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Impact of information intervention on stochastic hepatitis B model and its variable-order fractional network
This paper aims at analyzing the dynamical behavior of a SIR hepatitis B epidemic stochastic model via a novel approach by incorporating the effect of information interventions and random perturbations. Initially, we demonstrate the positivity and global existence of the solutions. Afterward, we der...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8814815/ https://www.ncbi.nlm.nih.gov/pubmed/35136487 http://dx.doi.org/10.1140/epjs/s11734-022-00453-5 |
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author | Din, Anwarud Li, Yongjin Yusuf, Abdullahi Liu, Jinping Aly, Ayman A. |
author_facet | Din, Anwarud Li, Yongjin Yusuf, Abdullahi Liu, Jinping Aly, Ayman A. |
author_sort | Din, Anwarud |
collection | PubMed |
description | This paper aims at analyzing the dynamical behavior of a SIR hepatitis B epidemic stochastic model via a novel approach by incorporating the effect of information interventions and random perturbations. Initially, we demonstrate the positivity and global existence of the solutions. Afterward, we derive the stochastic threshold parameter [Formula: see text] , followed by the fact that this number concludes the transmission of hepatitis B from the population. By increasing the intensity of noise, we get [Formula: see text] less than one, inferring that ultimately hepatitis B will lapse. While decreasing the intensity of noise to a sufficient level, we have [Formula: see text] . For the case [Formula: see text] , adequate results for the presence of stationary distribution are achieved, showing the prevalence of hepatitis B. The present study also involves the derivation of the necessary conditions for the persistence of the epidemic. Finally, the main theoretical solutions are plotted through simulations. Discussion on theoretical and numerical results shows that utilizing random perturbations and information interventions have a pronounced impact on the syndrome’s dynamics. Furthermore, since most communities interact with each other, and the disease spread rate is affected by this factor, a new variable-order fractional network of the stochastic hepatitis B model is offered. Subsequently, this study will provide a robust theoretical basis for comprehending worldwide SIR stochastic and variable-order fractional network-related case studies. |
format | Online Article Text |
id | pubmed-8814815 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-88148152022-02-04 Impact of information intervention on stochastic hepatitis B model and its variable-order fractional network Din, Anwarud Li, Yongjin Yusuf, Abdullahi Liu, Jinping Aly, Ayman A. Eur Phys J Spec Top Regular Article This paper aims at analyzing the dynamical behavior of a SIR hepatitis B epidemic stochastic model via a novel approach by incorporating the effect of information interventions and random perturbations. Initially, we demonstrate the positivity and global existence of the solutions. Afterward, we derive the stochastic threshold parameter [Formula: see text] , followed by the fact that this number concludes the transmission of hepatitis B from the population. By increasing the intensity of noise, we get [Formula: see text] less than one, inferring that ultimately hepatitis B will lapse. While decreasing the intensity of noise to a sufficient level, we have [Formula: see text] . For the case [Formula: see text] , adequate results for the presence of stationary distribution are achieved, showing the prevalence of hepatitis B. The present study also involves the derivation of the necessary conditions for the persistence of the epidemic. Finally, the main theoretical solutions are plotted through simulations. Discussion on theoretical and numerical results shows that utilizing random perturbations and information interventions have a pronounced impact on the syndrome’s dynamics. Furthermore, since most communities interact with each other, and the disease spread rate is affected by this factor, a new variable-order fractional network of the stochastic hepatitis B model is offered. Subsequently, this study will provide a robust theoretical basis for comprehending worldwide SIR stochastic and variable-order fractional network-related case studies. Springer Berlin Heidelberg 2022-02-04 2022 /pmc/articles/PMC8814815/ /pubmed/35136487 http://dx.doi.org/10.1140/epjs/s11734-022-00453-5 Text en © The Author(s), under exclusive licence to EDP Sciences, Springer-Verlag GmbH Germany, part of Springer Nature 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Regular Article Din, Anwarud Li, Yongjin Yusuf, Abdullahi Liu, Jinping Aly, Ayman A. Impact of information intervention on stochastic hepatitis B model and its variable-order fractional network |
title | Impact of information intervention on stochastic hepatitis B model and its variable-order fractional network |
title_full | Impact of information intervention on stochastic hepatitis B model and its variable-order fractional network |
title_fullStr | Impact of information intervention on stochastic hepatitis B model and its variable-order fractional network |
title_full_unstemmed | Impact of information intervention on stochastic hepatitis B model and its variable-order fractional network |
title_short | Impact of information intervention on stochastic hepatitis B model and its variable-order fractional network |
title_sort | impact of information intervention on stochastic hepatitis b model and its variable-order fractional network |
topic | Regular Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8814815/ https://www.ncbi.nlm.nih.gov/pubmed/35136487 http://dx.doi.org/10.1140/epjs/s11734-022-00453-5 |
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