Loading [MathJax]/jax/output/SVG/jax.js
Research article

Dynamical analysis of a heterogeneous spatial diffusion Zika model with vector-bias and environmental transmission


  • Received: 05 November 2023 Revised: 03 January 2024 Accepted: 26 January 2024 Published: 31 January 2024
  • In this study, we formulate a reaction-diffusion Zika model which incorporates vector-bias, environmental transmission and spatial heterogeneity. The main question of this paper is the analysis of the threshold dynamics. For this purpose, we establish the mosquito reproduction number R1 and basic reproduction number R0. Then, we analyze the dynamical behaviors in terms of R1 and R0. Numerically, we find that the ignorance of the vector-bias effect will underestimate the infection risk of the Zika disease, ignorance of the spatial heterogeneity effect will overestimate the infection risk, and the environmental transmission is indispensable.

    Citation: Liping Wang, Xinyu Wang, Dajun Liu, Xuekang Zhang, Peng Wu. Dynamical analysis of a heterogeneous spatial diffusion Zika model with vector-bias and environmental transmission[J]. Electronic Research Archive, 2024, 32(2): 1308-1332. doi: 10.3934/era.2024061

    Related Papers:

    [1] Rou Lin, Min Zhao, Jinlu Zhang . Random uniform exponential attractors for non-autonomous stochastic Schrödinger lattice systems in weighted space. AIMS Mathematics, 2023, 8(2): 2871-2890. doi: 10.3934/math.2023150
    [2] Ailing Ban . Asymptotic behavior of non-autonomous stochastic Boussinesq lattice system. AIMS Mathematics, 2025, 10(1): 839-857. doi: 10.3934/math.2025040
    [3] Xin Liu . Stability of random attractors for non-autonomous stochastic p-Laplacian lattice equations with random viscosity. AIMS Mathematics, 2025, 10(3): 7396-7413. doi: 10.3934/math.2025339
    [4] Xintao Li, Yunlong Gao . Random uniform attractors for fractional stochastic FitzHugh-Nagumo lattice systems. AIMS Mathematics, 2024, 9(8): 22251-22270. doi: 10.3934/math.20241083
    [5] Chunting Ji, Hui Liu, Jie Xin . Random attractors of the stochastic extended Brusselator system with a multiplicative noise. AIMS Mathematics, 2020, 5(4): 3584-3611. doi: 10.3934/math.2020233
    [6] Xintao Li, Lianbing She, Rongrui Lin . Invariant measures for stochastic FitzHugh-Nagumo delay lattice systems with long-range interactions in weighted space. AIMS Mathematics, 2024, 9(7): 18860-18896. doi: 10.3934/math.2024918
    [7] Hamood Ur Rehman, Aziz Ullah Awan, Sayed M. Eldin, Ifrah Iqbal . Study of optical stochastic solitons of Biswas-Arshed equation with multiplicative noise. AIMS Mathematics, 2023, 8(9): 21606-21621. doi: 10.3934/math.20231101
    [8] Xiaobin Yao . Random attractors for non-autonomous stochastic plate equations with multiplicative noise and nonlinear damping. AIMS Mathematics, 2020, 5(3): 2577-2607. doi: 10.3934/math.2020169
    [9] Xiao Bin Yao, Chan Yue . Asymptotic behavior of plate equations with memory driven by colored noise on unbounded domains. AIMS Mathematics, 2022, 7(10): 18497-18531. doi: 10.3934/math.20221017
    [10] Li Yang . Pullback random attractors of stochastic strongly damped wave equations with variable delays on unbounded domains. AIMS Mathematics, 2021, 6(12): 13634-13664. doi: 10.3934/math.2021793
  • In this study, we formulate a reaction-diffusion Zika model which incorporates vector-bias, environmental transmission and spatial heterogeneity. The main question of this paper is the analysis of the threshold dynamics. For this purpose, we establish the mosquito reproduction number R1 and basic reproduction number R0. Then, we analyze the dynamical behaviors in terms of R1 and R0. Numerically, we find that the ignorance of the vector-bias effect will underestimate the infection risk of the Zika disease, ignorance of the spatial heterogeneity effect will overestimate the infection risk, and the environmental transmission is indispensable.



    Lattice dynamical systems arise from a variety of applications in electrical engineering, biology, chemical reaction, pattern formation and so on, see, e.g., [4,7,14,19,33]. Many researchers have discussed broadly the deterministic models in [6,12,34,39], etc. Stochastic lattice equations, driven by additive independent white noise, was discussed for the first time in [2], followed by extensions in [8,13,15,16,21,23,27,32,35,36,37,38,40].

    In this paper, we will study the long term behavior of the following second order non-autonomous stochastic lattice system driven by additive white noise: for given τR, t>τ and iZ,

    {¨u+νA˙u+h(˙u)+Au+λu+f(u)=g(t)+a˙ω(t),u(τ)=(uτi)iZ=uτ,˙u(τ)=(u1τi)iZ=u1τ, (1.1)

    where u=(ui)iZ is a sequence in l2, ν and λ are positive constants, ˙u=(˙ui)iZ and ¨u=(¨ui)iZ denote the fist and the second order time derivatives respectively, Au=((Au)i)iZ, A˙u=((A˙u)i)iZ, A is a linear operators defined in (2.2), a=(ai)iZl2, f(u)=(fi(ui))iZ and h(˙u)=(hi(˙ui))iZ satisfy certain conditions, g(t)=(gi(t))iZL2loc(R,l2) is a given time dependent sequence, and ω(t)=W(t,ω) is a two-sided real-valued Wiener process on a probability space.

    The approximation we use in the paper was first proposed in [18,22] where the authors investigated the chaotic behavior of random equations driven by Gδ(θtω). Since then, their work was extended by many scholars. To the best of my knowledge, there are three forms of Wong-Zakai approximations Gδ(θtω) used recenly, Euler approximation of Brownian [3,10,17,20,25,28,29,30], Colored noise [5,11,26,31] and Smoothed approximation of Brownian motion by mollifiers [9]. In this paper, we will focus on Euler approximation of Brownian and compare the long term behavior of system (1.1) with pathwise deterministic system given by

    {¨uδ+νA˙uδ+h(˙uδ)+Auδ+λuδ+f(uδ)=g(t)+aGδ(θtω),uδ(τ)=(uδτi)iZ=uδτ,˙uδ(τ)=(uδ,1τi)iZ=uδ,1τ, (1.2)

    for δR with δ0, τR, t>τ and iZ, where Gδ(θtω) is defined in (3.2). Note that the solution of system (1.2) is written as uδ to show its dependence on δ.

    This paper is organized as follows. In Section 2, we prove the existence and uniqueness of random attractors of system (1.1). Section 3 is devoted to consider the the Wong-Zakai approximations associated with system (1.1). In Section 4, we establish the convergence of solutions and attractors for approximate system (1.2) when δ0.

    Throughout this paper, the letter c and ci(i=1,2,) are generic positive constants which may change their values from line to line.

    In this section, we will define a continuous cocycle for second order non-autonomous stochastic lattice system (1.1), and then prove the existence and uniqueness of pullback attractors.

    A standard Brownian motion or Wiener process (Wt)tR (i.e., with two-sided time) in R is a process with W0=0 and stationary independent increments satisfying WtWsN(0,|ts|I). F is the Borel σ-algebra induced by the compact-open topology of Ω, and P is the corresponding Wiener measure on (Ω,F), where

    Ω={ωC(R,R):ω(0)=0},

    the probability space (Ω,F,P) is called Wiener space. Define the time shift by

    θtω()=ω(+t)ω(t),ωΩ, tR.

    Then (Ω,F,P,{θt}tR) is a metric dynamical system (see [1]) and there exists a {θt}tR-invariant subset ˜ΩΩ of full measure such that for each ωΩ,

    ω(t)t0ast±. (2.1)

    For the sake of convenience, we will abuse the notation slightly and write the space ˜Ω as Ω.

    We denote by

    lp={u|u=(ui)iZ,uiR, iZ|ui|p<+},

    with the norm as

    upp=iZ|ui|p.

    In particular, l2 is a Hilbert space with the inner product (,) and norm given by

    (u,v)=iZuivi,u2=iZ|ui|2,

    for any u=(ui)iZ, v=(vi)iZl2.

    Define linear operators B, B, and A acting on l2 in the following way: for any u=(ui)iZl2,

    (Bu)i=ui+1ui,(Bu)i=ui1ui,

    and

    (Au)i=2uiui+1ui1. (2.2)

    Then we find that A=BB=BB and (Bu,v)=(u,Bv) for all u,vl2.

