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Discrete Dynamics in Nature and Society
Volume 2008 (2008), Article ID 746951, 13 pages
http://dx.doi.org/10.1155/2008/746951
Research Article

A Delayed Epidemic Model with Pulse Vaccination

1Department of Applied Mathematics, Dalian University of Technology, Dalian 116024, China
2School of Sciences, Jimei University, Xiamen 361021, China

Received 14 November 2007; Revised 7 January 2008; Accepted 18 February 2008

Academic Editor: Leonid Berezansky

Copyright © 2008 Chunjin Wei and Lansun Chen. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

A delayed SEIRS epidemic model with pulse vaccination and nonlinear incidence rate is proposed. We analyze the dynamical behaviors of this model and point out that there exists an infection-free periodic solution which is globally attractive if 𝑅1<1, 𝑅2>1, and the disease is permanent. Our results indicate that a short period of pulse or a large pulse vaccination rate is the sufficient condition for the eradication of the disease. The main feature of this paper is to introduce time delay and impulse into SEIRS model and give pulse vaccination strategies.

1. Introduction

Infectious diseases are usually caused by pathogenic microorganisms, such as bacteria, viruses, parasites, or fungi; the diseases can be spread directly or indirectly. The severe and sudden epidemics of infectious diseases have a great influence on the human life and socioeconomy, which compel scientists to design and implement more effective control and preparedness pro- grams. Pulse vaccination is an effective method to use in attempts to control infectious diseases.

In recent years, epidemic mathematical models of ordinary differential equations have been studied by many authors (e.g., [13]). In most of the research literatures, authors always assume that the disease incubation is negligible, therefore, once infected, each susceptible in- dividual becomes infectious instantaneously and later recovers with a temporary acquired im- munity. An epidemic model based on these assumptions is customarily called SIR (susceptible, infectious, recovered) model. However, many diseases incubate inside the hosts for a period of time before the hosts become infectious. We assume that a susceptible individual first goes through a latent period after infection before becoming infectious. The resulting model is called SEIRS (susceptible, exposed, infectious, recovered) model. The SEIRS infections disease model is a very important biologic model and has been studied by many authors (e.g., [46]).

Bilinear and standard incidence rates have been frequently used in classical epidemic models [7]. Simple dynamics of these models seem related to such functions. These different incidence rates have been proposed by researchers. Anderson et al. pointed out that standard incidence is more suitable than bilinear incidence [810]. Levin et al. have adopted an incidence form like 𝛽𝑆𝑞𝐼𝑝 or 𝛽𝑆𝑞𝐼𝑝/𝑁 which depends on different infective disease and environments [11]. L. S. Chen and J. Chen [12] set forth transmission effect like the saturation effect 𝛽𝑆(𝑡)/(1+𝑎𝑆(𝑡)) as the infection rate. In this paper, we will adopt the infection rate 𝛽𝑆(𝑡)/(1+𝑎𝑆(𝑡)) because it includes the behavioral change and crowding effect of the infective individuals and prevents the unboundedness of the contact rate by choosing suitable parameters.

On the one hand, the newborns of the infectious may already be infected with the disease at birth such as hepatitis and phthisis, and so forth. This is called vertical transmission. On the other hand, some diseases may be spread from one individual to another via horizontal contacting transmission. Some epidemic models with vertical transmission were studied by many authors. However, only a few literatures [13] deal with the analysis of disease with pulse vaccination, vertical and horizontal transmissions.

Most of the research literature on these epidemic models are established by ODE, delayed ODE or impulsive ODE. However, impulsive equations with time delay are not many [14, 15]. In this paper, we establish a delayed SEIRS epidemic disease model with pulse vaccination and nonlinear incidence rate. We study their dynamic behaviors, establish sufficient condition for disease-eradication, as well as investigate the role of incubation in disease transmission. The main feature of this paper is to introduce time delay and pulse vaccination into epidemic model and obtain some important qualitative properties with valid pulse vaccination strategy.

The organization of this paper is as follows. In the next section, we introduce the delayed SEIRS model with pulse vaccination. To prove our main results, we also give several definitions, notations, and lemmas. In Section 3, we investigate the dynamic behavior of the model with nonlinear incidence and the sufficient condition is obtained for the global attractivity of infection-free periodic solution and the permanence of the model. In the final section, we try to interpret our mathematical results in terms of their ecological implication and also point out some future research directions.

