufeng
Hattaf, Khalid
author_facet Alkhazzan, Abdulwasea
Wang, Jungang
Nie, Yufeng
Hattaf, Khalid
author_sort Alkhazzan, Abdulwasea
collection PubMed
description In this paper, an SVIR epidemic model with temporary immunities and general incidence rates is constructed and analyzed. By utilizing Lyapunov functions, we prove the existence and uniqueness of the positive global solution of the constructed model, as well as the sufficient conditions of extinction and persistence of disease, are provided. Due to the difficulty of obtaining the analytical solution to our model, we construct two numerical schemes to generate an approximate solution to the model. The first one is called the split-step [Formula: see text]-Milstein (SSTM) method, and the second one is called the stochastic split-step [Formula: see text]-nonstandard finite difference (SSSNSFD) method, which is designed by merging split-step [Formula: see text] method with stochastic nonstandard finite difference method for the first time in this paper. Further, we prove the positivity, boundedness, and stability of the SSSTNSFD method. By employing the two mentioned methods, we support the validity of the studied theoretical results, as well, the effect of the length of immunity periods, parameters values of the incidence rates, and noise on the dynamics of the model are discussed and simulated. The increase in the size of time step size plays a vital role in revealing the method that preserves positivity, boundedness, and stability. To this end, a comparison between the proposed numerical methods is carried out graphically.
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spelling pubmed-96107372022-10-28 A New Stochastic Split-Step θ-Nonstandard Finite Difference Method for the Developed SVIR Epidemic Model with Temporary Immunities and General Incidence Rates Alkhazzan, Abdulwasea Wang, Jungang Nie, Yufeng Hattaf, Khalid Vaccines (Basel) Article In this paper, an SVIR epidemic model with temporary immunities and general incidence rates is constructed and analyzed. By utilizing Lyapunov functions, we prove the existence and uniqueness of the positive global solution of the constructed model, as well as the sufficient conditions of extinction and persistence of disease, are provided. Due to the difficulty of obtaining the analytical solution to our model, we construct two numerical schemes to generate an approximate solution to the model. The first one is called the split-step [Formula: see text]-Milstein (SSTM) method, and the second one is called the stochastic split-step [Formula: see text]-nonstandard finite difference (SSSNSFD) method, which is designed by merging split-step [Formula: see text] method with stochastic nonstandard finite difference method for the first time in this paper. Further, we prove the positivity, boundedness, and stability of the SSSTNSFD method. By employing the two mentioned methods, we support the validity of the studied theoretical results, as well, the effect of the length of immunity periods, parameters values of the incidence rates, and noise on the dynamics of the model are discussed and simulated. The increase in the size of time step size plays a vital role in revealing the method that preserves positivity, boundedness, and stability. To this end, a comparison between the proposed numerical methods is carried out graphically. MDPI 2022-10-09 /pmc/articles/PMC9610737/ /pubmed/36298547 http://dx.doi.org/10.3390/vaccines10101682 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Alkhazzan, Abdulwasea
Wang, Jungang
Nie, Yufeng
Hattaf, Khalid
A New Stochastic Split-Step θ-Nonstandard Finite Difference Method for the Developed SVIR Epidemic Model with Temporary Immunities and General Incidence Rates
title A New Stochastic Split-Step θ-Nonstandard Finite Difference Method for the Developed SVIR Epidemic Model with Temporary Immunities and General Incidence Rates
title_full A New Stochastic Split-Step θ-Nonstandard Finite Difference Method for the Developed SVIR Epidemic Model with Temporary Immunities and General Incidence Rates
title_fullStr A New Stochastic Split-Step θ-Nonstandard Finite Difference Method for the Developed SVIR Epidemic Model with Temporary Immunities and General Incidence Rates
title_full_unstemmed A New Stochastic Split-Step θ-Nonstandard Finite Difference Method for the Developed SVIR Epidemic Model with Temporary Immunities and General Incidence Rates
title_short A New Stochastic Split-Step θ-Nonstandard Finite Difference Method for the Developed SVIR Epidemic Model with Temporary Immunities and General Incidence Rates
title_sort new stochastic split-step θ-nonstandard finite difference method for the developed svir epidemic model with temporary immunities and general incidence rates
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9610737/
https://www.ncbi.nlm.nih.gov/pubmed/36298547
http://dx.doi.org/10.3390/vaccines10101682
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