    Also, we let Fi(s)=s0fi(r)dr, h(˙u)=(hi(˙ui))iZ, f(u)=(fi(ui))iZ with fi,hiC1(R,R) satisfy the following assumptions:

    |fi(s)|α1(|s|p+|s|), (2.3)
    sfi(s)α2Fi(s)α3|s|p+1, (2.4)

    and

    hi(0)=0,0<h1hi(s)h2,sR, (2.5)

    where p>1, αi and hj are positive constants for i=1,2,3 and j=1,2.

    In addition, we let

    β=h1λ4λ+h22,β<1ν, (2.6)

    and

    σ=h1λ4λ+h22(h2+4λ+h22). (2.7)

    For any u,vl2, we define a new inner product and norm on l2 by

    (u,v)λ=(1νβ)(Bu,Bv)+λ(u,v),u2λ=(u,u)λ=(1νβ)Bu2+λu2.

    Denote

    l2=(l2,(,),),l2λ=(l2,(,)λ,λ).

    Then the norms and λ are equivalent to each other.

    Let E=l2λ×l2 endowed with the inner product and norm

    (ψ1,ψ2)E=(u(1),u(2))λ+(v(1),v(2)),ψ2E=u2λ+v2,

    for ψj=(u(j),v(j))T=((u(j)i),(v(j)i))TiZE, j=1,2,ψ=(u,v)T=((ui),(vi))TiZE.

    A family D={D(τ,ω):τR,ωΩ} of bounded nonempty subsets of E is called tempered (or subexponentially growing) if for every ϵ>0, the following holds:

    limteϵtD(τ+t,θtω)2=0,

    where D=supxDxE. In the sequel, we denote by D the collection of all families of tempered nonempty subsets of E, i.e.,

    D={D={D(τ,ω):τR,ωΩ}:Dis tempered inE}.

    The following conditions will be needed for g when deriving uniform estimates of solutions, for every τR,

    τeγsg(s)2ds<, (2.8)

    and for any ς>0

    limteςt0eγsg(s+t)2ds=0, (2.9)

    where γ=min{σ2,α2βp+1}.

    Let ˉv=˙u+βu and ˉφ=(u,ˉv)T, then system (1.1) can be rewritten as

    ˙ˉφ+L1(ˉφ)=H1(ˉφ)+G1(ω), (2.10)

    with initial conditions

    ˉφτ=(uτ,ˉvτ)T=(uτ,u1τ+βuτ)T,

    where

    L1(ˉφ)=(βuˉv(1νβ)Au+νAˉv+λu+β2uβˉv)+(0h(ˉvβu)),
    H1(ˉφ)=(0f(u)+g(t)),G1(ω)=(0a˙ω(t)).

    Denote

    v(t)=ˉv(t)aω(t)andφ=(u,v)T.

    By (2.10) we have

    ˙φ+L(φ)=H(φ)+G(ω), (2.11)

    with initial conditions

    φτ=(uτ,vτ)T=(uτ,u1τ+βuτaω(τ))T,

    where

    L(φ)=(βuv(1νβ)Au+νAv+λu+β2uβv)+(0h(vβu+aω(t))),
    H(φ)=(0f(u)+g(t)),G(ω)=(aω(t)βaω(t)νAaω(t)).

    Note that system (2.11) is a deterministic functional equation and the nonlinearity in (2.11) is locally Lipschitz continuous from E to E. Therefore, by the standard theory of functional differential equations, system (2.11) is well-posed. Thus, we can define a continuous cocycle Φ0:R+×R×Ω×EE associated with system (2.10), where for τR, tR+ and ωΩ

    Φ0(t,τ,ω,ˉφτ)=ˉφ(t+τ,τ,θτω,ˉφτ)=(u(t+τ,τ,θτω,uτ),ˉv(t+τ,τ,θτω,ˉvτ))T=(u(t+τ,τ,θτω,uτ),v(t+τ,τ,θτω,vτ)+a(ω(t)ω(τ)))T=φ(t+τ,τ,θτω,φτ)+(0,a(ω(t)ω(τ)))T,

    where vτ=ˉvτ+aω(τ).

    Lemma 2.1. Suppose that (2.3)–(2.8) hold. Then for every τR, ωΩ, and T>0, there exists c=c(τ,ω,T)>0 such that for allt[τ,τ+T], the solution φ of system (2.11) satisfies

    φ(t,τ,ω,φτ)2E+tτφ(s,τ,ω,φτ)2Edsctτ(g(s)2+|ω(s)|2+|ω(s)|p+1)ds+c(φτ2E+2iZFi(uτ,i)).

    Proof. Taking the inner product (,)E on both side of the system (2.11) with φ, it follows that

    12ddtφ2E+(L(φ),φ)E=(H(φ),φ)E+(G(ω),φ)E. (2.12)

    For the second term on the left-hand side of (2.12), we have

    (L(φ),φ)E=βu2λ+β2(u,v)βv2+ν(Av,v)+(h(vβu+aω(t)),v).

    By the mean value theorem and (2.5), there exists ξi(0,1) such that

    β2(u,v)+(h(vβu+aω(t)),v)=β2(u,v)+iZhi(ξi(viβui+aiω(t)))(viβui+aiω(t))vi(β2h2β)uv+h1v2h2|(aω(t),v)|.

    Then

    (L(φ),φ)Eσφ2Eh12v2(βσ)u2λ+(h12βσ)v2βh2λuλvh2|(aω(t),v)|,

    which along with (2.6) and (2.7) implies that

    (L(φ),φ)Eσφ2E+h12v2σ+h16v2c|ω(t)|2a2. (2.13)

    As to the first term on the right-hand side of (2.12), by (2.3) and (2.4) we get

    (H(φ),φ)E=(f(u),˙u+βuaω(t))+(g(t),v)ddt(iZFi(ui))α2βiZFi(ui)+α1iZ(|ui|p+|ui|)|aiω(t)|+(g(t),v)ddt(iZFi(ui))α2βp+1iZFi(ui)+c|ω(t)|p+1ap+1+σλ4u2+ca2|ω(t)|2+σ+h16v2+cg(t)2. (2.14)

    The last term of (2.12) is bounded by

    (G(ω),φ)E=ω(t)(a,u)λ+βω(t)(a,v)νω(t)(Aa,v)σ4u2λ+1σa2λ|ω(t)|2+σ+h16v2+c|ω(t)|2a2. (2.15)

    It follows from (2.12)–(2.15) that

    ddt(φ2E+2iZFi(ui))+γ(φ2E+2iZFi(ui))+γφ2Ec(g(t)2+|ω(t)|2+|ω(t)|p+1), (2.16)

    where γ=min{σ2,α2βp+1}. Multiplying (2.16) by eγt and then integrating over (τ,t) with tτ, we get for every ωΩ

    φ(t,τ,ω,φτ)2E+γtτeγ(st)φ(s,τ,ω,φτ)2Edseγ(τt)(φτ2E+2iZFi(uτ,i))+ctτeγ(st)(g(s)2+|ω(s)|2+|ω(s)|p+1)ds, (2.17)

    which implies desired result.

    Lemma 2.2. Suppose that (2.3)–(2.9) hold. Then the continuous cocycle Φ0 associated with system (2.10) has a closed measurable D-pullback absorbing set K0={K0(τ,ω):τR,ωΩ}D, where for every τR and ωΩ

    K0(τ,ω)={ˉφE:ˉφ2ER0(τ,ω)}, (2.18)

    where ˉφτtD(τt,θtω) and R0(τ,ω) is given by

    R0(τ,ω)=c+c|ω(τ)|2+c0eγs(g(s+τ)2+|ω(s)ω(τ)|2+|ω(s)ω(τ)|p+1)ds, (2.19)

    where c is a positive constant independent of τ, ω and D.