2. Model Formulation and Preliminary

In the following model, we study a population that is partitioned into four classes, the susceptible, exposed, infectious, and recovered, with sizes denoted by S, E, I, and R, respectively, and we consider pulse vaccination strategy in the delayed SEIRS epidemic model with nonlinear incidence rate 𝛽(𝑆/(1+𝑎𝑆))𝐼, the following mathematical model is formulated: 𝑆(𝑡)=𝐴𝛽𝑆(𝑡)𝐼(𝑡)𝐸1+𝑎𝑆(𝑡)𝜇𝑆(𝑡)(1𝑝)𝜇𝐼(𝑡)+𝛼𝑅(𝑡),𝑡𝑛𝑇,(𝑡)=𝛽𝑆(𝑡)𝐼(𝑡)1+𝑎𝑆(𝑡)𝛽𝑒𝜇𝜏𝑆(𝑡𝜏)𝐼(𝑡𝜏)𝐼1+𝑎𝑆(𝑡𝜏)𝜇𝐸(𝑡)+(1𝑝)𝜇𝐼(𝑡),𝑡𝑛𝑇,(𝑡)=𝛽𝑒𝜇𝜏𝑆(𝑡𝜏)𝐼(𝑡𝜏)𝑅1+𝑎𝑆(𝑡𝜏)(𝑟+𝑑+𝜇)𝐼(𝑡),𝑡𝑛𝑇,(𝑡)=𝑟𝐼(𝑡)𝜇𝑅(𝑡)𝛼𝑅(𝑡),𝑡𝑛𝑇,𝑆(𝑡+)=(1𝜃)𝑆(𝑡),𝑡=𝑛𝑇,𝑛=1,2,𝐸(𝑡+)=𝐸(𝑡),𝑡=𝑛𝑇,𝑛=1,2,𝐼(𝑡+)=𝐼(𝑡),𝑡=𝑛𝑇,𝑛=1,2,𝑅(𝑡+)=𝑅(𝑡)+𝜃𝑆(𝑡),𝑡=𝑛𝑇,𝑛=1,2,.(2.1)

Here, all coefficients are positive constants, 𝐴 denotes the influx or recruitment of the susceptible and the exposed. The death rate for disease and physical disease rate are 𝑑 and 𝜇, respectively. 𝑟 is the recovery rate of infectious individual. 𝜃(0<𝜃<1) is the proportion of those vaccinated successfully, which is called impulsive vaccination rate. 𝜏 is the latent period of the disease. Consider the death of exposed individuals during latent period of disease, that is, 𝛽𝑒𝜇𝜏(𝑆(𝑡𝜏)𝐼(𝑡𝜏)/(1+𝑎𝑆(𝑡𝜏))) term. The disease is propagated both vertically and horizontally, 𝑝𝜇𝐼(0<𝑝<1) is the number of newborns of infectious who transfer to the susceptible class, and (1𝑝)𝜇𝐼 is the number of newborns of the infectious who are infected vertically.

The total population size 𝑁(𝑡)=𝑆(𝑡)+𝐸(𝑡)+𝐼(𝑡)+𝑅(𝑡) can be determined by the differential equation𝑁(𝑡)=𝐴𝜇𝑁(𝑡)𝑑𝐼(𝑡),(2.2)which is derived by adding all equations in system (2.1). So we have 𝐴(𝜇+𝑑)𝑁(𝑡)𝑁(𝑡)𝐴𝜇𝑁(𝑡). It follows that𝐴𝜇+𝑑lim𝑡inf𝑁(𝑡)lim𝑡𝐴sup𝑁(𝑡)𝜇.(2.3)

Before going to any detail, we simplify model (2.1) and mainly discuss the following model:𝑆(𝑡)=𝐴𝛽𝑆(𝑡)𝐼(𝑡)𝐼1+𝑎𝑆(𝑡)𝜇𝑆(𝑡)(1𝑝)𝜇𝐼(𝑡)+𝛼𝑅(𝑡),𝑡𝑛𝑇,(𝑡)=𝛽𝑒𝜇𝜏𝑆(𝑡𝜏)𝐼(𝑡𝜏)𝑅1+𝑎𝑆(𝑡𝜏)(𝑟+𝑑+𝜇)𝐼(𝑡),𝑡𝑛𝑇,𝑁(𝑡)=𝑟𝐼(𝑡)𝜇𝑅(𝑡)𝛼𝑅(𝑡),𝑡𝑛𝑇,(𝑡)=𝐴𝜇𝑁(𝑡)𝑑𝐼(𝑡),𝑡𝑛𝑇,𝑆(𝑡+)=(1𝜃)𝑆(𝑡),𝑡=𝑛𝑇,𝑛=1,2,𝐼(𝑡+)=𝐼(𝑡),𝑡=𝑛𝑇,𝑛=1,2,𝑅(𝑡+)=𝑅(𝑡)+𝜃𝑆(𝑡),𝑡=𝑛𝑇,𝑛=1,2,𝑁(𝑡+)=𝑁(𝑡),𝑡=𝑛𝑇,𝑛=1,2,.(2.4)The initial condition of (2.4) is given as𝜙(𝜉)=(𝜙1(𝜉),𝜙2(𝜉),𝜙3(𝜉),𝜙4(𝜉))𝐶+,𝜙𝑖(0)>0,𝑖=1,2,3,4,(2.5)where 𝐶+=𝐶([𝜏,0],𝑅4+). From biological considerations, we discuss system (2.4) in the closed setΩ=(𝑆,𝐼,𝑅,𝑁)𝑅4+𝐴0𝑆+𝐼+𝑅𝜇𝐴,𝑁𝜇,(2.6)where 𝑅4+ denotes the nonnegative cone of 𝑅4 including its lower dimensional faces. It is easy to show that Ω is positively invariant with respect to (2.4).

