{"title":"DYNAMICS OF AN SIRS EPIDEMIC MODEL WITH PERIODIC INFECTION RATE ON A SCALE-FREE NETWORK","authors":"Hongquan Sun, Hong Li, Zhangsheng Zhu","doi":"10.1142/s0218339022500243","DOIUrl":null,"url":null,"abstract":"Influenced by seasonal changes, the infection rate of many infectious diseases fluctuates in cycles. In this paper, we propose and investigate an SIRS model on a scale-free network. To model seasonality, we assume that the infection rate is periodic. The existence and positivity of solutions of the proposed model are proved and the basic reproduction number [Formula: see text] is defined. The global stability of steady states is determined by rigorous mathematical analysis. When [Formula: see text], the disease-free equilibrium [Formula: see text] is globally asymptotically stable. When [Formula: see text], the system has a unique positive periodic solution [Formula: see text], and [Formula: see text] is globally asymptotically stable. Numerical simulations are performed to support our theoretic results, and the effects of various parameters on the amplitude and mean of infected individuals are studied. The sensitivity of parameters of the basic reproduction number [Formula: see text] is solved by the Sobol global sensitivity analysis method, and the results show that the effects of the parameters [Formula: see text] and [Formula: see text] on [Formula: see text] are remarkable.","PeriodicalId":54872,"journal":{"name":"Journal of Biological Systems","volume":" ","pages":""},"PeriodicalIF":1.3000,"publicationDate":"2022-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Biological Systems","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1142/s0218339022500243","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Influenced by seasonal changes, the infection rate of many infectious diseases fluctuates in cycles. In this paper, we propose and investigate an SIRS model on a scale-free network. To model seasonality, we assume that the infection rate is periodic. The existence and positivity of solutions of the proposed model are proved and the basic reproduction number [Formula: see text] is defined. The global stability of steady states is determined by rigorous mathematical analysis. When [Formula: see text], the disease-free equilibrium [Formula: see text] is globally asymptotically stable. When [Formula: see text], the system has a unique positive periodic solution [Formula: see text], and [Formula: see text] is globally asymptotically stable. Numerical simulations are performed to support our theoretic results, and the effects of various parameters on the amplitude and mean of infected individuals are studied. The sensitivity of parameters of the basic reproduction number [Formula: see text] is solved by the Sobol global sensitivity analysis method, and the results show that the effects of the parameters [Formula: see text] and [Formula: see text] on [Formula: see text] are remarkable.
期刊介绍:
The Journal of Biological Systems is published quarterly. The goal of the Journal is to promote interdisciplinary approaches in Biology and in Medicine, and the study of biological situations with a variety of tools, including mathematical and general systems methods. The Journal solicits original research papers and survey articles in areas that include (but are not limited to):
Complex systems studies; isomorphies; nonlinear dynamics; entropy; mathematical tools and systems theories with applications in Biology and Medicine.
Interdisciplinary approaches in Biology and Medicine; transfer of methods from one discipline to another; integration of biological levels, from atomic to molecular, macromolecular, cellular, and organic levels; animal biology; plant biology.
Environmental studies; relationships between individuals, populations, communities and ecosystems; bioeconomics, management of renewable resources; hierarchy theory; integration of spatial and time scales.
Evolutionary biology; co-evolutions; genetics and evolution; branching processes and phyllotaxis.
Medical systems; physiology; cardiac modeling; computer models in Medicine; cancer research; epidemiology.
Numerical simulations and computations; numerical study and analysis of biological data.
Epistemology; history of science.
The journal will also publish book reviews.