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Abstract and Applied Analysis

Volume 2014 (2014), Article ID 427639, 10 pages

http://dx.doi.org/10.1155/2014/427639

## Stability Analysis of Hepatitis B Virus Model with Incomplete Immunization of HepB Vaccine

^{1}School of Mathematical Sciences, Dalian University of Technology, Dalian 116024, China^{2}Department of Mathematics, Tonghua Normal University, Tonghua 136000, China^{3}School of Innovation Experiment, Dalian University of Technology, Dalian 116024, China

Received 25 March 2014; Accepted 19 May 2014; Published 12 June 2014

Academic Editor: Abdul Latif

Copyright © 2014 Yan Cheng et al. 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

In this paper a HBV infection model with impulsive vaccination is considered. By using fixed point theorem and stroboscopic map we prove the existence of disease-free T-periodic solution. Also by comparative theorem of impulsive differential equation we get the global asymptotic stability of the disease-free periodic solution and permanence of the disease. Numerical simulations show the influence of parameters on the dynamics of HBV, which provided references for seeking optimal measures to control the transmission of HBV.

#### 1. Introduction

Hepatitis B is a potentially life-threatening liver infection caused by the hepatitis B virus (HBV) and is a major global health problem. According to the data of World Health Organization (WHO), more than 2,000 million people have been infected with HBV and about 350 million remain infected chronically. Every year there are over 4 million acute clinical cases of HBV and about 25% of carriers. Hepatitis B causes about 1 million people to die from chronic active hepatitis, cirrhosis, or primary liver cancer annually [1].

The transmission of HBV occurs normally on contact with infected blood or body fluids. In high prevalence populations, transmission is largely vertical, that is, through mother to child during delivery or horizontal through household contact as skin breaches, open sores, or scratches in the early years of life. In contrast, HBV transmission in low endemicity populations typically occurs in adults via parenteral exposures and intravenous drug use or through sexual contact [2]. It can cause acute and chronic infection status. In acute infection status the individuals have highly infectiousness, and about 90% of adults who are infected with HBV will recover and be completely rid of the virus within six months. The rest of acute infectors turn into chronic infectors and acute hepatitis B occurs rarely in infants. The major routes of chronic hepatitis B infection are mother-infant vertical transmission and early childhood horizontal transmission [3]. Only a small fraction of chronic infectors could be cured completely [4]. Continuous chronic HBV infection exhibits various kinds of clinical symptoms, such as hepatocirrhosis and even hepatocellular carcinoma [5].

Vaccination is an effective control measures for HBV infection, an universal vaccination programme promoted in more than 170 countries since 1982 [6]. In New Zealand, the widespread introduction of infant hepatitis B vaccination in 1988 led to a dramatic decline in cases of acute HBV infection [7]. From 2002, the Ministry of Health of China integrated the infant HepB vaccination into the national immunization program with vaccine provided entirely by the government. According to 2006–2010 hepatitis B control program, China will consistently strengthen the general newborn hepatitis B vaccination and especially supply the first dose of 3-dose HepB series as soon as possible after birth [8].

Mathematical models have been used frequently to study the transmission dynamics of HBV, and qualitative results on such models can be found. Anderson and May first used a simple mathematical model to illustrate the effects of carriers on the transmission of HBV [9]. Thornley et al. [10] develop a hepatitis B mathematical model, proposed by Medley et al. [11], that was used to develop a strategy for eliminating the HBV spread in New Zealand in 2008. Zou et al. also proposed a mathematical model to understand the transmission dynamics and prevalence of HBV in mainland China [12]. Pang et al. [13] develop a model to explore the impact of vaccination and other controlling measures of HBV infection and a mathematical model which describes the spread of HBV is formulated in [14]. Zou et al. [15] promote an age structure model to predict the dynamics of HBV transmission and evaluate the long-term effectiveness of the vaccination programme in China. Wang et al. proposed and analyzed the hepatitis B virus infection in a diffusion model confined to a finite domain [16]. A hepatitis B virus (HBV) model with spatial diffusion and saturation response of the infection rate is investigated by Xu and Ma [17]. Transmission model of hepatitis B virus with the migration effect is presented by Khan et al. [18] who analyzed the effect of immigrants in the model to study the effect of immigrants for the host population.

