Citation: Jinliang Wang, Xiu Dong. Analysis of an HIV infection model incorporating latency age and infection age[J]. Mathematical Biosciences and Engineering, 2018, 15(3): 569-594. doi: 10.3934/mbe.2018026
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Determining the threshold dynamics of infection-free and infection equilibrium in viral infection model has made great progress in the last decades [1,2,4,8,9,10,16,17,24,31,36,32,33,34,35,40,44]. A key insight in this progress is that if threshold value (named, the basic reproduction number) is less than one then the infection-free equilibrium is globally asymptotically stable otherwise the endemic equilibrium attracts all solutions (is globally asymptotically stable) whenever it exists. One method adopted here is due to the classical Volterra type Lyapunov function, which was discovered by Volterra [30]. These confirmed global stability properties of steady states for within host virus model establish our understanding the virus dynamical behaviors, that is, whether the viruses die out or not.
Even large discrete and continuous delay differential equations of viral infection models have been successfully treated by Volterra type Lyapunov function, (ⅰ) nonlinear incidence rate functions [8,24,31]; (ⅱ) discrete delays [10,16,35] and finite distributed delays [17,31,36], and infinite distributed delays [8,24,34]; (ⅲ) immune responses [24,35,44,39,41]; and (ⅳ) additional infection processes [31]. It is still a hot topic in in-host model to determine how these factors affect the virus dynamical behaviors. We also refer the reader to see these citations for more references.
Recently, age-structured viral infection model has attracted much attentions of researchers. HIV latency remains a major obstacle to viral elimination. Although HIV-1 replication can be controlled by antiretroviral therapy in suppress the plasma viral load to below the detection limit, the time spent in this progress may last half life of months or years [21]. Virus persisting in reservoirs, such as latency infected CD4+ T cells, may the reason that long-term low viral load persistence in patients on antiretroviral therapy and keeping the virus from being eliminated. These latency infected CD4+ T cells are not affected by immune responses but can produce virus once activated by relevant antigens.
Some recent studies reveals the decay dynamics of the latent reservoir. For example, a model has been developed by Muller et al. [11] to describe the heterogeneity of latent cell activation. An ordinary differential equations (ODEs) model has been studied by Kim and Perelson [7] to include decreasing activation of latently infected cells. Activation of these latently infected cells needs specificity antigen. A recent study by Strain et al. [22] reveals that the dynamics of latently infected CD4+ T cells are often heterogeneous. They argued that cells specific to frequently encountered antigens are activated soon while cells specific to rare antigens need more time to be activated. Thus, the activation rate depends on the time spent since the cell is latently infected (that is the time elapsed since the establishment of latency), which we refer as latency age for short. A recent paper by Alshorman et al. [1] introduced a latency age model to mathematically analyze the dynamics of the latent reservoir under combination therapy. They give an affirmed answers that the long-term activation rate of latently infected cells plays an important role in determining the dynamics.
Taking into account the picture that the mortality rate and viral production rate of infected cells may depend on the infection age of cells, Nelson et al. [15], Huang et al. [4] and Wang et al. [37] have studied age-structured model of HIV infection by considering age to be a continuous variable rather than be constant in ODEs models. These assumptions lead to a hybrid system of ODEs and partial differential equations (PDEs) formulation and allow us to have a good understanding on productively infected cells. Together with the infinite-dimensional nature of system, this formulation creates some mathematical difficulties in establishing the existence of a global compact attractor, even in other epidemic models (see some relevant references for our discussion on age-structured models, [6,43,42,25,27,26,14]).
Denote by
The following assumptions are a compromise between generality and simplicity.
Assumption 1.1 (ⅰ) There is a small fraction (
(ⅱ) When latently infected cells are activated to become productively infected cells, an age-dependent remove rate
(ⅲ) We assume that production rate of viral particles
Biologically, (ⅰ) of Assumption 1.1 comes from the evidences that a very small fraction of CD4+ T cell infection leads to HIV latency. They don't produce new virus unless activated by antigens, please see [18,19,20]. (ⅱ) of Assumption 1.1 based on the fact the latently infected cell population is very likely to be heterogeneous [22,23]. Cells specific to frequently encountered antigens may be preferentially activated and quickly removed from the reservoir. It may depends on the time elapsed since latent infection and affect the activation rate, that is the reason why we are interested in the latent infection age. (ⅲ) of Assumption 1.1 it is known that viral proteins and unspliced viral RNA accumulate within the cytoplasm of an infected cell, and thus, they actually ramps up [3,12,29]. Therefore, infection age should be incorporated into the model.
In this paper, we introduce the following HIV infection model with latency and infection age,
{dT(t)dt=h−dT(t)−βT(t)V(t),(∂∂t+∂∂a)e(a,t)=−θ1(a)e(a,t),(∂∂t+∂∂b)i(b,t)=−θ2(b)i(b,t),dV(t)dt=∫∞0p(b)i(b,t)db−cV(t), | (1) |
with boundary and initial conditions
{e(0,t)=fβT(t)V(t),i(0,t)=(1−f)βT(t)V(t)+∫∞0ξ(a)e(a,t)da,T(0)=T0≥0, e(a,0)=e0(a)∈L1+(0,∞),i(b,0)=i0(b)∈L1+(0,∞), V(0)=V0≥0, |
where
Mathematically, for the ease of simplicity, we make the following assumptions.
