The paper considers the effects of fractional derivative with a high degree of accuracy in the boundary conditions for the transmission problem. It is shown that the existence and uniqueness of the solutions for the transmission problem in a bounded domain with a boundary condition given by a fractional term in the second equation are guaranteed by using the semigroup theory. Under an appropriate assumptions on the transmission conditions and boundary conditions, we also discuss the exponential and strong stability of solution by also introducing the theory of semigroups.
Citation: Noureddine Bahri, Abderrahmane Beniani, Abdelkader Braik, Svetlin G. Georgiev, Zayd Hajjej, Khaled Zennir. Global existence and energy decay for a transmission problem under a boundary fractional derivative type[J]. AIMS Mathematics, 2023, 8(11): 27605-27625. doi: 10.3934/math.20231412
[1] | Butsayapat Chaihao, Sujin Khomrutai . Extinction and permanence of a general non-autonomous discrete-time SIRS epidemic model. AIMS Mathematics, 2023, 8(4): 9624-9646. doi: 10.3934/math.2023486 |
[2] | Shufan Wang, Zhihui Ma, Xiaohua Li, Ting Qi . A generalized delay-induced SIRS epidemic model with relapse. AIMS Mathematics, 2022, 7(4): 6600-6618. doi: 10.3934/math.2022368 |
[3] | Xavier Bardina, Marco Ferrante, Carles Rovira . A stochastic epidemic model of COVID-19 disease. AIMS Mathematics, 2020, 5(6): 7661-7677. doi: 10.3934/math.2020490 |
[4] | Mireia Besalú, Giulia Binotto . Time-dependent non-homogeneous stochastic epidemic model of SIR type. AIMS Mathematics, 2023, 8(10): 23218-23246. doi: 10.3934/math.20231181 |
[5] | Yue Wu, Shenglong Chen, Ge Zhang, Zhiming Li . Dynamic analysis of a stochastic vector-borne model with direct transmission and media coverage. AIMS Mathematics, 2024, 9(4): 9128-9151. doi: 10.3934/math.2024444 |
[6] | Yubo Liu, Daipeng Kuang, Jianli Li . Threshold behaviour of a triple-delay SIQR stochastic epidemic model with Lévy noise perturbation. AIMS Mathematics, 2022, 7(9): 16498-16518. doi: 10.3934/math.2022903 |
[7] | Mahmoud A. Ibrahim . Threshold dynamics in a periodic epidemic model with imperfect quarantine, isolation and vaccination. AIMS Mathematics, 2024, 9(8): 21972-22001. doi: 10.3934/math.20241068 |
[8] | Zhengwen Yin, Yuanshun Tan . Threshold dynamics of stochastic SIRSW infectious disease model with multiparameter perturbation. AIMS Mathematics, 2024, 9(12): 33467-33492. doi: 10.3934/math.20241597 |
[9] | Xiaodong Wang, Kai Wang, Zhidong Teng . Global dynamics and density function in a class of stochastic SVI epidemic models with Lévy jumps and nonlinear incidence. AIMS Mathematics, 2023, 8(2): 2829-2855. doi: 10.3934/math.2023148 |
[10] | Chang Hou, Qiubao Wang . The influence of an appropriate reporting time and publicity intensity on the spread of infectious diseases. AIMS Mathematics, 2023, 8(10): 23578-23602. doi: 10.3934/math.20231199 |
The paper considers the effects of fractional derivative with a high degree of accuracy in the boundary conditions for the transmission problem. It is shown that the existence and uniqueness of the solutions for the transmission problem in a bounded domain with a boundary condition given by a fractional term in the second equation are guaranteed by using the semigroup theory. Under an appropriate assumptions on the transmission conditions and boundary conditions, we also discuss the exponential and strong stability of solution by also introducing the theory of semigroups.
Nowadays there are always various communicable diseases, such as malaria, dengue fever, HIV/AIDS, Zika virus, and COVID-19, which impair the health of people around the globe [2]. Especially, as of now, COVID-19 has killed more than 4 million people and is still prevailing in many countries over the world. Since Covid-19 was first identified in January 2020, thousands of mutations have been detected [34]. Moreover, it has been reported that various new strains of COVID-19 are considered as more dangerous than the original virus. In fact, the variation of pathogens is very common in epidemiology, we can refer to [4] for the instance of the mutation of influenza virus. Besides, Dengue fever is one of the most typical vector-borne infectious disease prevailing in the tropical and subtropical areas. Usually, the fever is caused by five different serotypes (DEN I-IV) and the corresponding fatality rates of these serotypes are dramatically different. This means that a person living in an endemic area might be facing the risk of infection from five distinct serotypes, and a individual who recovered form one of the serotypes could get permanent immunity to itself and only temporary cross-immune against the others. In recent years, mathematical model increasingly become a effective tool in the investigation of the spread of epidemics. With the aid of proper analysis for the mathematical models, we can better understand the transmission mechanism of infectious diseases and then take appropriate prevention and control measures to combat the diseases. In fact, the researches of epidemic dynamics models involving multi-strain interactions have attracted considerable attention of many scholars. Baba et al. [4] studied a two-strain model containing vaccination for both strains. Cai et al. [6] studied a two-strain model including vaccination, and analyzed the interaction between the strains under the vaccination theme. A class of multi-chain models with discrete time delays, moreover, is considered in the case of temporary immunity and multiple cross immunity by Bauer et al. [5]. For more literatures corresponding to pathogens with multiple strains, we can refer to [1,8,24,30,33,39] and the references.
In reality, accumulating empirical evidence shows that seasonal factors can affect the host-pathogen interactions [3], and the incidence of many infectious diseases fluctuates over time, often with a cyclical pattern(see, e.g., [16,31,37]). In addition, Yang, et al [35] found that temperature and relative humidity were mainly the driving factors on COVID-19 transmission. It is therefore necessary to consider infectious disease models with time-dependent parameters. Martcheva et al. [24] considered a class of multi-chain models with time-periodic coefficients. Precisely speaking, they presented sufficient conditions to guarantee the coexistence of the two-strain, and further proved that competitive exclusion would occur only when the transmission rates on each chain are linearly correlated.
At the same time, it is noticed that the resources, humidity and temperature are not uniformly distributed in space, then spatial heterogeneity should not be ignored a practical epidemiological model. From the point of view of model's rationalization, the main parameters, such as infection rate and recovery rate, should be intrinsically spatially dependent. Taking into consideration both the spatial heterogeneity of the environment and the impact of individual movement on disease transmission, Tuncer et al. [33] proposed the following two-strain model:
{∂S(x,t)∂t=dSΔS(x,t)−(β1(x)I1(x,t)+β2(x)I2(x,t))S(x,t)S(x,t)+I1(x,t)+I2(x,t) +r1(x,t)I1(x,t)+r2(x,t)I2(x,t),∂I1(x,t)∂t=d1ΔI1(x,t)+β1(x)S(x,t)I1(x,t)S(x,t)+I1(x,t)+I2(x,t)−r1(x,t)I1(x,t),∂I2(x,t)∂t=d2ΔI2(x,t)+β2(x)S(x,t)I2(x,t)S(x,t)+I1(x,t)+I2(x,t)−r2(x,t)I2(x,t). | (1.1) |
Furthermore, Acklehd et al. [1] studied a model with bilinear incidence, the results showed that the spatial heterogeneity facilitated the coexistence of strains. Taking into account alternation of seasons, Peng et al. [29] studied a reaction-diffusion SIS model, in which the disease transmission rate and recovery rate are all spatial-dependent and temporally periodic. The results show that temporal heterogeneity have little effect on the extinction and persistence of the diseases, nevertheless, the combination of temporal and spatial heterogeneity would increase the duration of the disease.
It is well known that the incubation period exist commonly in most infectious diseases, and the length of the incubation periods corresponding to different diseases are often different. We can refer Leung [19] for more information about the difference of the incubation period of COVID-19 between various different variants. During the incubation period, random movements of individuals can give rise to nonlocal effects, precisely speaking, the rate of gaining infectious individuals at current position at the present time actually depends on the infections at all possible locations and all possible previous times. This nonlocal interaction will affect the global dynamic behavior of the solutions [7,13], traveling wave phenomena [14], etc. Guo et al. [12] studied the threshold dynamics of a reaction-diffusion model with nonlocal effects. In particular, Zhao et al. [38] considered the threshold dynamics of a model with fixed latent period on the basis of model (1.1). In particular, when Ri0=1 and the infection rate is assumed to be strictly positive, they studied the threshold dynamics of the model by constructing the upper control system.
Due to the individual difference in age, nutrition, lifestyle and health status, there are significant difference in the immunity among different individuals [27]. This further lead to the difference of incubation periods in different individuals. As McAloon, et al. [27] points out, it is critically important to understand the variation in the distribution within the population. Thus, the fixed incubation period is not always an ideal description for most diseases. Takeuchi et al. [32] considered a vector-borne SIR infectious disease model with distributed time delay. Zhao et al. [39] studied a two-group reaction-diffusion model with distributed delay. In [39], the recovered individuals are assumed to be lifelong immune to the disease. However, this assumption is not suitable for all epidemics. Then it is very necessary to establish and analysis a SIRS model involving aforementioned various factors, and thus to further improve the existing relevant research. The purpose of this paper is to investigate the threshold dynamics of a two-strain SIRS epidemic model with distributed delay and spatiotemporal heterogeneity.
The remainder of this paper is organized as follows. In the next section, we derive the model and show its well-posedness. In section 3, we established the threshold dynamics for the system in term of the basic reproduction number Ri0 and the invasion number ˆRi0(i=1,2) for each strain i. At the end of the current paper, a brief but necessary discussion is presented to show some epidemiological implications of this study.
In this section, we propose a time-periodic two-strain SIRS model with distributed delay and spatiotemporal heterogeneity, and further analyze some useful properties of the solutions of the model.
Let Ω∈Rn denote the spatial habitat with smooth boundary ∂Ω. We suppose that only one mutant can appear in a pathogen, and a susceptible individual can only be infected by one virus strain. Denote the densities of the two different infectious classes with infection age a≥0 and at position x, and time t by E1(x,a,t) and E2(x,a,t), respectively. By a standard argument on structured population and spatial diffusion (see e.g., [28]), we obtain
{(∂∂t+∂∂a)Ei(x,a,t)=DiΔEi−(δi(x,a,t)+ri(x,a,t)+d(x,t))Ei(x,a,t), x∈Ω, a>0, t>0∂Ei(x,a,t)∂n=0, x∈∂Ω, a>0, t>0,i=1,2, | (2.1) |
where d(x,t) is the natural death rate at location x and time t; ri(x,a,t) and δi(x,a,t) represent the recovery rates and mortality rates induced by the disease of the i-th infectious classes with infection age a≥0 at position x and time t; the constants Di denote the diffusion rates of the i-th infectious class for i=1,2. We divide the population into six compartments: the susceptible group S(x,t), two latent groups Li(x,t), two infective groups Ii(x,t), and the recovered group R(x,t), i=1,2. Let N(x,t)=S(x,t)+∑i=1,2(Li(x,t)+Ii(x,t))+R(x,t). We assume that only a portion of recovered individuals would be permanently immune to the virus. Let α(x,a,t) be the loss of immunity rate with infection age a≥0 at position x and time t. In order to simplify the model reasonably, we further suppose that
δi(x,a,t)=δi(x,t), ri(x,a,t)=ri(x,t), α(x,a,t)=α(x,t), ∀x∈Ω, a,t≥0, i=1,2. |
On account of the individual differences of the incubation period among the different individuals, infections individuals of the i-th population be capable of infecting others until after a possible infection age a∈(0,τi], where the positive constant τi is the maximum incubation period of i-th strain, i=1,2. Let fi(r)dr denote the probability of becoming into the individuals who are capable of infecting others between the infection age r and r+dr, then Fi(a)=∫a0fi(r)dr represents the probability of turning into the individuals with infecting others before the infection age a for i=1,2. It is clear that Fi(a)≥0 for a∈(0,τi), Fi(a)≡1 for a∈[τi,+∞), i=1,2, and
Li(x,t)=∫τi0(1−Fi(a))Ei(x,a,t)da,Ii(x,t)=∫τi0Fi(a)Ei(x,a,t)da+∫+∞τiEi(x,a,t)da, i=1,2. | (2.2) |
Let
Ii,1(x,t)=∫τi0Fi(a)Ei(x,a,t)da, Ii,2(x,t)=∫+∞τiEi(x,a,t)da. |
It then follows that
∂Li(x,t)∂t=DiΔLi(x,t)−(δi(x,t)+ri(x,t)+d(x,t))Li(x,t)−∫τi0fi(a)Ei(x,a,t)da+Ei(x,0,t), |
and
∂Ii,1(x,t)∂t=DiΔIi,1(x,t)−(δi(x,t)+ri(x,t)+d(x,t))Ii,1(x,t)+∫τi0fi(a)Ei(x,a,t)da−Ei(x,τi,t), |
∂Ii,2(x,t)∂t=DiΔIi,2(x,t)−(δi(x,t)+ri(x,t)+d(x,t))Ii,2(x,t)+Ei(x,τi,t)−Ei(x,∞,t), |
where i=1,2. Biologically, we assume Ei(x,∞,t)=0(i=1,2). Then we have
∂Ii(x,t)∂t=DiΔIi(x,t)−(δi(x,t)+ri(x,t)+d(x,t))Ii(x,t)+∫τi0fi(a)Ei(x,a,t)da. |
Denote the infection rate by βi(x,t)≥0. Due to the fact that the contact of susceptible and infectious individuals yields the new infected individuals, we take Ei(x,0,t) as follows:
Ei(x,0,t)=βi(x,t)S(x,t)Ii(x,t)S(x,t)+I1(x,t)+I2(x,t)+R(x,t), i=1,2. |
In the absence of disease, moreover, we suppose that the evolution of the population density follows the following equation:
∂N(x,t)∂t=DNΔN(x,t)+μ(x,t)−d(x,t)N(x,t), |
where d(x,t) is the natural death rate, μ(x,t) is the recruiting rate, and DN denotes the diffusion rate. In conclusion, the disease dynamics is expressed by the following system:
{∂S(x,t)∂t=DSΔS(x,t)+μ(x,t)−d(x,t)S(x,t)+α(x,t)R(x,t)−β1(x,t)S(x,t)I1(x,t)S(x,t)+I1(x,t)+I2(x,t)+R(x,t)−β2(x,t)S(x,t)I2(x,t)S(x,t)+I1(x,t)+I2(x,t)+R(x,t),∂Li(x,t)∂t=DiΔLi(x,t)−(δi(x,t)+ri(x,t)+d(x,t))Li(x,t)+βi(x,t)S(x,t)Ii(x,t)S(x,t)+I1(x,t)+I2(x,t)+R(x,t)−∫τi0fi(a)Ei(x,a,t)da,∂Ii(x,t)∂t=DiΔIi(x,t)−(δi(x,t)+ri(x,t)+d(x,t))Ii(x,t)+∫τi0fi(a)Ei(x,a,t)da,∂R(x,t)∂t=DRΔR(x,t)+r1(x,t)(L1(x,t)+I1(x,t))+r2(x,t)(L2(x,t)+I2(x,t))−d(x,t)R(x,t)−α(x,t)R(x,t), i=1,2. | (2.3) |
We make the following basic assumption:
(H) DS,Di,DR>0, i=1,2, the functions d(x,t),μ(x,t),α(x,t),βi(x,t),δi(x,t),ri(x,t) are Hölder continuous and nonnegative nontrivial on ˉΩ×R, and periodic in time t with the same period T>0. Moreover, d(x,t)>0, x∈∂Ω, t>0.
For the sake of simplicity, we let hi(x,t)=δi(x,t)+ri(x,t)+d(x,t), i=1,2. In order to determine Ei(x,a,t), let Vi(x,a,ξ)=Ei(x,a,a+ξ), ∀ξ≥0, i=1,2. By a similar idea as that in [36], we have
{∂Vi(x,a,ξ)∂a=DiΔVi(x,a,ξ)−hi(x,t)Vi(x,a,ξ),Vi(x,0,ξ)=Ei(x,0,ξ)=βi(x,ξ)S(x,ξ)Ii(x,ξ)S(x,ξ)+I1(x,ξ)+I2(x,ξ)+R(x,ξ), i=1,2. |
Let Γi(x,y,t,s) with x,y∈Ω and t>s≥0 be the fundamental solution associated with the partial differential operator ∂t−DiΔ−hi(x,t)(i=1,2). Then we have
Vi(x,a,ξ)=∫ΩΓi(x,y,ξ+a,ξ)βi(y,ξ)S(y,ξ)Ii(y,ξ)S(y,ξ)+I1(y,ξ)+I2(y,ξ)+R(y,ξ)dy. | (2.4) |
According to the periodicity of hi and βi, Γi(x,y,t,s) is periodic, that is, Γi(x,y,t+T,s+T)=Γi(x,y,t,s), ∀x,y∈Ω, t>s≥0, i=1,2. It follows from Ei(x,a,t)=Vi(x,a,t−a) that
Ei(x,a,t)=∫ΩΓi(x,y,t,t−a)βi(y,t−a)S(y,t−a)Ii(y,t−a)S(y,t−a)+I1(y,t−a)+I2(y,t−a)+R(y,t−a)dy. | (2.5) |
Substituting (2.5) into (2.3), and dropping the Li equations from (2.3) (since they are decoupled from the other equations), we obtain the following system:
{∂S(x,t)∂t=DSΔS(x,t)+μ(x,t)−d(x,t)S(x,t)+α(x,t)R(x,t)−β1(x,t)S(x,t)I1(x,t)S(x,t)+I1(x,t)+I2(x,t)+R(x,t)−β2(x,t)S(x,t)I2(x,t)S(x,t)+I1(x,t)+I2(x,t)+R(x,t),∂Ii(x,t)∂t=DiΔIi(x,t)−(δi(x,t)+ri(x,t)+d(x,t))Ii(x,t)+∫τi0fi(a)⋅∫ΩΓi(x,y,t,t−a)βi(y,t−a)S(y,t−a)Ii(y,t−a)S(y,t−a)+I1(y,t−a)+I2(y,t−a)+R(y,t−a)dyda,∂R(x,t)∂t=DRΔR(x,t)+r1(x,t)I1(x,t)+r2(x,t)I2(x,t)−d(x,t)R(x,t)−α(x,t)R(x,t), i=1,2. | (2.6) |
Set τ=max{τ1,τ2}>0. Let X:=C(ˉΩ,R4) be the Banach space with a supremum norm ‖⋅‖X. Let Cτ:=C([−τ,0],X) be a Banach space with the norm ‖ϕ‖=maxθ∈[−τ,0]‖ϕ(θ)‖X, ∀ϕ∈Cτ. Define X+:=C(ˉΩ,R4+), C+τ:=C([−τ,0],X+), the (X,X+) and (Cτ,C+τ) are strongly ordered spaces. For σ>0 and a given function u(t):[−τ,σ]→X, we denote ut∈Cτ by
ut(θ)=u(t+θ), ∀θ∈[−τ,0]. |
Similarly, define Y=C(ˉΩ,R) and Y+=C(ˉΩ,R+). Furthermore, we consider the following system:
{∂ω(x,t)∂t=DSΔω(x,t)−d(x,t)ω(x,t), x∈Ω, t>0,∂ω(x,t)∂t=0, x∈∂Ω, t>0,ω(x,0)=ϕS(x), x∈Ω, ϕS∈Y+. | (2.7) |
By the arguments in [15], Eq (2.7) exists an evolution operator VS(t,s):Y+⟶Y+ for 0≤s≤t, which satisfies VS(t,t)=I, VS(t,s)VS(s,ρ)=VS(t,ρ), 0≤ρ≤s≤t, VS(t,0)ϕS=ω(x,t;ϕS), x∈Ω, t≥0, ϕS∈Y+, where ω(x,t;ϕS) is the solution of (2.7).
Consider the following periodic system:
{∂ˉωi(x,t)∂t=DiΔˉωi(x,t)−hi(x,t)ˉωi(x,t)),x∈Ω, t>0,∂ˉωi(x,t)∂n=0,x∈∂Ω, t>0,ˉωi(x,0)=ϕi(x),x∈Ω, ϕi∈Y+. | (2.8) |
and
{∂˜ωR(x,t)∂t=DRΔ˜ωR(x,t)−k(x,t)˜ωR(x,t)),x∈Ω, t>0,∂˜ωR(x,t)∂t=0,x∈∂Ω, t>0,˜ωR(x,0)=ϕR(x),x∈Ω, ϕR∈Y+, | (2.9) |
where k(x,t)=α(x,t)+d(x,t). Let Vi(t,s), i=1,2, and VR(t,s) be the evolution operators determined by (2.8) and (2.9), respectively. The periodicity hypothesis (H) combining with [9,Lemma 6.1] yield that VS(t+T,s+T)=VS(t,s), Vi(t+T,s+T)=Vi(t,s) and VR(t+T,s+T)=VR(t,s), t≥s≥0. In addition, for any t,s∈R and s<t. VS(t,s), Vi(t,s) and VR(t,s) are compact, analytic and strongly positive operators on Y+. It then follows from [9,Theorem 6.6] that there exist constants Q≥1, Qi≥1 and c0,ci∈R(i=1,2) such that
‖VS(t,s)‖,‖VR(t,s)‖≤Qe−c0(t−s), ‖Vi(t,s)‖≤Qie−ci(t−s), ∀t≥s, i=1,2. |
Let c∗i:=ˉω(Vi), where
ˉω(Vi)=inf{ω|∃M≥1: ∀s∈R, t≥0,||Vi(t+s,s)||≤M⋅eωt} |
is the exponent growth bound of the evolution operator Vi(t,s). It is clear that c∗i<0.
Define functions FS,Fi,FR:[0,∞)⟶Y respectively by
FS(t,ϕ)=μ(⋅,t)+α(⋅,t)ϕS(⋅,0)−2∑i=1βi(⋅,0)ϕS(⋅,0)ϕi(⋅,0)ϕS(⋅,0)+ϕ1(⋅,0)+ϕ2(⋅,0)+ϕR(⋅,0),Fi(t,ϕ)=∫τi0fi(a)∫ΩΓi(x,y,t,t−a)βi(y,t−a)ϕS(y,−a)ϕi(y,−a)ϕS(y,−a)+ϕ1(y,−a)+ϕ2(y,−a)+ϕR(y,−a)dyda,FR(t,ϕ)=r1(⋅,0)ϕ1(⋅,0)+r2(⋅,0)ϕ2(⋅,0). |
Let F=(FS,F1,F2,FR), it is clear that F is a function from [0,∞) to X. Define
U(t,s):=(VS(t,s)0000V1(t,s)0000V2(t,s)0000VR(t,s)). |
Then U(t,s) is an evolution operator from X to X. Note that VS, Vi(i=1,2) and VR are analytic operators, it follows that U(t,s) is an analytic operator for (t,s)∈R2 with t≥s≥0. Let
D(AS(t))={ψ∈C2(ˉΩ)∣上∂∂nψ=0 on ∂Ω};[AS(t)ψ](x)=DSΔψ(x)−d(x,t)ψ(x), ∀ψ∈D(AS(t));D(Ai(t))={ψ∈C2(ˉΩ)∣上∂∂nψ=0 on ∂Ω};[Ai(t)ψ](x)=DiΔψ(x)−hi(x,t)ψ(x), ∀ψ∈D(Ai(t)), |
and
D(AR(t))={ψ∈C2(ˉΩ)∣上∂∂nψ=0 on ∂Ω};[AR(t)ψ](x)=DRΔψ(x)−k(x,t)ψ(x), ∀ψ∈D(AR(t)). |
Moreover, we let
A(t):=(AS(t)0000A1(t)0000A2(t)0000AR(t)). |
Then (2.3) can be rewritten as the following Cauchy problem:
{∂u(x,t)∂t=A(t)u(x,t)+F(t,ut), x∈Ω, t>0,u(x,ζ)=ϕ(x,ζ), x∈Ω, ζ∈[−τ,0], | (2.10) |
where u(x,t)=(S(x,t),I1(x,t),I2(x,t),R(x,t))T. Furthermore, it can be rewritten as the following integral equation
u(t,ϕ)=U(t,0)ϕ(0)+∫t0U(t,s)F(t,us)ds, t≥0, ϕ∈C+τ. |
Then the solution of above integral equation is called a mild solution of (2.10).
Theorem 2.1. For each ϕ∈C+τ, system (2.6) admits a unique solution u(t,ϕ) on [0,+∞) with u0=ϕ, and u(t,ϕ) is globally bounded.
Proof. By the definition of F(t,ϕ) and the assumption (H), F(t,ϕ) is locally Lipschitz continuous on R+×C+τ. We first show
limθ→0+dist(ϕ(0)+θF(t,ϕ),X+)=0, ∀(t,ϕ)∈R+×C+τ. | (2.11) |
Set
ˉβ=max{maxx∈ˉΩ,t∈[0,τ]β1(x,t),maxx∈ˉΩ,t∈[0,τ]β2(x,t)};mi(x,t)=βi(x,t)ϕS(x,0)ϕi(x,0)ϕS(x,0)+ϕ1(x,0)+ϕ2(x,0)+ϕR(x,0);ni(x,t)=βi(x,t)ϕS(x,t)ϕi(x,t)ϕS(x,t)+ϕ1(x,t)+ϕ2(x,t)+ϕR(x,t). |
For any t≥0, θ≥0 and x∈ˉΩ, ϕ∈C+τ, we have
ϕ(x,0)+θF(t,ϕ)(x)=(ϕS(x,0)+θ[μ(x,t)+α(x,t)ϕR(x,0)−2∑i=1mi(x,t)]ϕ1(x,0)+θ∫τ10f1(a)∫ΩΓ1(x,y,t,t−a)ϕ1(y,t−a)dydaϕ2(x,0)+θ∫τ20f1(a)∫ΩΓ2(x,y,t,t−a)ϕ2(y,t−a)dydaϕR(x,0)+r1(x,t)ϕ1(x,0)+r2(x,t)ϕ2(x,0))≥(ϕS(x,0)(1−θ2∑i=1βi(x,t)ϕi(x,0)ϕS(x,0)+ϕ1(x,0)+ϕ2(x,0)+ϕR(x,0))ϕ1(x,0)ϕ2(x,0)ϕR(x,0))≥(ϕS(x,0)(1−θˉβ2∑i=1ϕi(x,0)ϕS(x,0)+ϕ1(x,0)+ϕ2(x,0)+ϕR(x,0))ϕ1(x,0)ϕ2(x,0)ϕR(x,0)). |
The above inequality implies that (2.11) holds when θ is small enough. Consequently, by [25,Corollary 4] with K=X+ and S(t,s)=U(t,s), system (2.6) admits a unique mild solution u(x,t;ϕ) with u0(⋅,⋅;ϕ)=ϕ, t∈[0,tϕ]. Since U(t,s) is an analytic operator on X for any t,s∈R, s<t, it follows that u(x,t;ϕ) is a classical solution for t>τ. Set
P(t)=∫Ω(S(x,t)+2∑i=1(Li(x,t)+Ii(x,t))+R(x,t))dx, |
μmax=sup(x,t)∈ˉΩ×[0,T]μ(x,t), ˉμmax=μmax⋅|Ω|, dmin=inf(x,t)∈ˉΩ×[0,T]d(x,t). |
Then
dP(t)dt=∫Ωμ(x,t)−d(x,t)(S(x,t)+2∑i=1(Li(x,t)+Ii(x,t))+R(x,t)) −2∑i=1δi(x,t)(Li(x,t)+Ii(x,t))−2∑i=1ri(x,t)Li(x,t)dx≤∫Ωμ(x,t)dx−∫Ωd(x,t)(S(x,t)+2∑i=1(Li(x,t)+Ii(x,t))+R(x,t))dx≤ˉμmax−dminP(t), t>0. |
We obtain that there are l:=lϕ large enough and M=ˉμmaxdmin+1>0, so that for each ϕ∈C+τ, one has
P(t)≤M, ∀t≥lT+τ. |
Then ∫ΩIi(x,t)dx≤M, ∀t≥lT+τ. According to [11] and assumption (H), we obtain that Γi(x,y,t,t−a) and βi(x,t) are uniformly bounded functions for any x,y∈Ω, t∈[a,a+T]. Set Bi=supx,y∈Ω,t∈[a,a+T]Γi(x,y,t,t−a)βi(y,t−a), then we obtain
∂Ii∂t≤DiΔIi−hi(x,t)Ii(x,t)+∫τi0fi(a)∫ΩΓi(x,y,t,t−a)βi(y,t−a)Ii(y,t−a)dyda≤DiΔIi−hi(x,t)Ii(x,t)+Bi∫τi0fi(a)∫ΩIi(y,t−a)dyda≤DiΔIi−hi(x,t)Ii(x,t)+BiMFi(τi)=DiΔIi−hi(x,t)Ii(x,t)+BiM, x∈Ω, t≥lT+τ. | (2.12) |
Consider the following equation:
{∂ωi(x,t)∂t=DiΔωi(x,t)−hi(x,t)ωi(x,t)+BiM,x∈Ω, t>lT+τ,∂ωi(x,t)∂n=0,x∈∂Ω, t>lT+τ. | (2.13) |
It is evident that system (2.13) admits a strictly positive periodic solution with the period T>0, which is globally attractive. According to (2.12), the first equation of system (2.6) can be dominated by (2.13) for any t>lT+τ. So there exists B1>0 such that for each ϕ∈C+τ, we can find a li=li(ϕ)≫l(ϕ) satisfying Ii(x,t;ϕ)≤B1(i=1,2) for x∈ˉΩ and t≥liT+τ. Thus
{∂R(x,t)∂t≤DRΔR(x,t)−k(x,t)R(x,t)+B1(r1(x,t)+r2(x,t)),x∈Ω, t>liT+τ,∂R(x,t)∂n=0,x∈∂Ω, t>liT+τ. | (2.14) |
Similarly, there exists B2>0 such that for each ϕ∈C+τ, there exists lR=lR(ϕ)≫li satisfying R(x,t;ϕ)≤B2 for x∈ˉΩ and t≥lRT+τ. Then we have
{∂S(x,t)∂t≤DSΔS(x,t)+μ(x,t)−d(x,t)S(x,t)+B2α(x,t),x∈Ω, t>lRT+τ,∂S(x,t)∂n=0,x∈∂Ω, t>lRT+τ. | (2.15) |
Hence, there are B3>0 and lS=lS(ϕ)≫lR such that for each ϕ∈C+τ, S(x,t;ϕ)≤B3(i=1,2) for x∈ˉΩ and t≥lST+τ, and hence, tϕ=+∞.
Theorem 2.2. System (2.6) generates a T-periodic semi-flow Φt:=ut(⋅):C+τ→C+τ, namely Φt(ϕ)(x,s)=ut(ϕ)(x,s)=u(x,t+s;ϕ) for any ϕ∈C+τ, t≥0 and s∈[−τ,0]. In addition, ΦT admits a global compact attractor on C+τ, where u(x,t;ϕ) is a solution of system (2.6).
Proof. By a similar argument as the proof of [26,Theorem 8.5.2], one can show that Φt(ϕ) is continuous for any ϕ∈C+τ and t≥0. In addition, similarly as the proof of [36,Lemma 2.1], we can further verify that Φt is a T-periodic semi-flow on C+τ. According to Theorem 2.1, we obtain that Φt is dissipative. Moreover, by the arguments similar to those in the proof of [15,Proposition 21.2], we get that there exists n0≥1 such that Φn0T=un0T is compact on C+τ for n0T≥τ. Following from [23,Theorem 2.9], we have that ΦT:C+τ→C+τ admits a global compact attractor.
In this section, we first analyze the threshold dynamics of a single-strain model with the help of the basic reproduction number, and then study the threshold dynamics of model (2.6).
Let Ij(x,t)≡0,∀x∈Ω, t>0, j=1,2, and i≠j. Then system (2.6) reduces to the following single-strain model:
{∂S∂t=DSΔS+μ(x,t)−d(x,t)S+α(x,t)R(x,t)−βi(x,t)S(x,t)Ii(x,t)S(x,t)+Ii(x,t)+R(x,t),∂Ii∂t=DiΔIi(x,t)−hi(x,t)Ii(x,t)+∫τi0fi(a)∫ΩΓi(x,y,t,t−a)βi(y,t−a)S(y,t−a)Ii(y,t−a)S(y,t−a)+Ii(y,t−a)+R(y,t−a)dyda,∂R∂t=DRΔR(x,t)+ri(x,t)Ii(x,t)−d(x,t)R(x,t)−α(x,t)R(x,t). | (3.1) |
Consider the following linear equation:
{∂S(x,t)∂t=DSΔS(x,t)+μ(x,t)−d(x,t)S(x,t),x∈Ω, t>0,∂S(x,t)∂n=0,x∈∂Ω, t>0. | (3.2) |
According to [36,Lemma 2.1], there is an unique T-periodic solution S∗(x,t) of (3.2). Linearizing the Ii-equation of system (3.1) at the disease-free periodic solution (S∗,0,0), we have
{∂ωi(x,t)∂t=DiΔωi(x,t)−hi(x,t)ωi(x,t) +∫τi0fi(a)∫ΩΓi(x,y,t,t−a)βi(y,t−a)ωi(y,t−a)dyda, x∈Ω, t>0,∂ωi(x,t)∂n=0, x∈∂Ω, t>0. | (3.3) |
Let
CT(ˉΩ×R,R):={u|u∈C(ˉΩ×R,R),u(x,t+T)=u(x,t),(x,t)∈Ω×R,T>0}, |
with the supremum norm, and define C+T as the positive cone of CT(ˉΩ×R,R), namely,
C+T:={u∈CT: u(t)(x)≥0, ∀t∈R, x∈ˉΩ}. |
Let ψi(x,t)∈CT(ˉΩ×R,R) be the initial distribution of infected individuals of the i-strain at the spatial position x∈ˉΩ and time t∈R, then Vi(t−a,s)ψi(s)(s<t−a) is the density of those infective individuals at location x who were infective at time s and retain infective at time t−a when time evolved from s to t−a. Furthermore, ∫t−a−∞Vi(t−a,s)ψi(s)ds is the density distribution of the accumulative infective individuals at positive x and time t−a for all previous time s<t−a. Hence the density of new infected individuals at time t and location x can be written as
∫τi0fi(a)∫ΩΓi(x,y,t,t−a)βi(y,t−a)∫t−a−∞(Vi(t−a,s)ψi(s))(x)dsdyda=∫τi0fi(a)∫ΩΓi(x,y,t,t−a)βi(y,t−a)∫+∞a(Vi(t−a,t−s)ψi(t−s))(x)dsdyda. |
Defining operator Ci:CT(ˉΩ×R,R)⟶CT(ˉΩ×R,R) by
(Ciψi)(x,t)=∫τi0fi(a)∫ΩΓi(x,y,t,t−a)βi(y,t−a)ψi(y,t−a)dyda. |
Set
Ai(ψi)(x,t)=(Ciψi)(x,t), Bi(ψi)(x,t)=∫+∞a(Vi(t,t−s+a)ψi(t−s+a))(x)ds. |
Defining other operators Li,ˆLi:CT⟶CT by
(Liψi):=∫τi0fi(a)∫ΩΓi(x,y,t,t−a)βi(y,t−a)∫+∞aVi(t−a,t−s)ψi(t−s)(x)dsdyda,(ˆLiψi)(x,t):=∫+∞0Vi(t,t−s)(Ciψi)(t−s)(x)ds, t∈R, s≥0. |
Clearly, Li=AiBi, ˆLi=BiAi, Li and ˆLi are compact, bounded and positive operators. Let r(Li) and r(ˆLi) are the spectral radius of Li and ˆLi respectively, then r(Li)=r(ˆLi). Similar to [18,20], we define the basic reproduction number for system (3.1), that is, Ri0=r(Li)=r(ˆLi).
Define Q:=C([−τ,0],Y), and let ||ϕ||Q:=maxθ∈[−τ,0]||ϕ(θ)||Y for any ϕ∈Q. Denote Q+:=C([−τ,0],Y+) as the positive cone of Q. Then (Q,Q+) is strongly ordered Banach space. Let P:=C(ˉΩ,R3) be the Banach space with supremum norm ‖⋅‖P. For τ>0, let Dτ:=C([−τ,0],P) be the Banach space with ‖ϕ‖=maxθ∈[−τ,0]‖ϕ(θ)‖P for all ϕ∈Dτ. Define P+:=C(ˉΩ,R3+) and D+τ:=C([−τ,0],P+), then both (P,P+) and (Dτ,D+τ) are strongly ordered space. By the arguments in [21,39], we have the following observation:
Theorem 3.1. The signs of Ri0−1 and ri−1 are same.
Consider the following equation
{∂ωi(x,t)∂t=DiΔωi(x,t)−hi(x,t)ωi(x,t) +∫τi0fi(a)∫ΩΓi(x,y,t,t−a)B3βi(y,t−a)B3+ωi(y,t−a)ωi(y,t−a)dyda, x∈Ω, t>0,∂ωi(x,s)=ψi(x,s), ψi∈Q+, x∈Ω, s∈[−τi,0],∂ωi(x,t)∂n=0, x∈∂Ω, t>0, | (3.4) |
where B3 is the constant in the proof of Theorem 2.1.
Theorem 3.2. Assume that ωi(x,t;ψi) is the solution of (3.4) with an initial value of ψi∈Q. If Ri0=1 and βi(x,t)>0 for all x∈ˉΩ, t>0, then ωi(x,t)≡0 is globally attractive.
Proof. By a straightforward computation, one has that (3.4) is dominated by (3.3). Define the map Pnoi:Q→Q by Pnoi(ψi)=ωn0i,T with ωn0i,T=ωi(x,n0T+s;ψi), where ωi(x,t;ψi) is the solution of (3.3). Similar to the argument in [18], Pnoi is strongly positive on Q+ when βi(x,t)>0,∀x∈ˉΩ, t>0. It follows from [20,Lemma 3.1] that Pnoi admits a positive and simple eigenvalue ri, and a strongly positive eigenfunction defined by ψi, that is Pi(ψi)=riψi. It follows from the strong positivity of ψi that ωi(x,t;ψi)≫0. According to Theorem 3.2, we have ri=1, and hence, μi=0. By similar arguments as the proof of [18,Lemma 3.2], we can show that there is a positive T-periodic function ν∗i(x,t)=e−μi⋅0ωi(x,t;ψi)=ωi(x,t;ψi) such that ν∗i(x,t) is a solution of (3.3). Then for each initial value ψi(x,s)∈Q, there exists a constant k>0 such that ψi(x,s)≤kν∗i(x,s) for all x∈Ω, t>0. Moreover, by the comparison principle, one has ωi(x,t;ψi)≤kν∗i(x,t) for all x∈Ω, t>0. Let
[0,kν∗i]Q={u∈Q:0≤u(x,s)≤kν∗i(x,s), ∀x∈ˉΩ, s∈[−τi,0]}, |
then
Sn0i(ψi):=ωi(x,noTω+S;ψI)⊆[0,kν∗i]Q, ∀x∈ˉΩ, s∈[−τi,0]. |
Hence the positive orbit γ+(ψi):={Skn0i(ψi):∀k∈N} of Sn0i(⋅) is precompact, and Sn0i maps [0,kν∗i]Q into [0,kν∗i]Q, Due to comparison principle, we get Sn0i(⋅) is monotone. According to [40,Theorem 2.2.2], we obtain that ωi(x,t)≡0 is globally attractive.
Theorem 3.3. Suppose that ˉS(x,t;ψ)=(S(x,t;ψ),Ii(x,t;ψ),R(x,t;ψ)) is the solution of (3.1) with the initial data ψ. If Ii(x,t0;ψ)≢0 for some t0≥0, then Ii(x,t;ψ)>0, ∀x∈ˉΩ, t>t0.
Proof. Obviously, for the secondly equation of (3.1), we get
{∂Ii(x,t)∂t≥DiΔIi(x,t)−hi(x,t)Ii(x,t), x∈Ω, t>0,∂Ii(x,t)∂n=0, x∈∂Ω, t>0, i=1,2, |
and Ii(x,t0;ψ)≢0, t0≥0, i=1,2. It follows from [15,Proposition 13.1] that Ii(x,t;ψ)>0 for all x∈ˉΩ and t>t0.
Theorem 3.4. Suppose that ˉS(x,t;ψ)=(S(x,t;ψ),Ii(x,t;ψ),R(x,t;ψ)) be the solution of (3.1) with the initial data ψ=(ψS,ψi,ψR)∈Dτ, i=1,2. Thenone has
(1) If Ri0=1 and βi(x,t)>0 for all x∈Ω and t>0, then (S∗,0,0) is globally attractive;
(2) If Ri0<1, then (S∗,0,0) is globally attractive;
(3) If Ri0>1, then there is a M>0 such that for any ψ∈D+τ, one has
lim inft→∞S(x,t;ψ)>M, lim inft→∞Ii(x,t;ψ)>M, lim inft→∞R(x,t;ψ)>M |
uniformly for x∈ˉΩ.
Proof. (1) According to the proof of Theorem 2.1, for t>lsT+τ, we have S(x,t;ϕ)≤B3, ∀x∈ˉΩ, ϕ∈C+τ. Thus, when t>lsT+τ, the second equation of (3.1) is dominated by (3.4) for x∈ˉΩ. In addition, one has Ii(x,t;ψ)≤ωi(x,t) for x∈ˉΩ and t>lsT+τ. Since Ri0=1 and βi(x,t)>0 for x∈ˉΩ, t>0. It follows from Theorem 3.5 that limt→∞ωi(x,t)=0 for all x∈ˉΩ. In addition, one has limt→∞Ii(x,t;ψ)=0 for all x∈ˉΩ, and limt→∞R(x,t;ψ)=0 for all x∈ˉΩ. Hence the first equation of (3.1) is asymptotic to (3.2). It follows from [36,Lemma 2.1] that system (3.2) admits an unique positive T-periodic solution S∗(x,t), which is globally attractive.
Let P=ΦT, J=ˉω(ψ) denotes the omega limit set for P. That is
J={(ϕ∗S,ϕ∗i,ϕ∗R)∈C+τ:∃{ki}→∞ s.t. limi→∞Pki(ϕS,ϕi,ϕR)=(ϕ∗S,ϕ∗i,ϕ∗R)}. |
It follows fron [17,Lemma 2.1] that J is an internally chain transitive sets for P. Since limt→∞Ii(x,t;ψ)=0 and limt→∞R(x,t;ψ)=0 for all x∈ˉΩ, then J=J1×{ˆ0}×{ˆ0}. According to Theorem 3.5, one has ˆ0∉J1. Let ω(x,t;ψS(⋅,0)) be the solution of (3.2) with the initial value ω(x,0)=ψS(x,0), where ψS∈Q+. Define
ωt(x,θ;ψS)={ω(x,θ+t;ψS(0)) t+θ>0, t>0, θ∈[−τ,0],ψ(x,θ+t) t+θ≤0, t>0, θ∈[−τ,0]. |
Then we define the solution semiflow ωt for (3.2).
Let ˉP=ωT(ψS), ˉω(ψS) denotes the omega limit set of ˉP. According to [36,Lemma 2.1], one has ˉω(ψS)={S∗}. Since P(J)=J and Ii(x,t;(ψS,ˆ0,ˆ0))≡0, R(x,t;(ψS,ˆ0,ˆ0))≡0, P(J)=ˉP(J1)×{ˆ0}×{ˆ0}, then ˉP(J1)=J1. Therefore, J1 is an internally chain transitive sets for ˉP. It follows from [36,Lemma 2.1] that {S∗} is globally attractive on Q+. In addition, J1∩WS{S∗}=J1∩ Q+=∅, where WS{S∗} is the stable set of S∗. According to [40,Theorem 1.2.1], one has J1⊆{S∗}, then J1={S∗}. Consequently, J={(S∗,0,0)}. By the definition of J, we have
limt→∞∥(S(⋅,t;ψ),Ii(⋅,t;ψ),R(⋅,t;ψ))−(S∗(⋅,t),0,0)∥=0. |
(2) Consider equation
{∂ω∗i(x,t)∂t=DiΔω∗i(x,t)−hi(x,t)ω∗i(x,t) +∫τi0fi(a)∫ΩΓi(x,y,t,t−a)(βi(y,t−a)+ε)ω∗i(y,t−a)dyda, x∈Ω, t>0,∂ω∗i(x,t)∂n=0, x∈∂Ω, t>0. | (3.5) |
Since Ri0<1, it follows from Theorem 2.1 that ri<1. Thus there exists a constant ε0>0 such that ri,ε<1 for ε∈[0,ε0). Then μi,ε:=lnri,εT<0 for ε∈[0,ε0). Similar to the proof of [18,Lemma 3.2], there is positive T-periodic function νεi(x,t) such that ωεi(x,t)=eμi,ενεi(x,t) satisfies (3.5). Since μi,ε<0, limt→∞ωεi(x,t)=0 uniformly for x∈Ω.
For x∈Ω, t>0, one has
{∂Ii(x,t)∂t≤DiΔIi(x,t)−hi(x,t)Ii(x,t) +∫τi0fi(a)∫ΩΓi(x,y,t,t−a)(βi(y,t−a)+ε)Ii(y,t−a)dyda, x∈Ω, t>0,∂Ii(x,t)∂n=0, x∈∂Ω, t>0. | (3.6) |
For any given initial distribution ψ∈D+τ, due to the boundedness of Ii(x,t;ψ), there exists α>0 such that Ii(x,t;ψ)≤α⋅ωεi(x,t), ∀t∈[kT,kT+τ], x∈ˉΩ, and hence, Ii(x,t;ψ)≤α⋅ωεi(x,t) for t≥kT+τ. Then limt→∞Ii(x,t;ψ)=0 and limt→∞R(x,t;ψ)=0 for all x∈ˉΩ. Furthermore, similar to the proof of (1), we have
limt→∞∥(S(⋅,t;ψ),Ii(⋅,t;ψ),R(⋅,t;ψ))−(S∗(⋅,t),0,0)∥=0. |
(3) Let
Wi0={ψ=(ψS,ψi,ψR)∈D+τ:ψi(⋅,0)≠0}, |
∂Wi0:=D+τ∖Wi0={ψ=(ψS,ψi,ψR)∈D+τ:ψi(⋅,0)≡0}. |
Define Φt:D+τ→D+τ by Φt(ψ)(x,s)=(S(x,t+s;ψ),Ii(x,t+s;ψ),R(x,t+s;ψ)). By Theorem 3.6, we know that Ii(x,t+s;ψ)>0 for any ψ∈W0i, x∈ˉΩ and t>0. Thus there exists k∈N such that Φkn0T(Wi0)⊆Wi0. Define
Mi∂:={ψ∈∂Wi0:Φkn0T(ψ)∈∂Wi0, ∀k∈N}. |
Let M:=(S∗,0,0) and ω(ψ) be the omega limit set of the orbit γ+:={Φkn0T(ψ):∀k∈N}. For any given ψ∈Mi∂, we have Φkn0T(ψ)∈∂Wi0. Thus Ii(x,t;ψ)≡0, ∀x∈ˉΩ, t≥0. Therefore R(x,t;ψ)≡0 for any x∈ˉΩ and t≥0. By similar arguments as the proof of (1), we have
limt→∞∥(S(⋅,t;ψ),Ii(⋅,t;ψ),R(⋅,t;ψ))−(S∗(⋅,t),0,0)∥=0. |
That is ω(ψ)=M for any ψ∈Mi∂.
For sufficient small ˉθ>0, consider the following system:
{∂vθi(x,t)∂t=DiΔvθi(x,t)−hi(x,t)vθi(x,t) +∫τi0fi(a)∫ΩΓi(x,y,t,t−a)βi(y,t−a)(S∗(y,t−a)−ˉθ)S∗(y,t−a)+ˉθvθi(y,t−a)dyda, x∈Ω, t>0,∂vθi(x,s)=ψi(x,s), ψi∈Q+, x∈Ω, s∈[−τi,0],∂vθi(x,t)∂n=0, x∈∂Ω, t>0. | (3.7) |
Let vθi(x,t;ψi) be the solution of (3.7). Note vθi,n0T(ψi)(x,s)=vθi(x,s+n0T;ψi) for all x∈Ω and s∈[−τi,0]. Define the poincareˊ map (\chi_{\theta}^i)^{n_0}:Q^+\rightarrow Q^+ by (\chi_{\theta}^i)^{n_0}(\psi_i) = v_{i, n_0T}^{\theta}(\psi_i) . It is easy to prove that (\chi_{\theta}^i)^{n_0} is a compact, strongly positive operator. Let (r_{\theta}^i)^{n_0} be the spectral radius of (\chi_{\theta}^i)^{n_0} . According to [15,Theorem 7.1], there is a positive eigenvalue (r_{\theta}^i)^{n_0} and a positive eigenfunction \tilde{\varphi}_i such that (\chi_{\theta}^i)^{n_0} = (r_{\theta}^i)^{n_0}\tilde{\varphi}_i . Since R_0^i > 1 , it follows from Theorem 2.1 that r^i > 1 . Then there exists a sufficient small number \theta_1 > 0 such that r_{\theta}^i > 1 for \theta\in (0, \theta_1) .
By the continuous dependence of solutions on initial value, there exists \theta_0\in (0, \theta_1) such that
\begin{equation*} \|S(x, t;\phi), I_i(x, t;\phi), R(x, t;\phi)-(S^*(x, t), 0, 0)\| < \bar{\theta}, \ \forall x\in \bar{\Omega}, \ t\in [0, T], \end{equation*} |
if
\|(\phi_S(x, s), \phi_i(x, s), \phi_R(x, s))-(S^*(x, s), 0, 0)\| < \theta_0, \ x\in \bar{\Omega}, \ s\in [-\tau_i, 0]. |
Claim. M is a uniformly weak repeller for W_0^i , that is,
\underset {k\rightarrow \infty }{\limsup }\|\Phi_{n_0T}^k(\psi)-M\|\ge \theta_0, \ \forall \psi\in W_0^i. |
Suppose, by contradiction, there exists \psi_0\in W_0^i such that
\underset {k\rightarrow \infty }{\limsup }\|\Phi_{n_0T}^k(\psi)-M\| < \theta_0. |
Then there exist a k_0\in N such that
\begin{align*} &|S(x, kn_0T+s;\psi_0)-S^*| < \theta_0, \ |I_i(x, kn_0T+s;\psi_0| < \theta_0, \\ &|R(x, kn_0T+s;\psi_0| < \theta_0, \ \forall x\in \bar{\Omega}, \ s\in [-\tau_i, 0], \ k\ge k_0. \end{align*} |
According to (3.11) , for any t > kn_0T and x\in \bar{\Omega} ,
\begin{align*} S^*-\bar{\theta} < S(x, t;\psi_0) < S^*+\bar{\theta}, \ 0 < I_i(x, t;\psi_0) < \bar{\theta}, \ 0 < R(x, t;\psi_0) < \bar{\theta}. \end{align*} |
Therefore, for I_i -equation of (3.1) , we have
\begin{equation} \begin{split} \frac{ \partial I_i(x, t)}{ \partial t}&\ge D_i\Delta I_i(x, t)-h_i(x, t)I_i(x, t) \\ &\ \ \ +\int_{0}^{\tau _i} f_i(a)\int_{\Omega }\Gamma_i(x, y, t, t-a)\frac{\beta_i(y, t-a)(S^*(y, t-a)-\bar{\theta})}{S^*(y, t-a)+\bar{\theta}}I_i(y, t-a)dyda, \\ &\ \ \ \ x\in \Omega , t > (k_0+1)n_0T.\\ \end{split} \end{equation} | (3.8) |
Since
I_i(x, t;\psi_0) > 0, \ x\in\bar{ \Omega} , \ t > (k_0+1)n_0T, |
there exist some \kappa > 0 , such that
I_i(x, (k_0+1)n_0T+s;\psi_0)\ge \kappa\tilde{\varphi}_i(x, s), \ \forall x\in \bar{\Omega}, \ s\in [-\tau_i, 0]. |
By (3.12) and the comparison principle, we have
I_i(x, t+s;\psi_0)\ge \kappa\nu _i^{\theta}(x, t-(k_0+1)n_0T+s;\tilde{\varphi}_i), \ \forall x\in \bar{\Omega} , \ t > (k_0+1)n_0T. |
Therefore, we have
\begin{equation} I_i(x, kn_0T+s;\psi_0)\ge \kappa\nu _i^{\theta}(x, k-(k_0+1)n_0T+s;\tilde{\varphi}_i) = \kappa(r_{\theta}^i)^{(k-k_0-1)n_0}\tilde{\varphi}_i(x, s), \end{equation} | (3.9) |
where k\ge k_0+1, \ s\in [-\tau_i, 0] . Since \tilde{\varphi}_i(x, s) > 0 for (x, s)\in \bar{\Omega}\times [-\tau_i, 0] , there is (x_i, s_i)\in \bar{\Omega}\times [-\tau_i, 0] such that \hat{\varphi}_i(x_i, s_i) > 0 . It follows from (r_{\theta}^i)^{n_0} > 1 that I_i(x_i, kn_0T+s_i; \psi_0)\rightarrow +\infty as k\rightarrow \infty , which contradicts to I_i(x, t;\psi_0)\in (0, \bar{\theta}) .
Let W^S(M) be the stable set of M . In conclusion, W^S(M) = M_{\partial}^i ; M is an isolated invariant set for \Phi_{n_0T} in W_0^i ; W^S(M)\cap W_0^i = M_{\partial}^i\cap W_0^i = \varnothing . According to [40,Theorem 1.3.1] and [40,Remark 1.3.1], one has there is \bar{\sigma} > o such that \inf d(\omega(\psi), \partial W_0^i)\ge \bar{\sigma} for any \psi\in W_0^i . That is \underset {t\rightarrow \infty }{\liminf }d(\Phi_{n_0T}^k, \partial W_0^i)\ge \bar{\sigma} for any \psi\in W_0^i . Therefore, \Phi_{n_0T}:D_{\tau } ^+\rightarrow D_{\tau}^+ is uniformly persistent with respect to (W_0^i, \partial W_0^i) . Similar to Theorem 2.1 , it can be proved that the solution \bar{S}(x, t;\psi) of 3.1 is globally bounded for any \psi\in D_{\tau}^+ . Therefore, \Phi_{n_0T}:D_{\tau}^+\rightarrow D_{\tau}^+ is point dissipative. It is easy to prove that \Phi_{n_0T} is compact on W_0^i for n_0T > \tau_i . It follows from [40,Section 1.1] that the compact map \Phi_{n_0T} is an \alpha- contraction of order 0 , and an \alpha- contraction of order 0 is \alpha- condensing. Then according to [23,Theorem 4.5], \Phi_{n_0T}: W_0^i\rightarrow W_0^i admits a compact global attractor Z_0^i .
Similar to the proof of [22,Theroem 4.1], let P:D_{\tau }^+\rightarrow [0, +\infty) by
P(\psi) = \underset {x\in \bar{\Omega}}{\min }\psi_i(x, 0), \ \forall \psi\in D_{\tau}^+. |
Since \Phi_{n_0T}(Z_0^i) = Z_0^i , we have that \psi_i(\cdot, 0) > 0 for any \psi \in Z_0^i . Let B_i: = \underset {t\in [0, n_0T]}{\cup}\Phi_t(Z_0^i) , then B_i\subseteq W_0^i . In addition, we get \underset {t\rightarrow \infty }{\lim}d(\Phi_t(\psi), B_i) = 0 for all \psi\in W_0^i . Since B_i is a compact subset of W_0^i , we have \underset {\psi\in B_i}{\min}P(\psi) > 0 . Thus, there exists a \sigma^* > 0 such that \underset {t\rightarrow \infty }{\liminf}I_i(\cdot, t; \psi)\ge \sigma^* . Furthermore, according to Theorem 3.6 , there exists M > 0 such that \underset {t\rightarrow \infty }{\liminf}I_i(\cdot, t; \psi)\ge M .
Consider the following equation:
\begin{equation} \begin{cases} \begin{split} \frac{ \partial \bar{S}(x, t)}{ \partial t} = &D_{\bar{S}}\Delta \bar{S}(x, t)+\mu(x, t)-d(x, t)\bar{S}(x, t)-\beta_1(x, t)\bar{S}(x, t)\\ &-\beta_2(x, t)\bar{S}(x, t), \ x\in \Omega , \ t > 0, \\ \frac{ \partial \bar{S}(x, t)}{ \partial n} = &0, \ x\in \partial \Omega , \ t > 0, \ i = 1, 2. \end{split} \end{cases} \end{equation} | (3.10) |
According to [36,Lemma 2.1], equation (3.10) admits a unique positive solution \bar{S}^* , which is T-periodic with respect to t\in R . Obviously, for the S -equation of (2.6), we have
\begin{equation} \begin{cases} \begin{split} \frac{ \partial S(x, t)}{ \partial t}\ge &D_S\Delta S(x, t)+\mu(x, t)-d(x, t)S(x, t)-\beta_1(x, t)S(x, t), \\ &-\beta_2(x, t)S(x, t), \ x\in \Omega , \ t > 0, \\ \frac{ \partial S(x, t)}{ \partial n} = &0, \ x\in \partial \Omega , \ t > 0, \ i = 1, 2. \end{split} \end{cases} \end{equation} | (3.11) |
It follows from the comparison principle, one has
\underset {t\rightarrow \infty }{\liminf}S(x, t)\ge \bar{S}^*(x, t), \ \forall x\in \bar{\Omega}. |
According to Theorem 2.1 , there exist constants B_1, B_2 and l_R , such that
I_i(x, t;\phi)\le B_1(i = 1, 2), \ R(x, t;\phi)\le B_2 |
for t\ge l_RT+\tau . Consider the following equation:
\begin{equation} \begin{cases} \begin{split} \frac{ \partial u_i(x, t)}{ \partial t} = &D_i\Delta u_i(x, t)-h_i(x, t)u_i(x, t) \\ &+\int_{0}^{\tau _i} f_i(a)\int_{\Omega }\Gamma_i(x, y, t, t-a)\beta_i(y, t-a)\frac {\bar{S}^*(x, t)}{\bar{S}^*(x, t)+B_1+B_2}u_i(y, t-a)dyda, \\ &\ x\in \Omega , \ t > 0, \\ \frac{ \partial u_i(x, t)}{ \partial n} = &0, \ x\in \partial \Omega , \ t > 0, \ i = 1, 2. \end{split} \end{cases} \end{equation} | (3.12) |
Let u_i(x, t;\phi_i) be the solution of (3.12) for \phi_i\in Q, (x, s)\in \bar{\Omega}\times [-\tau, 0] . Define \bar{P}_i:Q\rightarrow Q by \bar{P}_i(\phi_i) = u_{i, T}(\phi_i) for any \phi_i\in Q , where u_{i, T}(\phi_i)(x, t) = u_i(x, s+T; \phi_i), \ (x, s)\in \bar{\Omega}\times [-\tau, 0] . Let \rho_i^0 be the spectral of \bar{P}_i . We define the linear operator \bar{L}_i:C_T\rightarrow C_T by:
\begin{align*} \bar{L}_i(\psi_i)(x, t) = &\int_{0}^{\tau _i} f_i(a)\int_{\Omega }\Gamma_i(x, y, t, t-a)\beta_i(y, t-a)\frac {S^*(x, t)}{S^*(x, t)+B_1+B_2}\\ &\cdot\int_{a}^{\infty}(V_i(t-a, t-s)\psi_i(t-s))(y)dsdyda. \end{align*} |
Then the operator \bar{L}_i is positive and bounded on C_T(\bar{\Omega}\times R, R) . Let r(\bar{L}_i) denote the spectral radius of \bar{L}_i . Similar to [18,20], define the invasion number \hat{R}_0^i for strain i by \hat{R}_0^i: = r(\bar{L}_i) , and we have the following result.
Theorem 3.5. The signs of \hat{R}_0^i-1 and \rho_i^0-1 are same.
By the arguments similar to those in the proof of [38,Proposition 5.10], we further have the following observation.
Theorem 3.6. If \hat{R}_0^i > 1 , then R_0^i > 1, \ i = 1, 2.
Theorem 3.7. Suppose that \hat{R}_0^i > 1\; (i = 1, 2) . Then for any \psi = (\psi_S, \psi_1, \psi_2, \psi_R)\in C_{\tau}^+, \ \psi_i\not \equiv0\; (i = 1, 2) , there is an \eta > 0 such that
\underset {t\rightarrow \infty }{\liminf}S(x, t;\psi)\ge \eta, \ \underset {t\rightarrow \infty }{\liminf}I_i(x, t;\psi)\ge \eta, \ i = 1, 2. |
Proof. According to Theorem 3.6 and \hat{R}_0^i > 1\; (i = 1, 2) , one has R_0^i > 1\; (i = 1, 2) . Let
Z_0 = \{\psi = (\psi_S, \psi_1, \psi_2, \psi_R)\in C_{\tau}^+:\psi_1(\cdot, 0)\not \equiv0\ \rm{且}\ \psi_2(\cdot, 0)\not \equiv0\}, |
\partial Z_0: = C_{\tau}^+\backslash W_0 = \{\psi = (\psi_S, \psi_1, \psi_2, \psi_R)\in C_{\tau}^+:\psi_1(\cdot, 0)\equiv0\ \rm{或}\ \psi_2(\cdot, 0)\equiv0\}, |
and
Z_{\partial}: = \{\psi\in \partial Z_0: \Phi_{n_0T}^k(\psi)\in \partial Z_0, \ \forall k\in N\}. |
Define \Phi_t:C_{\tau}^+\rightarrow C_{\tau}^+ by \Phi_t(\psi)(x, s) = \tilde{S}(x, t+s; \psi) , \forall\psi\in C_{\tau}^+ and \Phi_{n_0T}^k(\psi): = \tilde{S}(x, n_0T+s; \psi) for k\in N and (x, s)\in\bar{\Omega}\times[-\tau, 0] . It is easy to obtain that \Phi_t(Z_0)\in Z_0 for t > 0 . Let
E_0: = (\bar{S}^*, 0, 0, 0), \ E_1: = \{(\psi_S, \psi_1, 0, \psi_R) \}, \ E_2: = \{(\psi_S, 0, \psi_2, \psi_R)\}, |
and \bar{\omega}(\psi) denotes the omega limit set of the orbit \gamma^+: = \{\Phi_{n_0T}^k(\psi): \forall k\in N\} for \psi\in Z_{\partial} , we then have the following claims.
Claim 1. \underset {\psi\in Z_{\partial}}{\cup}\bar{\omega}(\psi) = E_0\cup E_2\cup E_2 .
For any \Phi_{n_0T}^k(\psi)\in Z_{\partial} , it can be see that \Phi_{n_0T}^k(\psi)\in Z_{\partial}, \ \forall k\in N . Then I_1(x, t;\psi)\equiv0 or I_2(x, t;\psi)\equiv0 for x\in \bar{\Omega} and t > 0 . Suppose, by contradiction, if there exists t_i > 0 such that I_i(x, t;\psi)\not \equiv0 on x\in \bar{\Omega}, \ i = 1, 2 . Then the strong positivity of V_i(t, s)(t > s) implies that I_i(x, t;\psi) > 0 for all t > t_i and x\in \bar{\Omega}, \ i = 1, 2 , which contradicts with the fact \Phi_{n_0T}^k(\psi)\in Z_{\partial} . If I_1(x, t;\psi)\equiv0 on (x, t)\in \bar{\Omega}\times R^+ , it follows from Theorem 3.7 that \bar{\omega}(\psi) = E_0\cup E_2 . If I_2(x, t;\psi)\equiv0 on (x, t)\in \bar{\Omega}\times R^+ . Similarly, one has \bar{\omega}(\psi) = E_0\cup E_1 . Therefore, Claim 1 holds.
Claim 2. E_0 is a uniformly weak repeller for Z_0 , in the sense that,
\underset {k\rightarrow \infty }{\limsup }\|\Phi_{n_0T}^k(\psi)-E_0|\ge \varepsilon_0, \ \forall \psi\in Z_0 |
for \varepsilon_0 > 0 . The proof of Claim 2 is similar to those in Theorem 3.4(3), so we omit it.
Claim 3. E_1 and E_2 is a uniformly weak repeller for Z_0 , in the sense that,
\underset {k\rightarrow \infty }{\limsup }\|\Phi_{n_0T}^k(\psi)-E_i|\ge \varepsilon_0, \ \forall \psi\in Z_0, \ i = 1, 2 |
for some \varepsilon_0 > 0 small enough. We only give the proof for E_1 , the proof of E_2 is similar. Due to Theorem 2.1 , there are B_1, B_2 and l_R\gg0 , such that
I_i(x, t;\phi)\le B_1\; (i = 1, 2), \ R(x, t;\phi)\le B_2 |
for t\ge l_RT+\tau . For sufficient small \varepsilon > 0 , we consider the following system:
\begin{equation} \begin{cases} \begin{split} \frac{ \partial \omega_2^{\varepsilon}}{ \partial t} = &D_2\Delta \omega_2^{\varepsilon}(x, t)-h_2(x, t)\omega_2^{\varepsilon}(x, t) \\ &+\int_{0}^{\tau _2} f_2(a)\int_{\Omega }\Gamma_2(x, y, t, t-a)\beta_2(y, t-a)\frac {\bar{S}^*(x, t)-\varepsilon}{\bar{S}^*(x, t)+B_1+B_2}\omega_2^{\varepsilon}(y, t-a)dyda, \\ &\ x\in \Omega , \ t > 0, \\ \frac{\partial \omega_2^{\varepsilon}}{ \partial n} = &0, \ x\in \partial \Omega , \ t > 0, \ i = 1, 2, \end{split} \end{cases} \end{equation} | (3.13) |
where \bar{S}^* is the positive periodic solution of (3.11) . Let \omega_2^{\varepsilon}(x, t;\psi_2) be the solution of (3.13) with initial data \omega_2^{\varepsilon}(x, s) = \psi _2(x, s), \ \psi _2\in Q^+, \ x\in \Omega, \ s\in [-\tau, 0] . Note \omega_{2, n_0T}^{\varepsilon}(\psi_2)(x, s) = \omega_2^{\varepsilon}(x, s+n_0T;\psi_2) for all x\in \Omega and s\in[-\tau _1, 0] . Define (\Psi_2^{\varepsilon})^{n_0}:Q^+\rightarrow Q^+ by (\Psi_2^{\varepsilon})^{n_0}(\psi_2) = \omega_{2, n_0T}^{\varepsilon}(\psi_2) . Let \hat{r}_{\varepsilon}^2 and (\hat{r}_{\varepsilon}^2)^{n_0} be the spectral radius of \Psi_2^{\varepsilon} and (\Psi_2^{\varepsilon})^{n_0} , respectively. It is easy to prove that (\Psi_2^{\varepsilon})^{n_0} is compact, strongly positive operator. According to [15,Theorem 7.1], we get that (\Psi_2^{\varepsilon})^{n_0} admits a positive and simple eigenvalue (\hat{r}_{\varepsilon}^2)^{n_0} and a positive eigenfunction \varphi_2 satisfying (\Psi_2^{\varepsilon})^{n_0} = (\hat{r}_{\varepsilon}^2)^{n_0}\varphi_2 . Since R_0^2 > 1 , it follows from Theorem 3.5 that \rho_2^0 > 1 , then there exists a sufficient small number \varepsilon_1 > 0 such that r_{\varepsilon}^2 > 1 for any \varepsilon\in (0, \varepsilon_1) .
By the continuous dependence of solution on initial value, there exists \varepsilon_0\in (0, \varepsilon_1) such that
\begin{equation} \|\Phi_T^k(\psi)-E_1\| < \bar{\varepsilon}, \ \forall x\in \bar{\Omega}, \ t\in [0, T], \end{equation} | (3.14) |
if
\|\phi(x, s)-E_1\| < \varepsilon_0, \ x\in \bar{\Omega}, \ s\in [-\tau, 0]. |
Suppose, by contradiction, there exists \psi_0\in W_0 such that
\underset {k\rightarrow \infty }{\limsup }\|\Phi_{n_0T}^k(\psi)-E_1\| < \varepsilon_0. |
That is, there is k_0\in N such that
\bar{S}^*-\bar{\varepsilon} < S(x, t;\psi_0) < \bar{S}^*+\bar{\varepsilon}; \ 0 < I_1(x, t;\psi_0) < B_1; |
and
0 < I_2(x, t;\psi_0) < \bar{\varepsilon}; \ 0 < R(x, t;\psi_0) < B_2 |
for all k\ge k_0 . Therefore, for I_2 -equation of (2.6) , we have
\begin{equation} \begin{split} \frac{ \partial I_2(x, t)}{ \partial t}\ge &D_2\Delta I_2(x, t)-h_2(x, t)I_2(x, t)\\ &+\int_{0}^{\tau _2} f_1(a)\int_{\Omega }\Gamma_2(x, y, t, t-a)\beta_2(y, t-a)\frac{\bar{S}^*(y, t-a)-\bar{\varepsilon}}{\bar{S}^*+B_1+B_2}I_2(y, t-a)dyda \end{split} \end{equation} | (3.15) |
for x\in \Omega and t > (k_0+1)n_0T . Since
I_2(x, t;\psi_0) > 0, \ \forall x\in\bar{ \Omega} , \ t > (k_0+1)n_0T, |
there is some \kappa > 0 , such that
I_2(x, (k_0+1)n_0T+s;\psi_0)\ge \kappa\varphi_2(x, s), \ \forall x\in \bar{\Omega}, \ s\in [-\tau_2, 0]. |
By (3.15) and the comparison principle, we have
I_2(x, t+s;\psi_0)\ge \omega_2^{\varepsilon}(x, t-(k_0+1)n_0T+s;\varphi_2), \ \forall x\in \bar{\Omega} , \ t > (k_0+1)n_0T. |
Therefore, we have
\begin{equation} I_2(x, kn_0T+s;\psi_0)\ge \kappa \omega_2^{\varepsilon}(x, k-(k_0+1)n_0T+s;\varphi_2) = \kappa(\hat{r}_{\varepsilon}^2)^{(k-k_0-1)n_0}\varphi_2(x, s), \end{equation} | (3.16) |
where k\ge k_0+1, \ s\in [-\tau_2, 0] . Since \varphi_2(x, s) > 0 for (x, s)\in \bar{\Omega}\times [-\tau_2, 0] , there is (x_2, s_2)\in \bar{\Omega}\times [-\tau_2, 0] such that \varphi_2(x_2, s_2) > 0 . It follows from (r_{\varepsilon}^2)^{n_0} > 1 that I_2(x_2, kn_0T+s_2;\psi_0)\rightarrow +\infty as k\rightarrow \infty , which contradicts to I_2(x, t;\psi_0)\in (0, \bar{\varepsilon}) .
Let \Theta: = E_0\cup E_1\cup E_2 , W^S(\Theta) be the stable set of \Theta . In conclusion, W^S(\Theta) = Z_{\partial} ; \Theta is an isolated invariant set for \Phi_{n_0T} in Z_0 , W^S(\Theta)\cap Z_0 = Z_{\partial}\cap Z_0 = \varnothing . According to [10,Theorem 1.3.1] and [10,Remark 1.3.1], there exists \bar{\sigma} > 0 such that \inf d(\omega(\psi), \partial Z_0)\ge \bar{\sigma} for all \psi\in Z_0 . That is, \underset {t\rightarrow \infty }{\liminf }d(\Phi_{n_0T}^k, \partial Z_0)\ge \bar{\sigma} for any \psi\in Z_0 . Therefore, \Phi_{n_0T}:C_{\tau } ^+\rightarrow C_{\tau}^+ is uniformly persistent with respect to (Z_0, \partial Z_0) . Similar to Theorem 2.1 , it can be proved that the solution \tilde{S}(x, t;\psi) of (2.6) is globally bounded for any \psi\in D_{\tau}^+ . Therefore, \Phi_{n_0T}:C_{\tau}^+\rightarrow C_{\tau}^+ is point dissipative. It is easy to prove that \Phi_{n_0T} is compact on Z_0 for n_0T > \tau_1 . It then follows from [40,Section 1.1] that the compact map \Phi_{n_0T} is an \alpha- contraction of order 0 , and an \alpha- contraction of order 0 is \alpha- condensing. Then according to [23,Theorem 4.5], we obtain that \Phi_{n_0T}: Z_0\rightarrow Z_0 admits a compact global attractor N_0 .
Similar to the proof of [22,Theroem 4.1], let P:C_{\tau }^+\rightarrow [0, +\infty) by
P(\psi) = \min \{ \mathop {\min }\limits_{x \in \bar \Omega } {\psi _1}(x,0),\mathop {\min }\limits_{x \in \bar \Omega } {\psi _2}(x,0)\} , \ \forall \psi\in C_{\tau}^+. |
Since \Phi_{n_0T}(N_0) = N_0 , we have \psi_i(\cdot, 0) > 0 for any \psi \in N_0 . Let B_0: = \underset {t\in [0, n_0T]}{\cup}\Phi_t(N_0) , then B_0\subseteq Z_0 . In addition, we get \underset {t\rightarrow \infty }{\lim}d(\Phi_t(\psi), B_0) = 0 for all \psi\in Z_0 . Since B_0 is a compact subset of Z_0 . We have \underset {\psi\in B_0}{\min}P(\psi) > 0 . Thus, there exists \eta > 0 such that \underset {t\rightarrow \infty }{\liminf}I_1(\cdot, t; \psi)\ge \eta .
In this subsection, under the condition that the invasion numbers on two strains are greater than 1, it is proved that two strains will always persist uniformly. By the arguments similar to those in the proof of Theorems 3.7 and 3.2, we have the following observations.
Theorem 3.8. Suppose that \tilde{S}(x, t;\psi) = (S(x, t;\psi), I_1(x, t;\psi), I_2(x, t;\psi), R(x, t;\psi)) is the solution of (2.6) with initial data \psi = (\psi_S, \psi_1, \psi_2, \psi_R)\in C_{\tau} . If R_0^1 > 1 > R_0^2 and \psi_1(\cdot, 0)\not \equiv0 , then
\underset {t\rightarrow \infty }{\lim}I_2(x, t;\psi) = 0, |
and there is P > 0 such that
\begin{equation} \underset {t\rightarrow \infty }{\liminf}I_1(x, t;\psi)\ge P, \end{equation} | (3.17) |
uniformly for x\in \bar{\Omega} .
Theorem 3.9. Suppose that R_0^1 > 1 = R_0^2 and \beta_2(x, t) > 0 on (x, t)\in \bar{\Omega}\times [0, \infty) . If C_{\tau}^+ satisfies \psi_1(\cdot, 0)\not \equiv0 , then we have
\underset {t\rightarrow \infty }{\lim}I_2(x, t;\psi) = 0, |
and there is P > 0 such that
\underset {t\rightarrow \infty }{\liminf}I_1(x, t;\psi)\ge P, |
uniformly for x\in \bar{\Omega} .
Theorem 3.10. Suppose that R_0^2 > 1 > R_0^1 , if \psi\in C_{\tau}^+ satisfies \psi_2(\cdot, 0)\not \equiv0 , then we have
\underset {t\rightarrow \infty }{\lim}I_1(x, t;\psi) = 0, |
and there is P > 0 such that
\begin{equation} \underset {t\rightarrow \infty }{\liminf}I_2(x, t;\psi)\ge P, \end{equation} | (3.18) |
uniformly for x\in \bar{\Omega} .
Theorem 3.11. Suppose that R_0^2 > 1 = R_0^1 and \beta_1(x, t) > 0 on (x, t)\in \bar{\Omega}\times [0, \infty) . If \psi\in C_{\tau}^+ satisfies \psi_2(\cdot, 0)\not \equiv0 , then we have
\underset {t\rightarrow \infty }{\lim}I_1(x, t;\psi) = 0, |
and there is P > 0 such that
\underset {t\rightarrow \infty }{\liminf}I_2(x, t;\psi)\ge P, |
uniformly for x\in \bar{\Omega} .
Finally, we show that the periodic solution (S^*, 0, 0, 0) of (2.6) is globally attractive under some conditions.
Theorem 3.12. Suppose that R_0^i < 1 for i = 1, 2 . Then the periodic (S^*, 0, 0, 0) of (2.6) is globally attractive.
Proof. Due to R_0^i < 1, \ i = 1, 2 , similar to Theorem 3.4, one has
\underset {t\rightarrow \infty }{\lim}I_i(x, t; \psi) = 0, \ \forall x\in \bar{\Omega}, \ \psi\in C_{\tau}^+, \ i = 1, 2. |
By using the theory of chain transitive sets, we get
\underset {t\rightarrow \infty }{\lim}S(x, t; \psi) = S^*(x, t), \forall x\in \bar{\Omega}, \ \psi\in C_{\tau}^+. |
Therefore
\underset {t\rightarrow \infty }{\lim }\parallel( S(\cdot , t;\psi), I_1(\cdot , t;\psi) , I_2(\cdot , t;\psi), R(\cdot , t;\psi) )-\left(S^*(\cdot, t), 0, 0, 0\right)\parallel = 0. |
That is (S^*, 0, 0, 0) is globally attractive.
Theorem 3.13. Suppose that R_0^i = 1 and \beta_i(x, t) > 0 on \bar{\Omega}\times[0, \infty) for both i = 1, 2 . Then the periodic (S^*, 0, 0, 0) of (2.6) is globally attractive.
Proof. The proof is similar to Theorem 3.12 by using Theorem 3.2.
Combining Theorem 3.12 with Theorem 3.13, furthermore, we have the following conclusion.
Theorem 3.14. If R_0^i < 1, \ R_0^j = 1 and \beta_j(x, t) > 0 on (x, t)\in \bar{\Omega}\times[0, \infty), \ i, j = 1, 2, \ i\neq j , then the periodic (S^*, 0, 0, 0) of (2.6) is globally attractive.
In this paper, we proposed and investigated a two-strain SIRS epidemic model with distributed delay and spatiotemporal heterogeneity. The model is well suitable for simulating the pathogen mutation which is widely founded in variety viral infectious diseases. We have to remark that when the spatiotemporal heterogeneity and distributed delay are incorporated simultaneously, the analysis for the model becomes more difficult. To overcome these difficulties, we used the theory of chain transitive sets and persistence. After introducing the basic reproduction number R_0^i and the invasion number \hat{R}_0^i for each strain i , i = 1, 2 , we established the threshold dynamics for single-strain model and two-strain model, respectively. For the single-strain case, the threshold dynamics results shows that the basic reproduction number R_0^i is a threshold to determine whether the strain i can be persistent. In addition, in such case, we obtained a sufficient condition for the global attraction of the disease free equilibrium when R_0^i = 1 , i = 1, 2 . Under the condition that two strains is incorporated, we showed that if both of the invasion numbers \hat{R}_0^i are all larger than unit, then the two strains will be persistent uniformly. However, if only one of the reproduction numbers is larger than unit, that is, the other is less than unit, then the strain with larger reproduction number persists, while the strain with the smaller reproduction number dies out. This phenomenon is so called "competitive exclusion"[33]. Further, if both of the two reproduction numbers R_0^i are all less than unit, then the corresponding disease free equilibrium is globally attractive.
Apparently, the dynamical properties of the two-strain model are much more complicated than that of the single-strain case. The most fascinating phenomenon is the appearance of "competitive exclusion" in the two strain model. Generally speaking, the strain with highest basic reproduction number will eliminate the other strain. As is well known, in reality, proper vaccination is a critical for the prevention and control of the most viral infectious disease. Thereby, with the mutating of viruses, the main thing is to ensure the vaccine as safe and effective as possible. However, it is easy to make vaccine administration error. Although some improperly administered vaccines may be valid, sometimes such errors increases the possibility of vaccine recipients being unprotected against viral infection. This paper incorporated the distributed delay, seasonal factor effects and spatial heterogeneity into a two-strain SIRS simultaneously, so the model is more in line with reality. Further, based on these realistic factors, we obtained some valuable results for proper vaccination to viral infection theoretically.
The first author was supported by the innovation fund project for colleges and universities of Gansu Province of China (2021B-254), the second author was supported by NSF of China (12071193) and Natural Science Foundation of Gansu Province of China (21JR7RA549).
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
[1] |
Z. Achouri, N. Amroun, A. Benaissa, The Euler-Bernoulli beam equation with boundary dissipation of fractional derivative, Math. Method. Appl. Sci., 40 (2017), 3837–3854. https://doi.org/10.1002/mma.4267 doi: 10.1002/mma.4267
![]() |
[2] |
H. Atoui, A. Benaissa, Optimal energy decay for a transmission problem of waves under a nonlocal boundary control, Taiwanese J. Math., 23 (2019), 1201–1225. https://doi.org/10.11650/tjm/190108 doi: 10.11650/tjm/190108
![]() |
[3] |
M. R. Alaimia, N. E. Tatar, Blow up for the wave equation with a fractional damping, J. Appl. Anal., 11 (2005), 133–144. https://doi.org/10.1515/JAA.2005.133 doi: 10.1515/JAA.2005.133
![]() |
[4] |
W. Arendt, C. J. K. Batty, Tauberian theorems and stability of one-parameter semigroups, T. Am. Math. Soc., 306 (1988), 837–852. https://doi.org/10.2307/2000826 doi: 10.2307/2000826
![]() |
[5] |
R. L. Bagley, P. J. Torvik, A theoretical basis for the application of fractional calculus to viscoelasticity, J. Rheol., 27 (1983), 201–210. https://doi.org/10.1122/1.549724 doi: 10.1122/1.549724
![]() |
[6] |
L. R. Bagley, P. J. Torvik, Fractional calculus: A different approach to the analysis of viscoelastically damped structures, AIAA J., 21 (1983), 741–748. https://doi.org/10.2514/3.8142 doi: 10.2514/3.8142
![]() |
[7] |
P. J. Torvik, R. L. Bagley, On the appearance of the fractional derivative in the behavior of real material, J. Appl. Mech., 51 (1984), 294–298. https://doi.org/10.1115/1.3167615 doi: 10.1115/1.3167615
![]() |
[8] |
A. Beniani, N. Bahri, R. Alharbi, K. Bouhali, K. Zennir, Stability for weakly coupled wave equations with a general internal control of diffusive type, Axioms, 12 (2023), 48. https://doi.org/10.3390/axioms12010048 doi: 10.3390/axioms12010048
![]() |
[9] |
Y. Bidi, A. Beniani, K. Bouhali, K. Zennir, H. M. Elkhair, E. I. Hassan, et al., Local existence and blow-up of solutions for wave equation involving the fractional Laplacian with nonlinear source term, Axioms, 12 (2023), 343. https://doi.org/10.3390/axioms12040343 doi: 10.3390/axioms12040343
![]() |
[10] |
A. Borichev, Y. Tomilov, Optimal polynomial decay of functions and operator semigroups, Math. Ann., 347 (2010), 455–478. https://doi.org/10.1007/s00208-009-0439-0 doi: 10.1007/s00208-009-0439-0
![]() |
[11] | Y. Lyubich, P. Vu, Asymptotic stability of linear differential equations in Banach spaces, Stud. Math., 88 (1988), 37–42. |
[12] |
T. F. Ma, H. P. Oquendo, A transmission problem for beams on nonlinear supports, Bound. Value Probl., 2006 (2006), 75107. https://doi.org/10.1155/BVP/2006/75107 doi: 10.1155/BVP/2006/75107
![]() |
[13] | M. Mainardi, E. Bonetti, The applications of real order derivatives in linear viscoelasticity, In: Progress and Trends in Rheology II, 1988. https://doi.org/10.1007/978-3-642-49337-9_11 |
[14] |
B. Mbodje, Wave energy decay under fractional derivative controls, IAM J. Math. Control I., 23 (2006), 237–257. https://doi.org/10.1093/imamci/dni056 doi: 10.1093/imamci/dni056
![]() |
[15] |
B. Mbodje, G. Montseny, Boundary fractional derivative control of the wave equation, IEEE T. Automat. Contr., 40 (1995), 378–382. https://doi.org/10.1109/9.341815 doi: 10.1109/9.341815
![]() |
[16] | I. Podlubny, Fractional differential equations, 1999. |
[17] |
J. Prüss, On the spectrum of C_0-semigroups, T. Am. Math. Soc., 284 (1984), 847–857. https://doi.org/10.2307/1999112 doi: 10.2307/1999112
![]() |
[18] |
J. E. Muñoz Rivera, H. P. Oquendo, The transmission problem of viscoelastic waves, Acta Appl. Math., 62 (2000), 1–21. https://doi.org/10.1023/A:1006449032100 doi: 10.1023/A:1006449032100
![]() |
[19] | S. G. Samko, A. A. Kilbas, O. I. Marichev, Fractional integrals and derivatives, 1993. |
[20] |
A. Soufyane, Stabilisation de la poutre de Timoshenko, C. R. Acad. Sci. I, 328 (1999), 731–734. https://doi.org/10.1016/S0764-4442(99)80244-4 doi: 10.1016/S0764-4442(99)80244-4
![]() |
[21] |
C. Q. Xu, S. P. Yung, L. K. Li, Stabilization of the wave system with input delay in the boundary control, ESAIM Contr. Optim. Ca., 12 (2006), 770–785. https://doi.org/10.1051/cocv:2006021 doi: 10.1051/cocv:2006021
![]() |
1. | Zakaria Yaagoub, Karam Allali, Global Stability of Multi-Strain SEIR Epidemic Model with Vaccination Strategy, 2023, 28, 2297-8747, 9, 10.3390/mca28010009 |