In the above literatures, most models involving HepB vaccine strategy often assumed that the vaccine is completely effective in preventing the infection of vaccinated individuals. In fact, it is well known to all that the HepB vaccine should be taken in three doses at 0, 1, and 6 months. Usually 30–50% of individuals will gain anti-HBs antibody after the first dose, 80–90% will gain after the second dose, and almost all the individuals will have high anti-HBs concentrations one month after the last dose that 99.8% of vaccinees gained anti-HBs antibody [19]. So, as soon as the susceptible individuals begin the vaccination process, they are different from susceptible individuals. But they should also be distinguished from recovered individuals who have immunity against the disease. It means that a few of vaccinated individuals may still be susceptible to infection, but they will be infected at a lower rate than unvaccinated susceptible individuals. Epidemic models including incomplete immune compartment have been studied in [20–24], but the HBV transmission with the incomplete HepB vaccine immune is rarely considered.

Motivated by the above consideration, and based on the natural course of HBV infection, we promote a novel model to describe the transition dynamic of HBV. It is more reasonable to consider the impulsive vaccination strategy for the susceptible individuals; there are fewer literatures that researched HBV infection with impulsive vaccination already [25, 26]. We also consider the incomplete immune compartment in our model.

The remaining parts of this paper are organized as follows. In Section 2, we formulate the model. In Section 3, we study the global asymptotic stability of disease-free periodic solution and the conditions for the permanence of the disease by comparison techniques. Numerical simulations are presented in Section 4. In Section 5, we conclude this paper with some remarks.

#### 2. Modeling

Based on the fact that HepB vaccination is not completely effective, we improve the model of Zou et al. [12] in three aspects. Firstly, we considered that vaccinated individuals may still be susceptible to infection. Secondly, we studied impulsive vaccination strategy for the susceptible individuals. Finally, we add a latent period . We divide the population into six epidemiological groups: the susceptible individuals to infection ; latently infected ; those acute infectors ; chronic sufferers ; and recovered ; denotes the density of vaccinees who have begun the vaccination process. The individuals in are different from those in and ; the immune system will create antibody of HBV because vaccination doses are taken during this process, but it may not be in a fully protective level. According to the characteristics of HBV transmission, the flow diagram is shown in Figure 1.

The mathematical model of the transmission dynamics and prevalence of HBV is as follows: In these equations, all the parameters are nonnegative. is the per capita natural death rate and the birth rate of newborns, and is the per capita disease-induced death rate. is the transmission coefficient of acute HBV, and is the reduced transmission coefficient of chronic HBV. is the proportion of births without successful vaccination. is the rate at which individuals leave the acute infection class; a proportion of acute infection individuals become chronic carriers and other proportion rid of HBV, move directly to immunity class . is the recovery conversion rate of chronic infectors. is the proportion of unimmunized children born to chronic carrier mothers who have been infected (ignore perinatal infection of children born to mothers with acute infection). That denotes newborns who have been infected in perinatal infection and in chronic infection compartment, the rest newborns become susceptible individuals. The factor reflects the efficacy of vaccine, which means that the vaccine is not completely effective and that the vaccinated individuals have only partial immunity. For the vaccinated individuals, let denote the per capita rate coefficient at which the immunity wears off, which implies that the vaccinated individuals have the temporary immunity. is the fraction of impulsive vaccination, and is latent period. The period of vaccination is , and the vaccination is dose at time , .

Since the equations for the variables and in model (1) are both independent of other equations, then the dynamical behavior of (1) is determined by the following system: The initial conditions for system (2) take the forms For it follows that . Set is positively invariant of system (2).

Subsequently, we introduce the following lemma, which is useful for the later proof.

Lemma 1. *Consider the following impulsive differential equation:
**
Then the above system has a unique positive periodic solution given by
**
Consider that , which is globally asymptotically stable, where
*

*Proof. *It is easy to obtain the analytical solution of (4) between pulses as follows:
Furthermore, after each successive pulse, we can deduce the following stroboscopic map:
Denote ; then we have the following equations:
The unique positive fixed point is (), where
So, (4) has a unique period solution with initial values of .

In the following we prove the global stability of the period solution, and it suffices to prove the global stability of the fixed point (). The proof is similar to the proof of Lemma 2.1 in [22], so we omit the subsequent proof.