Assumption 1.2 (ⅰ)
(ⅱ) For
¯θi:=esssupa∈[0,∞)θi(a)<∞, ˉp:=esssupa∈[0,∞)p(a)<∞, ˉξ:=esssupa∈[0,∞)ξ(a)<∞, |
(ⅲ)
(ⅳ) There exists
(ⅴ) There exists a maximum age
Our goal of the present paper is to adopt previous model in [32,33] by incorporating the latency age for infected cells as discussed in [1], and to study the threshold dynamics of infection-free and infection equilibrium in viral infection model subject to latently age and infection age. We will show the existence of a compact attractor of all compact sets of nonnegative initial data and use the Lyapunov function to show that this attractor is the singleton set containing the endemic equilibrium. Roughly speaking, if the basic reproduction number is less than one then the infection-free equilibrium is globally asymptotically stable otherwise the endemic equilibrium attracts all solutions with active infection at some time.
The remaining part of this paper is organized as follows. In Section 2, we present some preliminary results including model formulation (equivalent integrated semigroup formulation and Volterra formulation), properties of solutions and existence of equilibria. Then we show the asymptotic smoothness of
For ease of notations, we introduce the following notations:
Ω(a)=e−∫a0θ1(τ)dτ and Γ(b)=e−∫b0θ2(τ)dτ for a,b≥0. |
Biologically,
Then, by (ⅱ) and (ⅴ) of Assumption 1.2, we have that for all
0≤Ω(a)≤e−μ0a and 0≤Γ(b)≤e−μ0b, dΩ(a)da=−θ1(a)Ω(a) and dΓ(b)db=−θ2(b)Γ(b). | (2) |
Following the line of [27], we reformulate the model (1) as a semilinear Cauchy problem. Taking into account the boundary conditions, we consider the following state space,
X=R×R×L1((0,∞),R)×R×L1((0,∞),R)×R, |
X+=R+×R+×L1+((0,∞),R)×R+×L1+((0,∞),R)×R+, |
endowed with the usual product norm, and set
X0=R×{0}×L1((0,∞),R)×{0}×L1((0,∞),R)×R, |
X0+=X0∩X+. |
We consider the linear operator
A(T(0e)(0i)V)=(−dT(−e(0)−e′−θ1(a)e)(−i(0)−i′−θ2(a)i)−cV) |
with
Dom(A)=R×{0}×W1,1((0,∞),R)×{0}×W1,1((0,∞),R)×R, |
where
Define nonlinear operator
F(T(0e)(0i)V)=(h−βTV(fβTV0L1)((1−f)βTV+M0L1)N). |
where
M(t)=∫∞0ξ(a)e(a,t)da, N(t)=∫∞0p(b)i(b,t)db. | (3) |
Then by setting
du(t)dt=Au(t)+F(u(t)) for t≥0 and u(0)∈X0+. |
If any initial value
e(0,0)=fβT0V0 |
and
i(0,0)=(1−f)βT0V0+∫∞0ξ(a)e0(a)da, |
then (1) is well-posed under Assumption 1.2 due to Iannelli [6] and Magal [14]. Denote
Y=R+×L1+(0,∞)×L1+(0,∞)×R+ |
with the norm
‖(x,φ,ψ,y)‖Y=|x|+‖φ‖L1+‖ψ‖L1+|y| for (x,φ,ψ,y)∈Y. |
In fact, for such solutions, it is not difficult to show that
Using the results presented in [14,27], thus we can get a continuous solution semi-flow
Φ(t,X0)=Φt(X0):=(T(t),e(⋅,t),i(⋅,t),V(t)),t≥0, X0∈Y. |
The precise result is the following proposition.
Proposition 1. For system (1), there exists a unique strongly continuous semiflow
∫t0x(s)ds∈Dom(A), and x(t)=x0+A∫t0x(s)ds+∫t0F(x(s))ds,∀t≥0. |
According to the Volterra formulation (see Webb [42] and Iannelli [6]), integrating the second and third equations of (1) along the characteristic lines
