{"title":"涉及移民和疫苗接种的COVID-19延迟传播模型的稳定性分析","authors":"","doi":"10.28919/cmbn/8151","DOIUrl":null,"url":null,"abstract":"In this paper, we propose and analyze the dynamical behavior of a delayed COVID-19 transmission model with immigration, vaccination and general incidence function. The time delay into the proposed model represents the incubation period. Firstly, the well-posedness of the model is investigated. Moreover, we construct appropriate Lyapunov function to prove the global stability of equilibria. To support the theoretical results, numerical simulations are presented at the end of the study.","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":"{\"title\":\"Stability analysis of a delayed COVID-19 transmission model involving immigration and vaccination\",\"authors\":\"\",\"doi\":\"10.28919/cmbn/8151\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose and analyze the dynamical behavior of a delayed COVID-19 transmission model with immigration, vaccination and general incidence function. The time delay into the proposed model represents the incubation period. Firstly, the well-posedness of the model is investigated. Moreover, we construct appropriate Lyapunov function to prove the global stability of equilibria. To support the theoretical results, numerical simulations are presented at the end of the study.\",\"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/8151\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Communications in Mathematical Biology and Neuroscience","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.28919/cmbn/8151","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Stability analysis of a delayed COVID-19 transmission model involving immigration and vaccination
In this paper, we propose and analyze the dynamical behavior of a delayed COVID-19 transmission model with immigration, vaccination and general incidence function. The time delay into the proposed model represents the incubation period. Firstly, the well-posedness of the model is investigated. Moreover, we construct appropriate Lyapunov function to prove the global stability of equilibria. To support the theoretical results, numerical simulations are presented at the end of the study.
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.