Before starting our main results, we give the following lemmas. Lemma 2.1 (See [16]). Consider the following delay differential equation: 𝑥(𝑡)=𝑎𝑥(𝑡𝜏)𝑏𝑥(𝑡),(2.7)where 𝑎,𝑏,𝜏>0 and 𝑥(𝑡)>0 for 𝑡[𝜏,0]. The following hold:
(i)if 𝑎<𝑏, then lim𝑡𝑥(𝑡)=0,(ii)if 𝑎>𝑏, then lim𝑡𝑥(𝑡)=+.
Lemma 2.2. Consider the following impulsive differential equations: 𝑢(𝑡)=𝑎𝑏𝑢(𝑡),𝑡𝑛𝑇,𝑢(𝑡+)=(1𝜃)𝑢(𝑡),𝑡=𝑛𝑇,𝑛𝑁,(2.8)where 𝑎>0,𝑏>0,0<𝜃<1. Then there exists a unique positive periodic solution of (2.8): 𝑢𝑒𝑎(𝑡)=𝑏+𝑢𝑎𝑏𝑒𝑏(𝑡𝑘𝑇),𝑘𝑇<𝑡<(𝑘+1)𝑇,(2.9)which is globally asymptotically stable, where 𝑢=𝑎(1𝜃)(1𝑒𝑏𝑇)/𝑏(1(1𝜃)𝑒𝑏𝑇).

3. Global Attractivity of Infection-Free Periodic Solution

In this section, we study the existence of the infection-free periodic solution of system (2.4), in which infectious individuals are entirely absent from the population permanently, that is, 𝐼(𝑡)=0 for all 𝑡0. Under this condition, system (2.4) becomes the following impulsive system without delay: 𝑆𝑅(𝑡)=𝐴𝜇𝑆(𝑡)+𝛼𝑅(𝑡),𝑡𝑛𝑇,𝑁(𝑡)=𝜇𝑅(𝑡)𝛼𝑅(𝑡),𝑡𝑛𝑇,(𝑡)=𝐴𝜇𝑁(𝑡),𝑡𝑛𝑇,𝑆(𝑡+)=(1𝜃)𝑆(𝑡),𝑡=𝑛𝑇,𝑛=1,2,𝑅(𝑡+)=𝑅(𝑡)+𝜃𝑆(𝑡),𝑡=𝑛𝑇,𝑛=1,2,𝑁(𝑡+)=𝑁(𝑡),𝑡=𝑛𝑇,𝑛=1,2,.(3.1) From the third and sixth equations of system (3.1), we have lim𝑡𝑁(𝑡)=𝐴/𝜇. Further, if 𝐼(𝑡)=0, it follows that lim𝑡𝐸(𝑡)=0 from the second and sixth equations of system (2.1). In the following, we show that the susceptible population 𝑆 and recovered population 𝑅 oscillate with period 𝑇, in synchronization with the periodic impulsive vaccination. Consider the following limit system of system (3.1): 𝐴𝑅(𝑡)=𝜇𝑆𝑆(𝑡),𝐴(𝑡)=(𝛼+𝜇)𝜇𝑆(𝑡),𝑡𝑛𝑇,𝑆(𝑡+)=(1𝜃)𝑆(𝑡),𝑡=𝑛𝑇,𝑛𝑁.(3.2)By Lemma 2.2, we know that the periodic solution of system (3.2), 𝑆𝑒𝐴(𝑡)=𝜇+𝑆𝐴𝜇𝑒(𝛼+𝜇)(𝑡𝑛𝑇),𝑛𝑇<𝑡(𝑛+1)𝑇,(3.3)is globally asymptotically stable, where 𝑆=𝐴(1𝜃)(1𝑒(𝛼+𝜇)𝑇)/𝜇(1(1𝜃)𝑒(𝛼+𝜇)𝑇).

Denote 𝑅1=𝛽𝑒𝜇𝜏𝛿/(1+𝑎𝛿)(𝑟+𝑑+𝜇), where 𝛿=𝐴(1𝑒(𝛼+𝜇)𝑇)/𝜇(1(1𝜃)𝑒(𝛼+𝜇)𝑇).