e(a,t)={fβT(t−a)V(t−a)Ω(a)=e(0,t−a)Ω(a),ift>a,e0(a−t)Ω(a)Ω(a−t),ift≤a; | (4) |
and
i(b,t)={[(1−f)βT(t−b)V(t−b)+M(t−b)]Γ(b)=i(0,t−b)Γ(b),ift>b,i0(b−t)Γ(b)Γ(b−t),ift≤b. | (5) |
Thus system (1) can be rewritten as the following Volterra-type equations,
{dT(t)dt=h−dT(t)−βT(t)V(t),dV(t)dt=∫t0p(b)Γ(b)((1−f)βT(t−b)V(t−b)+M(t−b))db+∫∞tp(b)i0(b−t)Γ(b)Γ(b−t)db−cV(t), |
where
Proposition 2. Define
Ξ:={X0=(T0,e0,i0,V0)∈Y|T0+‖e0(a)‖L1≤hμ0,T0+‖e0(a)‖L1+‖i0(b)‖L1≤hμ1,V0≤ˉphcμ0+hˉpˉξcμ20,‖X0‖Y≤h˜μ0}, |
where
Φ(t,X0)∈Ξforallt≥0andX0∈Ξ. |
Moreover,
Proof. By (4) and changes of variables, we have
‖e(⋅,t)‖L1= ∫t0e(0,t−a)Ω(a)da+∫∞te0(a−t)Ω(a)Ω(a−t)da= ∫t0e(0,σ)Ω(t−σ)dσ+∫∞0e0(τ)Ω(t+τ)Ω(τ)dτ. |
We derivative this equality,
d‖e(⋅,t)‖L1dt=e(0,t)Ω(0)+∫t0e(0,σ)dΩ(t−σ)dtdσ+∫∞0e0(τ)Ω(τ)dΩ(t+τ)dtdτ. |
By (2) and changing of variables, we have
d‖e(⋅,t)‖L1dt= e(0,t)Ω(0)−∫t0e(0,σ)θ1(t−σ)Ω(t−σ)dσ −∫∞0e0(τ)Ω(τ)θ1(t+τ)Ω(t+τ)dτ= e(0,t)Ω(0)−∫∞0θ1(a)e(a,t)da. |
By the first equation in (1), (ⅳ) of Assumption 1.2, and use
d(T(t)+‖e(⋅,t)‖L1)dt=h−dT(t)−βT(t)V(t)+fβT(t)V(t)−∫∞0θ1(a)e(a,t)da≤h−μ0(T(t)+‖e(⋅,t)‖L1). |
We integrate this differential inequality and obtain the a priori estimate,
T(t)+‖e(⋅,t)‖L1≤hμ0−e−μ0t{hμ0−(T0+‖e(⋅,t)‖L1)},t≥0. | (6) |
This implies that
T(t)+‖e(⋅,t)‖L1≤hμ0. |
Similarly, we have
d‖i(⋅,t)‖L1dt=i(0,t)Γ(0)−∫∞0θ2(b)i(b,t)db. |
We add the two equations,
d(T(t)+‖e(⋅,t)‖L1)+‖i(⋅,t)‖L1)dt=h−dT+∫∞0ξ(a)e(a,t)da−∫∞0θ1(a)e(a,t)da−∫∞0θ2(b)i(b,t)db. |
and since (ⅱ) and (ⅳ) of Assumption 1.2, obtain the estimates
d(T(t)+‖e(⋅,t)‖L1)+‖i(⋅,t)‖L1)dt≤h+ˉξhμ0−μ0(T(t)+‖e(⋅,t)‖L1+i(⋅,t)‖L1). |
We integrate this differential inequality and obtain the a priori estimate,
‖T(t)+‖e(⋅,t)‖L1)+‖i(⋅,t)‖L1≤ h+ˉξhμ0μ0−e−μ0t{h+ˉξhμ0μ0−(T(t)+‖e(⋅,t)‖L1+i(⋅,t)‖L1)}, t≥0. | (7) |
This implies
dV(t)dt≤ˉp‖i(⋅,t)‖L1−cV(t)≤ˉp(hμ0+ˉξhμ20)−cV(t). |
It follows (ⅳ) of Assumption 1.2, we have that
V(t)≤ ˉp(hμ0+ˉξhμ20)c−e−ct{ˉphcμ0+hˉpˉξcμ20−V0}≤ ˉphcμ0+hˉpˉξcμ20−e−μ0t{¯phcμ0+hˉpˉξcμ20−V0} | (8) |
Consequently, from (6), (7) and (8), we conclude that if
‖Φt(X0)‖Y≤(1+ˉξμ0+ˉpc+ˉpˉξcμ0)hμ0 | (9) |
−e−μ0t{(1+ˉξμ0+ˉpc+ˉpˉξcμ0)hμ0−X0Y}=h˜μ0−e−μ0t{h˜μ0−‖X0‖Y}≤h˜μ0. | (10) |
In summary, we have shown that
As a consequence of Proposition 2, we have the following result.
Proposition 3. Let
(ⅰ)
(ⅱ)
(ⅲ)
System (1) always has an infection-free equilibrium
P0=(T0,e0(a),i0(b),V0):=(hd,0,0,0). |
The equations for an equilibrium are obtained from (1) by setting the time derivatives equal to
{h−dT∗−βT∗V∗=0,ddae∗(a)=−θ1(a)e∗(a),ddai∗(b)=−θ2(b)i∗(b),∫∞0p(b)i∗(b)db=cV∗,e∗(0)=fβT∗V∗,i∗(0)=(1−f)βT∗V∗+∫∞0ξ(a)e∗(a)da. | (11) |
Denote
K=∫∞0ξ(a)Ω(a)da, J=∫∞0p(b)Γ(b)db. |
Biologically,
We define basic reproduction number,
ℜ0=fβT0KJc+(1−f)βT0Jc. |
which accounts for the total number of virons resulted from a single viron through the virus-to-cell infection mod.
Direct calculation yields that if
T∗=T0ℜ0, e∗(a)=fh(1−1ℜ0)Ω(a), i∗(b)=(1−f+fK)h(1−1ℜ0)Γ(b), V∗=1c∫∞0p(b)i∗(b)db. | (12) |
In summary, we have shown the following result.