    Proof. By (2.17), we get for every τR, tR+ and ωΩ

    φ(τ,τt,θτω,φτt)2E+γττteγ(sτ)φ(s,τt,θτω,φτt)2Edseγt(φτt2E+2iZFi(uτt,i))+cττteγ(sτ)(g(s)2+|ω(sτ)ω(τ)|2+|ω(sτ)ω(τ)|p+1)dseγt(φτt2E+2iZFi(uτt,i))+c0teγs(g(s+τ)2+|ω(s)ω(τ)|2+|ω(s)ω(τ)|p+1)ds. (2.20)

    By (2.1) and (2.8), the last integral on the right-hand side of (2.20) is well defined. For any sτt,

    ˉφ(s,τt,θτω,ˉφτt)=φ(s,τt,θτω,φτt)+(0,a(ω(sτ)ω(τ)))T,

    which along with (2.20) implies that

    ˉφ(τ,τt,θτω,ˉφτt)2E+γττteγ(sτ)ˉφ(s,τt,θτω,ˉφτt)2Eds2φ(τ,τt,θτω,φτt)2E+2γττteγ(sτ)φ(s,τt,θτω,φτt)2Eds+2a2(|ω(τ)|2+γττteγ(sτ)|ω(sτ)ω(τ)|2ds)4eγt(ˉφτt2E+a2|ω(t)ω(τ)|2+iZFi(uτt,i))+c|ω(τ)|2+c0eγs(g(s+τ)2+|ω(s)ω(τ)|2+|ω(s)ω(τ)|p+1)ds. (2.21)

    By (2.3) and (2.4) we have

    iZFi(uτt,i)1α2iZfi(uτt,i)uτt,i1α2maxuτtsuτt|fi(s)|uτt2. (2.22)

    Using ˉφτtD(τt,θtω), (2.1) and (2.22), we find

    lim supt+4eγt(ˉφτt2E+a2|ω(t)ω(τ)|2+iZFi(uτt,i))=0, (2.23)

    which along with (2.21) implies that there exists T=T(τ,ω,D)>0 such that for all tT,

    ˉφ(τ,τt,θτω,ˉφτt)2E+γττteγ(sτ)ˉφ(s,τt,θτω,ˉφτt)2Edsc+c|ω(τ)|2+c0eγs(g(s+τ)2+|ω(s)ω(τ)|2+|ω(s)ω(τ)|p+1)ds, (2.24)

    where c is a positive constant independent of τ, ω and D. Note that K0 given by (2.18) is closed measurable random set in E. Given τR, ωΩ, and DD, it follows from (2.24) that for all tT,

    Φ0(t,τt,θtω,D(τt,θtω))K0(τ,ω), (2.25)

    which implies that K0 pullback attracts all elements in D. By (2.1) and (2.9), one can easily check that K0 is tempered, which along with (2.25) completes the proof.

    Next, we will get uniform estimates on the tails of solutions of system (2.10).

    Lemma 2.3. Suppose that (2.3)–(2.9) hold. Then for every τR, ωΩ, D={D(τ,ω):τR,ωΩ}D and ε>0, there exist T=T(τ,ω,D,ε)>0 and N=N(τ,ω,ε)>0 such that for alltT, the solution ˉφ of system (2.10) satisfies

    |i|N|ˉφi(τ,τt,θτω,ˉφτt,i)|2Eε,

    where ˉφτtD(τt,θtω) and |ˉφi|2E=(1νβ)|Bu|2i+λ|ui|2+|ˉvi|2.

    Proof. Let η be a smooth function defined on R+ such that 0η(s)1 for all sR+, and

    η(s)={0,0s1;1,s2.

    Then there exists a constant C0 such that |η(s)|C0 for sR+. Let k be a fixed positive integer which will be specified later, and set x=(xi)iZ, y=(yi)iZ with xi=η(|i|k)ui, yi=η(|i|k)vi. Note ψ=(x,y)T=((xi),(yi))TiZ. Taking the inner product of system (2.11) with ψ, we have

    (˙φ,ψ)E+(L(φ),ψ)E=(H(φ),ψ)E+(G,ψ)E. (2.26)

    For the first term of (2.26), we have

    (˙φ,ψ)E=(1νβ)iZ(B˙u)i(Bx)i+λiZ˙uixi+iZ˙viyi=12ddtiZη(|i|k)|φi|2E+(1νβ)iZ(B˙u)i((Bx)iη(|i|k)(Bu)i)12ddtiZη(|i|k)|φi|2E(1νβ)C0kiZ|(B(vβu+aω(t))i||ui+1|12ddtiZη(|i|k)|φi|2Eckφ2Eck|ω(t)|2a2, (2.27)

    where |φi|2E=(1νβ)|Bu|2i+λ|ui|2+|vi|2. As to the second term on the left-hand side of (2.26), we get

    (L(φ),ψ)E=β(1νβ)(Au,x)+(1νβ)((Au,y)(Av,x))+ν(Av,y)+λβ(u,x)+β2(u,y)β(v,y)+(h(vβu+aω(t)),y).

    It is easy to check that

    (Au,x)=iZ(Bu)i(η(|i|k)(Bu)i+(Bx)iη(|i|k)(Bu)i)iZη(|i|k)|Bu|2i2C0ku2,
    (Av,y)=iZ(Bv)i(η(|i|k)(Bv)i+(By)iη(|i|k)(Bv)i)iZη(|i|k)|Bv|2i2C0kv2,

    and

    (Au,y)(Av,x)C0kiZ|(Bu)i||vi+1|C0kiZ|(Bv)i||ui+1|2C0k(u2+v2).

    By the mean value theorem and (2.5), there exists ξi(0,1) such that

    β2(u,y)+(h(vβu+aω(t)),y)=β2iZη(|i|k)uivi+iZhi(ξi(viβui+aiω(t)))(viβui+aiω(t))η(|i|k)viβ(βh2)iZη(|i|k)|uivi|+h1iZη(|i|k)|vi|2h2iZη(|i|k)|viaiω(t)|.

    Then

    (L(φ),φ)EσiZη(|i|k)|φi|2Eh12iZη(|i|k)|vi|2(βσ)iZη(|i|k)((1νβ)|Bu|2i+λu2i)+(h12βσ)iZη(|i|k)|vi|2βh2λiZη(|i|k)|vi|((1νβ)(Bu)2i+λ|ui|2)12h2iZη(|i|k)|viaiω(t)|ckφ2E,

    which along with (2.6) and (2.7) implies that

    (L(φ),φ)EσiZη(|i|k)|φi|2E+h12iZη(|i|k)|vi|2ckφ2Eh2iZη(|i|k)|viaiω(t)|σiZη(|i|k)|φi|2E+h16iZη(|i|k)|vi|2ckφ2EciZη(|i|k)|ai|2|ω(t)|2. (2.28)

    As to the first term on the right-hand side of (2.26), by (2.3) and (2.4)we get

    (H(φ),ψ)E=iZη(|i|k)fi(ui)(˙ui+βuiaiω(t))+iZη(|i|k)gi(t)viddt(iZη(|i|k)Fi(ui))α2βp+1iZη(|i|k)Fi(ui)+ciZη(|i|k)|ω(t)|p+1|ai|p+1+σλ4iZη(|i|k)|ui|2+ciZη(|i|k)|ai|2|ω(t)|2+σ6iZη(|i|k)|vi|2+ciZη(|i|k)|gi(t)|2. (2.29)

    For the last term of (2.26), we have

    (G,ψ)E=ω(t)(a,x)λ+βω(t)(a,y)νω(t)(Aa,y)=ω(t)(1νβ)(Ba,Bx)νω(t)(Ba,By)+λω(t)(a,x)+βω(t)(a,y), (2.30)

    As to the first two terms on the right-hand side of (2.30), we get

    ω(t)(1νβ)(Ba,Bx)=ω(t)(1νβ)iZ(ai+1ai)(η(|i+1|k)ui+1η(|i|k)ui)(iZη(|i+1|k)u2i+1)12(iZη(|i+1|k)(ω(t)(1νβ)(ai+1ai))2)12+(iZη(|i|k)u2i)12(iZη(|i|k)(ω(t)(1νβ)(ai+1ai))2)12σλ8iZη(|i|k)u2i+c|ω(t)|2|i|ka2i, (2.31)

    and

    νω(t)(Ba,By)=νω(t)iZ(ai+1ai)(η(|i+1|k)vi+1η(|i|k)vi)σ6iZη(|i|k)v2i+c|ω(t)|2|i|ka2i. (2.32)

    The last two terms of (2.30) is bounded by

    λω(t)(a,x)+βω(t)(a,y)σλ8iZη(|i|k)u2i+σ+h16iZη(|i|k)v2i+c|ω(t)|2|i|ka2i. (2.33)

    It follows from (2.26)–(2.33) that

    ddt(iZη(|i|k)(|φi|2E+2Fi(ui)))+γ(iZη(|i|k)(|φi|2E+2Fi(ui)))+γiZη(|i|k)|φ|2Eckφ2E+ck|ω(t)|2+c|i|k|ai|p+1|ω(t)|p+1+c|i|k|gi(t)|2+c|i|k|ai|2|ω(t)|2, (2.34)

    where γ=min{σ2,α2βp+1}. Multiplying (2.34) by eγt, replacing ω by θτω and integrating on (τt,τ) with tR+, we get for every ωΩ

    iZη(|i|k)(|φi(τ,τt,θτω,φτt,i)|2E+2Fi(ui(τ,τt,θτω,uτt,i)))eγt(iZη(|i|k)(|φτt,i|2E+2Fi(uτt,i)))+ckττteγ(sτ)φ(s,τt,θτω,φτt)2Eds+ck0eγs|ω(s)ω(τ)|2ds+c|i|k|ai|p+10eγs|ω(s)ω(τ)|p+1ds+c|i|k|ai|20eγs|ω(s)ω(τ)|2ds+c0eγs|i|k|gi(s+τ)|2ds. (2.35)

