In this paper, a two-strain SIRS epidemic model with distributed delay and spatiotemporal heterogeneity is proposed and investigated. We first introduce the basic reproduction number $ R_0^i $ and the invasion number $ \hat{R}_0^i\; (i = 1, 2) $ for each strain $ i $. Then the threshold dynamics of the model is established in terms of $ R_0^i $ and $ \hat{R}_0^i $ by using the theory of chain transitive sets and persistence. It is shown that if $ \hat{R}_0^i > 1\; (i = 1, 2) $, then the disease in two strains is persist uniformly; if $ R_0^i > 1\geq R_0^j\; (i\neq j, i, j = 1, 2) $, then the disease in $ i $-th strain is uniformly persist, but the disease in $ j $-th strain will disappear; if $ R_0^i < 1 $ or $ R_0^i = 1\; (i = 1, 2) $ and $ \beta_i(x, t) > 0 $, then the disease in two strains will disappear.
Citation: Jinsheng Guo, Shuang-Ming Wang. Threshold dynamics of a time-periodic two-strain SIRS epidemic model with distributed delay[J]. AIMS Mathematics, 2022, 7(4): 6331-6355. doi: 10.3934/math.2022352
[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 |
In this paper, a two-strain SIRS epidemic model with distributed delay and spatiotemporal heterogeneity is proposed and investigated. We first introduce the basic reproduction number $ R_0^i $ and the invasion number $ \hat{R}_0^i\; (i = 1, 2) $ for each strain $ i $. Then the threshold dynamics of the model is established in terms of $ R_0^i $ and $ \hat{R}_0^i $ by using the theory of chain transitive sets and persistence. It is shown that if $ \hat{R}_0^i > 1\; (i = 1, 2) $, then the disease in two strains is persist uniformly; if $ R_0^i > 1\geq R_0^j\; (i\neq j, i, j = 1, 2) $, then the disease in $ i $-th strain is uniformly persist, but the disease in $ j $-th strain will disappear; if $ R_0^i < 1 $ or $ R_0^i = 1\; (i = 1, 2) $ and $ \beta_i(x, t) > 0 $, then the disease in two strains will disappear.
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:
$ \begin{equation} \begin{cases} \begin{split} \frac{ \partial S(x, t)}{ \partial t}& = d_S\Delta S(x, t)-\frac{\left(\beta_1(x)I_1(x, t)+\beta_2(x)I_2(x, t)\right)S(x, t)}{S(x, t)+I_1(x, t)+I_2(x, t)}\\ &\ \ \ +r_1(x, t)I_1(x, t)+r_2(x, t)I_2(x, t), \\ \frac{ \partial I_1(x, t)}{ \partial t}& = d_1\Delta I_1(x, t)+\frac{\beta_1(x)S(x, t)I_1(x, t)}{S(x, t)+I_1(x, t)+I_2(x, t)}-r_1(x, t)I_1(x, t), \\ \frac{ \partial I_2(x, t)}{ \partial t}& = d_2\Delta I_2(x, t)+\frac{\beta_2(x)S(x, t)I_2(x, t)}{S(x, t)+I_1(x, t)+I_2(x, t)}-r_2(x, t)I_2(x, t). \\ \end{split} \end{cases} \end{equation} $ | (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 $ R_0^i = 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 $ R_0^i $ and the invasion number $ \hat{R}_0^i\; (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 $ \Omega \in R^n $ denote the spatial habitat with smooth boundary $ \partial \Omega $. 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\ge 0 $ and at position $ x $, and time $ t $ by $ E_1 (x, a, t) $ and $ E_2 (x, a, t) $, respectively. By a standard argument on structured population and spatial diffusion (see e.g., [28]), we obtain
$ \begin{equation} \begin{cases} \left(\frac{ \partial }{ \partial t}+\frac{ \partial }{ \partial a}\right)E_i (x, a, t) = D_i\Delta E_i-\left(\delta _i (x, a, t)+r_i(x, a, t)+d(x, t)\right)E_i (x, a, t), \ x \in \Omega, \ a > 0, \ t > 0\\ \frac{\partial E_i (x, a, t)}{\partial n} = 0, \ x \in \partial \Omega, \ a > 0, \ t > 0, i = 1, 2, \end{cases} \end{equation} $ | (2.1) |
where $ d(x, t) $ is the natural death rate at location $ x $ and time $ t $; $ r_i(x, a, t) $ and $ \delta_i (x, a, t) $ represent the recovery rates and mortality rates induced by the disease of the $ i $-th infectious classes with infection age $ a\ge 0 $ at position $ x $ and time $ t $; the constants $ D_i $ 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 $ L_i(x, t) $, two infective groups $ I_i(x, t) $, and the recovered group $ R(x, t) $, $ i = 1, 2 $. Let $ N(x, t) = S(x, t)+\sum_{i = 1, 2}\left(L_i(x, t)+I_i(x, t)\right)+R(x, t) $. We assume that only a portion of recovered individuals would be permanently immune to the virus. Let $ \alpha (x, a, t) $ be the loss of immunity rate with infection age $ a\ge 0 $ at position $ x $ and time $ t $. In order to simplify the model reasonably, we further suppose that
$ \delta _i (x, a, t) = \delta _i (x, t), \ r_i(x, a, t) = r_i(x, t), \ \alpha (x, a, t) = \alpha (x, t), \ \forall x\in \Omega, \ a, t\ge 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\in (0, \tau _i] $, where the positive constant $ \tau _i $ is the maximum incubation period of $ i $-th strain, $ i = 1, 2 $. Let $ f_i(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 $ F_i(a) = \int_{0}^a f_i(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 $ F_i(a)\ge 0 $ for $ a\in (0, \tau _i) $, $ F_i(a)\equiv1 $ for $ a\in [\tau _i, +\infty) $, $ i = 1, 2 $, and
$ \begin{equation} \begin{split} &L_i(x, t) = \int_{0}^{\tau _i}\left(1-F_i\left(a\right)\right)E_i (x, a, t)da, \\ &I_i(x, t) = \int_{0}^{\tau _i} F_i(a)E_i (x, a, t)da+\int_{\tau _i}^{+\infty }E_i (x, a, t)da, \ i = 1, 2. \end{split} \end{equation} $ | (2.2) |
Let
$ I_{i, 1}(x, t) = \int_{0}^{\tau _i} F_i(a)E_i (x, a, t)da, \ I_{i, 2}(x, t) = \int_{\tau _i}^{+\infty }E_i (x, a, t)da. $ |
It then follows that
$ \begin{align*} \frac{ \partial L_i(x, t)}{ \partial t} = &D_i\Delta L_i (x, t)-\left(\delta _i (x, t)+r_i(x, t)+d(x, t)\right)L_i (x, t)\\ &-\int_{0}^{\tau _i}f_i(a)E_i (x, a, t)da+E_i (x, 0, t), \end{align*} $ |
and
$ \begin{align*} \frac{ \partial I_{i, 1}(x, t)}{ \partial t} = &D_i\Delta I_{i, 1}(x, t)-\left(\delta _i (x, t)+r_i(x, t)+d(x, t)\right)I_{i, 1}(x, t)\\ &+\int_{0}^{\tau _i}f_i(a)E_i (x, a, t)da-E_i (x, \tau _i, t), \end{align*} $ |
$ \frac{ \partial I_{i, 2}(x, t)}{ \partial t} = D_i\Delta I_{i, 2}(x, t)-\left(\delta _i (x, t)+r_i(x, t)+d(x, t)\right)I_{i, 2}(x, t)+E_i (x, \tau _i, t)-E_i (x, \infty, t), $ |
where $ i = 1, 2 $. Biologically, we assume $ E_i (x, \infty, t) = 0\; (i = 1, 2) $. Then we have
$ \frac{ \partial I_i(x, t)}{ \partial t} = D_i\Delta I_i(x, t)-\left(\delta _i (x, t)+r_i(x, t)+d(x, t)\right)I_i(x, t)+\int_{0}^{\tau _i}f_i(a)E_i (x, a, t)da. $ |
Denote the infection rate by $ \beta_i(x, t)\geq0 $. Due to the fact that the contact of susceptible and infectious individuals yields the new infected individuals, we take $ E_i (x, 0, t) $ as follows:
$ E_i (x, 0, t) = \frac{\beta_i(x, t)S(x, t)I_i(x, t)}{S(x, t)+I_1(x, t)+I_2(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:
$ \frac{ \partial N(x, t)}{ \partial t} = D_N\Delta N(x, t)+\mu (x, t)-d(x, t)N(x, t), $ |
where $ d(x, t) $ is the natural death rate, $ \mu (x, t) $ is the recruiting rate, and $ D_N $ denotes the diffusion rate. In conclusion, the disease dynamics is expressed by the following system:
$ \begin{equation} \begin{cases} \begin{split} \frac{ \partial S(x, t)}{ \partial t}& = D_S\Delta S(x, t)+\mu(x, t)-d(x, t)S(x, t)+\alpha(x, t)R(x, t) \\ &-\frac{\beta_1(x, t)S(x, t)I_1(x, t)}{S(x, t)+I_1(x, t)+I_2(x, t)+R(x, t)}-\frac{\beta_2(x, t)S(x, t)I_2(x, t)}{S(x, t)+I_1(x, t)+I_2(x, t)+R(x, t)}, \\ \frac{ \partial L_i(x, t)}{ \partial t}& = D_i\Delta L_i (x, t)-\left(\delta _i (x, t)+r_i(x, t)+d(x, t)\right)L_i(x, t) \\ &+\frac{\beta_i(x, t)S(x, t)I_i(x, t)}{S(x, t)+I_1(x, t)+I_2(x, t)+R(x, t)}-\int_{0}^{\tau _i} f_i(a)E_i (x, a, t)da, \\ \frac{ \partial I_i(x, t)}{ \partial t}& = D_i\Delta I_i(x, t)-\left(\delta _i (x, t)+r_i(x, t)+d(x, t)\right)I_i(x, t)+\int_{0}^{\tau _i} f_i(a)E_i (x, a, t)da, \\ \frac{ \partial R(x, t)}{ \partial t}& = D_R\Delta R(x, t)+r_1(x, t)(L_1(x, t)+I_1(x, t)) +r_2(x, t)(L_2(x, t)+I_2(x, t)) \\ &-d(x, t)R(x, t)-\alpha(x, t)R(x, t), \ i = 1, 2. \end{split} \end{cases} \end{equation} $ | (2.3) |
We make the following basic assumption:
(H) $ D_S, D_i, D_R > 0, \ i = 1, 2 $, the functions $ d(x, t), \mu(x, t), \alpha(x, t), \beta_i(x, t), \delta _i (x, t), r_i(x, t) $ are Hölder continuous and nonnegative nontrivial on $ \bar{\Omega} \times R $, and periodic in time $ t $ with the same period $ T > 0 $. Moreover, $ d(x, t) > 0 $, $ x\in \partial \Omega, \ t > 0 $.
For the sake of simplicity, we let $ h_i(x, t) = \delta _i (x, t)+r_i(x, t)+d(x, t), \ i = 1, 2 $. In order to determine $ E_i (x, a, t) $, let $ V_i(x, a, \xi) = E_i (x, a, a+\xi) $, $ \forall\xi\ge 0 $, $ i = 1, 2 $. By a similar idea as that in [36], we have
$ \begin{align*} \begin{cases} \frac{ \partial V_i(x, a, \xi )}{ \partial a} = D_i\Delta V_i (x, a, \xi )-h_i(x, t)V_i(x, a, \xi ), \\ V_i(x, 0, \xi ) = E_i (x, 0, \xi ) = \frac{\beta_i(x, \xi )S(x, \xi )I_i(x, \xi)}{S(x, \xi)+I_1(x, \xi)+I_2(x, \xi)+R(x, \xi)}, \ i = 1, 2. \end{cases} \end{align*} $ |
Let $ \Gamma_i(x, y, t, s) $ with $ x, y\in \Omega $ and $ t > s\ge 0 $ be the fundamental solution associated with the partial differential operator $ \partial t-D_i\Delta -h_i(x, t)(i = 1, 2) $. Then we have
$ \begin{equation} V_i(x, a, \xi ) = \int_{\Omega }\Gamma_i(x, y, \xi +a, \xi )\frac{\beta_i(y, \xi)S(y, \xi)I_i(y, \xi)}{S(y, \xi)+I_1(y, \xi)+I_2(y, \xi)+R(y, \xi)}dy. \end{equation} $ | (2.4) |
According to the periodicity of $ h_i $ and $ \beta_i $, $ \Gamma_i(x, y, t, s) $ is periodic, that is, $ \Gamma_i(x, y, t+T, s+T) = \Gamma_i(x, y, t, s), \ \forall x, y\in \Omega, \ t > s\ge 0 $, $ i = 1, 2 $. It follows from $ E_i(x, a, t) = V_i(x, a, t-a) $ that
$ \begin{equation} E_i(x, a, t) = \int_{\Omega }\Gamma_i(x, y, t, t-a)\frac{\beta_i(y, t-a)S(y, t-a)I_i(y, t-a)}{S(y, t-a)+I_1(y, t-a)+I_2(y, t-a)+R(y, t-a)}dy. \end{equation} $ | (2.5) |
Substituting $ (2.5) $ into $ (2.3) $, and dropping the $ L_i $ equations from $ (2.3) $ (since they are decoupled from the other equations), we obtain the following system:
$ \begin{equation} \begin{cases} \begin{split} \frac{ \partial S(x, t)}{ \partial t}& = D_S\Delta S(x, t)+\mu(x, t)-d(x, t)S(x, t)+\alpha(x, t)R(x, t) \\ &-\frac{\beta_1(x, t)S(x, t)I_1(x, t)}{S(x, t)+I_1(x, t)+I_2(x, t)+R(x, t)}-\frac{\beta_2(x, t)S(x, t)I_2(x, t)}{S(x, t)+I_1(x, t)+I_2(x, t)+R(x, t)}, \\ \frac{ \partial I_i(x, t)}{ \partial t}& = D_i\Delta I_i(x, t)-\left(\delta _i (x, t)+r_i(x, t)+d(x, t)\right)I_i(x, t)+\int_{0}^{\tau _i} f_i(a)\\ &\cdot\int_{\Omega }\Gamma_i(x, y, t, t-a)\frac{\beta_i(y, t-a)S(y, t-a)I_i(y, t-a)}{S(y, t-a)+I_1(y, t-a)+I_2(y, t-a)+R(y, t-a)}dyda, \\ \frac{ \partial R(x, t)}{ \partial t}& = D_R\Delta R(x, t)+r_1(x, t)I_1(x, t)+r_2(x, t)I_2(x, t)-d(x, t)R(x, t) \\ &-\alpha(x, t)R(x, t), \ i = 1, 2. \end{split} \end{cases} \end{equation} $ | (2.6) |
Set $ \tau = \max\{\tau _1, \tau _2\} > 0 $. Let $ X: = C\left(\bar{\Omega }, R^4\right) $ be the Banach space with a supremum norm $ \|\cdot\|_X $. Let $ C_\tau: = C([-\tau, 0], X) $ be a Banach space with the norm $ \|{\phi }\| = \underset {\theta \in [-\tau, 0]}{\max}\|{\phi (\theta)\|}_X, \ \forall \phi\in C_\tau $. Define $ X^+: = C\left(\bar{\Omega }, R_+^4\right) $, $ C_\tau ^+: = C([-\tau, 0], X^+) $, the $ (X, X^+) $ and $ (C_\tau, C_\tau ^+) $ are strongly ordered spaces. For $ \sigma > 0 $ and a given function $ u(t): [-\tau, \sigma]\rightarrow X $, we denote $ u_t\in C_\tau $ by
$ u_t(\theta) = u(t+\theta), \ \forall \theta \in [-\tau, 0] . $ |
Similarly, define $ Y = C\left(\bar{\Omega }, R\right) $ and $ Y^+ = C\left(\bar{\Omega }, R^+\right) $. Furthermore, we consider the following system:
$ \begin{equation} \begin{cases} \frac{ \partial \omega (x, t)}{ \partial t} = D_S\Delta \omega (x, t)-d(x, t)\omega (x, t), \ x\in \Omega, \ t > 0, \\ \frac{ \partial \omega (x, t)}{ \partial t} = 0, \ \ x\in \partial \Omega, \ t > 0, \\ \omega (x, 0) = \phi _S(x), \ x\in \Omega , \ \phi _S\in Y^+. \end{cases} \end{equation} $ | (2.7) |
By the arguments in [15], Eq (2.7) exists an evolution operator $ V_S(t, s):Y_+\longrightarrow Y_+ $ for $ 0\le s\le t $, which satisfies $ V_S(t, t) = I, \ V_S(t, s)V_S(s, \rho) = V_S(t, \rho), \ 0\le \rho \le s\le t, \ V_S(t, 0)\phi_S = \omega (x, t;\phi_S), \ x\in \Omega, \ t\ge 0, \ \phi _S\in Y_+ $, where $ \omega (x, t;\phi_S) $ is the solution of (2.7).
Consider the following periodic system:
$ \begin{equation} \begin{cases} \frac{ \partial \bar {\omega} _i(x, t)}{ \partial t} = D_i\Delta \bar {\omega} _i(x, t)-h_i(x, t)\bar {\omega} _i(x, t)), &x\in \Omega, \ t > 0, \\ \frac{ \partial \bar {\omega} _i(x, t)}{ \partial n} = 0, & x\in \partial \Omega, \ t > 0, \\ \bar {\omega} _i(x, 0) = \phi _i(x), &x\in \Omega , \ \phi _i\in Y^+. \end{cases} \end{equation} $ | (2.8) |
and
$ \begin{equation} \begin{cases} \frac{ \partial \tilde {\omega} _R(x, t)}{ \partial t} = D_R\Delta \tilde {\omega} _R(x, t)-k(x, t)\tilde {\omega} _R(x, t)), &x\in \Omega, \ t > 0, \\ \frac{ \partial \tilde {\omega} _R(x, t)}{ \partial t} = 0, &x\in \partial \Omega, \ t > 0, \\ \tilde {\omega} _R(x, 0) = \phi _R(x), &x\in \Omega , \ \phi _R\in Y^+, \end{cases} \end{equation} $ | (2.9) |
where $ k(x, t) = \alpha(x, t)+d(x, t) $. Let $ V_i(t, s) $, $ i = 1, 2 $, and $ V_R(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 $ V_S(t+T, s+T) = V_S(t, s), \ V_i(t+T, s+T) = V_i(t, s) $ and $ V_R(t+T, s+T) = V_R(t, s), \ t\ge s\ge 0 $. In addition, for any $ t, s\in R $ and $ s < t $. $ V_S(t, s) $, $ V_i(t, s) $ and $ V_R(t, s) $ are compact, analytic and strongly positive operators on $ Y_+ $. It then follows from [9,Theorem 6.6] that there exist constants $ Q\geq1 $, $ Q_i\geq1 $ and $ c_0, c_i\in R\; (i = 1, 2) $ such that
$ \|V_S(t, s)\|, \|V_R(t, s)\|\le Qe^{-c_0(t-s)}, \ \|V_i(t, s)\|\le Q_ie^{-c_i(t-s)}, \ \forall t\ge s, \ i = 1, 2. $ |
Let $ c_i^*: = \bar{\omega }(V_i) $, where
$ \bar{\omega }(V_i) = \inf \{\omega |\exists M\ge 1: \ \forall s\in R, \ t\ge 0, ||V_i(t+s, s)||\le M\cdot e^{\omega t}\} $ |
is the exponent growth bound of the evolution operator $ V_i(t, s) $. It is clear that $ c_i^* < 0 $.
Define functions $ F_S, F_i, F_R: [0, \infty)\longrightarrow Y $ respectively by
$ \begin{align*} &F_S(t, \phi) = \mu (\cdot , t)+\alpha (\cdot , t)\phi_S(\cdot , 0)-\mathop {\mathop \sum \limits_{i = 1} }\limits^2 \frac{\beta_i(\cdot , 0)\phi_S(\cdot , 0)\phi_i(\cdot , 0)}{\phi_S(\cdot , 0)+\phi_1(\cdot , 0)+\phi_2(\cdot , 0)+\phi_R(\cdot , 0)}, \\ &F_i(t, \phi) = \int_{0}^{\tau _i} f_i(a)\int_{\Omega }\Gamma_i(x, y, t, t-a)\frac{\beta_i(y, t-a)\phi_S(y, -a)\phi_i(y, -a)}{\phi_S(y, -a)+\phi_1(y, -a)+\phi_2(y, -a)+\phi_R(y, -a)}dyda, \\ &F_R(t, \phi) = r_1(\cdot , 0)\phi_1(\cdot , 0)+r_2(\cdot , 0)\phi_2(\cdot , 0). \end{align*} $ |
Let $ F = (F_S, F_1, F_2, F_R) $, it is clear that $ F $ is a function from $ [0, \infty) $ to $ X $. Define
$ U(t, s): = \begin{pmatrix}V_S(t, s) & 0 & 0 & 0 \\ 0 & V_1(t, s) & 0 & 0 \\ 0 & 0 & V_2(t, s) & 0 \\ 0 & 0 & 0 & V_R(t, s) \end{pmatrix}.\quad $ |
Then $ U(t, s) $ is an evolution operator from $ X $ to $ X $. Note that $ V_S, \ V_i\; (i = 1, 2) $ and $ V_R $ are analytic operators, it follows that $ U(t, s) $ is an analytic operator for $ (t, s)\in R^2 $ with $ t\ge s\ge 0 $. Let
$ \begin{align*} &D(A_S(t)) = \left\{\psi \in C^2(\bar {\Omega })\mid \; \rm{上}\; \frac{\partial }{\partial n}\psi = 0\ \rm{on} \ \partial \Omega\right\}; \\ &[A_S(t)\psi](x) = D_S\Delta \psi (x)-d(x, t)\psi (x), \ \forall \psi \in D(A_S(t)); \\ &D(A_i(t)) = \left\{\psi \in C^2(\bar {\Omega })\mid \; \rm{上}\; \frac{ \partial }{ \partial n}\psi = 0\ \rm{on} \ \partial \Omega\right\}; \\ &[A_i(t)\psi](x) = D_i\Delta \psi (x)-h_i(x, t)\psi (x), \ \forall \psi \in D(A_i(t)), \end{align*} $ |
and
$ \begin{align*} &D(A_R(t)) = \left\{\psi \in C^2(\bar {\Omega })\mid \; \rm{上}\; \frac{ \partial }{ \partial n}\psi = 0\ \rm{on} \ \partial \Omega \right\}; \\ &[A_R(t)\psi](x) = D_R\Delta \psi (x)-k(x, t)\psi (x), \ \forall \psi \in D(A_R(t)). \end{align*} $ |
Moreover, we let
$ A(t): = \begin{pmatrix}A_S(t) & 0 & 0 & 0 \\ 0 & A_1(t) & 0 & 0 \\ 0 & 0 & A_2(t) & 0 \\ 0 & 0 & 0 & A_R(t) \end{pmatrix}. $ |
Then (2.3) can be rewritten as the following Cauchy problem:
$ \begin{equation} \begin{cases} \frac{ \partial u(x, t)}{ \partial t} = A(t)u(x, t)+F(t, u_t), \ x\in \Omega, \ t > 0, \\ u(x, \zeta ) = \phi (x, \zeta ), \ x\in \Omega , \ \zeta \in [-\tau , 0], \end{cases} \end{equation} $ | (2.10) |
where $ u(x, t) = (S(x, t), I_1(x, t), I_2(x, t), R(x, t))^\mathrm{T} $. Furthermore, it can be rewritten as the following integral equation
$ u(t, \phi) = U(t, 0)\phi(0)+\int_{0}^{t}U(t, s)F(t, u_s)ds, \ t\ge 0, \ \phi\in C_{\tau}^+. $ |
Then the solution of above integral equation is called a mild solution of (2.10).
Theorem 2.1. For each $ \phi\in C_{\tau}^+ $, system $ (2.6) $ admits a unique solution $ u(t, \phi) $ on $ [0, +\infty) $ with $ u_0 = \phi $, and $ u(t, \phi) $ is globally bounded.
Proof. By the definition of $ F(t, \phi) $ and the assumption (H), $ F(t, \phi) $ is locally Lipschitz continuous on $ R_+\times C_\tau^+ $. We first show
$ \begin{equation} \underset {\theta \rightarrow 0^+}{\lim}\rm{dist}(\phi (0)+\theta F(t, \phi ), X^+) = 0, \ \forall (t, \phi )\in R_+\times C_\tau^+. \end{equation} $ | (2.11) |
Set
$ \begin{align*} &\bar {\beta } = \max \{\underset {x\in \bar {\Omega }, t\in [0, \tau ]}{\max}\beta _1(x, t), \underset {x\in \bar {\Omega }, t\in [0, \tau ]}{\max}\beta _2(x, t)\}; \\ &m_i(x, t) = \frac{\beta_i(x, t)\phi _S(x, 0)\phi _i(x, 0)}{\phi _S(x, 0)+\phi _1(x, 0)+\phi _2(x, 0)+\phi _R(x, 0)}; \\ &n_i(x, t) = \frac{\beta_i(x, t)\phi _S(x, t)\phi _i(x, t)}{\phi _S(x, t)+\phi _1(x, t)+\phi _2(x, t)+\phi _R(x, t)}. \end{align*} $ |
For any $ t\geq0, \ \theta \geq0 $ and $ x\in \bar{\Omega }, \ \phi \in C_\tau^+ $, we have
$ \begin{align*} \phi (x, 0)+\theta F(t, \phi )(x) & = \left(\begin{matrix}\phi _S(x, 0)+\theta [\mu (x, t)+\alpha (x, t)\phi _R(x, 0)-\mathop {\mathop \sum \limits_{i = 1} }\limits^2 m_i(x, t)]\\ \phi _1(x, 0)+\theta \int_{0}^{\tau _1} f_1(a)\int_{\Omega }\Gamma _1(x, y, t, t-a)\phi_1(y, t-a)dyda\\ \phi _2(x, 0)+\theta \int_{0}^{\tau _2} f_1(a)\int_{\Omega }\Gamma _2(x, y, t, t-a)\phi_2(y, t-a)dyda\\ \phi _R(x, 0)+r_1(x, t)\phi _1(x, 0)+r_2(x, t)\phi _2(x, 0) \end{matrix}\right )\\ &\ge \left(\begin{matrix}\phi _S(x, 0)\left(1-\theta \mathop {\mathop \sum \limits_{i = 1} }\limits^2 \frac{\beta_i(x, t)\phi _i(x, 0)}{\phi _S(x, 0)+\phi _1(x, 0)+\phi _2(x, 0)+\phi _R(x, 0)}\right)\\ \phi _1(x, 0)\\ \phi _2(x, 0)\\ \phi _R(x, 0) \end{matrix}\right ) \\ &\ge \left(\begin{matrix}\phi _S(x, 0)\left(1-\theta \bar {\beta }\mathop {\mathop \sum \limits_{i = 1} }\limits^2 \frac{\phi _i(x, 0)}{\phi _S(x, 0)+\phi _1(x, 0)+\phi _2(x, 0)+\phi _R(x, 0)}\right)\\ \phi _1(x, 0)\\ \phi _2(x, 0)\\ \phi _R(x, 0) \end{matrix}\right). \end{align*} $ |
The above inequality implies that (2.11) holds when $ \theta $ 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;\phi) $ with $ u_0(\cdot, \cdot; \phi) = \phi, \ t\in [0, t_\phi] $. Since $ U(t, s) $ is an analytic operator on $ X $ for any $ t, s\in R, \ s < t $, it follows that $ u(x, t;\phi) $ is a classical solution for $ t > \tau $. Set
$ P(t) = \int_{\Omega }\left(S(x, t)+\mathop {\mathop \sum \limits_{i = 1} }\limits^2 \left(L_i(x, t)+I_i(x, t)\right)+R(x, t)\right)dx, $ |
$ \mu _{\max } = \underset {(x, t)\in \bar {\Omega }\times[0, T]}{\sup }\mu (x, t), \ \bar {\mu }_{\max } = \mu _{\max }\cdot |\Omega |, \ d _{\min } = \underset {(x, t)\in \bar {\Omega }\times[0, T]}{\inf }d (x, t). $ |
Then
$ \begin{align*} \frac{dP(t)}{dt}& = \int_{\Omega }\mu (x, t)-d(x, t)\left(S(x, t)+\mathop {\mathop \sum \limits_{i = 1} }\limits^2 \left(L_i(x, t)+I_i(x, t)\right)+R(x, t)\right) \\ & \ \ \ -\mathop {\mathop \sum \limits_{i = 1} }\limits^2 \delta _i (x, t)\left(L_i(x, t)+I_i(x, t)\right)-\mathop {\mathop \sum \limits_{i = 1} }\limits^2 r_i(x, t)L_i(x, t)dx\\ &\le \int_{\Omega }\mu (x, t)dx-\int_{\Omega }d(x, t)\left(S(x, t)+\mathop {\mathop \sum \limits_{i = 1} }\limits^2 \left(L_i(x, t)+I_i(x, t)\right)+R(x, t)\right)dx\\ &\le \bar {\mu }_{\max }-d _{\min }P(t), \ t > 0. \end{align*} $ |
We obtain that there are $ l: = l_{\phi } $ large enough and $ M = \frac{\bar {\mu }_{\max }}{d _{\min }}+1 > 0 $, so that for each $ \phi\in C_{\tau }^+ $, one has
$ P(t)\le M, \ \forall t\ge lT+\tau . $ |
Then $ \int_{\Omega }I_i(x, t)dx\le M, \ \forall t\ge lT+\tau $. According to [11] and assumption (H), we obtain that $ \Gamma _i(x, y, t, t-a) $ and $ \beta _i(x, t) $ are uniformly bounded functions for any $ x, y\in \Omega, \ t\in [a, a+T] $. Set $ B_i = \underset {x, y\in \Omega, t\in [a, a+T]}{\sup }\Gamma _i(x, y, t, t-a)\beta _i(y, t-a) $, then we obtain
$ \begin{equation} \begin{split} \frac{\partial I_i}{\partial t} &\le D_i\Delta I_i-h _i (x, t)I_i(x, t)+\int_{0}^{\tau _i} f_i(a)\int_{\Omega }\Gamma_i(x, y, t, t-a)\beta_i(y, t-a)I_i(y, t-a)dyda\\ &\le D_i\Delta I_i-h _i (x, t)I_i(x, t)+B_i\int_{0}^{\tau _i} f_i(a)\int_{\Omega }I_i(y, t-a)dyda\\ &\le D_i\Delta I_i-h _i (x, t)I_i(x, t)+B_iMF_i(\tau _i)\\ & = D_i\Delta I_i-h _i (x, t)I_i(x, t)+B_iM, \ x\in \Omega , \ t\ge lT+\tau . \end{split} \end{equation} $ | (2.12) |
Consider the following equation:
$ \begin{equation} \begin{cases} \frac{ \partial \omega _i(x, t)}{ \partial t} = D_i\Delta \omega _i(x, t)-h_i(x, t)\omega _i(x, t)+B_iM, &x\in \Omega, \ t > lT+\tau , \\ \frac{ \partial \omega _i(x, t)}{ \partial n} = 0, &x\in \partial \Omega, \ t > lT+\tau . \\ \end{cases} \end{equation} $ | (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+\tau $. So there exists $ B_1 > 0 $ such that for each $ \phi\in C_{\tau }^+ $, we can find a $ l_i = l_i(\phi)\gg l(\phi) $ satisfying $ I_i(x, t;\phi)\le B_1(i = 1, 2) $ for $ x\in \bar {\Omega } $ and $ t \ge l_iT+\tau $. Thus
$ \begin{equation} \begin{cases} \frac{ \partial R(x, t)}{ \partial t}\le D_R\Delta R(x, t)-k(x, t)R(x, t)+B_1(r_1(x, t)+r_2(x, t)), &x\in \Omega, \ t > l_iT+\tau , \\ \frac{ \partial R(x, t)}{ \partial n} = 0, &x\in \partial \Omega, \ t > l_iT+\tau . \\ \end{cases} \end{equation} $ | (2.14) |
Similarly, there exists $ B_2 > 0 $ such that for each $ \phi\in C_{\tau }^+ $, there exists $ l_R = l_R(\phi)\gg l_i $ satisfying $ R(x, t;\phi)\le B_2 $ for $ x\in \bar {\Omega } $ and $ t \ge l_RT+\tau $. Then we have
$ \begin{equation} \begin{cases} \frac{ \partial S(x, t)}{ \partial t}\le D_S\Delta S(x, t)+\mu (x, t)-d(x, t)S(x, t)+B_2\alpha (x, t), &x\in \Omega, \ t > l_RT+\tau , \\ \frac{ \partial S(x, t)}{ \partial n} = 0, &x\in \partial \Omega, \ t > l_RT+\tau . \\ \end{cases} \end{equation} $ | (2.15) |
Hence, there are $ B_3 > 0 $ and $ l_S = l_S(\phi)\gg l_R $ such that for each $ \phi\in C_{\tau }^+ $, $ S(x, t;\phi)\le B_3(i = 1, 2) $ for $ x\in \bar {\Omega } $ and $ t \ge l_ST+\tau $, and hence, $ t_{\phi} = +\infty $.
Theorem 2.2. System $ (2.6) $ generates a T-periodic semi-flow $ \Phi _t: = u_t(\cdot):C_{\tau }^+\rightarrow C_{\tau }^+ $, namely $ \Phi _t(\phi)(x, s) = u_t(\phi)(x, s) = u(x, t+s; \phi) $ for any $ \phi \in C_{\tau }^+, \ t\ge 0 $ and $ s\in [-\tau, 0] $. In addition, $ \Phi _T $ admits a global compact attractor on $ C_\tau^+ $, where $ u(x, t; \phi) $ 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 $ \Phi_t(\phi) $ is continuous for any $ \phi \in C_{\tau}^+ $ and $ t\ge 0 $. In addition, similarly as the proof of [36,Lemma 2.1], we can further verify that $ \Phi_t $ is a T-periodic semi-flow on $ C_{\tau}^+ $. According to Theorem $ 2.1 $, we obtain that $ \Phi_t $ is dissipative. Moreover, by the arguments similar to those in the proof of [15,Proposition 21.2], we get that there exists $ n_0\ge1 $ such that $ \Phi_T^{n_0} = u_{n_0T} $ is compact on $ C_{\tau}^+ $ for $ n_0T\ge \tau $. Following from [23,Theorem 2.9], we have that $ \Phi_T:C_{\tau}^+ \rightarrow C_{\tau}^+ $ 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 $ I_j(x, t)\equiv0, \forall x\in \Omega, \ t > 0, \ j = 1, 2 $, and $ i\neq j $. Then system (2.6) reduces to the following single-strain model:
$ \begin{equation} \begin{cases} \begin{split} \frac{ \partial S}{ \partial t}\! = \!&D_S\Delta S\!+\!\mu(x, t)\!-\!d(x, t)S\!+\!\alpha(x, t)R(x, t) \!-\!\frac{\beta_i(x, t)S(x, t)I_i(x, t)}{S(x, t)\!+\!I_i(x, t)\!+\!R(x, t)}, \\ \frac{ \partial I_i}{ \partial t}\! = \!&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)I_i(y, t-a)}{S(y, t-a)\!+\!I_i(y, t-a)\!+\!R(y, t-a)}dyda, \\ \frac{ \partial R}{ \partial t}\! = \!&D_R\Delta R(x, t)+r_i(x, t)I_i(x, t)-d(x, t)R(x, t) -\alpha(x, t)R(x, t). \end{split} \end{cases} \end{equation} $ | (3.1) |
Consider the following linear equation:
$ \begin{equation} \begin{cases} \frac{ \partial S(x, t)}{ \partial t} = D_S\Delta S(x, t)+\mu(x, t)-d(x, t)S(x, t), &x\in \Omega , \ t > 0, \\ \frac{ \partial S(x, t)}{ \partial n} = 0, &x\in \partial \Omega , \ t > 0. \end{cases} \end{equation} $ | (3.2) |
According to [36,Lemma 2.1], there is an unique T-periodic solution $ S^*(x, t) $ of (3.2). Linearizing the $ I_i $-equation of system (3.1) at the disease-free periodic solution $ (S^*, 0, 0) $, we have
$ \begin{equation} \begin{cases} \begin{split} \frac{ \partial \omega _i(x, t)}{ \partial t}& = D_i\Delta \omega _i(x, t)-h_i(x, t)\omega _i(x, t) \\ &\ \ \ +\int_{0}^{\tau _i} f_i(a)\int_{\Omega }\Gamma_i(x, y, t, t-a)\beta_i(y, t-a)\omega _i(y, t-a)dyda, \ x\in \Omega , \ t > 0, \\ \frac{ \partial \omega _i(x, t)}{ \partial n}& = 0, \ x\in \partial \Omega , \ t > 0. \end{split} \end{cases} \end{equation} $ | (3.3) |
Let
$ C_T(\bar {\Omega }\times R, R): = \{u|u\in C(\bar {\Omega }\times R, R), u(x, t+T) = u(x, t), (x, t)\in \Omega \times R, T > 0\}, $ |
with the supremum norm, and define $ C_T^+ $ as the positive cone of $ C_T(\bar {\Omega }\times R, R) $, namely,
$ C_T^+: = \{u\in C_T:\ u(t)(x)\ge 0, \ \forall t\in R, \ x\in \bar {\Omega }\}. $ |
Let $ \psi _i(x, t)\in C_T(\bar {\Omega }\times R, R) $ be the initial distribution of infected individuals of the $ i $-strain at the spatial position $ x\in \bar{\Omega} $ and time $ t\in R $, then $ V_i(t-a, s)\psi _i(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, $ \int_{-\infty }^{t-a}V_i(t-a, s)\psi _i(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
$ \begin{align*} &\int_{0}^{\tau _i} f_i(a)\int_{\Omega }\Gamma_i(x, y, t, t-a)\beta_i(y, t-a)\int_{-\infty }^{t-a}\left(V_i(t-a, s)\psi _i(s)\right)(x)dsdyda \\ = &\int_{0}^{\tau _i} f_i(a)\int_{\Omega }\Gamma_i(x, y, t, t-a)\beta_i(y, t-a)\int_{a}^{+\infty }\left(V_i(t-a, t-s)\psi _i(t-s)\right)(x)dsdyda. \end{align*} $ |
Defining operator $ C_i:C_T(\bar {\Omega }\times R, R)\longrightarrow C_T(\bar {\Omega }\times R, R) $ by
$ \left (C_i\psi _i\right)(x, t) = \int_{0}^{\tau _i} f_i(a)\int_{\Omega }\Gamma_i(x, y, t, t-a)\beta_i(y, t-a)\psi _i(y, t-a)dyda. $ |
Set
$ A_i(\psi _i)(x, t) = (C_i\psi _i)(x, t), \ B_i(\psi _i)(x, t) = \int_{a}^{+\infty }\left(V_i(t, t-s+a)\psi _i(t-s+a)\right)(x)ds. $ |
Defining other operators $ L_i, \hat {L}_i:C_T\longrightarrow C_T $ by
$ \begin{align*} &\left (L_i\psi _i\right): = \int_{0}^{\tau _i} f_i(a)\int_{\Omega }\Gamma_i(x, y, t, t-a)\beta_i(y, t-a)\int_{a}^{+\infty }V_i(t-a, t-s)\psi _i(t-s)(x)dsdyda, \\ &\left (\hat {L}_i\psi _i\right)(x, t): = \int_{0}^{+\infty }V_i(t, t-s)\left (C_i\psi _i\right)(t-s)(x)ds, \ t\in R, \ s\ge 0. \end{align*} $ |
Clearly, $ L_i = A_iB_i, \ \hat {L}_i = B_iA_i $, $ L_i $ and $ \hat {L}_i $ are compact, bounded and positive operators. Let $ r(L_i) $ and $ r(\hat {L}_i) $ are the spectral radius of $ L_i $ and $ \hat {L}_i $ respectively, then $ r(L_i) = r(\hat {L}_i) $. Similar to [18,20], we define the basic reproduction number for system $ (3.1) $, that is, $ R_0^i = r(L_i) = r(\hat {L}_i). $
Define $ Q: = C([-\tau, 0], Y) $, and let $ ||\phi ||_Q: = \underset {\theta \in [-\tau, 0]}{\max }||\phi (\theta)||_Y $ for any $ \phi \in Q $. Denote $ Q^+: = C([-\tau, 0], Y^+) $ as the positive cone of $ Q $. Then $ (Q, Q^+) $ is strongly ordered Banach space. Let $ P: = C\left(\bar{\Omega }, R^3\right) $ be the Banach space with supremum norm $ \|\cdot\|_P $. For $ \tau > 0 $, let $ D_\tau : = C([-\tau, 0], P) $ be the Banach space with $ \|{\phi }\| = \underset {\theta \in [-\tau, 0]}{\max}\|{\phi (\theta)\|}_P $ for all $ \phi \in D_\tau $. Define $ P^+: = C\left(\bar{\Omega }, R_+^3\right) $ and $ D_\tau ^+: = C([-\tau, 0], P^+) $, then both $ (P, P^+) $ and $ (D_\tau, D_\tau ^+) $ are strongly ordered space. By the arguments in [21,39], we have the following observation:
Theorem 3.1. The signs of $ R_0^i-1 $ and $ r^i-1 $ are same.
Consider the following equation
$ \begin{equation} \begin{cases} \begin{split} \frac{ \partial \omega _i(x, t)}{ \partial t}& = D_i\Delta \omega _i(x, t)-h_i(x, t)\omega _i(x, t) \\ &\ \ \ +\int_{0}^{\tau _i} f_i(a)\int_{\Omega }\Gamma_i(x, y, t, t-a)\frac{B_3\beta_i(y, t-a)}{B_3+\omega_i(y, t-a)}\omega _i(y, t-a)dyda, \\ &\ \ \ \ x\in \Omega , \ t > 0, \\ { \partial \omega _i(x, s)}& = \psi _i(x, s), \ \psi _i\in Q^+ , \ x\in \Omega , \ s\in [-\tau _i, 0], \\ \frac{ \partial \omega _i(x, t)}{ \partial n}& = 0, \ x\in \partial \Omega , \ t > 0, \end{split} \end{cases} \end{equation} $ | (3.4) |
where $ B_3 $ is the constant in the proof of Theorem $ 2.1 $.
Theorem 3.2. Assume that $ \omega_i(x, t;\psi_i) $ is the solution of $ (3.4) $ with an initial value of $ \psi_i\in Q $. If $ R_0^i = 1 $ and $ \beta_i(x, t) > 0 $ for all $ x\in \bar{\Omega}, \ t > 0 $, then $ \omega_i(x, t)\equiv0 $ is globally attractive.
Proof. By a straightforward computation, one has that $ (3.4) $ is dominated by $ (3.3) $. Define the map $ P_i^{n_o}:Q\rightarrow Q $ by $ P_i^{n_o}(\psi_i) = \omega_{i, T}^{n_0} $ with $ \omega_{i, T}^{n_0} = \omega_i(x, n_0T+s; \psi_i) $, where $ \omega_i(x, t; \psi_i) $ is the solution of $ (3.3) $. Similar to the argument in [18], $ P_i^{n_o} $ is strongly positive on $ Q^+ $ when $ \beta_i(x, t) > 0, \forall x\in \bar{\Omega}, \ t > 0 $. It follows from [20,Lemma 3.1] that $ P_i^{n_o} $ admits a positive and simple eigenvalue $ r^i $, and a strongly positive eigenfunction defined by $ \psi_i $, that is $ P_i(\psi_i) = r^i\psi_i $. It follows from the strong positivity of $ \psi_i $ that $ \omega_i(x, t;\psi_i)\gg0 $. According to Theorem 3.2, we have $ r^i = 1 $, and hence, $ \mu^i = 0 $. By similar arguments as the proof of [18,Lemma 3.2], we can show that there is a positive $ T $-periodic function $ \nu_i^*(x, t) = e^{-\mu^i\cdot0}\omega_i(x, t;\psi_i) = \omega_i(x, t;\psi_i) $ such that $ \nu_i^*(x, t) $ is a solution of $ (3.3) $. Then for each initial value $ \psi_i(x, s)\in Q $, there exists a constant $ k > 0 $ such that $ \psi_i(x, s)\le k\nu_i^*(x, s) $ for all $ x\in \Omega, \ t > 0 $. Moreover, by the comparison principle, one has $ \omega_i(x, t;\psi_i)\le k\nu_i^*(x, t) $ for all $ x\in \Omega, \ t > 0 $. Let
$ [0, k\nu_i^*]_Q = \{u\in Q: 0\le u(x, s)\le k\nu_i^*(x, s), \ \forall x \in \bar{\Omega}, \ s \in[-\tau_i, 0]\}, $ |
then
$ S_i^{n_0}(\psi_i): = \omega_i(x, n_oT\omega+S; \psi_I)\subseteq[0, k\nu_i^*]_Q, \ \ \forall x \in \bar{\Omega}, \ s \in [-\tau_i, 0]. $ |
Hence the positive orbit $ \gamma_+(\psi_i): = \{S_i^{kn_0}(\psi_i):\forall k \in N\} $ of $ S_i^{n_0}(\cdot) $ is precompact, and $ S_i^{n_0} $ maps $ [0, k\nu_i^*]_Q $ into $ [0, k\nu_i^*]_Q $, Due to comparison principle, we get $ S_i^{n_0}(\cdot) $ is monotone. According to [40,Theorem 2.2.2], we obtain that $ \omega_i(x, t)\equiv0 $ is globally attractive.
Theorem 3.3. Suppose that $ \bar{S}(x, t;\psi) = (S(x, t;\psi), I_i(x, t;\psi), R(x, t;\psi)) $ is the solution of $ (3.1) $ with the initial data $ \psi $. If $ I_i(x, t_0;\psi)\not\equiv0 $ for some $ t_0\ge 0 $, then $ I_i(x, t;\psi) > 0, \ \forall x \in \bar{\Omega}, \ t > t_0 $.
Proof. Obviously, for the secondly equation of $ (3.1) $, we get
$ \begin{cases} \frac{ \partial I_i(x, t)}{ \partial t}\ge D_i\Delta I_i(x, t)-h_i(x, t)I_i(x, t), \ x\in \Omega , \ t > 0, \\ \frac{ \partial I_i(x, t)}{ \partial n} = 0, \ x\in \partial \Omega , \ t > 0, \ i = 1, 2, \end{cases} $ |
and $ I_i(x, t_0;\psi)\not\equiv0, \ t_0\ge 0, \ i = 1, 2 $. It follows from [15,Proposition 13.1] that $ I_i(x, t;\psi) > 0 $ for all $ x\in \bar{\Omega} $ and $ t > t_0 $.
Theorem 3.4. Suppose that $ \bar{S}(x, t;\psi) = (S(x, t;\psi), I_i(x, t;\psi), R(x, t;\psi)) $ be the solution of $ (3.1) $ with the initial data $ \psi = (\psi_S, \psi_i, \psi_R)\in D_{\tau }, \ i = 1, 2 $. Thenone has
$ {\rm(1)} $ If $ R_0^i = 1 $ and $ \beta_i(x, t) > 0 $ for all $ x\in \Omega $ and $ t > 0 $, then $ (S^*, 0, 0) $ is globally attractive;
$ {\rm(2)} $ If $ R_0^i < 1 $, then $ (S^*, 0, 0) $ is globally attractive;
$ {\rm(3)} $ If $ R_0^i > 1 $, then there is a $ M > 0 $ such that for any $ \psi\in D_{\tau }^+ $, one has
$ \underset {t\rightarrow \infty }{\liminf }S(x, t;\psi) > M, \ \underset {t\rightarrow \infty }{\liminf }I_i(x, t;\psi) > M, \ \underset {t\rightarrow \infty }{\liminf }R(x, t;\psi) > M $ |
uniformly for $ x\in \bar{\Omega} $.
Proof. $ (1) $ According to the proof of Theorem 2.1, for $ t > l_sT+\tau $, we have $ S(x, t;\phi)\le B_3, \ \forall x\in\bar{\Omega}, \ \phi\in C_{\tau }^+ $. Thus, when $ t > l_sT+\tau $, the second equation of $ (3.1) $ is dominated by (3.4) for $ x\in \bar{\Omega} $. In addition, one has $ I_i(x, t;\psi)\le \omega_i(x, t) $ for $ x\in \bar{\Omega} $ and $ t > l_sT+\tau $. Since $ R_0^i = 1 $ and $ \beta_i(x, t) > 0 $ for $ x\in \bar{\Omega}, \ t > 0 $. It follows from Theorem $ 3.5 $ that $ \underset {t\rightarrow \infty }{\lim }\omega_i(x, t) = 0 $ for all $ x\in \bar{\Omega} $. In addition, one has $ \underset {t\rightarrow \infty }{\lim }I_i(x, t;\psi) = 0 $ for all $ x\in\bar{\Omega} $, and $ \underset {t\rightarrow \infty }{\lim }R(x, t;\psi) = 0 $ for all $ x\in\bar{\Omega} $. 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 = \Phi_T, \ J = \bar{\omega}(\psi) $ denotes the omega limit set for $ P $. That is
$ J = \{(\phi_S^*, \phi_i^*, \phi_R^*)\in C_{\tau}^+:\exists \{k_i\}\rightarrow \infty \ s. t.\ \underset {i\rightarrow \infty }{\lim }P^{k_i}(\phi_S, \phi_i, \phi_R) = (\phi_S^*, \phi_i^*, \phi_R^*)\}. $ |
It follows fron [17,Lemma 2.1] that $ J $ is an internally chain transitive sets for $ P $. Since $ \underset {t\rightarrow \infty }{\lim }I_i(x, t;\psi) = 0 $ and $ \underset {t\rightarrow \infty }{\lim }R(x, t;\psi) = 0 $ for all $ x\in \bar{\Omega} $, then $ J = J_1\times\{\hat{0}\}\times\{\hat{0}\} $. According to Theorem $ 3.5 $, one has $ \hat{0}\notin J_1 $. Let $ \omega(x, t;\psi_S(\cdot, 0)) $ be the solution of $ (3.2) $ with the initial value $ \omega(x, 0) = \psi_S(x, 0) $, where $ \psi_S\in Q^+ $. Define
$ \omega_t(x, \theta;\psi_S) = \begin{cases} \omega(x, \theta+t;\psi_S(0))\ \ &t+\theta > 0, \ t > 0, \ \theta\in [-\tau, 0], \\ \psi(x, \theta+t)\ \ &t+\theta\le 0, \ t > 0, \ \theta\in [-\tau, 0]. \end{cases} $ |
Then we define the solution semiflow $ \omega_t $ for $ (3.2) $.
Let $ \bar{P} = \omega_T(\psi_S), \ \bar{\omega}(\psi_S) $ denotes the omega limit set of $ \bar{P} $. According to [36,Lemma 2.1], one has $ \bar{\omega}(\psi_S) = \{S^*\} $. Since $ P(J) = J $ and $ I_i(x, t;(\psi_S, \hat{0}, \hat{0}))\equiv0, \ R(x, t;(\psi_S, \hat{0}, \hat{0}))\equiv0 $, $ P(J) = \bar{P}(J_1)\times\{\hat{0}\}\times\{\hat{0}\} $, then $ \bar{P}(J_1) = J_1 $. Therefore, $ J_1 $ is an internally chain transitive sets for $ \bar{P} $. It follows from [36,Lemma 2.1] that $ \{S^*\} $ is globally attractive on $ Q^+ $. In addition, $ J_1\cap W^S\{S^*\} = J_1\cap\ Q^+ = \emptyset $, where $ W^S\{S^*\} $ is the stable set of $ S^* $. According to [40,Theorem 1.2.1], one has $ J_1\subseteq\{S^*\} $, then $ J_1 = \{S^*\} $. Consequently, $ J = \{(S^*, 0, 0)\} $. By the definition of $ J $, we have
$ \underset {t\rightarrow \infty }{\lim }\parallel( S(\cdot , t;\psi), I_i(\cdot , t;\psi) , R(\cdot , t;\psi) )-(S^*(\cdot, t), 0, 0)\parallel = 0. $ |
$ (2) $ Consider equation
$ \begin{equation} \begin{cases} \begin{split} \frac{ \partial \omega _i^*(x, t)}{ \partial t}& = D_i\Delta \omega _i^*(x, t)-h_i(x, t)\omega _i^*(x, t) \\ &\ \ \ +\int_{0}^{\tau _i} f_i(a)\int_{\Omega }\Gamma_i(x, y, t, t-a)(\beta_i(y, t-a)+\varepsilon)\omega _i^*(y, t-a)dyda, \\ &\ \ \ \ x\in \Omega , \ t > 0, \\ \frac{ \partial \omega _i^*(x, t)}{ \partial n}& = 0, \ x\in \partial \Omega , \ t > 0. \end{split} \end{cases} \end{equation} $ | (3.5) |
Since $ R_0^i < 1 $, it follows from Theorem 2.1 that $ r^i < 1 $. Thus there exists a constant $ \varepsilon_0 > 0 $ such that $ r^{i, \varepsilon} < 1 $ for $ \varepsilon\in [0, \varepsilon_0) $. Then $ \mu ^{i, \varepsilon}: = \frac{\ln {r^{i, \varepsilon}}}{T} < 0 $ for $ \varepsilon\in [0, \varepsilon_0) $. Similar to the proof of [18,Lemma 3.2], there is positive T-periodic function $ \nu_i^{\varepsilon}(x, t) $ such that $ \omega_i^{\varepsilon}(x, t) = e^{\mu ^{i, \varepsilon}}\nu_i^{\varepsilon}(x, t) $ satisfies $ (3.5) $. Since $ \mu ^{i, \varepsilon} < 0 $, $ \underset {t\rightarrow \infty }{\lim }\omega_i^{\varepsilon}(x, t) = 0 $ uniformly for $ x\in \Omega $.
For $ x\in \Omega, \ t > 0 $, one has
$ \begin{equation} \begin{cases} \begin{split} \frac{ \partial I_i(x, t)}{ \partial t}&\le 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)(\beta_i(y, t-a)+\varepsilon)I_i(y, t-a)dyda, \\ &\ \ \ \ x\in \Omega , \ t > 0, \\ \frac{ \partial I_i(x, t)}{ \partial n}& = 0, \ x\in \partial \Omega , \ t > 0. \end{split} \end{cases} \end{equation} $ | (3.6) |
For any given initial distribution $ \psi\in D_{\tau}^+ $, due to the boundedness of $ I_i(x, t;\psi) $, there exists $ \alpha > 0 $ such that $ I_i(x, t;\psi)\le \alpha\cdot \omega_i^{\varepsilon}(x, t), \ \forall t\in[kT, kT+\tau], \ x\in\bar{\Omega} $, and hence, $ I_i(x, t;\psi)\le \alpha\cdot \omega_i^{\varepsilon}(x, t) $ for $ t\ge kT+\tau $. Then $ \underset {t\rightarrow \infty }{\lim}I_i(x, t;\psi) = 0 $ and $ \underset {t\rightarrow \infty }{\lim}R(x, t;\psi) = 0 $ for all $ x\in \bar{\Omega} $. Furthermore, similar to the proof of (1), we have
$ \underset {t\rightarrow \infty }{\lim }\parallel( S(\cdot , t;\psi), I_i(\cdot , t;\psi) , R(\cdot , t;\psi) )-(S^*(\cdot, t), 0, 0)\parallel = 0. $ |
$ (3) $ Let
$ W_0^i = \{\psi = (\psi_S, \psi_i, \psi_R)\in D_{\tau}^+:\psi_i(\cdot, 0)\neq0\}, $ |
$ \partial W_0^i: = D_{\tau}^+\backslash W_0^i = \{\psi = (\psi_S, \psi_i, \psi_R)\in D_{\tau}^+:\psi_i(\cdot, 0)\equiv0\}. $ |
Define $ \Phi_t:D_{\tau}^+\rightarrow D_{\tau}^+ $ by $ \Phi_t(\psi)(x, s) = (S(x, t+s; \psi), I_i(x, t+s; \psi), R(x, t+s; \psi)) $. By Theorem $ 3.6 $, we know that $ I_i(x, t+s; \psi) > 0 $ for any $ \psi\in W_i^0, \ x\in \bar{\Omega} $ and $ t > 0 $. Thus there exists $ k\in N $ such that $ \Phi_{n_0T}^k(W_0^i)\subseteq W_0^i $. Define
$ M_{\partial}^i: = \{\psi\in \partial W_0^i: \Phi_{n_0T}^k(\psi)\in \partial W_0^i, \ \forall k\in N\}. $ |
Let $ M: = (S^*, 0, 0) $ and $ \omega(\psi) $ be the omega limit set of the orbit $ \gamma^+: = \{\Phi_{n_0T}^k(\psi): \forall k\in N\} $. For any given $ \psi\in M_{\partial}^i $, we have $ \Phi_{n_0T}^k(\psi)\in \partial W_0^i $. Thus $ I_i(x, t;\psi)\equiv0, \ \forall x\in \bar{\Omega}, \ t\ge 0 $. Therefore $ R(x, t;\psi)\equiv0 $ for any $ x\in \bar{\Omega} $ and $ t\ge 0 $. By similar arguments as the proof of $ (1) $, we have
$ \underset {t\rightarrow \infty }{\lim }\parallel( S(\cdot , t;\psi), I_i(\cdot , t;\psi) , R(\cdot , t;\psi) )-(S^*(\cdot, t), 0, 0)\parallel = 0. $ |
That is $ \omega(\psi) = {M} $ for any $ \psi\in M_{\partial}^i $.
For sufficient small $ \bar{\theta} > 0 $, consider the following system:
$ \begin{equation} \begin{cases} \begin{split} \frac{ \partial v_i^{\theta}(x, t)}{ \partial t}& = D_i\Delta v_i^{\theta}(x, t)-h_i(x, t)v_i^{\theta}(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}}v_i^{\theta}(y, t-a)dyda, \\ &\ \ \ \ x\in \Omega , \ t > 0, \\ { \partial v_i^{\theta}(x, s)}& = \psi _i(x, s), \ \psi _i\in Q^+ , \ x\in \Omega , \ s\in [-\tau _i, 0], \\ \frac{ \partial v_i^{\theta}(x, t)}{ \partial n}& = 0, \ x\in \partial \Omega , \ t > 0. \end{split} \end{cases} \end{equation} $ | (3.7) |
Let $ v_i^{\theta}(x, t;\psi_i) $ be the solution of $ (3.7) $. Note $ v_{i, n_0T}^{\theta}(\psi_i)(x, s) = v_i^{\theta}(x, s+n_0T;\psi_i) $ for all $ x\in \Omega $ and $ s\in[-\tau _i, 0] $. Define the poincar$ \acute{e} $ 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] |
A. Ackleh, K. Deng, Y. Wu, Competitive exclusion and coexistence in a two-strain pathogen model with diffusion, Math. Biosci. Eng., 13 (2016), 1–18. http://dx.doi.org/10.3934/mbe.2016.13.1 doi: 10.3934/mbe.2016.13.1
![]() |
[2] | P. Agarwal, J. J. Nieto, M. Ruzhansky, D. F. Torres, Analysis of infectious disease problems (Covid-19) and their global impact, Singapore: Springer Nature Singapore Pte Ltd, 2021. http://dx.doi.org/10.1007/978-981-16-2450-6 |
[3] |
S. Altizer, A. Dobson, P. Hosseini, P. Hudson, M. Pascua, P. Rohani, Seasonality and the dynamics of infectious disease, Ecol. Lett., 9 (2006), 467–484. http://dx.doi.org/10.1111/j.1461-0248.2005.00879.x doi: 10.1111/j.1461-0248.2005.00879.x
![]() |
[4] |
I. A. Baba, B. Kaymakamzade, E. Hincal, Two-strain epidemic model with two vaccinations, Chaos Soliton. Fract., 106 (2018), 342–348. http://dx.doi.org/10.1016/j.chaos.2017.11.035 doi: 10.1016/j.chaos.2017.11.035
![]() |
[5] |
L. Bauer, J. Bassett, P. H$\ddot{o}$vel, Y. N. Kyrychko, k. B. Blyuss, Chimera states in multi-strain epidemic models with temporary immunity, Chaos, 27 (2017), 114317. http://dx.doi.org/10.1063/1.5008386 doi: 10.1063/1.5008386
![]() |
[6] |
L. Cai, J. Xiang, X. Z. Li, A. A. Lashari, A two-strain epidemic model with mutant strain and vaccination, J. Appl. Math. Comput., 40 (2012), 125–142. http://dx.doi.org/10.1007/s12190-012-0580-x doi: 10.1007/s12190-012-0580-x
![]() |
[7] | M. X. Chang, B. S. Han, X. M. Fan, Spatiotemporal dynamics for a Belousov-Zhabotinsky reaction-diffusion system with nonlocal effects, Appl. Anal., 2021. https://doi.org/10.1080/00036811.2020.1869948 |
[8] |
Z. W. Chen, Z. T. Xu, A delayed diffusive influenza model with two-strain and two vaccinations, Appl. Math. Comput., 349 (2019), 439–453. http://dx.doi.org/10.1016/j.amc.2018.12.065 doi: 10.1016/j.amc.2018.12.065
![]() |
[9] | D. Dancer, P. Koch Medina, Abstract ecolution equations, Periodic problem and applications, Essex: Longman Scientific & Technical, 1992. |
[10] |
P. van den Driessche, J. Watmough, Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission, Math. Biosci., 180 (2002), 29–48. http://dx.doi.org/10.1016/S0025-5564(02)00108-6 doi: 10.1016/S0025-5564(02)00108-6
![]() |
[11] | A. Friedman, Partial differential equations of parabolic type, Englewood Cliffs: Prentice-Hall, 1964. |
[12] |
Z. Guo, F. Wang, X. Zou, Threshold dynamics of an infective disease model with a fixed latent period and non-local infections, J. Math. Biol., 65 (2012), 1387–1410. http://dx.doi.org/10.1007/s00285-011-0500-y doi: 10.1007/s00285-011-0500-y
![]() |
[13] |
B. S. Han, Y. Yang, W. J. Bo, H. Tang, Global dynamics of a Lotka-Volterra competition diffusion system with nonlocal effects, Int. J. Bifurcat. Chaos, 30 (2020), 2050066. http://dx.doi.org/10.1142/S0218127420500662 doi: 10.1142/S0218127420500662
![]() |
[14] |
B. S. Han, Z. Feng, W. J. Bo, Traveling wave phenomena of a nonlocal reaction-diffusion equation with degenerate nonlinearity, Commun. Nonlinear Sci., 103 (2021), 105990. http://dx.doi.org/10.1016/j.cnsns.2021.105990 doi: 10.1016/j.cnsns.2021.105990
![]() |
[15] | P. Hess, Periodic-parabolic boundary value problems and positivity, Essex: Longman Scientific & Technical, 1991. |
[16] |
H. W. Hethcote, Asymptotic behavior in a deterministic epidemic model, B. Math. Biol., 36 (1973), 607–614. http://dx.doi.org/10.1007/BF02458365 doi: 10.1007/BF02458365
![]() |
[17] |
M. W. Hirsch, H. L. Smith, X. Q. Zhao, Chain transitivity, attractivity and strong repellors for semidynamical systems, J. Dyn. Differ. Equ., 13 (2001), 107–131. http://dx.doi.org/10.1023/A:1009044515567 doi: 10.1023/A:1009044515567
![]() |
[18] |
Y. Jin, X. Q. Zhao, Spatial dynamics of a nonlocal periodic reaction-diffusion model with stage structure, SIAM J. Math. Anal., 40 (2009), 2496–2516. http://dx.doi.org/10.1137/070709761 doi: 10.1137/070709761
![]() |
[19] |
C. Leung, The difference in the incubation period of 2019 novel coronavirus (SARS-CoV-2) infection between travelers to Hubei and nontravelers: The need for a longer quarantine period, Infect. Cont. Hosp. Ep., 41 (2020), 594–596. http://dx.doi.org/10.1017/ice.2020.81 doi: 10.1017/ice.2020.81
![]() |
[20] |
X. Liang, X. Q. Zhao, Asymptotic speeds of spread and traveling waves for monotone semiflows with applications, Commun. Pure Appl. Math., 60 (2007), 1–40. http://dx.doi.org/10.1002/cpa.20154 doi: 10.1002/cpa.20154
![]() |
[21] |
X. Liang, L. Zhang, X. Q. Zhao, Basic reproduction ratios for periodic abstract functional differential equations (with application to a spatial model for lyme disease), J. Dyn. Differ. Equ., 31 (2019), 1247–1278. http://dx.doi.org/10.1007/s10884-017-9601-7 doi: 10.1007/s10884-017-9601-7
![]() |
[22] |
Y. Lou, X. Q. Zhao, Threshold dynamics in a time-delayed periodic SIS epidemic model, Discrete Cont. Dyn. B, 12 (2009), 169–186. http://dx.doi.org/10.3934/dcdsb.2009.12.169 doi: 10.3934/dcdsb.2009.12.169
![]() |
[23] |
P. Magal, X. Q. Zhao, Global attractors and steady states for uniformly persistent dynamical systems, SIAM J. Math. Anal., 37 (2005), 251–275. http://dx.doi.org/10.1137/S0036141003439173 doi: 10.1137/S0036141003439173
![]() |
[24] |
M. Martcheva, A non-autonomous multi-strain SIS epidemic model, J. Biol. Dynam., 3 (2009), 235–251. http://dx.doi.org/10.1080/17513750802638712 doi: 10.1080/17513750802638712
![]() |
[25] |
R. Martain, H. L. Smith, Abstract functional differential equations and reaction-diffusion system, T. Am. Math. Soc., 321 (1990), 1–44. http://dx.doi.org/10.2307/2001590 doi: 10.2307/2001590
![]() |
[26] | R. H. Martin, Nonlinear operators and differential equations in Banach spaces, 1986. |
[27] |
C. McAloon, Á. Collins, K. Hunt, A. Barber, F. Butler, M. Casey, et al., Incubation period of COVID-19: A rapid systematic review and meta-analysis of observational research, BMJ open, 10 (2020), e039652. http://dx.doi.org/10.1136/bmjopen-2020-039652 doi: 10.1136/bmjopen-2020-039652
![]() |
[28] | J. A. J. Metz, O. Diekmann, The dynamics of physiologically structured populations, Springer, 1986. http://dx.doi.org/10.1007/978-3-662-13159-6 |
[29] |
R. Peng, X. Q. Zhao, A reaction-diffusion SIS epidemic model in a time-periodic environment, Nonlinearity, 25 (2012), 1451–1471. http://dx.doi.org/10.1088/0951-7715/25/5/1451 doi: 10.1088/0951-7715/25/5/1451
![]() |
[30] |
P. J. Sansonetti, J. Arondel, Construction and evaluation of a double mutant of Shigella flexneri as a candidate for oral vaccination against shigellosis, Vaccine, 7 (1989), 443–450. http://dx.doi.org/10.1016/0264-410X(89)90160-6 doi: 10.1016/0264-410X(89)90160-6
![]() |
[31] |
H. L. Smith, Multiple stable subharmonics for a periodic epidemic model, J. Math. Biol., 17 (1983), 179–190. http://dx.doi.org/10.1007/BF00305758 doi: 10.1007/BF00305758
![]() |
[32] |
Y. Takeuchi, W. Ma, E. Beretta, Global asymptotic properties of delay SIR epidemic model with finite incubation times, Nonlinear Anal., 42 (2000), 931–947. http://dx.doi.org/10.1016/S0362-546X(99)00138-8 doi: 10.1016/S0362-546X(99)00138-8
![]() |
[33] |
N. Tuncer, M. Martcheva, Analytical and numerical approaches to coexistence of strains in a two-strain SIS model with diffusion, J. Biol. Dynam., 6 (2012), 406–439. http://dx.doi.org/10.1080/17513758.2011.614697 doi: 10.1080/17513758.2011.614697
![]() |
[34] |
H. Xi, H. Jiang, M. Juhas, Y. Zhang, Multiplex biosensing for simultaneous detection of mutations in SARS-CoV-2, ACS Omega, 6 (2021), 25846–25859. http://dx.doi.org/10.1021/acsomega.1c04024 doi: 10.1021/acsomega.1c04024
![]() |
[35] |
X. Yang, H. Li, Y. Cao, Influence of meteorological factors on the COVID-19 transmission with season and geographic location, Int. J. Environ. Res. Public. Health, 18 (2021), 484. http://dx.doi.org/10.3390/ijerph18020484 doi: 10.3390/ijerph18020484
![]() |
[36] |
L. Zhang, Z. C. Wang, X. Q. Zhao, Threshold dynamics of a time periodic reaction-diffusion epidemic model with latent period, J. Differ. Equ., 258 (2015), 3011–3036. http://dx.doi.org/10.1016/j.jde.2014.12.032 doi: 10.1016/j.jde.2014.12.032
![]() |
[37] |
T. Zhang, Z. Teng, On a nonautonomous SEIR model in epidemiology, B. Math. Biol., 69 (2007), 2537–2560. http://dx.doi.org/10.1007/s11538-007-9231-z doi: 10.1007/s11538-007-9231-z
![]() |
[38] |
L. Zhao, Z. C. Wang, S. Ruan, Dynamics of a time-periodic two-strain SIS epidemic model with diffusion and latent period, Nonlinear Anal. Real, 51 (2020), 102966. http://dx.doi.org/10.1016/j.nonrwa.2019.102966 doi: 10.1016/j.nonrwa.2019.102966
![]() |
[39] |
L. Zhao, Z. C. Wang, L. Zhang, Threshold dynamics of a time periodic and two-group epidemic model with distributed delay, Math. Biosci. Eng., 14 (2017), 1535–1563. http://dx.doi.org/10.3934/mbe.2017080 doi: 10.3934/mbe.2017080
![]() |
[40] | X. Q. Zhao, Dynamical systems in population biology, New York: Springer, 2003. http://dx.doi.org/10.1007/978-0-387-21761-1 |
1. | Zakaria Yaagoub, Karam Allali, Global Stability of Multi-Strain SEIR Epidemic Model with Vaccination Strategy, 2023, 28, 2297-8747, 9, 10.3390/mca28010009 |