Stability Analysis and Clinic Phenomenon Simulation of a Fractional-Order HBV Infection Model

In this paper, a fractional-order HBV model was set up based on standard mass action incidences and quasisteady assumption. The basic reproductive number R0 and the cytotoxic T lymphocytes’ immune-response reproductive number R1 were derived. There were three equilibrium points of the model, and sta...

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Main Authors: Yongmei Su, Sinuo Liu, Shurui Song, Xiaoke Li, Yongan Ye
Format: Article
Language:English
Published: Wiley 2020-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2020/8864403
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author Yongmei Su
Sinuo Liu
Shurui Song
Xiaoke Li
Yongan Ye
author_facet Yongmei Su
Sinuo Liu
Shurui Song
Xiaoke Li
Yongan Ye
author_sort Yongmei Su
collection DOAJ
description In this paper, a fractional-order HBV model was set up based on standard mass action incidences and quasisteady assumption. The basic reproductive number R0 and the cytotoxic T lymphocytes’ immune-response reproductive number R1 were derived. There were three equilibrium points of the model, and stable analysis of each equilibrium point was given with corresponding hypothesis about R0 or R1. Some numerical simulations were also given based on HBeAg clinical data, and the simulation showed that there existed positive logarithmic correlation between the number of infected cells and HBeAg, which was consistent with the clinical facts. The simulation also showed that the clinical individual differences should be reflected by the fractional-order model.
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issn 1076-2787
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publishDate 2020-01-01
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spelling doaj-art-c2e50bde88074f2980860da39df0800c2025-02-03T01:05:21ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/88644038864403Stability Analysis and Clinic Phenomenon Simulation of a Fractional-Order HBV Infection ModelYongmei Su0Sinuo Liu1Shurui Song2Xiaoke Li3Yongan Ye4School of Mathematics and Physics, University of Science and Technology Beijing, Beijing 100083, ChinaSchool of Mathematics and Physics, University of Science and Technology Beijing, Beijing 100083, ChinaSchool of Mathematics and Physics, University of Science and Technology Beijing, Beijing 100083, ChinaInstitute of Liver Diseases, Beijing University of Chinese Medicine, Dongzhimen Hospital Affiliated to Beijing University of Chinese Medicine, Beijing 100700, ChinaInstitute of Liver Diseases, Beijing University of Chinese Medicine, Dongzhimen Hospital Affiliated to Beijing University of Chinese Medicine, Beijing 100700, ChinaIn this paper, a fractional-order HBV model was set up based on standard mass action incidences and quasisteady assumption. The basic reproductive number R0 and the cytotoxic T lymphocytes’ immune-response reproductive number R1 were derived. There were three equilibrium points of the model, and stable analysis of each equilibrium point was given with corresponding hypothesis about R0 or R1. Some numerical simulations were also given based on HBeAg clinical data, and the simulation showed that there existed positive logarithmic correlation between the number of infected cells and HBeAg, which was consistent with the clinical facts. The simulation also showed that the clinical individual differences should be reflected by the fractional-order model.http://dx.doi.org/10.1155/2020/8864403
spellingShingle Yongmei Su
Sinuo Liu
Shurui Song
Xiaoke Li
Yongan Ye
Stability Analysis and Clinic Phenomenon Simulation of a Fractional-Order HBV Infection Model
Complexity
title Stability Analysis and Clinic Phenomenon Simulation of a Fractional-Order HBV Infection Model
title_full Stability Analysis and Clinic Phenomenon Simulation of a Fractional-Order HBV Infection Model
title_fullStr Stability Analysis and Clinic Phenomenon Simulation of a Fractional-Order HBV Infection Model
title_full_unstemmed Stability Analysis and Clinic Phenomenon Simulation of a Fractional-Order HBV Infection Model
title_short Stability Analysis and Clinic Phenomenon Simulation of a Fractional-Order HBV Infection Model
title_sort stability analysis and clinic phenomenon simulation of a fractional order hbv infection model
url http://dx.doi.org/10.1155/2020/8864403
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