Lemma 2 (see [27]). *Assume that the sequence satisfies with . Let be quasi-monotone nondecreasing in x for each t, and is nondecreasing in u for . Suppose that , satisfy
**
Then implies that for .*

Lemma 3 (see [28]). *Consider the following equation: , where , , , and for . We have
*

#### 3. Stability and Persistence

##### 3.1. Global Stability of the Disease-Free Periodic Solution

Now we will prove the disease-free periodic solution is locally stable and globally attractive. We first demonstrate the existence of the disease-free periodic solution, in which infectious individuals are entirely absent from the population permanently; that is, and for all . Under this condition, the growth of susceptible individuals must satisfy By Lemma 1, we obtain the periodic solution of system (13): where is globally asymptotically stable. Hence, the system (2) has a disease-free periodic solution .

Denote

Theorem 4. *Let be any solution of (2); then the disease-free periodic solution is globally asymptotically stable provided that and .*

*Proof . *Since and , we can choose sufficiently small such that
From the equations of system (2), we have and ; then we consider the following comparison system with pulse:
In view of Lemma 1, we obtain
where
By Lemma 2 there exists an integer , such that
Furthermore, from the second and third equations, we have
for , . Then, according to (17) and Lemma 3, we have . So, ; there must exist an integer , such that , for all .

When , from the first equation of system (2), we have
Consider the following comparison impulsive differential equation for all :
By Lemma 1, we have the unique periodic solution of system (25) given by
where
By comparison theorem, there exists an integer such that
Because , , , and are sufficiently small, it follows from (22) and (28) that , . Therefore, the disease-free solution of system (2) is globally attractive. The proof is completed.

Theorem 4 determines the global attractiveness of (2) in for the cases and . Its epidemiological implication is that the infectious population vanishes in time so the disease dies out.

##### 3.2. Persistence

In this section we say the disease is endemic if the infectious population persists above a certain positive level for sufficiently large time. The endemicity of the disease can be well captured and studied through the notion of uniform persistence.

*Definition 5. *System (2) is said to be uniformly persistent if there exist positive constants , (both are independent of the initial values), such that every solution with positive initial conditions of system (2) satisfies

Theorem 6. *If and , then there is a positive constant such that each positive solution of system (2) satisfies for all sufficiently large.*

*Proof. *Let be any solution with initial values of system (2); then it is obvious that , , , and for all . We are left to prove that there exist positive constants , , , and ( is sufficiently large) such that , , and for all .

Firstly, from the first equation of system (2), we have
Consider the following comparison equations:
By Lemma 1 and the comparison theorem there exist , ; we know that for any sufficiently small , there exists a ( is sufficiently large) such that
Next, we will prove that there exist and a sufficiently large such that for all .

Since and , there exist and sufficiently small such that
where and are as in (38).

We claim that for any , it is impossible that for all . Suppose that the claim is not valid. There exists a such that for all . It follows from the first and fourth equations of system (2) that for ,
Consider the comparison impulsive system for :
According to Lemma 1, (35) have unique periodic solution
where
So there exists such that
for all .

We denote
From (2), we have
for .

From (33), we obtain , for , which implies that , . This is contrary to the fact that is bounded. Hence, there exists a such that .

Next we prove that there exists a such that any positive solution of (2) satisfies .

Define
where .

First, if for all , then our aim is obtained.

Second oscillates about for all large ; setting , there are two possible cases for .

We hope to show that for all large . The conclusion is evident in the first case. For the second case, let and satisfy , and , for . Therefore, it is certain that there exists a such that
In this case, we will discuss three possible cases in terms of the sizes of , , and .*Case I*. If , then for .*Case II*. If , then from equations of system (2), we can deduce , where for and ; it is obvious that for .*Case III.* If , we will consider the following two cases, respectively.*Case IIIa*. For , it is easy to obtain .*Case IIIb*. For , it is easy to obtain . Then, proceeding exactly as the proof for the above claim, we see that for . Since this kind of interval is chosen in an arbitrary way (we only need to be large), we conclude that for all large in the second case. In view of our above discussions, the choices of are independent of the positive solution, and we have proved that any positive solution of (2) satisfies for all large . The proof is completed.

#### 4. Numerical Simulations

In this section, we present some numerical simulations to demonstrate the transmission dynamic of HBV. According to the natural history of HBV transmission and prior research [10, 12], we set some parameter values of the model: ; ; ; ; ; ; ; ; ; ; ; ; . And we choose , respectively; the number of susceptible individuals, latently infected, acute infectors and chronic sufferers are seen in Figure 2. It is easy to see that the lower of (the higher of vaccine efficacy) the fewer of the number of infected individuals. So, knowing the efficacy of HBV vaccine is necessary for the extinct of disease.

