Cargando…
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...
Autores principales: | , , , |
---|---|
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 |
_version_ | 1784819350923902976 |
---|---|
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. |
format | Online Article Text |
id | pubmed-9610737 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT alkhazzanabdulwasea anewstochasticsplitstepthnonstandardfinitedifferencemethodforthedevelopedsvirepidemicmodelwithtemporaryimmunitiesandgeneralincidencerates AT wangjungang anewstochasticsplitstepthnonstandardfinitedifferencemethodforthedevelopedsvirepidemicmodelwithtemporaryimmunitiesandgeneralincidencerates AT nieyufeng anewstochasticsplitstepthnonstandardfinitedifferencemethodforthedevelopedsvirepidemicmodelwithtemporaryimmunitiesandgeneralincidencerates AT hattafkhalid anewstochasticsplitstepthnonstandardfinitedifferencemethodforthedevelopedsvirepidemicmodelwithtemporaryimmunitiesandgeneralincidencerates AT alkhazzanabdulwasea newstochasticsplitstepthnonstandardfinitedifferencemethodforthedevelopedsvirepidemicmodelwithtemporaryimmunitiesandgeneralincidencerates AT wangjungang newstochasticsplitstepthnonstandardfinitedifferencemethodforthedevelopedsvirepidemicmodelwithtemporaryimmunitiesandgeneralincidencerates AT nieyufeng newstochasticsplitstepthnonstandardfinitedifferencemethodforthedevelopedsvirepidemicmodelwithtemporaryimmunitiesandgeneralincidencerates AT hattafkhalid newstochasticsplitstepthnonstandardfinitedifferencemethodforthedevelopedsvirepidemicmodelwithtemporaryimmunitiesandgeneralincidencerates |