Theorem 3.1. If 𝑅1<1, then the infection-free periodic solution (𝑆𝑒𝑆(𝑡),0,𝐴/𝜇𝑒(𝑡),𝐴/𝜇) of system (2.4) is globally attractive.Proof. Since 𝑅1<1, we can choose 𝜀>0 small enough such that𝛽𝑒𝜇𝜏(𝛿+𝜀)1+𝑎(𝛿+𝜀)<𝑟+𝑑+𝜇.(3.4)From the first equation of system (2.4), it follows that 𝑆(𝑡)(𝛼+𝜇)((𝐴/𝜇)𝑆(𝑡)). Thus consider the following comparison impulsive differential system:𝑧𝐴(𝑡)=(𝛼+𝜇)𝜇𝑧(𝑡),𝑡𝑛𝑇,𝑧(𝑡+)=(1𝜃)𝑧(𝑡),𝑡=𝑛𝑇,𝑛𝑁.(3.5)By (3.2), we know that the periodic solution of system (3.5),𝑧𝑒𝑆(𝑡)=𝑒𝐴(𝑡)=𝜇+𝑆𝐴𝜇𝑒(𝛼+𝜇)(𝑡𝑛𝑇),𝑛𝑇<𝑡(𝑛+1)𝑇,(3.6)is globally asymptotically stable, where 𝑆=𝐴(1𝜃)(1𝑒(𝛼+𝜇)𝑇)/𝜇(1(1𝜃)𝑒(𝛼+𝜇)𝑇). Let (𝑆(𝑡),𝐼(𝑡),𝑅(𝑡),𝑁(𝑡)) be the solution of system (2.4) with initial condition (2.5) and 𝑆(0+)=𝑆0>0,𝑧(𝑡) be the solution of system (3.5) with initial value 𝑧(0+)=𝑆0. By the comparison theorem for impulsive differential equations [17], there exists an integer 𝑛1>0 such that𝑆(𝑡)<𝑧(𝑡)<𝑧𝑒(𝑡)+𝜀,𝑛𝑇<𝑡(𝑛+1)𝑇,𝑛>𝑛1,(3.7)that is,𝑆(𝑡)<𝑧𝑒𝐴(𝑡)+𝜀1𝑒(𝛼+𝜇)𝑇𝜇1(1𝜃)𝑒(𝛼+𝜇)𝑇+𝜀𝜂.(3.8)Further, from the second equation of system (2.4), we have that, for all 𝑡>𝑛𝑇+𝜏,𝑛>𝑛1,𝐼(𝑡)𝛽𝜂𝑒𝜇𝜏1+𝑎𝜂𝐼(𝑡𝜏)(𝑟+𝑑+𝜇)𝐼(𝑡).(3.9)Consider the following comparison equation:𝑦(𝑡)=𝛽𝜂𝑒𝜇𝜏1+𝑎𝜂𝑦(𝑡𝜏)(𝑟+𝑑+𝜇)𝑦(𝑡).(3.10)From (3.4), we have that𝛽𝜂𝑒𝜇𝜏1+𝑎𝜂<(𝑟+𝑑+𝜇).(3.11)According to Lemma 2.1, we obtain that lim𝑡𝑦(𝑡)=0.
Set (𝑆(𝑡),𝐼(𝑡),𝑅(𝑡),𝑁(𝑡)) be the solution of system (2.4) with initial condition (2.5) and 𝐼(𝜉)=𝜙(𝜉)>0(𝜉[𝜏,0]),𝑦(𝑡) be the solution of (3.10) with initial condition 𝑦(𝜉)=𝜙(𝜉)>0(𝜉[𝜏,0]). By the comparison theorem in differential equation and the positivity of solution (with 𝐼(𝑡)0), we have thatlim𝑡𝐼(𝑡)=0.(3.12)Therefore, for any 𝜀1>0 (sufficiently small), there exists an 𝑛2(𝑛2𝑇>𝑛1𝑇+𝜏) such that 0<𝐼(𝑡)<𝜀1 for all 𝑡>𝑛2𝑇. By the fourth equation of system (2.4), we have𝑁(𝑡)>𝐴𝜇𝑁(𝑡)𝑑𝜀1for𝑡>𝑛2𝑇.(3.13)Consider the following comparison equation: 𝑧1(𝑡)=(𝐴𝑑𝜀1)𝜇𝑧1(𝑡).
It is clear that lim𝑡𝑧1(𝑡)=(𝐴𝑑𝜀1)/𝜇; by the comparison theorem, we have that there exists an integer 𝑛3>𝑛2 such that for all 𝑡>𝑛3𝑇,𝑁(𝑡)(𝐴𝑑𝜀1)/𝜇𝜀1. Since 𝜀1 is arbitrarily small, we havelim𝑡𝐴𝑁(𝑡)=𝜇.(3.14)It follows from (3.12) and (3.14) that, there exists 𝑛4>𝑛3 such that𝐼(𝑡)<𝜀1𝐴,𝑁(𝑡)>𝜇𝜀1for𝑡>𝑛4𝑇.(3.15)From the second equation of system (2.1), we have 𝐸(𝑡)𝐴𝛽𝜀1𝜇+𝑎𝐴+(1𝑝)𝜇𝜀1𝜇𝐸(𝑡)for𝑡>𝑛4𝑇.(3.16) It is easy to obtain that there exists an 𝑛5>𝑛4 such that 𝐸(𝑡)<𝛿1+𝜀1for𝑡>𝑛5𝑇,(3.17)where 𝛿1=(𝐴𝛽𝜀1+(𝜇+𝑎𝐴)(1𝑝)𝜇𝜀1)/𝜇(𝜇+𝐴𝑎). So from the first equation of system (2.4), we have 𝑆(𝑡)𝐴+𝛼𝐴𝜇(1𝑝)𝜇𝜀1𝛼𝛿13𝛼𝜀1𝛽𝜀1+𝜇+𝛼𝑆(𝑡).(3.18)Consider the following comparison impulsive differential equations for 𝑡>𝑛5𝑇 and 𝑛>𝑛5: 𝑢(𝑡)=𝐴+𝛼𝐴𝜇(1𝑝)𝜇𝜀1𝛼𝛿13𝛼𝜀1𝛽𝜀1+𝜇+𝛼𝑢(𝑡),𝑡𝑛𝑇,𝑢(𝑡+)=(1𝜃)𝑢(𝑡),𝑡=𝑛𝑇,𝑛𝑁.(3.19)By Lemma 2.2, we know that the periodic solution of system (3.19) is𝑢𝑒(𝑡)=Θ+(𝑢Θ)𝑒(𝛼+𝜇+𝛽𝜀1)(𝑡𝑛𝑇),𝑛𝑇<𝑡(𝑛+1)𝑇,(3.20)which is globally asymptotically stable, where Θ=𝐴+𝐴𝛼/𝜇𝛼𝛿13𝛼𝜀1(1𝑝)𝜇𝜀1𝛼+𝜇+𝛽𝜀1,𝑢=Θ(1𝜃)1𝑒(𝛼+𝜇+𝛽𝜀1)𝑇1(1𝜃)𝑒(𝛼+𝜇+𝛽𝜀1)𝑇.(3.21)By using the comparison theorem of impulsive differential equation [17], there exists an 𝑛6>𝑛5 such that𝑆(𝑡)>𝑢𝑒(𝑡)𝜀1,𝑛𝑇<𝑡(𝑛+1)𝑇,𝑛>𝑛6.(3.22)Let 𝜀10, then it follows from (3.8) and (3.22) that 𝑆𝑒𝐴(𝑡)=𝜇1𝜃𝑒(𝛼+𝜇)(𝑡𝑛𝑇)1(1𝜃)𝑒(𝛼+𝜇)𝑇,𝑛𝑇<𝑡(𝑛+1)𝑇,(3.23)is globally attractive, that is,lim𝑡𝑆𝑆(𝑡)=𝑒(𝑡).(3.24)By the positivity of 𝐸(𝑡) and sufficiently small 𝜀1, it follows from (3.17) that lim𝑡𝐸(𝑡)=0.(3.25) From the restriction 𝑁(𝑡)=𝑆(𝑡)+𝐸(𝑡)+𝐼(𝑡)+𝑅(𝑡), we have lim𝑡𝑆𝑅(𝑡)=𝐴/𝜇𝑒(𝑡). Therefore, the infection-free periodic solution (𝑆𝑒𝑆(𝑡),0,𝐴/𝜇𝑒(𝑡),𝐴/𝜇) is globally attractive. This completes the proof.
Corollary 3.2. In system (2.4), the following states are true.
(i)If 𝐴𝛽𝑒𝜇𝜏<(𝑟+𝑑+𝜇)(𝜇+𝐴𝑎),then infection-free periodic solution (𝑆𝑒𝑆(𝑡),0,𝐴/𝜇𝑒(𝑡),𝐴/𝜇) is globally attractive.(ii)If 𝐴𝛽𝑒𝜇𝜏>(𝑟+𝑑+𝜇)(𝜇+𝐴𝑎) and 𝑇<𝑇, then infection-free periodic solution (𝑆𝑒𝑆(𝑡),0,𝐴/𝜇𝑒(𝑡),𝐴/𝜇) is globally attractive, where 𝑇=1/(𝛼+𝜇)ln(1+(𝜃(𝑟+𝑑+𝜇)𝜇)/(𝐴𝛽𝑒𝜇𝜏𝑎𝐴(𝑟+𝑑+𝜇)(𝑟+𝑑+𝜇)𝜇).(iii)If 𝜃>𝜃, then infection-free periodic solution (𝑆𝑒𝑆(𝑡),0,𝐴/𝜇𝑒(𝑡),𝐴/𝜇) is globally attractive, where 𝜃=(𝑟+𝑑𝜇)𝑒(𝛼+𝜇)𝑇(𝑟+𝑑+𝜇)𝜇+(𝐴𝛽𝑒𝜇𝜏𝑎(𝑟+𝑑+𝜇)𝐴)(1𝑒(𝛼+𝜇)𝑇)/𝜇(𝑟+𝑑+𝜇)𝑒(𝛼+𝜇)𝑇.

