Md Kamrujjaman, Md Shahriar Mahmud, Md Shafiqul Islam
{"title":"具有治疗影响和流行病学非线性发生率的扩散疫苗模型的动力学。","authors":"Md Kamrujjaman, Md Shahriar Mahmud, Md Shafiqul Islam","doi":"10.1080/17513758.2020.1849831","DOIUrl":null,"url":null,"abstract":"<p><p>In this paper, we study a more general diffusive spatially dependent vaccination model for infectious disease. In our diffusive vaccination model, we consider both therapeutic impact and nonlinear incidence rate. Also, in this model, the number of compartments of susceptible, vaccinated and infectious individuals are considered to be functions of both time and location, where the set of locations (equivalently, spatial habitats) is a subset of <math><msup><mrow><mi>R</mi></mrow><mi>n</mi></msup></math> with a smooth boundary. Both local and global stability of the model are studied. Our study shows that if the threshold level <math><msub><mrow><mi>R</mi></mrow><mn>0</mn></msub><mo>≤</mo><mn>1</mn><mo>,</mo></math> the disease-free equilibrium <math><msub><mi>E</mi><mn>0</mn></msub></math> is globally asymptotically stable. On the other hand, if <math><msub><mrow><mi>R</mi></mrow><mn>0</mn></msub><mo>></mo><mn>1</mn></math> then there exists a unique stable disease equilibrium <math><msup><mi>E</mi><mo>∗</mo></msup></math>. The existence of solutions of the model and uniform persistence results are studied. Finally, using finite difference scheme, we present a number of numerical examples to verify our analytical results. Our results indicate that the global dynamics of the model are completely determined by the threshold value <math><msub><mrow><mi>R</mi></mrow><mn>0</mn></msub></math>.</p>","PeriodicalId":48809,"journal":{"name":"Journal of Biological Dynamics","volume":"15 sup1","pages":"S105-S133"},"PeriodicalIF":1.8000,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/17513758.2020.1849831","citationCount":"7","resultStr":"{\"title\":\"Dynamics of a diffusive vaccination model with therapeutic impact and non-linear incidence in epidemiology.\",\"authors\":\"Md Kamrujjaman, Md Shahriar Mahmud, Md Shafiqul Islam\",\"doi\":\"10.1080/17513758.2020.1849831\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>In this paper, we study a more general diffusive spatially dependent vaccination model for infectious disease. In our diffusive vaccination model, we consider both therapeutic impact and nonlinear incidence rate. Also, in this model, the number of compartments of susceptible, vaccinated and infectious individuals are considered to be functions of both time and location, where the set of locations (equivalently, spatial habitats) is a subset of <math><msup><mrow><mi>R</mi></mrow><mi>n</mi></msup></math> with a smooth boundary. Both local and global stability of the model are studied. Our study shows that if the threshold level <math><msub><mrow><mi>R</mi></mrow><mn>0</mn></msub><mo>≤</mo><mn>1</mn><mo>,</mo></math> the disease-free equilibrium <math><msub><mi>E</mi><mn>0</mn></msub></math> is globally asymptotically stable. On the other hand, if <math><msub><mrow><mi>R</mi></mrow><mn>0</mn></msub><mo>></mo><mn>1</mn></math> then there exists a unique stable disease equilibrium <math><msup><mi>E</mi><mo>∗</mo></msup></math>. The existence of solutions of the model and uniform persistence results are studied. Finally, using finite difference scheme, we present a number of numerical examples to verify our analytical results. Our results indicate that the global dynamics of the model are completely determined by the threshold value <math><msub><mrow><mi>R</mi></mrow><mn>0</mn></msub></math>.</p>\",\"PeriodicalId\":48809,\"journal\":{\"name\":\"Journal of Biological Dynamics\",\"volume\":\"15 sup1\",\"pages\":\"S105-S133\"},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2021-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1080/17513758.2020.1849831\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Biological Dynamics\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1080/17513758.2020.1849831\",\"RegionNum\":4,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2020/11/18 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"ECOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Biological Dynamics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1080/17513758.2020.1849831","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2020/11/18 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"ECOLOGY","Score":null,"Total":0}
Dynamics of a diffusive vaccination model with therapeutic impact and non-linear incidence in epidemiology.
In this paper, we study a more general diffusive spatially dependent vaccination model for infectious disease. In our diffusive vaccination model, we consider both therapeutic impact and nonlinear incidence rate. Also, in this model, the number of compartments of susceptible, vaccinated and infectious individuals are considered to be functions of both time and location, where the set of locations (equivalently, spatial habitats) is a subset of with a smooth boundary. Both local and global stability of the model are studied. Our study shows that if the threshold level the disease-free equilibrium is globally asymptotically stable. On the other hand, if then there exists a unique stable disease equilibrium . The existence of solutions of the model and uniform persistence results are studied. Finally, using finite difference scheme, we present a number of numerical examples to verify our analytical results. Our results indicate that the global dynamics of the model are completely determined by the threshold value .
期刊介绍:
Journal of Biological Dynamics, an open access journal, publishes state of the art papers dealing with the analysis of dynamic models that arise from biological processes. The Journal focuses on dynamic phenomena at scales ranging from the level of individual organisms to that of populations, communities, and ecosystems in the fields of ecology and evolutionary biology, population dynamics, epidemiology, immunology, neuroscience, environmental science, and animal behavior. Papers in other areas are acceptable at the editors’ discretion. In addition to papers that analyze original mathematical models and develop new theories and analytic methods, the Journal welcomes papers that connect mathematical modeling and analysis to experimental and observational data. The Journal also publishes short notes, expository and review articles, book reviews and a section on open problems.