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Mathematical analysis of a new nonlinear stochastic hepatitis B epidemic model with vaccination effect and a case study

This work present a detailed analysis of a stochastic delayed model which governs the transmission mechanism of the Hepatitis B virus (HBV) while considering the white noises and the effect of vaccinations. It is assumed that the perturbations are nonlinear and an individual may lose his/her immunit...

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Autores principales: Din, Anwarud, Li, Yongjin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9073523/
https://www.ncbi.nlm.nih.gov/pubmed/35542829
http://dx.doi.org/10.1140/epjp/s13360-022-02748-x
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author Din, Anwarud
Li, Yongjin
author_facet Din, Anwarud
Li, Yongjin
author_sort Din, Anwarud
collection PubMed
description This work present a detailed analysis of a stochastic delayed model which governs the transmission mechanism of the Hepatitis B virus (HBV) while considering the white noises and the effect of vaccinations. It is assumed that the perturbations are nonlinear and an individual may lose his/her immunity after the vaccination, that is, the vaccination can produce temporal immunity. Based on the characteristics of the disease and the underlying assumptions, we formulated the associated deterministic model for which the threshold parameter [Formula: see text] is calculated. The model was further extended to a stochastic model and it is well-justified that the model is both mathematically and biologically feasible by showing that the model solution exists globally, bounded stochastically and is positive. By utilizing the concepts of stochastic theory and by constructing appropriate Lyapunov functions, we developed the theory for the extinction and persistence of the disease. Further, it is shown that the model is ergodic and has a unique stationary distribution. The stochastic bifurcation theory is utilized and a detailed bifurcation analysis of the model is presented. By using the standard curve fitting tools, we fitted the model against the available HBV data in Pakistan from March 2018 to February 2019 and accordingly the parameters of the model were estimated. These estimated values were used in simulating the model, theoretical findings of the study are validated through simulations and predictions were drawn. Simulations suggest that for a complete understanding of HBV dynamics, one must include time delay into such studies, and improvements in every vaccination program are unavoidable.
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spelling pubmed-90735232022-05-06 Mathematical analysis of a new nonlinear stochastic hepatitis B epidemic model with vaccination effect and a case study Din, Anwarud Li, Yongjin Eur Phys J Plus Regular Article This work present a detailed analysis of a stochastic delayed model which governs the transmission mechanism of the Hepatitis B virus (HBV) while considering the white noises and the effect of vaccinations. It is assumed that the perturbations are nonlinear and an individual may lose his/her immunity after the vaccination, that is, the vaccination can produce temporal immunity. Based on the characteristics of the disease and the underlying assumptions, we formulated the associated deterministic model for which the threshold parameter [Formula: see text] is calculated. The model was further extended to a stochastic model and it is well-justified that the model is both mathematically and biologically feasible by showing that the model solution exists globally, bounded stochastically and is positive. By utilizing the concepts of stochastic theory and by constructing appropriate Lyapunov functions, we developed the theory for the extinction and persistence of the disease. Further, it is shown that the model is ergodic and has a unique stationary distribution. The stochastic bifurcation theory is utilized and a detailed bifurcation analysis of the model is presented. By using the standard curve fitting tools, we fitted the model against the available HBV data in Pakistan from March 2018 to February 2019 and accordingly the parameters of the model were estimated. These estimated values were used in simulating the model, theoretical findings of the study are validated through simulations and predictions were drawn. Simulations suggest that for a complete understanding of HBV dynamics, one must include time delay into such studies, and improvements in every vaccination program are unavoidable. Springer Berlin Heidelberg 2022-05-06 2022 /pmc/articles/PMC9073523/ /pubmed/35542829 http://dx.doi.org/10.1140/epjp/s13360-022-02748-x Text en © The Author(s), under exclusive licence to Società Italiana di Fisica and 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
Mathematical analysis of a new nonlinear stochastic hepatitis B epidemic model with vaccination effect and a case study
title Mathematical analysis of a new nonlinear stochastic hepatitis B epidemic model with vaccination effect and a case study
title_full Mathematical analysis of a new nonlinear stochastic hepatitis B epidemic model with vaccination effect and a case study
title_fullStr Mathematical analysis of a new nonlinear stochastic hepatitis B epidemic model with vaccination effect and a case study
title_full_unstemmed Mathematical analysis of a new nonlinear stochastic hepatitis B epidemic model with vaccination effect and a case study
title_short Mathematical analysis of a new nonlinear stochastic hepatitis B epidemic model with vaccination effect and a case study
title_sort mathematical analysis of a new nonlinear stochastic hepatitis b epidemic model with vaccination effect and a case study
topic Regular Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9073523/
https://www.ncbi.nlm.nih.gov/pubmed/35542829
http://dx.doi.org/10.1140/epjp/s13360-022-02748-x
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