    For any sτt,

    ˉφ(s,τt,θτω,ˉφτt)=φ(s,τt,θτω,φτt)+(0,a(ω(sτ)ω(τ)))T,

    which along with (2.35) implies that

    iZη(|i|k)(|ˉφi(τ,τt,θτω,ˉφτt,i)|2E+2Fi(ui(τ,τt,θτω,uτt,i)))4eγt(iZη(|i|k)(|ˉφτt,i|2E+|ai|2|ω(t)ω(τ)|2+Fi(uτt,i)))+ckττteγ(sτ)ˉφ(s,τt,θτω,ˉφτt)2Eds+ck0eγs|ω(s)ω(τ)|2ds+c|i|k|ai|p+10eγs|ω(s)ω(τ)|p+1ds+c|i|k|ai|20eγs|ω(s)ω(τ)|2ds+c0eγs|i|k|gi(s+τ)|2ds+2|i|k|ai|2|ω(τ)|2. (2.36)

    By (2.1) and (2.8), the last four integrals in (2.36) are well defined. By (2.3) and (2.4), we obtain

    iZη(|i|k)Fi(ui,τt)1α2iZη(|i|k)fi(uτt,i)uτt,i1α2maxuτtsuτt|fi(s)|uτt2,

    which along with ˉφτtD(τt,θtω) and (2.1) implies that

    lim supt+4eγt(iZη(|i|k)(|ˉφτt,i|2E+|ai|2|ω(t)ω(τ)|2+Fi(uτt,i)))=0.

    Then there exists T1=T1(τ,ω,D,ε)>0 such that for all tT1,

    4eγt(iZη(|i|k)(|ˉφτt,i|2E+|ai|2|ω(t)ω(τ)|2+Fi(uτt,i)))ε4. (2.37)

    By (2.1) and (2.24), there exist T2=T2(τ,ω,D,ε)>T1 and N1=N1(τ,ω,ε)>0 such that for all tT2 and kN1

    ckττteγ(sτ)ˉφ(s,τt,θτω,ˉφτt)2Eds+ck0eγs|ω(s)ω(τ)|2dsε4. (2.38)

    By (2.8), there exists N2=N2(τ,ω,ε)>N1 such that for all kN2,

    2|i|k|ai|2|ω(τ)|2+c0eγs|i|k|gi(s+τ)|2dsε4. (2.39)

    By (2.1) again, we find that there exists N3=N3(τ,ω,ε)>N2 such that for all kN3,

    c|i|k|ai|p+10eγs|ω(s)ω(τ)|p+1ds+c|i|k|ai|20eγs|ω(s)ω(τ)|2dsε4. (2.40)

    Then it follows from (2.36)–(2.40) that for all tT2 and kN3

    |i|2k|ˉφi(τ,τt,θτω,ˉφτt,i)|2EiZη(|i|k)|ˉφi(τ,τt,θτω,ˉφτt,i)|2Eε.

    This concludes the proof.

    As a consequence of Lemma 2.2 and Lemma 2.3, we get the existence of D-pullback attractors for Φ0 immediately.

    Theorem 2.1. Suppose that (2.3)–(2.9) hold. Then the continuous cocycle Φ0 associated with system (2.10) has a unique D-pullback attractors A0={A0(τ,ω):τR, ωΩ}D in E.

    In this section, we will approximate the solutions of system (1.1) by the pathwise Wong-Zakai approximated system (1.2). Given δ0, define a random variable Gδ by

    Gδ(ω)=ω(δ)δ,for allωΩ. (3.1)

    From (3.1) we find

    Gδ(θtω)=ω(t+δ)ω(t)δandt0Gδ(θsω)ds=t+δtω(s)δds+0δω(s)δds. (3.2)

    By (3.2) and the continuity of ω we get for all tR,

    limδ0t0Gδ(θsω)ds=ω(t). (3.3)

    Note that this convergence is uniform on a finite interval as stated below.

    Lemma 3.1. ([17]). Let τR, ωΩ and T>0. Then for every ε>0, there exists δ0=δ0(ε,τ,ω,T)>0 such that for all 0<|δ|<δ0 and t[τ,τ+T],

    |t0Gδ(θsω)dsω(t)|<ε.

    By Lemma 3.1, we find that there exist c=c(τ,ω,T)>0 and ˜δ0=˜δ0(τ,ω,T)>0 such that for all 0<|δ|<˜δ0 and t[τ,τ+T],

    |t0Gδ(θsω)ds|c. (3.4)

    By (3.3) we find that Gδ(θtω) is an approximation of the white noise in a sense. This leads us to consider system (1.2) as an approximation of system (1.1).

    Let ˉvδ=˙uδ+βuδ and ˉφδ=(uδ,ˉvδ), the system (1.2) can be rewritten as

    ˙ˉφδ+Lδ,1(ˉφδ)=Hδ,1(ˉφδ)+Gδ,1(ω), (3.5)

    with initial conditions

    ˉφδ,τ=(uδτ,ˉvδτ)T=(uδτ,uδ,1τ+βuδτ)T,

    where

    Lδ,1(ˉφ)=(βuδˉvδ(1νβ)Auδ+νAˉvδ+λuδ+β2uδβˉvδ)+(0h(ˉvδβuδ)),
    Hδ,1(¯φδ)=(0f(uδ)+g(t)),Gδ,1(ω)=(0aGδ(θtω)).

    Denote

    vδ(t)=ˉvδ(t)at0Gδ(θsω)dsandφδ=(uδ,vδ)T.

    By (3.5) we have

    ˙φδ+Lδ(φδ)=Hδ(φδ)+Gδ(ω), (3.6)

    with initial conditions

    φδ,τ=(uδτ,vδτ)T=(uδτ,uδ,1τ+βuδτaτ0Gδ(θsω)ds)T,

    where

    Lδ(φδ)=(βuδvδ(1νβ)Auδ+νAvδ+λuδ+β2uδβvδ)+(0h(vδβuδ+at0Gδ(θsω)ds)),
    Hδ(φδ)=(0f(uδ)+g(t)),Gδ(ω)=(at0Gδ(θsω)dsβat0Gδ(θsω)dsνAat0Gδ(θsω)ds).

    Note that system (3.6) is a deterministic functional equation and the nonlinearity in (3.6) is locally Lipschitz continuous from E to E. Therefore, by the standard theory of functional differential equations, system (3.6) is well-posed. Thus, we can define a continuous cocycle Φδ:R+×R×Ω×EE associated with system (3.5), where for τR, tR+ and ωΩ

    Φδ(t,τ,ω,ˉφδ,τ)=ˉφδ(t+τ,τ,θτω,ˉφδ,τ)=(uδ(t+τ,τ,θτω,uδτ),ˉvδ(t+τ,τ,θτω,ˉvδτ))T=(uδ(t+τ,τ,θτω,uδτ),vδ(t+τ,τ,θτω,vδτ)+atτGδ(θsω)ds)T=φδ(t+τ,τ,θτω,φδ,τ)+(0,atτGδ(θsω)ds)T,

    where vδτ=ˉvδτa0τGδ(θsω)ds.

    For later purpose, we now show the estimates on the solutions of system (3.6) on a finite time interval.

    Lemma 3.2. Suppose that (2.3)–(2.8) hold. Then for every τR, ωΩ, and T>0, there exist δ0=δ0(τ,ω,T)>0 and c=c(τ,ω,T)>0 such that for all 0<|δ|<δ0 andt[τ,τ+T], the solution φδ of system (3.6) satisfies

    φδ(t,τ,ω,φδ,τ)2E+tτφδ(s,τ,ω,φδ,τ)2Edsc(φδ,τ2E+2iZFi(uδτ,i))+ctτ(g(s)2+|s0Gδ(θlω)dl|2+|s0Gδ(θlω)dl|p+1|)ds.