Proposition 4. (ⅰ) System (1) always has an infection-free equilibrium
(ⅱ) If
By Proposition 2 and 3, the semiflow is point-dissipative and
Definition 3.1. [28] A set
Recall that
Proposition 5. For any solution of (1), the associated functions
Proof. Let
M(t+h)−M(t)= ∫∞0ξ(a)e(a,t+h)da−∫∞0ξ(a)e(a,t)da≤ ∫h0ξ(a)e(a,t+h)da+∫∞hξ(a)e(a,t+h)da−∫∞0ξ(a)e(a,t)da≤ ∫h0ξ(a)e(0,t+h−a)Ω(a)da +∫∞hξ(a)e(a,t+h)da−∫∞0ξ(a)e(a,t)da. | (13) |
By applying
M(t+h)−M(t)≤fβA2ˉξh+∫∞0ξ(σ+h)e(σ+h,t+h)dσ−∫∞0ξ(a)e(a,t)da |
It follows from (4) that
e(σ+h,t+h)=e(σ,t)Ω(σ+h)Ω(σ). |
Thus,
M(t+h)−M(t)≤ fβA2ˉξh+∫∞0(ξ(a+h)Ω(a+h)Ω(a)−ξ(a))e(a,t)da= fβA2ˉξh+∫∞0(ξ(a+h)e−∫a+haθ1(s)ds−ξ(a))e(a,t)da= fβA2ˉξh+∫∞0ξ(a+h)(e−∫a+haθ1(s)ds−1)e(a,t)da +∫∞0(ξ(a+h)−ξ(a))e(a,t)da. |
From (ⅱ) of Assumption 1.2, we obtain
0≤ξ(a+h)|e−∫a+haθ1(s)ds−1|≤ˉξ¯θ1h. |
Recall that
M(t+h)−M(t)≤fβA2ˉξh+ˉξ¯θ1Ah+MξAh. |
Hence,
Next we divide
Θ(t,X0):=(0,˜φe(⋅,t),˜φi(⋅,t),0),Ψ(t,X0):=(T(t),˜e(⋅,t),˜i(⋅,t),V(t)), |
where
˜φe(a,t)={0, if t>a≥0,e(a,t), if a≥t≥0; ˜φi(b,t)={0, if t>b≥0,i(b,t), if b≥t≥0; |
˜e(a,t)={e(a,t),ift>a≥0,0,ifa≥t≥0;˜i(b,t)={i(b,t),ift>b≥0,0,ifb≥t≥0. |
Then
Theorem 3.2. For
(ⅰ) There exists a function
(ⅱ) For
proof Proof of (ⅰ) of Theorem 3.2. Let
˜φe(a,t)={0,ift>a≥0,e0(a−t)Ω(a)Ω(a−t),ifa≥t≥0; |
and
˜φi(b,t)={0,ift>b≥0,i0(b−t)Γ(b)Γ(b−t),ifb≥t≥0. |
Then, for
‖Θ(t,X0)‖Y= |0|+‖˜φe(⋅,t)‖L1+‖˜φi(⋅,t)‖L1+|0|= ∫∞t|e0(a−t)Ω(a)Ω(a−t)|da+∫∞t|i0(b−t)Γ(b)Γ(b−t)|db= ∫∞0|e0(σ)Ω(σ+t)Ω(σ)|dσ+∫∞0|i0(σ)Γ(σ+t)Γ(σ)|dσ= ∫∞0|e0(σ)e−∫σ+tσθ1(τ)dτ|dσ+∫∞0|i0(σ)e−∫σ+tσθ2(τ)dτ|dσ≤ e−μ0t‖e0‖L1+e−μ0t‖i0‖L1≤ e−μ0t‖X0‖Y. |
Proof of (ⅱ) of Theorem 3.2. It is sufficient to show that
(ⅰ) The supremum of
(ⅱ)
(ⅲ)
(ⅳ)
It follows from (4), (5), Proposition 3 and (2) that
Next we verify condition (ⅲ). For sufficiently small
∫∞0|˜e(a+h,t)−˜e(a,t)|da=∫t−h0|e(a+h,t)−e(a,t)|da+∫tt−h|0−e(a,t)|da=∫t−h0|e(0,t−a−h)Ω(a+h)−e(0,t−a)Ω(a)|da+∫tt−h|e(0,t−a)Ω(a)|da≤Δ1+Δ2+fβA2h, |
where
Δ1=∫t−h0e(0,t−a−h)|Ω(a+h)−Ω(a)|da |
and
Δ2=∫t−h0|e(0,t−a−h)−e(0,t−a)|Ω(a)da. |
We first get an estimate of
∫t−h0|Ω(a+h)−Ω(a)|da= ∫t−h0(Ω(a)−Ω(a+h))da= ∫t−h0Ω(a)da−∫thΩ(a)da= ∫t−h0Ω(a)da−∫t−hhΩ(a)da−∫tt−hΩ(a)da= ∫h0Ω(a)da−∫tt−hΩ(a)da≤ h, |
it follows from Proposition 3 that
Δ1≤fβA2h. |
Next we estimate
Δ2= ∫t−h0|fβT(t−a−h)V(t−a−h)−fβT(t−a)V(t−a)|Ω(a)da. |
It is easy to see that
Δ2≤Gh∫t−h0e−μ0ada≤Ghμ0. |
Hence
∫∞0|˜e(a+h,t)−˜e(a,t)|da≤ (2fβA2+Gμ0)h, |
and condition (ⅲ) directly follows.
As to
∫∞0|˜i(b+h,t)−˜i(b,t)|db=∫t−h0|i(b+h,t)−i(b,t)|db+∫tt−h|0−i(b,t)|db=∫t−h0|i(0,t−b−h)Γ(b+h)−i(0,t−b)Γ(b)|db+∫tt−h|i(0,t−b)Γ(b)|db≤Υ1+Υ2+[(1−f)βA2+ˉξA]h, |
where
Υ1=∫t−h0i(0,t−b−h)|Γ(b+h)−Γ(b)|db |
and
Υ2=∫t−h0|i(0,t−b−h)−i(0,t−b)|Γ(b)db. |
Similarly, we have
Υ1≤[(1−f)βA2+ˉξA]h. |
Next we estimate
Υ2=∫t−h0|(1−f)βT(t−a−h)V(t−a−h)+M(t−a−h)−(1−f)βT(t−a)V(t−a)−M(t−a)|Γ(b)da≤(1−f)β∫t−h0|T(t−a−h)V(t−a−h)−T(t−a)V(t−a)|Γ(b)da+∫t−h0|M(t−a−h)−M(t−a)|Γ(b)da. |
As before,
Υ2≤M1h∫t−h0e−μ0bdb≤Hhμ0. |
Finally, we have
∫∞0|˜i(b+h,t)−˜i(b,t)|db≤{2[(1−f)βA2+ˉξA]+Hμ0}h, |
thus condition (ⅲ) directly follows. This completes the proof.