In order to find better control strategies for HBV infection, we would like to see what parameters can affect the change of the acute infectors number. From Figure 3(a) we can see that the increase of and decrease of will make the number of acute infectors lower. If is higher, that is to say, the efficacy of vaccination is lower, higher vaccination cannot keep the disease extinct. So, to control the disease spread, knowing the vaccine efficacy is important.

In Figure 3(b) we plot the number of acute infectors which change with parameters and . We can see that with the increase of the number of acute infectors decreases even if the efficacy of vaccination is lower. That is to say, take measures to cure the acute infectors in time is a necessary method to decrease the number of acute infectors. So, doing check regularly and treatment at early time are necessary. In Figure 3(c) we find not only the increase of but also the parameter has effect on the number of acute infections; the higher the acute individuals treatment rate, the lower the number of acute infections.

In Figure 3(d), we detect that the decrease of and will make the number of infected individuals lower. So successful immunization of both newborns and susceptible individuals is an efficient intervention strategy. The optimal control strategy will be a combination of improving the vaccine efficacy, increasing the immunization of newborns and susceptible individuals, and increasing the treatment to the acute infected individuals.

#### 5. Conclusion

Hepatitis B virus is highly prevalent in many countries of the world; we promote a new epidemic model based on the spread characters of the HBV, and consider the fact that the HepB vaccine is incomplete immunization in the vaccination process. Our model is more approach to the realistic problem and different from [13, 14]. Moreover, the methods in disposing the model are different from the existing results because more factors are considered. We find when and ; the disease-free periodic solution is globally attractive; if and , the disease is permanent by using the comparison theorem of impulsive differential equation. By some simulation experiments, Figures 2 and 3 show some effects of parameters on the number of acute individuals and provides an optimal control strategy for the HBV transmission.

#### Conflict of Interests

The authors declare that there is no conflict of interests regarding the publication of this paper.

#### Acknowledgment

The work is supported by the National Natural Science Foundation of China (no. 1124319).