Theorem 3.1 determines the global attractivity of system (2.4) in Ω for the case 𝑅1<1. From Corollary 3.2, we can see that a short pulse periodic (with 𝑇) or a large pulse vaccination rate (with 𝜃) is the sufficient condition for the global attractivity of infection-free periodic solution (𝑆𝑒𝑆(𝑡),0,𝐴/𝜇𝑒(𝑡),𝐴/𝜇).

4. Permanence

In this section, it is noted that the disease is endemic if the infectious population persists above a certain threshold for sufficiently large time. The endemicity of the disease can be well captured and studied through the notion of uniform persistence and permanence.Definition 4.1. System (2.4) is said to be uniformly persistent if there exists an 𝑚>0 (independent of the initial data) such that every solution (𝑆(𝑡),𝐼(𝑡),𝑅(𝑡),𝑁(𝑡)) with initial conditions (2.5) of system (2.4) satisfieslim𝑡inf𝑆(𝑡)𝑚,lim𝑡inf𝐼(𝑡)𝑚,lim𝑡inf𝑅(𝑡)𝑚,lim𝑡inf𝑁(𝑡)𝑚.(4.1)Definition 4.2. System (2.4) is said to be permanent if there exists a compact region Ω0intΩ such that every solution of system (2.4) with initial data (2.5) will eventually enter and remain in region Ω0.

Denote𝑅2=𝛽𝑒𝜇𝜏/(𝑟+𝑑+𝜇)𝑎𝐴(1𝜃)1𝑒𝜇𝑇𝜇1(1𝜃)𝑒𝜇𝑇,𝐼=𝑅𝐴𝜇21𝐴𝛽+(1𝑝)𝜇2𝑅2.(4.2)