    Proof. Taking the inner product (,)E on both side of the system (3.6) with φδ, it follows that

    12ddtφδ2E+(Lδ(φδ),φδ)E=(Hδ(φδ),φδ)E+(Gδ(ω),φδ)E. (3.7)

    By the similar calculations in (2.13)–(2.15), we get

    (Lδ(φδ),φδ)Eσφδ2E+h12vδ2σ+h16vδ2c|t0Gδ(θsω)ds|2a2, (3.8)
    (Hδ(φδ),φδ)Eddt(iZFi(uδi))α2βp+1iZFi(uδi)+c|t0Gδ(θsω)ds|p+1ap+1+σλ4uδ2+ca2|t0Gδ(θsω)ds|2+cg(t)2+σ+h16vδ2, (3.9)

    and

    (Gδ(ω),φδ)Eσ4uδ2λ+ca2|t0Gδ(θsω)ds|2+σ+h16vδ2. (3.10)

    It follows from (3.7)–(3.10) that

    ddt(φδ2E+2iZFi(uδi))+γ(φδ2E+2iZFi(uδi))+γφδ2Ec(g(t)2+|t0Gδ(θsω)ds|2+|t0Gδ(θsω)ds|p+1), (3.11)

    where γ=min{σ2,α2βp+1}. Multiplying (3.11) by eγt and integrating on (τ,t) with tτ, we get for every ωΩ

    φδ(t,τ,ω,φδ,τ)2E+γtτeγ(st)φδ(s,τ,ω,φδ,τ)2Edseγ(τt)(φδ,τ2E+2iZFi(uδτ,i))+ctτeγ(st)(g(s)2+|s0Gδ(θlω)dl|2+|s0Gδ(θlω)dl|p+1)ds,

    which implies the desired result.

    In what follows, we derive uniform estimates on the solutions of system (3.5) when t is sufficiently large.

    Lemma 3.3. Suppose that (2.3)–(2.8) hold. Then for every δ0, τR, ωΩ, and D={D(τ,ω):τR,ωΩ}D, there exists T=T(τ,ω,D,δ)>0 such that for alltT, the solution ˉφδ of system (3.5) satisfies

    ˉφδ(τ,τt,θτω,ˉφδ,τt)2E+γττteγ(sτ)ˉφδ(s,τt,θτω,ˉφδ,τt)2EdsRδ(τ,ω),

    where ˉφδ,τtD(τt,θtω) and Rδ(τ,ω) is given by

    Rδ(τ,ω)=c0eγs(g(s+τ)2+|sτGδ(θlω)dl|2+|sτGδ(θlω)dl|p+1)ds+c+c|0τGδ(θlω)dl|2, (3.12)

    where c is a positive constant independent of τ, ω and δ.

    Proof. Multiplying (3.11) by eγt, replacing ω by θτω and integrating on (τt,τ) with tR+, we get for every ωΩ

    φδ(τ,τt,θτω,φδ,τt)2E+2iZFi(uδi(τ,τt,θτω,uδτt,i))+γττteγ(sτ)φδ(s,τt,θτω,φδ,τt)2Edseγt(φδ,τt2E+2iZFi(uδτt,i))+c0eγs(g(s+τ)2+|sτGδ(θlω)dl|2+|sτGδ(θlω)dl|p+1)ds. (3.13)

    By (2.1), (2.8) and (3.2), the last integral on the right-hand side of (3.13) is well defined. For any sτt,

    ˉφδ(s,τt,θτω,ˉφδ,τt)=φδ(s,τt,θτω,φδ,τt)+(0,as0Gδ(θlτω)dl)T,

    which along with (3.13) shows that

    ˉφδ(τ,τt,θτω,ˉφδ,τt)2E+γττteγ(sτ)ˉφδ(s,τt,θτω,ˉφτt)2Eds4eγt(ˉφδ,τt2E+a2|tτGδ(θlω)dl|2+iZFi(uτt,i))+c|0τGδ(θlω)dl|2+c0eγs(g(s+τ)2+|sτGδ(θlω)dl|2+|sτGδ(θlω)dl|p+1)ds, (3.14)

    Note that (2.3) and (2.4) implies that

    iZFi(uδτt,i)1α2iZfi(uδτt,i)uδτt,i1α2maxuδτtsuδτt|fi(s)|uδτt2,

    which along with ˉφδ,τtD(τt,θtω), (2.1) and (3.2) implies that

    lim supt+4eγt(ˉφδ,τt2E+a2|tτGδ(θlω)dl|2+iZFi(uτt,i))=0. (3.15)

    Then (3.14) and (3.15) can imply the desired estimates.

    Next, we show that system (3.5) has a D-pullback absorbing set.

    Lemma 3.4. Suppose that (2.3)–(2.9) hold. Then the continuous cocycle Φδ associated with system (3.5) has a closed measurable D-pullback absorbing set Kδ={Kδ(τ,ω):τR,ωΩ}D, where for every τR and ωΩ

    Kδ(τ,ω)={ˉφδE:ˉφδ2ERδ(τ,ω)}, (3.16)

    where Rδ(τ,ω) is given by (3.12).In addition, we have for every τR and ωΩ

    limδ0Rδ(τ,ω)=R0(τ,ω), (3.17)

    where R0(τ,ω) is defined in (2.19).

    Proof. Note Kδ given by (3.16) is closed measurable random set in E. Given τR, ωΩ, and DD, it follows from Lemma 3.3 that there exists T0=T0(τ,ω,D,δ) such that for all tT0,

    Φδ(t,τt,θtω,D(τt,θtω))Kδ(τ,ω),

    which implies that Kδ pullback attracts all elements in D. By (2.1), (2.8) and (3.2), we can prove Kδ(τ,ω) is tempered. The convergence (3.17) can be obtained by Lebesgue dominated convergence as in [17].

    We are now in a position to derive uniform estimates on the tail of solutions of system (3.5).

    Lemma 3.5. Suppose that (2.3)–(2.8) hold. Then for every τR, ωΩ and ε>0, there exist δ0=δ0(ω)>0, T=T(τ,ω,ε)>0 and N=N(τ,ω,ε)>0 such that for alltT and 0<|δ|<δ0, the solution ˉφδ of system (3.5) satisfies

    |i|N|ˉφδ,i(τ,τt,θτω,ˉφδ,τt,i)|2Eε,

    where ˉφδ,τtKδ(τt,θtω) and |ˉφδ,i|2E=(1νβ)|Buδ|2i+λ|uδi|2+|ˉvδi|2.

    Proof. Let η be a smooth function defined in Lemma 2.3, and set x=(xi)iZ, y=(yi)iZ with xi=η(|i|k)uδi, yi=η(|i|k)vδi. Note ψ=(x,y)T=((xi),(yi))TiZ. Taking the inner product of system (3.6) with ψ, we have

    (˙φδ,ψ)E+(Lδ(φδ),ψ)E=(Hδ(φδ),ψ)E+(Gδ,ψ)E. (3.18)

    For the first term of (3.18), we have

    (˙φδ,ψ)E=(1νβ)iZ(B˙uδ)i(Bx)i+λiZ˙uδixi+iZ˙vδiyi=12ddtiZη(|i|k)|φδ,i|2E+(1νβ)iZ(B˙uδ)i((Bx)iη(|i|k)(Buδ)i)12ddtiZη(|i|k)|φδ,i|2E(1νβ)C0kiZ|B(vδβuδ+at0Gδ(θsω)ds)|i|uδi+1|12ddtiZη(|i|k)|φδ,i|2Eckφδ2Eck|t0Gδ(θsω)ds|2a2, (3.19)

    where |φδ,i|2E=(1νβ)|Buδ|2i+λ|uδi|2+|vδi|2. By the similar calculations in (2.28)–(2.33), we get

    (Lδ(φδ),ψ)EσiZη(|i|k)|φδ,i|2E+h16iZη(|i|k)|vδi|2ckφδ2EciZη(|i|k)|ai|2|t0Gδ(θsω)ds|2, (3.20)
    (Hδ(φδ),ψ)Eddt(iZη(|i|k)Fi(uδi))α2βp+1iZη(|i|k)Fi(uδi)+σλ4iZη(|i|k)|uδi|2+σ6iZη(|i|k)|vδi|2+ciZη(|i|k)|gi(t)|2+ciZη(|i|k)|ai|2|t0Gδ(θsω)ds|2+ciZη(|i|k)|ai|p+1|t0Gδ(θsω)ds|p+1, (3.21)

    and

    (Gδ,ψ)E=(1νβ)t0Gδ(θsω)ds(Bx,Ba)λ+βt0Gδ(θsω)ds(y,a)σλ4iZη(|i|k)|uδi|2+(h16+σ3)iZη(|i|k)|vδi|2+c|t0Gδ(θsω)ds|2iZη(|i|k)|ai|2. (3.22)