#### References

- World Health Organization,
*Hepatitis B*, WHO/CDS/CSR/LYO/2002.2: Hepatitis B, 2002, http://www.who.int/csr/disease/hepatitis/whocdscsrlyo20022/en/. - New Zealand Ministry of Health,
*Immunisation Handbook 2006*, New Zealand Ministry of Health, Wellington, New Zealand, 2006. - J.-D. Jia, “Hepatitis B in China: From guideline to practice,”
*Virologica Sinica*, vol. 23, no. 2, pp. 152–155, 2008. View at Publisher · View at Google Scholar · View at Scopus - S. J. Liu and Q. Zhu,
*HBV Disabusing and Answering Doubt*, Chinese Medicine and Scientific Technology, Beijing, China, 2003. - B. Ezquieta, E. Cueva, A. Oliver, and R. Gracia, “SHOX intragenic microsatellite analysis in patients with short stature,”
*Journal of Pediatric Endocrinology and Metabolism*, vol. 15, no. 2, pp. 139–148, 2002. View at Google Scholar · View at Scopus - F.-M. Lu and H. Zhuang, “Management of hepatitis B in China,”
*Chinese Medical Journal*, vol. 122, no. 1, pp. 3–4, 2009. View at Publisher · View at Google Scholar · View at Scopus - World Health Organisation, “Hepatitis B vaccines. Position paper,”
*Weekly Epidemiol Record*, vol. 40, pp. 405–420, 2009. View at Google Scholar - New Zealand Ministry of Health,
*Immunisation Handbook 2002*, New Zealand Ministry of Health, Wellington, New Zealand, 2002. - R. M. Anderson and R. M. May,
*Disease of Humans: Dynamics and Control*, Oxford University Press, Oxford, UK, 1991. - S. Thornley, C. Bullen, and M. Roberts, “Hepatitis B in a high prevalence New Zealand population: a mathematical model applied to infection control policy,”
*Journal of Theoretical Biology*, vol. 254, no. 3, pp. 599–603, 2008. View at Publisher · View at Google Scholar · View at MathSciNet - G. F. Medley, N. A. Lindop, W. J. Edmunds, and D. J. Nokes, “Hepatitis-B virus endemicity: Heterogeneity, catastrophic dynamics and control,”
*Nature Medicine*, vol. 7, no. 5, pp. 619–624, 2001. View at Publisher · View at Google Scholar · View at Scopus - L. Zou, W. Zhang, and S. Ruan, “Modeling the transmission dynamics and control of hepatitis B virus in China,”
*Journal of Theoretical Biology*, vol. 262, no. 2, pp. 330–338, 2010. View at Publisher · View at Google Scholar · View at MathSciNet - J. Pang, J.-a. Cui, and X. Zhou, “Dynamical behavior of a hepatitis B virus transmission model with vaccination,”
*Journal of Theoretical Biology*, vol. 265, no. 4, pp. 572–578, 2010. View at Publisher · View at Google Scholar · View at MathSciNet - S. Zhang and Y. Zhou, “The analysis and application of an HBV model,”
*Applied Mathematical Modelling*, vol. 36, no. 3, pp. 1302–1312, 2012. View at Publisher · View at Google Scholar · View at MathSciNet - L. Zou, S. Ruan, and W. Zhang, “An age-structured model for the transmission dynamics of hepatitis B,”
*SIAM Journal on Applied Mathematics*, vol. 70, no. 8, pp. 3121–3139, 2010. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet - K. Wang, W. Wang, and S. Song, “Dynamics of an HBV model with diffusion and delay,”
*Journal of Theoretical Biology*, vol. 253, no. 1, pp. 36–44, 2008. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet - R. Xu and Z. Ma, “An HBV model with diffusion and time delay,”
*Journal of Theoretical Biology*, vol. 257, no. 3, pp. 499–509, 2009. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet - M. A. Khan, S. Islam, M. Arif, and Z. Ul Haq, “Transmission model of hepatitis b virus with the migration effect,”
*BioMed Research International*, vol. 2013, Article ID 150681, 10 pages, 2013. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus - A. Gabbuti, L. Romanò, P. Blanc et al., “Long-term immunogenicity of hepatitis B vaccination in a cohort of Italian healthy adolescents,”
*Vaccine*, vol. 25, no. 16, pp. 3129–3132, 2007. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus - X. Liu, Y. Takeuchi, and S. Iwami, “SVIR epidemic models with vaccination strategies,”
*Journal of Theoretical Biology*, vol. 253, no. 1, pp. 1–11, 2008. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet - Y. Xiao and S. Tang, “Dynamics of infection with nonlinear incidence in a simple vaccination model,”
*Nonlinear Analysis: Real World Applications*, vol. 11, no. 5, pp. 4154–4163, 2010. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet - J. Li and Y. Yang, “SIR-SVS epidemic models with continuous and impulsive vaccination strategies,”
*Journal of Theoretical Biology*, vol. 280, no. 1, pp. 108–116, 2011. View at Publisher · View at Google Scholar · View at MathSciNet - X. Song, Y. Jiang, and H. Wei, “Analysis of a saturation incidence SVEIRS epidemic model with pulse and two time delays,”
*Applied Mathematics and Computation*, vol. 214, no. 2, pp. 381–390, 2009. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet - Y. Jiang, H. Wei, X. Song, L. Mei, G. Su, and S. Qiu, “Global attractivity and permanence of a delayed SVEIR epidemic model with pulse vaccination and saturation incidence,”
*Applied Mathematics and Computation*, vol. 213, no. 2, pp. 312–321, 2009. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet - M. Qiao, H. Qi, and Y. Chen, “Qualitative analysis of hepatitis B virus infection model with impulsive vaccination and time delay,”
*Acta Mathematica Scientia B*, vol. 31, no. 3, pp. 1020–1034, 2011. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet - M. Qiao, A. Liu, and U. Foryś, “Qualitative analysis of the SICR epidemic model with impulsive vaccinations,”
*Mathematical Methods in the Applied Sciences*, vol. 36, no. 6, pp. 695–706, 2013. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet - V. Lakshmikantham, D. D. Baĭnov, and P. S. Simeonov,
*Theory of Impulsive Differential Equations*, vol. 6 of*Series in Modern Applied Mathematics*, World Scientific, Singapore, 1989. View at MathSciNet - Y. Kuang,
*Delay Differential Equations with Applications in Population Dynamics*, vol. 191 of*Mathematics in Science and Engineering*, Academic Press, New York, NY, USA, 1993. View at MathSciNet