Consequently, we have the following theorem for the semi-flow
Theorem 3.3. The semi-flow
This section is spent on proving that (1) is uniformly persistent under the condition
Let
{dT(t)dt=h−dT(t)−1fˆe(t),e(a,t)={ˆe(t−a)Ω(a),ift≥a≥0,e0(a−t)Ω(a)Ω(a−t),ifa≥t≥0;i(b,t)={ˆi(t−b)Γ(b),ift≥b≥0,i0(b−t)Γ(b)Γ(b−t),ifb≥t≥0, | (14) |
where
ˆe(t)= fβT(t)V(t) | (15) |
and
ˆi(t)=(1−f)βT(t)V(t)+∫t0ξ(a)Ω(a)ˆe(t−a)da+∫∞tξ(a)Ω(a)Ω(a−t)e0(a−t)da. | (16) |
Lemma 4.1. If
lim supt→∞ˆe(t)>ϵ0. | (17) |
Proof. We first get an estimate on
ˆi(t)≥(1−f)βT(t)V(t)+∫t0ξ(a)Ω(a)ˆe(t−a)da. | (18) |
Solving the fourth equation of (1) with initial condition
V(t)=V0e−ct+∫t0∫∞0p(b)i(b,τ)db⋅e−c(t−τ)dτ |
Then
V(t)≥∫t0e−c(t−τ)∫τ0p(b)i(b,τ)dbdτ=∫t0e−c(t−τ)∫τ0p(b)Γ(b)ˆi(τ−b)dbdτ. |
This, combined with (18), gives us
ˆi(t)≥(1−f)βT(t)∫t0e−c(t−τ)∫τ0p(b)Γ(b)ˆi(τ−b)dbdτ+fβ∫t0ξ(a)Ω(a)T(t−a)∫t−a0e−c(t−a−τ)∫τ0p(b)Γ(b)ˆi(τ−b)dbdτda. | (19) |
Since
(1−f)βch−ϵ1d∫∞0p(b)Γ(b)db+fβch−ϵ1d∫∞0p(b)Γ(b)db∫∞0ξ(a)Ω(a)da> 1. |
We claim that (17) holds for this
ˆe(t)≤ϵ0 for all t≥T. |
Then it follows from (14) that
ˆi(t)≥ (1−f)βh−ϵ1d∫t0e−c(t−τ)∫τ0p(b)Γ(b)ˆi(τ−b)dbdτ +fβh−ϵ1d∫t0ξ(a)Ω(a)∫t−a0e−c(t−a−τ)∫τ0p(b)Γ(b)ˆi(τ−b)dbdτda | (20) |
for all
L[ˆi]≥(1−f)βh−1d∫∞0e−λt∫t0e−c(t−τ)∫τ0p(b)Γ(b)ˆi(τ−b)dbdτdt+fβh−1d∫∞0e−λt∫t0ξ(a)Ω(a)∫t−a0e−c(t−a−τ)∫τ0p(b)Γ(b)ˆi(τ−b)dbdτdadt |
= (1−f)βh−ϵ1d1c+λ∫∞0e−λbp(b)Γ(b)dbL[ˆi] +fβh−ϵ1d1c+λ∫∞0e−λbp(b)Γ(b)db∫∞0e−λaξ(a)Ω(a)daL[ˆi]. |
Here
1≥(1−f)βch−ϵ1d∫∞0p(b)Γ(b)db+fβch−ϵ1d∫∞0p(b)Γ(b)db∫∞0ξ(a)Ω(a)da, |
which yields a contradiction.
In order to apply a technique used by Smith and Thieme [25,Chapter 9] (see also McCluskey [13,Section 8]), we consider a total
Let
ϕ(r+t)= Φ(t,ϕ(r)) for t≥0 and r∈R,e(a,r)= e(0,r−a)Ω(a)=ˆe(r−a)Ω(a) for r∈R and a≥0,i(b,r)= i(0,r−b)Γ(b)=ˆi(r−b)Γ(b) for r∈R and b≥0. |
So it follows from (14)-(15) that
{dT(r)dr=h−dT(r)−1fˆe(r),ˆe(r)=fβT(r)V(r),ˆi(r)=(1−f)βT(r)V(r)+∫∞0ξ(a)Ω(a)ˆe(r−a)da,dV(r)dr=∫∞0p(b)Γ(b)ˆi(r−b)db−cV(r), for r∈R. |
By the similar arguments as in McCluskey [13,Section 8] and Wang et al. [38,Section 5] and a slight modification of the proof in [17, Lemma 4.1], actually, a total
Thus Lemma 4.1 tells us that if
Theorem 4.2. If
When
lim inft→∞‖e(⋅,t)‖L1≥ˆe∞∫∞0Ω(a)da, |
where
Theorem 4.3. If
lim inft→∞T(t)≥ϵ,lim inft→∞‖e(⋅,t)‖L1≥ϵ,lim inft→∞‖i(⋅,t)‖L1≥ϵ,lim inft→∞V(t)≥ϵ. |
This section is devoted to investigate the local stability of equilibria of (1).