    It follows from (3.18)–(3.22) that

    ddt(iZη(|i|k)(|φδ,i|2E+2Fi(uδi)))+γ(iZη(|i|k)(|φδ,i|2E+2Fi(uδi)))+γiZη(|i|k)|φδ,i|2Eckφδ2E+ck|t0Gδ(θsω)ds|2+c|i|k|gi(t)|2+c|i|k|ai|p+1|t0Gδ(θsω)ds|p+1+c|i|k|ai|2|t0Gδ(θsω)ds|2, (3.23)

    where γ=min{σ2,α2βp+1}. Multiplying (3.23) by eγt, replacing ω by θτω and integrating on (τt,τ) with tR+, we get for every ωΩ

    iZη(|i|k)(|φδ,i(τ,τt,θτω,φδ,τt,i)|2E+2Fi(uδi(τ,τt,θτω,uδτt,i)))eγtiZη(|i|k)(|φδ,τt,i|2E+2Fi(uδτt,i))+ckττteγ(sτ)φδ(s,τt,θτω,φδ,τt)2Eds+ck0eγs|sτGδ(θlω)dl|2ds+c0eγs|i|k|gi(s+τ)|2ds+c|i|k|ai|20eγs|sτGδ(θlω)dl|2ds+c|i|k|ai|p+10eγs|sτGδ(θlω)dl|p+1ds. (3.24)

    For any sτt,

    ˉφδ(s,τt,θτω,ˉφδ,τt)=φδ(s,τt,θτω,φδ,τt)+(0,as0Gδ(θlτω)dl)T,

    which along with (3.24) shows that

    iZη(|i|k)|ˉφδ,i(τ,τt,θτω,ˉφδ,τt,i)|2E2iZη(|i|k)|φδ,i(τ,τt,θτω,φδ,τt,i)|2E+2iZη(|i|k)|aiτ0Gδ(θlτω)dl|22|i|k|ai0τGδ(θlω)dl|2+4eγtiZη(|i|k)(|ˉφδ,τt,i|2E+|aitτGδ(θlω)dl|2+Fi(uδτt,i))+ckττteγ(sτ)ˉφδ(s,τt,θτω,ˉφδ,τt)2Eds+ck0eγs|sτGδ(θlω)dl|2ds+c0eγs|i|k|gi(s+τ)|2ds+c|i|k|ai|20eγs|sτGδ(θlω)dl|2ds+c|i|k|ai|p+10eγs|sτGδ(θlω)dl|p+1ds. (3.25)

    By (2.1) and (2.8), the last four integrals on the right-hand side of (3.24) are well defined. Note that (2.3) and (2.4) implies that

    iZη(|i|k)Fi(uδτt,i)1α2iZη(|i|k)fi(uδτt,i)uδτt,i1α2maxuδτtsuδτt|fi(s)|uδτt2.

    Since ˉφδ,τtKδ(τt,θtω), we find

    lim supt+eγtiZη(|i|k)|ˉφδ,τt,i|2Elim supt+eγtKδ(τt,θtω)2E=0,

    which along with (2.1) and (3.2) shows that there exist T1=T1(τ,ω,ε)>0 and δ0>0 such that for all tT1 and 0<|δ|<δ0,

    4eγtiZη(|i|k)(|ˉφδ,τt,i|2E+|aitτGδ(θlω)dl|2+Fi(uδτt,i))ε4. (3.26)

    By Lemma 3.3, (2.1) and (3.2), there exist T2=T2(τ,ω,ε)>T1 and N1=N1(τ,ε)>0 such that for all tT2, kN1 and 0<|δ|<δ0

    ckττteγ(sτ)ˉφδ(s,τt,θτω,ˉφδ,τt)2Eds+ck0eγs|sτGδ(θlω)dl|2dsε4. (3.27)

    By (2.8), there exists N2=N2(τ,ε)>N1 such that for all kN2,

    2|i|k|ai0τGδ(θlω)dl|2+c0eγs|i|k|gi(s+τ)|2dsε4. (3.28)

    By (2.1) and (3.2) again, we find that there exists N3=N3(τ,ε)>N2 such that for all kN3 and 0<|δ|<δ0,

    c|i|k|ai|p+10eγs|sτGδ(θlω)dl|p+1ds+c|i|k|ai|20eγs|sτGδ(θlω)dl|2dsε4. (3.29)

    Then it follows from (3.25)–(3.29) that for all tT2, kN3 and 0<|δ|<δ0,

    |i|2k|ˉφδ,i(τ,τt,θτω,ˉφδ,τt,i)|2EiZη(|i|k)|ˉφδ,i(τ,τt,θτω,ˉφδ,τt,i)|2Eε.

    This concludes the proof.

    By Lemma 3.4, Φδ has a closed D-pullback absorbing set, and Lemma 3.5 shows that Φδ is asymptotically null in E with respect to D. Therefore, we get the existence of D-pullback attractors for Φδ.

    Lemma 3.6. Suppose that (2.3)–(2.9) hold. Then the continuous cocycle Φδ associated with (3.5) has a unique D-pullback attractors Aδ={Aδ(τ,ω):τR, ωΩ}D in E.

    For the attractor Aδ of Φδ, we have the uniform compactness as showed below.

    Lemma 3.7. Suppose that (2.3)–(2.9) hold. Then for every τR, ωΩ, there exists δ0=δ0(ω)>0 such that0<|δ|<δ0Aδ(τ,ω) is precompact in E.

    Proof. Given ε>0, we will prove that 0<|δ|<δ0Aδ(τ,ω) has a finite covering of balls of radius less than ε. By (3.2) we have

    0sGδ(θlω)dl=s+δsω(l)δdl+δ0ω(l)δdl. (3.30)

    By limδ0δ0ω(r)δdr=0, there exists δ1=δ1(ω)>0 such that for all 0<|δ|<δ1,

    |δ0ω(l)δdl|1. (3.31)

    Similarly, there exists l1 between s and s+δ such that s+δsω(l)δdl=ω(l1), which along with (2.1) implies that there exists T1=T1(ω)<0 such that for all sT1 and |δ|1,

    |s+δsω(l)δdl|1s. (3.32)

    Let δ2=min{δ1,1}. By (3.30)–(3.32) we get for all 0<|δ|<δ2 and sT1,

    |0sGδ(θlω)dl|<2s. (3.33)

    By (3.4), there exist δ0=δ0(ω)(0,δ2) and c1(ω)>0 such that for all 0<|δ|δ0 and T1s0,

    |0sGδ(θlω)dl|c1(ω),

    which along with (3.33) implies that for all 0<|δ|<δ0 and s0,

    |0sGδ(θlω)dl|s+c2(ω), (3.34)

    where c2(ω)=2+c1(ω). Denote by

    B(τ,ω)={ˉφδE:ˉφδ2R(τ,ω)},

    and

    R(τ,ω)=c0eγs(g(s+τ)2+2(c2s)2+2(|τ|+c2)2+2p(c2s)p+1+2p(|τ|+c2)p+1)ds+c+2c(|τ|+c2)2, (3.35)

    with c and c2 being as in (3.12) and (3.34). By (3.12) and (3.35) we find that for all 0<|δ|<δ0,

    Rδ(τ,ω)R(τ,ω). (3.36)

    By (3.35) and (3.36), we find that Kδ(τ,ω)B(τ,ω) for all 0<|δ|<δ0, τR and ωΩ. Therefore, for every τR, ωΩ,

    0<|δ|<δ0Aδ(τ,ω)0<|δ|<δ0Kδ(τ,ω)B(τ,ω). (3.37)

    By Lemma 3.5, there exist T=T(τ,ω,ε)>0 and N=N(τ,ω,ε)>0 such that for all tT and 0<|δ|<δ0,

    |i|N|ˉφδ,i(τ,τt,θτω,ˉφδ,τt,i)|2Eε4, (3.38)

    for any ˉφδ,τtKδ(τt,θtω). By (3.38) and the invariance of Aδ, we obtain

    |i|N|ˉφi|2Eε4,for allˉφ=(ˉφi)iZ0<|δ|<δ0Aδ(τ,ω). (3.39)

    We find that (3.37) implies the set {(ˉφi)|i|<N:ˉφ0<|δ|<δ0Aδ(τ,ω)} is bounded in a finite dimensional space and hence is precompact. This along with (3.39) implies 0<|δ|<δ0Aδ(τ,ω) has a finite covering of balls of radius less than ε in E. This completes the proof.

