Global Dynamics of HIV Infection of CD 4 + T Cells and Macrophages

We study the global dynamics of anHIV infectionmodel describing the interaction of theHIVwith CD4 T cells andmacrophages. The incidence rate of virus infection and the growth rate of the uninfected CD4 T cells and macrophages are given by general functions. We have incorporated two types of distributed delays into the model to account for the time delay between the time the uninfected cells are contacted by the virus particle and the time for the emission of infectious (matures) virus particles. We have established a set of conditions which are sufficient for the global stability of the steady states of the model. Using Lyapunov functionals and LaSalle’s invariant principle, we have proven that if the basic reproduction number R 0 is less than or equal to unity, then the uninfected steady state is globally asymptotically stable (GAS), and if the infected steady state exists, then it is GAS.


Introduction
Recently, many mathematical models have been developed to describe the interaction of human immunodeficiency virus (HIV) with the immune system [1].Those mathematical models can provide some insights into the dynamics of HIV viral load in vivo and may play a significant role in the development of a better understanding of HIV/AIDS and drug therapies.For example, they provided a quantitative understanding of the level of virus production during the long asymptomatic stage of HIV infection [2].
The basic mathematical model describing the dynamics of HIV infection of CD4 + T cells is given by [3] ẋ =  −  − V, where , , and V represent the populations of the uninfected CD4 + T cells, infected cells, and free virus particles, respectively.The uninfected cells are generated from sources within the body at a rate .The parameter  is the death rate constant of the uninfected cells.The incidence rate is given by the bilinear form V, where  is the rate constant characterizing infections of the cells.Equation (2) describes the population dynamics of the infected cells and shows that they die with rate constant .The virus particles are produced by the infected cells with a rate constant  and are cleared from plasma with a rate constant .Many researchers suggested that the bilinear incidence rate is insufficient to describe the infection process in detail [4][5][6][7][8].Therefore, different forms of the incidence rate of infection have been proposed such as saturated incidence rate V/(1+V) [4], Holling type II functional response V/(1+ ) [5], Beddington-DeAngelis infection rate V/(1 +  + V) [6], Crowley-Martin functional response V/((1 + )(1 + V)) [7,8], where ,  ≥ 0, and a general function (, V) [9].
In model ( 1)- (3), it is assumed that the infection could occur and the viruses are produced from infected cells instantaneously, once the uninfected cells are contacted by the virus particles.However, this assumption is unrealistic.Therefore, more realistic HIV dynamics models incorporate the delay between the time of viral entry into the uninfected cell and the time for the production of new virus particles, modeled with discrete time delay or distributed time delay using functional differential equations (see, e.g., [2,5,[10][11][12][13][14][15][16][17][18]).As pointed by Li and Shu [18], the period between the time for HIV to enter the target cell and the time for new virions to be produced from the infected cell needs the following stages: (i) the period between the viral entry of a target cell and integration of viral DNA into the host genome, (ii) the period from the integration of viral DNA to the transcription of viral RNA and translation of viral proteins such as reverse transcriptase, integrase, and protease, and (iii) the period between the transcription of viral RNA and the release and maturation of virus [18].
All of the afore mentioned delayed HIV infection models are mainly modeled with the interaction of the HIV with one class of target cells, CD4 + T cells.More accurate modeling was developed in 1997 when Perelson et al. [19] observed that, after the rapid first phase of decay during the initial 1-2 weeks of antiretroviral treatment, plasma virus levels declined at a considerably slower rate.This second phase of viral decay was attributed to the turnover of a longer-lived virus reservoir of infected cells.These cells are called macrophages and considered as the second target cell for the HIV.To model the second class of target cells, two additional equations describing the population dynamics of the uninfected and infected macrophages have to be added to the basic model ( 1)-( 3) (see [20,21]).In [20][21][22][23][24][25][26][27], the HIV models have been proposed to describe the HIV dynamics with the CD4 + T cells and macrophages.The global stability analysis of these models has been investigated in [24][25][26][27].Elaiw [24] studied the global properties of HIV infection model with bilinear and nonlinear incidence rates.In [25], Beddington-DeAngelis functional response has been considered.In [24,25], the effect of time delay is neglected.Elaiw et al. [26] studied the global stability of HIV model with Beddington-DeAngelis functional response and one kind of discrete time delay.Elaiw [27] studied the global dynamics of a delay HIV model with saturated functional response.
In this paper, we study the global dynamics of HIV infection of CD4 + T cells and macrophages.We assume that the incidence rate and the growth rate of the uninfected cells are given by general functions.We incorporate two types of distributed delays into the model to account for the time delay between the time the uninfected cells are contacted by the virus particle and the time for the emission of infectious (mature) virus particles.We established a set of conditions which are sufficient for the global stability of the steady states of the model.Using Lyapunov functionals and LaSalle's invariant principle, we prove that if the basic reproduction number  0 is less than or equal to unity, then the uninfected steady state is globally asymptotically stable (GAS), and if the infected steady state exists, then it is GAS.