Theorem 5.1. (ⅰ) If
(ⅱ) If
Proof. Proof. of (ⅰ) of Theorem 5.1. Linearizing (1) around the infection-free equilibrium
x1(t)=T(t)−hd, x2(a,t)=e(a,t), x3(b,t)=i(b,t), x4(t)=V(t), |
we get
{dx1(t)dt=−dx1(t)−βhdx4(t),(∂∂t+∂∂a)x2(a,t)=−θ1(a)x2(a,t),(∂∂t+∂∂b)x3(b,t)=−θ2(b)x3(b,t),dx4(t)dt=∫∞0p(b)x3(b,t)db−cx4(t),x2(0,t)=fβhdx4(t),x3(0,t)=(1−f)βhdx4(t)+∫∞0ξ(a)x2(a,t)da. | (21) |
Set
x1(t)=x01eλt, x2(a,t)=x02(a)eλt, x3(b,t)=x03(b)eλt, x4(t)=x04eλt, | (22) |
where
λx01=−dx01−hβdx04, |
{λx02(a)+dx02(a)da=−θ1(a)x02(a),x02(0)=fβhdx04, | (23) |
{λx03(b)+dx03(b)db=−θ2(b)x03(b),x03(0)=(1−f)hβdx04+∫∞0ξ(a)x02(a)da, | (24) |
λx04=∫∞0p(b)x03(b)db−cx04. | (25) |
We integrate the first equation of Equ (23) and Equ (24) from
x02(a)= x02(0)e−λa−∫a0θ1(s)ds, | (26) |
and
x03(b)= x03(0)e−λb−∫b0θ2(s)ds= [(1−f)hβdx04+∫∞0ξ(a)x02(a)da]e−λb−∫b0θ2(s)ds. | (27) |
From (25), (26) and (27),
x04= ∫∞0p(b)x03(b)dbλ+c= 1−fλ+chβdx04∫∞0p(b)e−λb−∫b0θ2(s)dsdb +x02(0)λ+chd∫∞0ξ(a)e−λa−∫a0θ1(s)dsda∫∞0p(b)e−λb−∫b0θ2(s)dsdb. | (28) |
Combining (23) into (28), it follows the equation that
W(λ)=1, | (29) |
where
W(λ)= fβλ+chd∫∞0ξ(a)e−λa−∫a0θ1(s)dsda∫∞0p(b)e−λb−∫b0θ2(s)dsdb +1−fλ+chβd∫∞0p(b)e−λb−∫b0θ2(s)dsdb. |
Since
limλ→∞W(λ)=0, limλ→−∞W(λ)=∞, W′(λ)<0, |
Thus (29) admits a unique real root,
1=|W(λ)|=|W(μ+νi)|≤W(μ), |
which implies that
Proof of (ⅱ) of Theorem 5.1. Linearizing the system (1) at
y1(t)=T(t)−T∗, y2(a,t)=e(a,t)−e∗(a), y3(b,t)=i(b,t)−i∗(b), y4(t)=V(t)−V∗, |
we get
{dy1(t)dt=−dℜ0y1(t)−βT∗y4(t),(∂∂t+∂∂a)y2(a,t)=−θ1(a)y2(a,t),(∂∂t+∂∂b)y3(b,t)=−θ2(b)y3(b,t),dy4(t)dt=∫∞0p(b)y3(b,t)db−cy4(t),y2(0,t)=fd(ℜ0−1)y1(t)+fβT∗y4(t),y3(0,t)=(1−f)d(ℜ0−1)y1(t)+(1−f)βT∗y4(t)+∫∞0ξ(a)y2(a,t)da, | (30) |
Set
y1(t)=y01eλt, y2(a,t)=y02(a)eλt, y3(b,t)=y03(b)eλt, y4(t)=y04eλt, | (31) |
where
λy01=−dℜ0y01−βT∗y04, | (32) |
{λy02(a)+dy02(a)da=−θ1(a)y02(a),y02(0)=fd(ℜ0−1)y01+fβT∗y04, | (33) |
{λy03(b)+dy03(b)db=−θ2(b)y03(b),y03(0)=(1−f)d(ℜ0−1)y01+(1−f)βT∗y04+y02(0)∞∫0ξ(a)e−λa−a∫0θ1(s)dsda, | (34) |
and
λy04=∫∞0p(b)y03(b)db−cy04. | (35) |
We integrate the first equation of (33), (34) from
y02(a)= y02(0)e−λa−∫a0θ1(s)ds, |
and
y03(b)= y03(0)e−λb−∫b0θ2(s)ds= [(1−f)d(ℜ0−1)y01+(1−f)βT∗y04]e−λb−∫b0θ2(s)ds +y02(0)∫∞0ξ(a)e−λa−∫a0θ1(s)dsda⋅e−λb−∫b0θ2(s)ds. |
and from (35), we have
y04= ∫∞0p(b)y03(b)dbλ+c= 1−fλ+c(d(ℜ0−1)y01+βT∗y04)∫∞0p(b)e−λb−∫b0θ2(s)dsdb+y02(0)λ+c∫∞0ξ(a)e−λa−∫a0θ1(s)dsda∫∞0p(b)e−λb−∫b0θ2(s)dsdb. | (36) |
Combining (32), (33) into (36), yields the characteristic equation at
G(λ)=(λ+d)W1(λ)−λ−dℜ0=0, | (37) |
where
W1(λ)= (1−f)βT∗λ+c∫∞0p(b)e−λb−∫b0θ2(s)dsdb+fβT∗λ+c∫∞0ξ(a)e−λa−∫a0θ1(s)dsda∫∞0p(b)e−λb−∫b0θ2(s)dsdb. |
It is sufficient to show that (37) has no roots with non-negative real parts. Suppose that it has a root
(μ+νi+d)W1(μ+νi)−μ−νi−dℜ0=0. |
Separating the real part of the above equality gives
Re W1(μ+νi)=(μ+dℜ0)(μ+d)+ν2(μ+d)2+ν2>1. | (38) |
Noticing that
Re W1(μ+νi)≤|W1(μ)|=W1(μ)≤W1(0)=1, |
which yields a contradiction. This completes the proof.