    In this section, we will study the limiting of solutions of (3.5) as δ0. Hereafter, we need an additional condition on f: For all iZ and sR,

    |fi(s)|α4|s|p1+κi, (4.1)

    where α4 is a positive constant, κ=(κi)iZl2 and p>1.

    Lemma 4.1. Suppose that (2.3)–(2.7) and (4.1) hold. Let ˉφ and ˉφδ are the solutions of (2.10) and (3.5), respectively. Then for every τR, ωΩ, T>0 and ε(0,1), there exist δ0=δ0(τ,ω,T,ε)>0 and c=c(τ,ω,T)>0 such that for allt[τ,τ+T] and 0<|δ|<δ0,

    ˉφδ(t,τ,ω,ˉφδ,τ)ˉφ(t,τ,ω,ˉφτ)2E2ec(tτ)ˉφδ,τˉφτ2E+cε.

    Proof. Let ˜φ=φδφ and ˜φ=(˜u,˜v)T, where ˜u=uδu, ˜v=vδv, φ and φδ are the solutions of (2.11) and (3.6), respectively. By (2.11) and (3.6) we get

    ˙˜φ+˜L(˜φ)=˜H(˜φ)+˜G(ω), (4.2)

    where

    ˜L(˜φ)=(β˜u˜v(1νβ)A˜u+νA˜v+λ˜u+β2˜uβ˜v)+(0h(vδβuδ+at0Gδ(θsω)ds)h(vβu+aω(t))),
    ˜H(˜φ)=(0f(uδ)+f(u)),˜G(ω)=(a(t0Gδ(θsω)dsω(t))(βaνAa)(t0Gδ(θsω)dsω(t))).

    Taking the inner product of (4.2) with ˜φ in E, we have

    12ddt˜φ2E+(˜L(˜φ),˜φ)E=(˜H(˜φ),˜φ)E+(˜G(ω),˜φ)E. (4.3)

    For the second term on the left-hand side of (4.3), using the similar calculations in (2.13) we have

    (˜L(˜φ),˜φ)Eσ˜φ2E+h12˜v2h2|(a(t0Gδ(θsω)dsω(t)),˜v)|σ˜φ2E+h14˜v2c|t0Gδ(θsω)dsω(t))|2a2. (4.4)

    For the first term on the right-hand side of (4.3), by (4.1) we get

    (f(u)f(uδ),˜v)=iZ(fi(ui)fi(uδi))˜vi=1h1iZ|fi(ui)fi(uδi)|2+h14iZ|˜vi|2c(φ2p2E+φδ2p2E)˜φ2E+h14˜v2+2κ2h1λ˜φ2E. (4.5)

    As to the last term of (4.3), we have

    (a(t0Gδ(θsω)dsω(t)),˜u)λ+((βaνAa)(t0Gδ(θsω)dsω(t)),˜v)σ˜u2λ+14σ|t0Gδ(θsω)dsω(t)|2a2λ+σ˜v2+c|t0Gδ(θsω)dsω(t)|2a2. (4.6)

    It follows from (4.3)–(4.6) that

    ddt˜φ2Ec(φ2p2E+φδ2p2E+1)˜φ2E+c|t0Gδ(θsω)dsω(t)|2. (4.7)

    By Lemma 2.1 and Lemma 3.2, there exists δ1=δ1(τ,ω,T)>0 and c1=c1(τ,ω,T)>0 such that for all 0<|δ|<δ1 and t[τ,τ+T],

    φδ(t,τ,ω,φδ,τ)2E+φ(t,τ,ω,φτ)2Ec1,

    which along with (4.7) shows that for all 0<|δ|<δ1 and t[τ,τ+T]

    ddt˜φ2Ec˜φ2E+c|t0Gδ(θsω)dsω(t)|2. (4.8)

    Applying Gronwall's inequality and Lemma 3.1 to (4.8), we see that for every ε(0,1), there exists δ0=δ0(τ,ω,T,ε)(0,δ1) such that for all 0<|δ|<δ0 and t[τ,τ+T]

    ˜φ(t,τ,ω,˜φτ)2Eec(tτ)˜φτ2E+cε. (4.9)

    On the other hand, we have

    ˉφδ(t,τ,ω,ˉφδ,τ)ˉφ(t,τ,ω,ˉφτ)=˜φ+(0,a(t0Gδ(θs)dsω(t)))T,

    which along with (4.9) implies the desired result.

    Finally, we establish the upper semicontinuity of random attractors as δ0.

    Theorem 4.1. Suppose that (2.3)–(2.9) and (4.1) hold. Then for every τR and ωΩ,

    limδ0dE(Aδ(τ,ω),A0(τ,ω))=0, (4.10)

    where dE(Aδ(τ,ω),A0(τ,ω))=supxAδ(τ,ω)infyA0(τ,ω)xyE.

    Proof. Let δn0 and ˉφδn,τˉφτ in E. Then by Lemma 4.1, we find that for all τR, t0 and ωΩ,

    Φδn(t,τ,ω,ˉφδn,τ)Φ0(t,τ,ω,ˉφτ)inE. (4.11)

    By (3.16)–(3.17) we have, for all τR and ωΩ,

    limδ0Kδ(τ,ω)2ER0(τ,ω). (4.12)

    Then by (4.11), (4.12) and Lemma 3.7, (4.10) follows from Theorem 3.1 in [24] immediately.

    In this paper we use similar idea in [30] but apply to second order non-autonomous stochastic lattice dynamical systems with additive noise. we establish the convergence of solutions of Wong-zakai approximations and the upper semicontinuity of random attractors of the approximate random system as the step-length of the Wiener shift approaches zero. In addition, as to the second order non-autonomous stochastic lattice dynamical systems with multiplicative noise, we can use the similar method in [29] to get the corresponding results.

    The authors would like to thank anonymous referees and editors for their valuable comments and constructive suggestions.

    The authors declare no conflict of interest.



