Stability Analysis for an HIV Infection Model with Immune Response and Cure Rate

Similar documents
Research Article Mathematical Modeling of Cytotoxic Lymphocyte-Mediated Immune Response to Hepatitis B Virus Infection

Global Stability of SACR Epidemic Model for Hepatitis C on Injecting Drug Users

A Delay-Differential Equation Model of

Analysis and Simulations of Dynamic Models of Hepatitis B Virus

VIRUS POPULATION DYNAMICS

RESEARCH & KNOWLEDGE

On the behavior of solutions in viral dynamical models

Mathematical Model of Hepatitis B in. the Bosomtwe District of Ashanti Region, Ghana

Mathematical Model Approach To HIV/AIDS Transmission From Mother To Child

Design and Dynamic Modeling of Flexible Rehabilitation Mechanical Glove

Reduction of Mortality Rate Due to AIDS When Treatment Is Considered

Mathematical Analysis of an HIV/AIDS Epidemic Model

Local Stability of AIDS Epidemic Model Through Treatment and Vertical Transmission with Time Delay

Modeling of HIV and CTL Response

Australian Journal of Basic and Applied Sciences. Stability Analysis and Qualitative Behavior of Giving up Smoking Model with Education Campaign

Modeling the HIV Transmission with Reinfection

A Mathematical Model of Tuberculosis Control Incorporating Vaccination, Latency and Infectious Treatments (Case Study of Nigeria)

Influence of anti-viral drug therapy on the evolution of HIV-1 pathogens

Homework 6 Solutions

Decay characteristics of HIV-1- infected compartments during combination therapy

ON ATTAINING MAXIMAL AND DURABLE SUPPRESSION OF THE VIRAL LOAD. Annah M. Jeffrey, Xiaohua Xia and Ian K. Craig

A mathematical model of glucose-insulin interaction

Modeling Kinetics of HBV Infection and Recommendations for Moving Forward

Delay Differential Model for Tumor-Immune Dynamics with HIV Infection of CD4 + T Cells

Study on control of bird flu outbreak within a poultry farm

Optimal Control of The HIV-Infection Dynamics

Author's personal copy

NUMERICAL SOLUTION OF THE MODEL FOR HIV INFECTION OF CD4 + T CELLS BY USING MULTISTAGE DIFFERENTIAL TRANSFORM METHOD.

Correlation between Hepatitis and Cancer: A Mathematical Model

A patient-specific treatment model for Graves hyperthyroidism

Modelling the H1N1 influenza using mathematical and neural network approaches.

Mathematical Formulation and Numerical Simulation of Bird Flu Infection Process within a Poultry Farm

Determination of glucose in human urine by cyclic voltammetry method using gold electrode

MODELING THE DRUG THERAPY FOR HIV INFECTION

Optimal control strategy of HIV-1 epidemic model for recombinant virus

The 2016 Summer Institute in Statistics and Modeling of Infectious Diseases Module 6: Infectious Diseases, Immunology and Within-Host Models Author:

Towards Modeling HIV Long Term Behavior

Hepatitis B Cure: from discovery to regulatory endpoints in HBV clinical research A summary of the AASLD/EASL statement

Mathematical Models for HIV infection in vivo - A Review

Andronov-Hopf bifurcation and sensitivity analysis of a time-delay HIV model with logistic growth and antiretroviral treatment

The GCD of m Linear Forms in n Variables Ben Klein

A Comparison Study of the Mathematical Model of HIV Infection of CD 4 + T Cells Using Homotopy Perturbation and Variational Iteration Methods

Mathematical studies of the glucose-insulin regulatory system models.

Modeling Multi-Mutation And Drug Resistance: A Case of Immune-Suppression

Hepatitis B Antiviral Drug Development Multi-Marker Screening Assay

Modeling the Effects of Time Delay on HIV-1 in Vivo Dynamics in the Presence of ARVs

Article Epidemic Analysis and Mathematical Modelling of H1N1 (A) with Vaccination

Simple Mathematical Models Do Not Accurately Predict Early SIV Dynamics

EFFECT OF INTERFERON AND RIBAVIRIN ON HEPATITIS C VIRUS

National Institute for Health and Care Excellence

A Mathematical Model for the Epidemiology of Tuberculosis with Estimate of the Basic Reproduction Number

A Mathematical Approach to Characterize the Transmission Dynamics of the Varicella-Zoster Virus

Tumour-Immune Interaction Model with Cell Cycle Effects Including G 0 Phase

Design and Implementation study of Remote Home Rehabilitation Training Operating System based on Internet

APPLICATION OF MATHEMATICAL MODELING TO IMMUNOLOGICAL PROBLEMS

Epidemiological Model of HIV/AIDS with Demographic Consequences

A Mathematical Model for the Transmission Dynamics of Cholera with Control Strategy

A Model for the CD4 Cell Counts in an HIV/AIDS Patient and its Application in Treatment Interventions

Mathematical Model on Influenza Disease with Re-Susceptibility

= Λ μs βs I N, (1) (μ + d + r)i, (2)

Mathematical models of the activated immune system during HIV infection

A Novel Recombinant Virus Reagent Products for Efficient Preparation Of Hepatitis B Animal Models

Using mathematical model to depict the immune response to Hepatitis B virus infection

Design and Implementation of Software Planning System for Dental Robot

Modelling the spread of HIV/AIDS epidemic in the presence of irresponsible infectives

Fe-doped ZnO synthesized by parallel flow precipitation process for improving photocatalytic activity

Hepatitis B. HBV Cure: Insights for the Biotechnology and the Research Analyst Community November 11, Lalo Flores, PhD Global Head HBV R&D

Mathematical Modeling of Hand-Foot-Mouth Disease: Quarantine as a Control Measure

Adults and Children estimated to be living with HIV, 2013

The frequency of resistant mutant virus before antiviral therapy

Chapter 3: Linear & Non-Linear Interaction Models

ScienceDirect. A mathematical study of combined use of anti-hiv drugs and a mutagen

Heroin Epidemic Models

Modeling the Endemic Equilibrium of Typhoid Fever

Journal of Physics: Conference Series. Related content PAPER OPEN ACCESS

A TRIDENT SCHOLAR PROJECT REPORT

Mathematical Biology. Optimal HIV treatment by maximising immune response. Rebecca V. Culshaw Shigui Ruan Raymond J. Spiteri. 1.

HCV eradication with direct acting antivirals (DAAs)? Why is viral cure possible in HCV? Emilie Estrabaud

Mathematics Model Development Deployment of Dengue Fever Diseases by Involve Human and Vectors Exposed Components

Mathematical Models of Hepatitis B Virus Dynamics during Antiviral Therapy

A Mathematical Model for Treatment-Resistant Mutations of HIV

A Simulation Model Including Vaccination and Seasonality for Influenza A-H1N1 Virus

Supplementary data for:

Richard Colonno Executive Vice President and Chief Scientific Officer of Virology Operations

Targeting HBV Core Protein to Clear Infection and Achieve Higher Cure Rates

Find the slope of the line that goes through the given points. 1) (-9, -68) and (8, 51) 1)

Design a system of measurement of heart rate, oxygen saturation in blood and body temperature with non-invasive method

Mathematical Model to Simulate Tuberculosis Disease Population Dynamics

Xiao-Ling Chi, Mei-Jie Shi, Huan-Ming Xiao, Yu-Bao Xie, and Gao-Shu Cai. Correspondence should be addressed to Xiao-Ling Chi;

Mathematical modelling using improved SIR model with more realistic assumptions

Optimal Control Theory Applied to the Anti-Viral Treatment of AIDS

Mathematical Models for Linking Within-Host and Between-Host Viral Dynamics

Continuous Monitoring of Blood Pressure Based on Heart Pulse Analysis

Diagnostic test pepsinogen I and combination with tumor marker CEA in gastric cancer

3. On the role of alcohol drinking on the dynamics transmission of Hepatitis B

Dynamic analysis of lymphocyte subsets of peripheral blood in patients with acute self-limited hepatitis B

Classification of normal and abnormal images of lung cancer

Modeling of cancer virotherapy with recombinant measles viruses

The infectious particle of hepatitis B virus (HBV)

Drug Resistance in Acute Viral Infections: Rhinovirus as a Case Study

Transcription:

IOP Conference Series: Materials Science and Engineering PAPER OPEN ACCESS Stability Analysis for an HIV Infection Model with Immune Response and Cure Rate To cite this article: Linli Zhang and Lin Wang 8 IOP Conf Ser: Mater Sci Eng 39 69 View the article online for updates and enhancements This content was downloaded from IP address 485383 on 5//8 at 3:3

IOP Conf Series: Materials Science and Engineering 3456789 39 (8) 69 doi:88/757-899x/39/6/69 Stability Analysis for an HIV Infection Model with Immune Response and Cure Rate Linli Zhang,,Lin Wang Hainan University, Danzhou 57737, China; Haikou University of Economics, Haikou 577, China E-mail: zhanglinli63@63com, whu5@qqcom Abstract The dynamics of HIV infection model with immune response and cure rate is investigated The explicit expression for the basic reproduction number of the model which determines where the virus dies out or not is obtained With characteristic equation and Hurwitz criterion, the local stability of the equilibriums is analyzed Introduction The human immuno-deficiency virus (HIV) infection, which can cause acquired immuno-deficiency syndrome(aids), has become an important infectious disease in both the developed and the developing nations It causes mortality of millions of people and expenditure of a huge amount of money in disease control and health care In recent years, some scholars have achieved many significant results by establishing the mathematical model of HIV pathogenesis which is used to study the HIV virus concentration and the change of CD4 + T cells concentration in the body [-7] The research [8] shows that, for a chemotherapy of HBV infection, under the effect of drugs, the infection of target cells can overflow from the nucleus into uninfected state covalently closed circular DNA (cccdna) Zhou et al [6], consider a HIV pathological model with the cure rate, and the results show that it will be able to effectively extend the duration of HIV infection if the cure rate is improved in a certain extent The immune response following viral infection is universal and necessary in controlling or even eliminating the disease [9] Under the inspiration of these references, we will consider a HIV infection model with immune response and cure rate in this paper as follows: x( t) dxxyy, y () t xy ay pyz y, () z ( t) cyz bz Here x() t is the concentration of uninfected cells at time t ; yt () is the concentration of infected cells that produce virus at time t ; () zt is the concentration of antigen-specific CTLs at time t is the growth rate of new healthy cells a and d are the death rate of infected cells and uninfected cells, respectively is the rate constant characterizing infection of the cells p is the death rate of infected cells due to the immune system is the rate at which infected cells return to healthy cells after treatment The immune response is supposed to decay exponentially at a rate bz and get stronger at a rate cyz All parameters in the model are positive Model () needs to be analyzed with the following initial conditions: Content from this work may be used under the terms of the Creative Commons Attribution 3 licence Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI Published under licence by Ltd

IOP Conf Series: Materials Science and Engineering 3456789 39 (8) 69 doi:88/757-899x/39/6/69 x, y, It can be proved that the solution of system () - () exists and is positive z () Equilibrium States By solving the equations (3), we can obtain the three types of nonnegative equilibrium of model () dx xy y, xy ay pyz y, (3) cyz bz Model () always has an infection-free equilibrium, where E ( x,,),, d We denote: c cd a cd a R d a, R R ab ab ab R and R are defined as the basic reproductive number and the immune reproduction number of model (), respectively When R, Model () has an unique immune-absence equilibrium E besides E, where a d a E ( x, y, z),, a When R, Model () has an unique interior immune-presence equilibrium and E, where E x y z cd a R ab,,,, dc b c p( dc b) c b b E besides E 3 Local Stability Next, with characteristic equation and Hurwitz criterion, we analyze the local stability of model () Theorem Consider model () (i) If R, the infection-free equilibrium E is locally asymptotically stable; (ii) If R and R, the immune-absence equilibrium E is locally asymptotically stable; (iii) If R and bc, the immune-present equilibrium E is locally asymptotically stable Proof (i) The Jacobian matrix of model () at E is obtained as follows: d x JE x a b The characteristic equation of J E takes the form: d r x x a r br By solving the third order determinant, equation (4) can be simplified as follows: rd rb rax (5) The equation (5) has three roots: r d, r b, r a R When R, that is r 3, 3 equation (5) has three negative real roots, hence E is locally asymptotically stable When R, that is r3, equation (5) has a positive real root, thus E is unstable (4)

IOP Conf Series: Materials Science and Engineering 3456789 39 (8) 69 doi:88/757-899x/39/6/69 (ii) The Jacobian matrix of model () at E is obtained as follows: d y x JE y cy b The characteristic equation of J E takes the form: d y r x y r (6) cy b r By solving the third order determinant, equation (6) can be simplified as follows: brcy r d y ry x (7) The equation (7) a characteristic root: rcybbr When R, that is r The rest of the characteristic roots satisfy the equation (8): r d y ry x (8) a Because x, the equation (8) is simplified as follows: r d y rya (9) All coefficients of quadratic equation (9) are positive, and hence its roots have negative real parts That is R ensures that all eigenvalues have negative real parts of equation (7) and hence the immune-absence equilibrium E is locally asymptotically stable if R and R (iii) The Jacobian matrix of model () at E is obtained as follows: d y x J E y py cz The characteristic equation of J E takes the form: d y r x y r py By solving the third order determinant, the equation () can be simplified as follows: 3 r ar ar a, () where a d y, a cpy z d y, b a cz py y y y cz py y y cz py y c, cz r b aa a d y y y dy y c () 3

IOP Conf Series: Materials Science and Engineering 3456789 39 (8) 69 doi:88/757-899x/39/6/69 When b c is greater than zero, it ensures that aa ais greater than zero By the Routh- Hurwitz theorem, all roots of the equation () have negative real part, and the immune-present equilibrium E is locally asymptotically stable if R and bc 4 Conclusion In this paper, the dynamics of HIV infection model with immune response and cure rate is investigated The explicit expression for the basic reproduction number of the model which determines where the virus dies out or not is obtained The sufficient condition of local asymptotic stability of equilibrium is obtained by using the characteristic equation and Hurwitz criterion The infection-free equilibrium E of model () is locally asymptotically stable when R ; the immune-absence equilibrium E of model () is locally asymptotically stable when R and R ; the immune-present equilibrium of model () is locally asymptotically stable when R and bc The concentration of CD4 + T cell is an important indicator of HIV infection progression Because x is a monotone increasing function of cure rate Therefore, increasing the cure rate will further improve the concentration of CD4 + T cells in the equilibrium point of the disease, thereby prolonging the duration of HIV infection and thus effectively controlling the effect of HIV infection In this paper, the immune reproduction number R is the monotone decreasing function of cure rate, which means the increase of cure rate reduces the production of immune cells in the body The mechanism is: the cure rate is to vaccinate measures can be considered in this study Because vaccination is to replace the function of immune cells, the infection to the stimulation of immune becomes smaller Thus, vaccination can reduce the generation of immune cells in the body Acknowledgments This reserach is supported by Hainan Provincial Natural Science Foundation of China (774; 8MS84) References [] L Wang, MY Li Mathematical analysis of the global dynamic of a model for HIV infection of CD4+T cells[j] Mathematical Biosciences, 6, (): 44-57 [] RL Fan, YP Dong, G Huang, et al Apoptosis in virus infection dynamics models [J] Journal of Biological Dynamics, 4, 8(): -4 [3] AS Perelson, AU Neumann, M Markowitz, et al HIV- dynamics in vivo: Virion clearance rate, infected cell life-span, and viral generation time [J] Science, 996, 7(555): 58-586 [4] XD Liu, H Wang, ZX Hu, et al Stability of an HIV Pathogenesis Model with Delay and Cure Rate [J] Journal of Biomathematics,, 6(): 8-6 [5] XY Song, AU Neumann Global stability and periodic solution of the viral dynamics [J] Journal If Mathematical Analysis and Applications, 7, 39[]: 8-396 [6] XY Zhou, XY Song, XY Shi A differential equation model of HIV infection of CD4 + T- cells with cure rate [J] Journal of Mathematical Analysis and Applications, 8, 34(): 34-355 [7] AVM Herz, S Bonhoer, RM Anderson, et al Viral dynamics in vivo: limitations on estimates of intracellular delay and virus decay [J] Proceedings of the National Academy of Sciences of the United States of America, 996, 93(4): 747-75 [8] S Lewinb, T Waltersa, S Locarnini Hepatitis B treatment: rational combination chemotherapy based on viral kinetic and animal model studies [J] Antiviral Research,, 55(3): 38-396 [9] G Huang, H Yokoi, Y Takeuchi, T Kajiwara and T Sasaki Impact of intracellular delay, immune activation delay and nonlinear incidence on viral dynamics [J] Japan Journal of E 4

IOP Conf Series: Materials Science and Engineering 3456789 39 (8) 69 doi:88/757-899x/39/6/69 Industrial and Applied Mathematics,, 8(): 383-4 5