The Model
In this sections we propose an HIV dynamics model which describes the interaction of the HIV with the CD4 + T cells and macrophages.Two types of distributed time delays are incorporated into the model where   and   represent the populations of the uninfected and infected cells, respectively, where  = 1 and 2 correspond to CD4 + T cells and macrophages.Parameters    and   satisfy    < 1 and   <   ,  = 1, 2. All the variables and other parameters of the model have the same meanings as given in model ( 1)-(3).To take into account the delay between viral infection of an uninfected target cell and the production of an actively infected target cell, we let  be the random variable that describes the time between viral entry and the transcription of viral RNA (stages (i) and (ii)) with a probability distribution   () over the interval [0, ℎ  ] and ℎ  is limit superior of this delay.On the other hand, to consider the delay between viral RNA transcription and viral release and maturation, we let  be the random variable that is the time between these two events with a probability distribution   () over the interval [0,   ] and   is limit superior of this delay [18].The probability distribution functions   () : [0, ℎ  ] → R + and   () : [0,   ] → R + are integral functions with Function   (  , V) represents the rate for the uninfected target cell of class  to be infected by the mature viruses.Special forms of function   (  , V) have been presented in the literature as follows: (i) bilinear incidence rate [3]: (, V) = V, (ii) saturated incidence rate [4,28,29]: (iii) Holling type II functional response [5]: (iv) Beddington-DeAngelis infection rate [6,25]: Crowley-Martin functional response [7,8,30]: The growth rate of the uninfected cells is given by general function   (  ).The following particular forms of function   (  ) have widely been used in the literature of HIV dynamics: where   is the maximum proliferation rate of the target cells of class  and  ,max is the maximum level of uninfected cells population in the body [13,16,31].
We assume that functions   and   satisfy the following assumptions.

Steady States.
Let Assumptions 1 and 2 be satisfied; then system (4)-( 6) has an uninfected steady state  0 ( 0 1 ,  0 2 ,  0 1 ,  0 2 , V 0 ), where  0  is defined in Assumption 1,  0  = 0,  = 1, 2, and V 0 = 0.The system can also have another steady state  * ( * 1 ,  * 2 ,  * 1 ,  * 2 , V * ) which is the infected steady state; the coordinates of the infected steady state, if they exist, satisfy the equalities We define the basic reproduction number for system (4)-( 6) as The term   ( 0  , 0)/V denotes the maximal average number of target cells  that each virus infects, and   is the basic reproduction number for the dynamics of the virus and the uninfected cell of class .

Global Stability Analysis.
In this section, we establish a set of conditions which are sufficient for the global stability of the uninfected and infected steady states of system ( 4)- (6).The strategy of the proofs is to use suitable Lyapunov functionals which are similar in nature to those used in [33,34].We will use the following notation:  = () for any  ∈ {  ,   , V,  = 1, 2}.We also define a function  : (0, ∞) → [0, ∞) as It is clear that () ≥ 0 for any  > 0 and  has the global minimum (1) = 0.
The global stability of the uninfected steady state will be established in the next theorem.
To establish the global stability of the infected steady state, we need the following conditions.

Conclusion
In this paper, we have proposed an HIV dynamics model describing the interaction of the HIV with CD4 + T cells and macrophages.The incidence rate of virus infection and the growth rate of the uninfected cells are given by general functions.Two types of distributed delays have been incorporated into the model to account for the time delay between the time the uninfected cells are contacted by the virus particle and the time for the emission of infectious (mature) virus particles.We have established a set of conditions which are sufficient for the global stability of the steady states of the model.Using Lyapunov functionals and LaSalle's invariant principle, we have proven that if  0 ≤ 1, then the uninfected steady state is GAS, and if the infected steady state exists, then it is GAS.