    [1] World Health Organization (WHO), Emergency Committee on Zika virus and observed increase in neurological disorders and neonatal malformations, 2016. Available from: https://www.chinadaily.com.cn/world/2016-02/02/content_23348858.htm.
    [2] G. Lucchese, D. Kanduc, Zika virus and autoimmunity: from microcephaly to Guillain-Barré syndrome, and beyond, Autoimmun Rev., 15 (2016), 801–808. https://doi.org/10.1016/j.autrev.2016.03.020 doi: 10.1016/j.autrev.2016.03.020
    [3] I. Bogoch, O.Brady, M. Kraemer, M. German, M. Creatore, S. Brent, et al., Potential for Zika virus introduction and transmission in resource-limited countries in Africa and the Asia-Pacific region: a modelling study, Lancet Infect Dis., 16 (2016), 1237–1245. https://doi.org/10.1016/S1473-3099(16)30270-5 doi: 10.1016/S1473-3099(16)30270-5
    [4] B. Zheng, L. Chang, J. Yu, A mosquito population replacement model consisting of two differential equations, Electron. Res. Arch., 30 (2016), 978–994. https://doi.org/10.3934/era.2022051 doi: 10.3934/era.2022051
    [5] Z. Lv, J. Zeng, Y. Ding, X. Liu, Stability analysis of time-delayed SAIR model for duration of vaccine in the context of temporary immunity for COVID-19 situation, Electron. Res. Arch., 31 (2023), 1004–1030. https://doi.org/10.3934/era.2023050 doi: 10.3934/era.2023050
    [6] H. Cao, M. Han, Y. Bai, S. Zhang, Hopf bifurcation of the age-structured SIRS model with the varying population sizes, Electron. Res. Arch., 30 (2022), 3811–3824. https://doi.org/10.3934/era.2022194 doi: 10.3934/era.2022194
    [7] X. Zhou, X. Shi, Stability analysis and backward bifurcation on an SEIQR epidemic model with nonlinear innate immunity, Electron. Res. Arch., 30 (2022), 3481–3508. https://doi.org/10.3934/era.2022178 doi: 10.3934/era.2022178
    [8] G. Fan, N. Li, Application and analysis of a model with environmental transmission in a periodic environmen, Electron. Res. Arch., 31 (2023), 5815–5844. https://doi.org/10.3934/era.2023296 doi: 10.3934/era.2023296
    [9] S. Guo, X. Yang, Z. Zheng, Global dynamics of a time-delayed malaria model with asymptomatic infections and standard incidence rate, Electron. Res. Arch., 31 (2023), 3534–3551. https://doi.org/10.3934/era.2023179 doi: 10.3934/era.2023179
    [10] K. Wang, H. Zhao, H. Wang, R. Zhang, Traveling wave of a reaction-diffusion vector-borne disease model with nonlocal effects and distributed delay, J. Dyn. Differ. Equations, 35 (2023), 3149–3185. https://doi.org/10.1007/s10884-021-10062-w doi: 10.1007/s10884-021-10062-w
    [11] K. Wang, H. Wang, H. Zhao, Aggregation and classification of spatial dynamics of vector-borne disease in advective heterogeneous environment, J. Differ. Equations, 343 (2023), 285–331. https://doi.org/10.1016/j.jde.2022.10.013 doi: 10.1016/j.jde.2022.10.013
    [12] W. E. Fitzgibbon, J. J. Morgan, G. F. Webb, An outbreak vector-host epidemic model with spatial structure: the 2015–2016 Zika outbreak in Rio De Janeiro, Theor. Biol. Med. Model., 14 (2017), 1–17. https://doi.org/10.1186/s12976-017-0051-z doi: 10.1186/s12976-017-0051-z
    [13] T. Y. Miyaoka, S. Lenhart, J. F. Meyer, Optimal control of vaccination in a vector-borne reaction-diffusion model applied to Zika virus, J. Math. Biol., 79 (2019), 1077–1104. https://doi.org/10.1007/s00285-019-01390-z doi: 10.1007/s00285-019-01390-z
    [14] K. Yamazaki, Zika virus dynamics partial differential equations model with sexual transmission route, Nonlinear Anal.-Real, 50 (2019), 290–315. https://doi.org/10.1016/j.nonrwa.2019.05.003 doi: 10.1016/j.nonrwa.2019.05.003
    [15] Y. Cai, K. Wang, W. Wang, Global transmission dynamics of a zika virus model, Appl. Math. Lett., 92 (2019), 190–195. https://doi.org/10.1016/j.aml.2019.01.015 doi: 10.1016/j.aml.2019.01.015
    [16] L. Duan, L. Huang, Threshold dynamics of a vector-host epidemic model with spatial structure and nonlinear incidence rate, Proc. Amer. Math. Soc., 149 (2021), 4789–4797. https://doi.org/10.1090/proc/15561 doi: 10.1090/proc/15561
    [17] P. Magal, G. Webb, Y. Wu, On a vector-host epidemic model with spatial structure, Nonlinearity, 31 (2018), 5589–5614. https://doi.org/10.1088/1361-6544/aae1e0 doi: 10.1088/1361-6544/aae1e0
    [18] P. Magal, G. Webb, Y. Wu, On the basic reproduction number of reaction-diffusion epidemic models, SIAM J. Appl. Math., 79 (2019), 284–304. https://doi.org/10.1137/18M1182243 doi: 10.1137/18M1182243
    [19] F. Li, X. Q. Zhao, Global dynamics of a reaction–diffusion model of Zika virus transmission with seasonality, B. Math. Biol., 83 (2021), 43. https://doi.org/10.1007/s11538-021-00879-3 doi: 10.1007/s11538-021-00879-3
    [20] S. Du, Y. Liu, J. Liu, J. Zhao, C. Champagne, L. Tong, et al., Aedes mosquitoes acquire and transmit Zika virus by breeding in contaminated aquatic environments, Nat. Commun., 10 (2019), 1324. https://doi.org/10.1038/s41467-019-09256-0 doi: 10.1038/s41467-019-09256-0
    [21] L. Wang, H. Zhao, Modeling and dynamics analysis of Zika transmission with contaminated aquatic environments, Nonlinear Dyn., 104 (2021), 845–862. https://doi.org/10.1007/s11071-021-06289-3 doi: 10.1007/s11071-021-06289-3
    [22] L. Wang, P. Wu, M. Li, L. Shi, Global dynamics analysis of a Zika transmission model with environment transmission route and spatial heterogeneity, AIMS Math., 7 (2022), 4803–4832. https://doi.org/10.3934/math.2022268 doi: 10.3934/math.2022268
    [23] L. Wang, P. Wu, Threshold dynamics of a Zika model with environmental and sexual transmissions and spatial heterogeneity, Z. Angew. Math. Phys., 73 (2022), 1–22. https://doi.org/10.1007/s00033-022-01812-x doi: 10.1007/s00033-022-01812-x
    [24] J. Wang, Y. Chen, Threshold dynamics of a vector-borne disease model with spatial structure and vector-bias, Appl. Math. Lett., 100 (2020), 106052. https://doi.org/10.1016/j.aml.2019.106052 doi: 10.1016/j.aml.2019.106052
    [25] Y. Pan, S. Zhu, J. Wang, A note on a ZIKV epidemic model with spatial structure and vector-bias, AIMS Math., 7 (2022), 2255–2265. https://doi.org/10.3934/math.2022128 doi: 10.3934/math.2022128
    [26] P. Hess, Periodic-parabolic boundary value problems and positivity, Longman Scientific and Technical, Harlow, 1991. https://doi.org/10.1112/blms/24.6.619
    [27] H. L. Smith, Monotone Dynamical Systems: An Introduction to the Theory of Competitive and Cooperative Systems, American Mathematical Society, Rhode Island, 1995. https://doi.org/10.1090/surv/041
    [28] X. Ren, Y. Tian, L. Liu, X. Liu, A reaction–diffusion within-host HIV model with cell-to-cell transmission, J. Math. Biol., 76 (2018), 1831–1872. https://doi.org/10.1007/s00285-017-1202-x doi: 10.1007/s00285-017-1202-x
    [29] M. Wang, Nonlinear Elliptic Equations, Science Publication, Beijing, 2010.
    [30] R. H. Martin, H. L. Smith, Abstract functional-differential equations and reaction-diffusion systems, Trans. Amer. Math. Soc., 321 (1990), 1–44. https://doi.org/10.1090/S0002-9947-1990-0967316-X doi: 10.1090/S0002-9947-1990-0967316-X
    [31] W. Wang, X. Q. Zhao, Basic reproduction numbers for reaction-diffusion epidemic models, SIAM J. Appl. Dyn. Syst., 11 (2012), 1652–1673. https://doi.org/10.1137/120872942 doi: 10.1137/120872942
    [32] Y. C. Shyu, R. N. Chien, F. B. Wang, Global dynamics of a West Nile virus model in a spatially variable habitat, Nonlinear Anal.-Real, 41 (2018), 313–333. https://doi.org/10.1016/j.nonrwa.2017.10.017 doi: 10.1016/j.nonrwa.2017.10.017
    [33] S. B. Hsu, F. B. Wang, X. Q. Zhao, Global dynamics of zooplankton and harmful algae in flowing habitats, J. Differ. Equations, 255 (2013), 265–297. https://doi.org/10.1016/j.jde.2013.04.006 doi: 10.1016/j.jde.2013.04.006
    [34] S. B. Hsu, F. B. Wang, X. Q. Zhao, Dynamics of a periodically pulsed bio-reactor model with a hydraulic storage zone, J. Dyn. Differ. Equations, 23 (2011), 817–842. https://doi.org/10.1007/s10884-011-9224-3 doi: 10.1007/s10884-011-9224-3
    [35] P. Magal, X. Q. Zhao, Global attractors and steady states for uniformly persistent dynamical systems, SIAM J. Math. Anal., 37 (2005), 251–275. https://doi.org/10.1137/S0036141003439173 doi: 10.1137/S0036141003439173
    [36] X. Q. Zhao, Dynamical Systems in Population Biology, 2nd edition, Springer, New York, 2017. https://doi.org/10.1007/978-3-319-56433-3
    [37] R. Wu, X. Q. Zhao, A reaction-diffusion model of vector-borne disease with periodic delays, J Nonlinear Sci., 29 (2019), 29–64. https://doi.org/10.1007/s00332-018-9475-9 doi: 10.1007/s00332-018-9475-9
    [38] F. Li, X. Q. Zhao, Global dynamics of a nonlocal periodic reaction-diffusion model of bluetongue disease, J. Differ. Equations, 272 (2021), 127–163. https://doi.org/10.1016/j.jde.2020.09.019 doi: 10.1016/j.jde.2020.09.019
    [39] Brazil Ministry of Health, Zika cases from the Brazil Ministry of Health, 2018. Available from: http://portalms.saude.gov.br/boletins-epidemiologicos.
    [40] City Populations Worldwide, Brazil population, 2018. Available from: http://population.city/brazil/.
  • This article has been cited by:

    1. Ming Huang, Lili Gao, Lu Yang, Regularity of Wong-Zakai approximations for a class of stochastic degenerate parabolic equations with multiplicative noise, 2024, 0, 1937-1632, 0, 10.3934/dcdss.2024097
  • Reader Comments
  • © 2024 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(1128) PDF downloads(59) Cited by(0)

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog