Global Stability of a Delayed SIRI Epidemic Model with Nonlinear Incidence

In this paper we propose the global dynamics of an SIRI epidemic model with latency and a general nonlinear incidence function. Themodel is based on the susceptible-infective-recovered (SIR) compartmental structure with relapse (SIRI). Sufficient conditions for the global stability of equilibria (the disease-free equilibrium and the endemic equilibrium) are obtained bymeans of LyapunovLaSalle theorem. Also some numerical simulations are given to illustrate this result.


Introduction
Epidemic models have long been an important tool for understanding and controlling the spread of infectious diseases.Most of them are described by delayed differential equations.The introduction of time delay is often used to model the latent period, that is, the time from the acquisition of infection to the time when the host becomes infectious [1,2].
Recently, considerable attention has been paid to model the relapse phenomenon, that is, the return of signs and symptoms of a disease after a remission.Hence, the recovered individual can return to the infectious class (see [3][4][5][6]).For the biological explanations of the relapse phenomenon, we cite two examples.
(i) For malaria, Bignami [7] proposed that relapses derived from persistence of small numbers of parasite in the blood.Also, it has been observed that the proportion of patients who have successive relapses is relatively constant (see [8]).(ii) For tuberculosis, relapse can be caused by incomplete treatment or by latent infection, being observed that HIV-positive patients are significantly more likely to relapse than HIV-negative patients, although it is often difficult to differentiate relapse from reinfection (see [9]).

International Journal of Engineering Mathematics
Here   = ( − ) for any given function ,  = , where  =  +  +  is the total number of population,  is the number of susceptible individuals,  is the number of infectious individuals,  is the number of recovered individuals,  is the recruitment rate of the population,  is the natural death of the population,  is the death rate due to disease,  is the nonlinear incidence function,  is the recovery rate of the infective individuals,  is the rate that recovered individuals relapse and regained infectious class, and  is the latent period.
In [5] (1990), Tudor developed and analyzed qualitatively one of the first SIRI epidemic models for the spread of a herpes-type infection in either human or animal populations.This model consists of a system of nonlinear ordinary differential equations with a bilinear incidence rate (i.e., (, ) = ) and a constant total population (i.e.,  =  +  +  = constant).
In [25] (1997), Moreira and Wang extended a Tudormodel to include nonlinear incidence functions.By using an elementary analysis of Liénard's equation and Lyapunov's direct method, they derived sufficient conditions for the global asymptotic stability of the disease-free and endemic equilibria.
In [23] (2000), Castillo-Garsow et al. considered an SIRI model for drug use in a population of adolescents.The authors assumed that  = constant and (, ) = /; they estimated the parameters of the model and they determined a rough approximation of the basic reproductive number.Based on these parameters, they performed some simulations that clearly showed the endemic character of tobacco use among adolescents.
In [27] (2007), van den Driessche and Zou proposed an integrodifferential equation to model a general relapse phenomenon in infectious diseases.The resulting model, in particular case, is a delay differential equation with a constant population and standard incidence.The basic reproduction number for this model is identified and some global results are obtained by employing the Lyapunov-Razumikhin technique.
In [10] (2007), Van Den Driessche and co-authors formulated a delay differential SIRI model (System (1) with (, ) = ).For this system, the endemic equilibrium is locally asymptotically stable if  0 > 1, and the disease is shown to be uniformly persistent with the infective population size either approaching or oscillating about the endemic level.
In [22] (2011), Liu et al. proposed a mathematical model for a disease with a general exposed distribution, the possibility of relapse and nonlinear incidence rate ((, ) = (/)).By the method of Lyapunov functionals, they showed that the disease dies out if  0 = 1 and that the disease becomes endemic if  0 > 1.They also analyzed, as a special case of this model, the system (1) with (, ) = () ⋅ ; the result confirms that the endemic equilibrium is globally asymptotically stable.
In [29] (2013), Vargas-De-Leon presented the global stability conditions of an ordinary SIRI model with bilinear and standard incidence rates, respectively, that includes recruitment rate of susceptible individuals into the community and that the disease produces nonnegligible death in the infectious class.The author presented the construction of Lyapunov functions using suitable combinations of known functions, common quadratic and Volterra-type, and a composite Volterra-type function.
In [21] (2013), Georgescu and Zhang analyzed the dynamics of an ordinary SIRI model under the assumption that the incidence of infection is given by (, ) = ()().They obtained by means of Lyapunov's second method sufficient conditions for the local stability of equilibria and they showed that global stability can be attained under suitable monotonicity conditions.
In [30] (2013), Shuai and van den Driessche presented two systematic methods for the construction of Lyapunov functions for general infectious disease models (Ordinary SEIRI, SIS, etc.).Specifically, a matrix-theoretic method using the Perron eigenvector is applied to prove the global stability of the disease-free equilibrium, while a graph-theoretic method based on Kirchhoff's matrix tree theorem and two new combinatorial identities are used to prove the global stability of the endemic equilibrium.
In [31] (2014), Xu investigated a delayed SIRI model (system (1) with (, ) = ).The author established the global stability of a disease-free equilibrium and an endemic equilibrium by means of suitable Lyapunov functionals and LaSalle's invariance principle.
In this paper we extend the global stability results presented in [31] to a delayed SIRI epidemic model (system (1)) with a general nonlinear incidence function.It is shown that global stability can be attained under suitable monotonicity conditions and it is established that the basic reproduction number  0 is a threshold parameter for the stability of a delayed SIRI model.The rest of the paper is organized as follows.In Section 2, the global stability of disease-free and endemic equilibria are established.In Section 3, numerical simulations and concluding remarks are provided.In the appendix, some results on the global stability are stated.

Global Stability Analysis of Delayed SIRI Model
In this section, we discuss the global stability of a disease-free equilibrium  0 and an endemic equilibrium  * of system (1).Since (/)( +  + ) ≤  − ( +  + ), we have lim sup( +  + ) ≤ /.Hence we discuss system (1) in the closed set It is easy to show that Ω is positively invariant with respect to system (1).Next we consider the global asymptotic stability of the disease-free equilibrium  0 and the endemic equilibrium  * of (1) by Lyapunov functionals, respectively.

Numerical Simulations and Concluding Remarks
In this section, we give a numerical simulation supporting the theoretical analysis given in Section 2. Let  (, ) =  1 +  1  +  2  .
We take the parameters of the system (1) as follows: By Proposition 2, the endemic equilibrium  * is globally asymptotically stable; see Figure 1.
In this paper, we presented a mathematical analysis and numerical simulations for an SIRI epidemiological model applied to the evolution of the spread of disease with relapse in a given population.We denote  0 the basic reproduction number.It is defined as the average number of contagious persons infected by a typical infectious in a population of susceptible.We prove in this paper that the basic reproduction number,  0 , depends on the incubation period and we show that the disease-free equilibrium  0 is globally asymptotically stable if  0 ≤ 1 and that a unique endemic equilibrium  * is globally asymptotically stable if  0 > 1.  Definition A.1 (see [32, page 30]).We say  :  →  is a Lyapunov functional on a set  in  for (A.1) if it is continuous on  (the closure of ) and V ≤ 0 on .We also

Figure 1 :
Figure 1: Solutions (, , ) of the SIRI epidemic model (1) are globally asymptotically stable and converge to the endemic equilibrium  * .