This section is devoted to investigate the global stability of the equilibria by using Lyapunov functionals under the threshold value. In what follows, we introduce an important function
Theorem 6.1. The infection-free equilibrium
Proof. Considering the candidate Lyapunov function as follows,
LIFE(t)=L1(t)+L2(t)+L3(t)+L4(t), |
where
dL1(t)dt=−dT0(T0T+TT0−2)−βTV+βT0V. |
By integration by parts, we calculate the derivative of
dL2(t)dt= ∫∞0ϕ(a)∂e(a,t)∂tda=−∫∞0ϕ(a)[θ1(a)e(a,t)+∂e(a,t)∂a]da= −ϕ(a)e(a,t)|∞0+∫∞0ϕ′(a)e(a,t)da−∫∞0ϕ(a)θ1(a)e(a,t)da= ϕ(0)e(0,t)+∫∞0(ϕ′(a)−ϕ(a)θ1(a))e(a,t)da. |
An argument similar to the one used in calculating the derivative of
dL3(t)dt=ψ(0)i(0,t)+∫∞0(ψ′(b)−ψ(b)θ2(b))i(b,t)db. |
We calculate the derivative of
dL4(t)dt=βT0c∫∞0p(b)i(b,t)db−βT0V. |
Secondly, we have
dLIFE(t)dt=−dT0(T0T+TT0−2)−βTV+ϕ(0)fβTV+ψ(0)(1−f)βTV+∫∞0(ϕ′(a)−ϕ(a)θ1(a)+ψ(0)ξ(a))e(a,t)da+∫∞0(ψ′(b)−ψ(b)θ2(b)+βT0cp(b))i(b,t)db. |
Choosing
{ψ(b)=∫∞bβT0cp(u)e−∫ubθ2(ω)dωdu,ϕ(a)=∫∞aψ(0)ξ(u)e−∫uaθ1(ω)dωdu. |
Then it is easy to see that
{ψ(0)=βT0Jc, ϕ(0)=βT0JKc,ψ′(b)−ψ(b)θ2(b)+βT0cp(b)=0,ϕ′(a)−ϕ(a)θ1(a)+ψ(0)ξ(a)=0. |
Consequently,
dLIFE(t)dt=−dT0(T0T+TT0−2)+(ℜ0−1)βTV. |
Notice that
To establish the global stability of the infection equilibrium, we introduce the following Lemma.
Lemma 6.2. Suppose that
(1−f)βT∗V∗[1−e(0,t)i∗(0)e∗(0)i(0,t)]+∫∞0ξ(a)e∗(a)[1−e(a,t)i∗(0)e∗(a)i(0,t)]da=0, | (39) |
Proof. We give the proof for (39). In fact,
(1−f)βT∗V∗+∫∞0ξ(a)e∗(a)da −(1−f)βT∗V∗e(0,t)i∗(0)e∗(0)i(0,t)−∫∞0ξ(a)e∗(a)e(a,t)i∗(0)e∗(a)i(0,t)da |
= i∗(0)−((1−f)βTV+∫∞0ξ(a)e(a,t)da)i∗(0)i(0,t)= 0 |
This immediately gives (39).
Theorem 6.3. If
Proof. Let
G[x,y]=x−y−ylnxy, for x,y>0. |
It is easy to see that
Considering the following candidate Lyapunov function,
LEE(t)=H1(t)+H2(t)+H3(t)+H4(t), |
where
H1(t)=G[T,T∗], H2(t)=∫∞0ϕ1(a)G[e(a,t),e∗(a)]da, H3(t)=∫∞0ψ1(b)G[i(b,t),i∗(b)]db, H4(t)=βT∗cG[V,V∗]. |
We define
ψ1(b)=∫∞bβT∗cp(u)e−∫ubθ2(ω)dωdu, |
and
ϕ1(a)=∫∞aψ1(0)ξ(u)e−∫uaθ1(ω)dωdu, |
it follows that
ψ′1(b)−ψ1(b)θ2(b)= −βT∗cp(b). |
ϕ′1(a)−ϕ1(a)θ1(a)= −ψ1(0)ξ(a). |
Firstly, we calculate the derivative of
dH1(t)dt=−dT∗(TT∗+T∗T−2)+1f(1−T∗T)(e∗(0)−e(0,t)) |
By using (4),
H2(t)= ∫t0ϕ1(a)G[e(0,t−a)Ω(a),e∗(a)]da +∫∞tϕ1(a)G[e0(a−t)e−∫aa−tθ1(ω)dω,e∗(a)]da= ∫t0ϕ1(t−r)G[e(0,r)Ω(t−r),e∗(t−r)]dr +∫∞0ϕ1(t+r)G[e0(r)e−∫t+rrθ1(ω)dω,e∗(t+r)]dr= B1(t)+B2(t). |
The derivative of
dB1(t)dt=ϕ1(0)G[e(0,t),e∗(0)]+∫t0ϕ′1(t−r)G[e(0,r)e−∫t−r0θ1(ω)dω,e∗(t−r)]dr −∫t0ϕ1(t−r)θ1(t−r)[e(0,r)e−∫t−r0θ1(ω)dωGx[e(0,r)e−∫t−r0θ1(ω)dω,e∗(t−r)] +e∗(t−r)Gy[e(0,r)e−∫t−r0θ1(ω)dω,e∗(t−r)]]dr, |
and
dB2(t)dt=∫∞0ϕ′1(t+r)G[e0(r)e−∫t+rrθ1(ω)dω,e∗(t+r)]dr −∫∞0ϕ1(t+r)θ1(t+r)[e0(r)e−∫t+rrθ1(ω)dωGx[e0(r)e−∫t+rrθ1(ω)dω,e∗(t+r)] +e∗(t+r)Gy[e0(r)e−∫t+rrθ1(ω)dω,e∗(t+r)]]dr. |
We obtain the derivative of
dH2(t)dt=ϕ1(0)G[e(0,t),e∗(0)]+∫∞0[ϕ1′(a)−ϕ1(a)θ1(a)]G[e(a,t),e∗(a)]da=ϕ1(0)G[e(0,t),e∗(0)]−∫∞0ψ1(0)ξ(a)G[e(a,t),e∗(a)]da. |
A similar argument as in the derivative of
dH3(t)dt= ψ1(0)G[i(0,t),i∗(0)]+∫∞0[ψ′(b)−ψ(b)θ2(b)]G[i(b,t),i∗(b)]db= ψ1(0)G[i(0,t),i∗(0)]−∫∞0βT∗cp(b)G[i(b,t),i∗(b)]db. |
We calculate the derivative of