Theorem 4.3. If 𝑅2>1, then there exists a positive constant 𝑚 such that each positive solution (𝑆(𝑡),𝐼(𝑡),𝑅(𝑡),𝑁(𝑡)) of system (2.4) satisfies 𝐼(𝑡)𝑚 for 𝑡 large enough.Proof. Note that the second equation of system (2.4) can be rewritten as follows:𝐼(𝑡)=𝐼(𝑡)𝛽𝑒𝜇𝜏𝑆(𝑡)1+𝑎𝑆(𝑡)(𝑟+𝑑+𝜇)𝛽𝑒𝜇𝜏𝑑𝑑𝑡𝑡𝑡𝜏𝑆(𝑢)𝐼(𝑢)1+𝑎𝑆(𝑢)𝑑𝑢.(4.3)Define𝑉(𝑡)=𝐼(𝑡)+𝛽𝑒𝜇𝜏𝑡𝑡𝜏𝑆(𝑢)1+𝑎𝑆(𝑢)𝐼(𝑢)𝑑𝑢.(4.4)According to (4.3), we calculate the derivative of 𝑉 along the solution of (2.4):𝑉(𝑡)=𝐼(𝑡)𝛽𝑒𝜇𝜏𝑆(𝑡)1+𝑎𝑆(𝑡)(𝑟+𝑑+𝜇)=(𝑟+𝑑+𝜇)𝐼(𝑡)𝛽𝑒𝜇𝜏𝑆(𝑡).(𝑟+𝑑+𝜇)(1+𝑎𝑆(𝑡))1(4.5)Since 𝑅2>1, then 𝐼>0 and there exists sufficiently small 𝜀>0 such that𝛽𝑒𝜇𝜏𝜎(𝑟+𝑑+𝜇)(1+𝑎𝜎)>1,(4.6)where𝜎=𝐴(1𝑝)𝜇𝐼(1𝜃)1𝑒(𝛽𝐼+𝜇)𝑇(𝛽𝐼+𝜇)1(1𝜃)𝑒(𝛽𝐼+𝜇)𝑇𝜀>0.(4.7)We claim that for any 𝑡0>0, it is impossible that 𝐼(𝑡)<𝐼 for all 𝑡𝑡0. Otherwise, there is a 𝑡0>0 such that 𝐼(𝑡)<𝐼 for all 𝑡𝑡0. It follows from the first equation of (2.4) that we have𝑆(𝑡)>𝐴(1𝑝)𝜇𝐼(𝛽𝐼+𝜇)𝑆(𝑡).(4.8)Consider the following comparison impulsive system for 𝑡𝑡0:𝑣(𝑡)=𝐴(1𝑝)𝜇𝐼(𝛽𝐼+𝜇)𝑣(𝑡),𝑡𝑛𝑇,𝑣(𝑡+)=(1𝜃)𝑣(𝑡),𝑡=𝑛𝑇,𝑛𝑁.(4.9)According to Lemma 2.2, we obtain that𝑣𝑒(𝑡)=𝐴(1𝑝)𝜇𝐼𝛽𝐼+𝑣+𝜇𝐴(1𝑝)𝜇𝐼𝛽𝐼𝑒+𝜇(𝛽𝐼+𝜇)(𝑡𝑛𝑇),𝑛𝑇<𝑡(𝑛+1)𝑇,(4.10)is the unique globally asymptotically stable positive periodic solution, where 𝑣=
By the comparison theorem for impulsive differential equation [17], we know that there exists (𝐴(1𝑝)𝜇𝐼) such that the following inequality holds for (1𝜃):(1𝑒(𝛽𝐼+𝜇)𝑇)Thus/(𝛽𝐼+𝜇)(1(1𝜃)𝑒(𝛽𝐼+𝜇)𝑇).From (4.6), we have 𝑡1>𝑡0+𝜏 By (4.5) and (4.12), we have𝑡>𝑡1Let𝑣𝑆(𝑡)>𝑒(𝑡)𝜀.(4.11)We will show that 𝑆(𝑡)>𝑣𝜀𝜎>0for𝑡𝑡1.(4.12) for all 𝛽𝑒𝜇𝜏𝜎/(𝑟+𝑑+𝜇)(1+𝑎𝜎)>1.. Otherwise, there is a 𝑉(𝑡)>(𝑟+𝑑+𝜇)𝐼(𝑡)𝛽𝑒𝜇𝜏𝜎(𝑟+𝑑+𝜇)(1+𝑎𝜎)1for𝑡𝑡1.(4.13) such that 𝐼𝑙=min𝑡[𝑡1,𝑡1+𝜏]𝐼(𝑡).(4.14) for 𝐼(𝑡)𝐼𝑙 and 𝑡𝑡1. However, the second equation of systems (2.4) and (4.12) imply that𝑇0>0This is a contradiction, thus, 𝐼(𝑡)𝐼𝑙 for all 𝑡[𝑡1,𝑡1+𝜏+𝑇0],𝐼(𝑡1+𝜏+𝑇0)=𝐼𝑙,. As a consequence, (4.13) leads to𝐼(𝑡1+𝜏+𝑇0)0which implies that 𝐼𝑡1+𝜏+𝑇0(𝑟+𝑑+𝜇)𝐼𝑙𝛽𝑒𝜇𝜏𝜎(𝑟+𝑑+𝜇)(1+𝑎𝜎)1>0.(4.15) as 𝐼(𝑡)𝐼𝑙 This contradicts with 𝑡𝑡1 Hence, for any 𝑉(𝑡)>(𝑟+𝑑+𝜇)𝐼𝑙𝛽𝑒𝜇𝜏𝜎(𝑟+𝑑+𝜇)(1+𝑎𝜎)1>0for𝑡𝑡1,(4.16) the inequality 𝑉(𝑡) cannot hold for all 𝑡. Next, we are left to consider two cases:
