{"title":"Modeling and control of hepatitis B virus transmission dynamics using fractional order differential equations","authors":"","doi":"10.28919/cmbn/8174","DOIUrl":null,"url":null,"abstract":"Hepatitis B virus (HBV) continues to pose a significant global health burden, necessitating the development of accurate and effective mathematical models to understand its transmission dynamics and devise optimal control strategies. In this research paper, we present a fractional order model for Hepatitis B virus transmission, incorporating the complexities of memory effects and non-local interactions in disease spread. The proposed fractional order model is formulated as a system of differential equations, with distinct compartments. We employ fractional order derivatives to capture the long-term memory and non-local interactions inherent in HBV transmission, offering a more realistic representation of the epidemic dynamics. To assess the stability and control potential of the model, we conduct rigorous mathematical analysis. The basic reproduction number is computed using the next generation matrix approach to determine the disease’s potential for spreading in the population. Critical points of the model are identified, and disease-free equilibrium points are obtained to assess their stability conditions. Furthermore, we derive endemic equilibrium points for the model, and their stability is analyzed using Jacobian transformation.To optimize control measures, sensitivity analysis of the model parameters is performed to identify influential factors affecting disease transmission. Numerical simulations of the fractional order model are implemented using the Adams-type Predictor-Corrector method, and the results demonstrate the effectiveness of the proposed control strategies in curbing the spread of HBV.","PeriodicalId":44079,"journal":{"name":"Communications in Mathematical Biology and Neuroscience","volume":null,"pages":null},"PeriodicalIF":0.5000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Communications in Mathematical Biology and Neuroscience","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.28919/cmbn/8174","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Hepatitis B virus (HBV) continues to pose a significant global health burden, necessitating the development of accurate and effective mathematical models to understand its transmission dynamics and devise optimal control strategies. In this research paper, we present a fractional order model for Hepatitis B virus transmission, incorporating the complexities of memory effects and non-local interactions in disease spread. The proposed fractional order model is formulated as a system of differential equations, with distinct compartments. We employ fractional order derivatives to capture the long-term memory and non-local interactions inherent in HBV transmission, offering a more realistic representation of the epidemic dynamics. To assess the stability and control potential of the model, we conduct rigorous mathematical analysis. The basic reproduction number is computed using the next generation matrix approach to determine the disease’s potential for spreading in the population. Critical points of the model are identified, and disease-free equilibrium points are obtained to assess their stability conditions. Furthermore, we derive endemic equilibrium points for the model, and their stability is analyzed using Jacobian transformation.To optimize control measures, sensitivity analysis of the model parameters is performed to identify influential factors affecting disease transmission. Numerical simulations of the fractional order model are implemented using the Adams-type Predictor-Corrector method, and the results demonstrate the effectiveness of the proposed control strategies in curbing the spread of HBV.
期刊介绍:
Communications in Mathematical Biology and Neuroscience (CMBN) is a peer-reviewed open access international journal, which is aimed to provide a publication forum for important research in all aspects of mathematical biology and neuroscience. This journal will accept high quality articles containing original research results and survey articles of exceptional merit.