dH4(t)dt=βT∗c∫∞0p(b)i(b,t)db−βT∗V+βT∗V∗−βT∗V∗cV∫∞0p(b)i(b,t)db. |
If follows from
dLEEdt=−dT∗(TT∗+T∗T−2)+1f(1−T∗T)(e∗(0)−e(0,t))+ϕ1(0)G[e(0,t),e∗(0)]−∫∞0ψ1(0)ξ(a)G[e(a,t),e∗(a)]da+ψ1(0)G[i(0,t),i∗(0)]−∫∞0βT∗cp(b)G[i(b,t),i∗(b)]db+∫∞0βT∗cp(b)i(b,t)db+βT∗V∗−βT∗V−V∗V∫∞0βT∗cp(b)i(b,t)db. | (40) |
Recall that
(1−f)(βT∗V∗−βTV)+∫∞0ξ(a)(e∗(a)−e(a,t))da=i∗(0)−i(0,t), |
and
fβT∗KJc+(1−f)βT∗Jc=(fβKJc+(1−f)βJc)T0ℜ0=1. |
Thus (40) becomes
dLEE(t)dt=−dT∗(TT∗+T∗T−2)+1f(1−T∗T)(e∗(0)−e(0,t))+1fG[e(0,t),e∗(0)]−∫∞0βT∗cp(b)G[i(b,t),i∗(b)]db+βT∗Jc[(1−f)βT∗V∗lne(0,t)i∗(0)e∗(0)i(0,t)+∫∞0ξ(a)e∗(a)lne(a,t)i∗(0)e∗(a)i(0,t)da]+∫∞0βT∗cp(b)i(b,t)db+βT∗V∗−βT∗V−V∗V∫∞0βT∗cp(b)i(b,t)db. |
It follows that,
dLEE(t)dt=−dT∗(TT∗+T∗T−2)−1fe∗(0)(T∗T−lne(0,t)e∗(0))−∫∞0βT∗cp(b)G[i(b,t),i∗(b)]db+βT∗Jc[(1−f)βT∗V∗lne(0,t)i∗(0)e∗(0)i(0,t)+∫∞0ξ(a)e∗(a)lne(a,t)i∗(0)e∗(a)i(0,t)da]+∫∞0βT∗cp(b)i(b,t)db+βT∗V∗−V∗V∫∞0βT∗cp(b)i(b,t)db. | (41) |
Recall that
dLEE(t)dt=−dT∗(TT∗+T∗T−2) +βT∗Jc[(1−f)βT∗V∗lne(0,t)i∗(0)e∗(0)i(0,t)+∫∞0ξ(a)e∗(a)lne(a,t)i∗(0)e∗(a)i(0,t)da] +∫∞0βT∗cp(b)i∗(b)(2+lni(b,t)i∗(b)−T∗T−lne(0,t)e∗(0)−V∗i(b,t)Vi∗(b))db. |
Further, we have
dLEE(t)dt=−dT∗(TT∗+T∗T−2)+βT∗Jc(1−f)βT∗V∗(1−e(0,t)i∗(0)e∗(0)i(0,t)+lne(0,t)i∗(0)e∗(0)i(0,t))+βT∗Jc∫∞0ξ(a)e∗(a)(1−e(a,t)i∗(0)e∗(a)i(0,t)+lne(a,t)i∗(0)e∗(a)i(0,t))da+∫∞0βT∗p(b)ci∗(b)(2−T∗T+lnT∗T−V∗i(b,t)Vi∗(b)+lnV∗i(b,t)Vi∗(b))db | (42) |
−βT∗Jc{(1−f)βT∗V∗[1−e(0,t)i∗(0)e∗(0)i(0,t)] +∫∞0ξ(a)e∗(a)[1−e(a,t)i∗(0)e∗(a)i(0,t)]da}. |
Recall that Lemma 6.2 holds. Putting (39) into (42), we have
dLEE(t)dt= −dT∗(TT∗+T∗T−2) −βT∗Jc[∫∞0ξ(a)e∗(a)g(e(a,t)i∗(0)e∗(a)i(0,t))da +(1−f)∫∞0βT∗cp(b)i∗(b)g(e(0,t)i∗(0)e∗(0)i(0,t))db] −∫∞0βT∗cp(b)i∗(b)[g(T∗T)+g(V∗i(b,t)Vi∗(b))]db≤ 0 |
and
i(b,t)i∗(b)=i(0,t)i∗(0)=VV∗=e(0,t)e∗(0)=e(a,t)e∗(a), for all a, b≥0. |
It is not difficult to check that the largest invariant subset
This paper is devoted to the global dynamics of an HIV infection model subject to latency age and infection age, where the model formulation, basic reproduction number computation, and rigorous mathematical analysis, such as relative compactness and persistence of the solution semi-flows, and existence of a global attractor are involved. We have shown that the existence of a compact attractor of all compact sets of nonnegative initial data and used the Lyapunov functional to show that this attractor is the singleton set containing the equilibrium. Given that the model is so complex, the proof does require some rigorous calculation. The dynamics (at least the long-term dynamics) of the model do not appear to have been altered by adding the
The authors would like to thank the anonymous referees and editor for very helpful suggestions and comments which led to improvements of our original manuscript. J. Wang is supported by National Natural Science Foundation of China (No. 11226255 and No. 11201128), the Science and Technology Innovation Team in Higher Education Institutions of Heilongjiang Province (No. 2014TD005). X. Dong is supported by Graduate Students Innovation Research Program of Heilongjiang University (No. YJSCX2017-177HLJU).
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