(1)𝑉(𝑡)(𝐴/𝜇)(1+𝐴𝜏𝛽𝑒𝜇𝜏/𝜇). for 𝑡0>0, large enough;(2)𝐼(𝑡)<𝐼 oscillates about 𝑡𝑡0. for 𝐼(𝑡)𝐼 large enough.It is clear that if 𝑡 for 𝐼(𝑡) large enough, then our aim is obtained. So we only need consider the case 𝐼
Let𝑡In the following, we will show that 𝐼(𝑡)𝐼 for 𝑡 large enough, let (2). and 𝐼𝑚=min2,𝐼𝑒(𝑟+𝑑+𝜇)𝜏.(4.17) satisfy 𝐼(𝑡)𝑚 and 𝑡 for 𝑡>0 where 𝜄>0 is sufficiently large such that 𝐼(𝑡)=𝐼(𝜄+𝑡)=𝐼, for 𝐼(𝑡)<𝐼 we can conclude that 𝑡<𝑡<𝑡+𝜄, is uniformly continuous since the positive solution of (2.4) is ultimately bounded and 𝑡 is not affected by impulsive effects. Hence there exists a constant 𝑆(𝑡)>𝜎 and 𝑡<𝑡<𝑡+𝜄, is independent of the choice if 𝐼(𝑡) such that 𝐼(𝑡) for 𝑇1(0<𝑇1<𝜏, If 𝑇1our aim is obtained. If 𝑡), since 𝐼(𝑡)>𝐼/2, and 𝑡𝑡𝑡+𝑇1., it is obvious that 𝜄𝑇1, for 𝑇1<𝜄𝜏. If 𝐼(𝑡)>(𝑟+𝑑+𝜇)𝐼(𝑡) by the second equation of (2.4), we obtain 𝐼(𝑡)=𝐼 for 𝐼(𝑡)𝐼𝑒(𝑟+𝑑+𝜇)𝜏 The same arguments can be continued, we can obtain 𝑡<𝑡<𝑡+𝜄 for 𝜄>𝜏;. Since the interval 𝐼(𝑡)𝐼𝑒(𝑟+𝑑+𝜇)𝜏 is arbitrarily chosen, we can conclude that 𝑡<𝑡<𝑡+𝜏. for 𝐼(𝑡)𝐼𝑒(𝑟+𝑑+𝜇)𝜏 large enough. Based on the above discussions, the choice of 𝑡+𝜏<𝑡<𝑡+𝜄 is independent of the positive solution of (2.4), and we have proved that any positive solution of (2.4) satisfies [𝑡,𝑡+𝜄] for all sufficiently large 𝐼(𝑡)𝑚. This completes the proof.
Theorem 4.4. If 𝑡 then the system (2.4) is permanent.Proof. Suppose that 𝑚 be any solution of (2.4). From the first equation of (2.4), we have𝐼(𝑡)𝑚Similarly, we have𝑡where𝑅2>1,By Theorem 4.3, the third equation of (2.4) becomes(𝑆(𝑡),𝐼(𝑡),𝑅(𝑡),𝑁(𝑡))It is easy to obtain that𝑆(𝑡)𝑝𝐴𝛽𝐴𝜇+𝜇𝑆(𝑡).(4.18)
Setlim𝑡𝑆(𝑡)𝑞,(4.19)By Theorem 3.1 and above discussions, we know that the set 𝑞=𝑝𝐴𝜇𝛽𝐴+𝜇2(1𝜃)1𝑒(𝛽(𝐴/𝜇)+𝜇)𝑇1(1𝜃)𝑒(𝛽(𝐴/𝜇)+𝜇)𝑇𝜀.(4.20) is a global attractor in 𝑅(𝑡)𝑟𝑚(𝜇+𝛼)𝑅(𝑡).(4.21) and, of course, every solution of system (2.4) with initial condition (2.5) will eventually enter and remain in region 𝑅(𝑡)𝑟𝑚𝜇+𝛼𝜀𝜔.(4.22). Hence system (2.4) is permanent. This completes the proof.
Denote Ω0=𝐴(𝑆,𝐼,𝑅,𝑁)𝑞𝑆,𝑚𝐼,𝜔𝑅,𝑆+𝐼+𝑅𝜇,𝐴𝐴𝜇+𝑑𝜀𝑁𝜇.(4.23)Corollary 4.5. The following results are true.
(1)If Ω0 then system (2.4) is permanent.(2)If Ω then system (2.4) is permanent.

