Deva Siva Sai Murari Kanumoori, D. Prakash, D. Vamsi, C. Sanjeevi
{"title":"A Study of Within-Host Dynamics of Dengue Infection incorporating both Humoral and Cellular Response with a Time Delay for Production of Antibodies","authors":"Deva Siva Sai Murari Kanumoori, D. Prakash, D. Vamsi, C. Sanjeevi","doi":"10.1515/cmb-2020-0118","DOIUrl":null,"url":null,"abstract":"Abstract a. Background: Dengue is an acute illness caused by a virus. The complex behaviour of the virus in human body can be captured using mathematical models. These models helps us to enhance our understanding on the dynamics of the virus. b. Objectives: We propose to study the dynamics of within-host epidemic model of dengue infection which incorporates both innate immune response and adaptive immune response (Cellular and Humoral). The proposed model also incorporates the time delay for production of antibodies from B cells. We propose to understand the dynamics of the this model using the dynamical systems approach by performing the stability and sensitivity analysis. c. Methods used: The basic reproduction number (R0) has been computed using the next generation matrix method. The standard stability analysis and sensitivity analysis were performed on the proposed model. d. Results: The critical level of the antibody recruitment rate(q) was found to be responsible for the existence and stability of various steady states. The stability of endemic state was found to be dependent on time delay(τ). The sensitivity analysis identified the production rate of antibodies (q) to be highly sensitive parameter. e. Conclusions: The existence and stability conditions for the equilibrium points have been obtained. The threshold value of time delay (τ0) has been computed which is critical for change in stability of the endemic state. Sensitivity analysis was performed to identify the crucial and sensitive parameters of the model.","PeriodicalId":34018,"journal":{"name":"Computational and Mathematical Biophysics","volume":"9 1","pages":"66 - 80"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1515/cmb-2020-0118","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational and Mathematical Biophysics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1515/cmb-2020-0118","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Mathematics","Score":null,"Total":0}
引用次数: 2
Abstract
Abstract a. Background: Dengue is an acute illness caused by a virus. The complex behaviour of the virus in human body can be captured using mathematical models. These models helps us to enhance our understanding on the dynamics of the virus. b. Objectives: We propose to study the dynamics of within-host epidemic model of dengue infection which incorporates both innate immune response and adaptive immune response (Cellular and Humoral). The proposed model also incorporates the time delay for production of antibodies from B cells. We propose to understand the dynamics of the this model using the dynamical systems approach by performing the stability and sensitivity analysis. c. Methods used: The basic reproduction number (R0) has been computed using the next generation matrix method. The standard stability analysis and sensitivity analysis were performed on the proposed model. d. Results: The critical level of the antibody recruitment rate(q) was found to be responsible for the existence and stability of various steady states. The stability of endemic state was found to be dependent on time delay(τ). The sensitivity analysis identified the production rate of antibodies (q) to be highly sensitive parameter. e. Conclusions: The existence and stability conditions for the equilibrium points have been obtained. The threshold value of time delay (τ0) has been computed which is critical for change in stability of the endemic state. Sensitivity analysis was performed to identify the crucial and sensitive parameters of the model.