5. Discussion

In this paper, we introduce the delayed SEIRS epidemic model with pulse vaccination and nonlinear incidence rate of the form Ω0 As a result, it is observed that nonlinear incidence, the latent period of disease, pulse vaccination rate, and pulse vaccination period bring effects on the dynamics of our model. Theorems 3.1 and 4.4 show that 𝑇1=𝜇1ln𝜃1𝜃1𝛽𝑒𝜇𝜏/𝐴𝑟+𝑑+𝜇𝑎𝛽𝑒𝜇𝜏/,𝜃𝑟+𝑑+𝜇𝑎𝐴𝜇=1𝜇𝑒𝜇𝑇𝐴𝛽𝑒𝜇𝜏/𝑒𝑟+𝑑+𝜇𝑎𝜇𝑇.1+𝜇(4.24) or 𝑇>𝑇, implies that the disease will be eradicated, whereas 𝜃<𝜃, or 𝛽(𝑆(𝑡)𝐼(𝑡)/(1+𝑎𝑆(𝑡))). implies that the disease will be epidemic. Our results indicate that a short pulse time or a large pulse vaccinate rate will lead to eradication of the disease. In this paper, we only discuss 𝑅1<1,𝜃>𝜃, and 𝑇<𝑇 but for closed interval 𝑅2>1,𝜃<𝜃, the dynamical behaviors of system (2.4) have not been studied, that is, the threshold parameter for the reproducing number between the eradication and the permanence of the disease has not been studied, which will be left in the future research.

Acknowledgment

This work was supported by National Natural Science Foundation of China (10771179).

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