- Open Access
Global dynamics for an SIR patchy model with susceptibles dispersal
© Liu et al.; licensee Springer 2012
- Received: 10 January 2012
- Accepted: 20 July 2012
- Published: 1 August 2012
An epidemiological model with suscptibles dispersal between two patches is addressed and discussed. The basic reproduction numbers and are defined as the threshold parameters. It shows that if both and are below unity, the disease-free equilibrium is shown to be globally asymptotically stable by using the comparison principle of the cooperative systems. If is above unity and is below unity, the disease persists in the first patch provided . If is above unity, is below unity, and , the disease persists in the second patch. And if and are above unity, and further and are satisfied, the unique endemic equilibrium is globally asymptotically stable by constructing the Lyapunov function. Furthermore, it follows that the susceptibles dispersal in the population does not alter the qualitative behavior of the epidemiological model.
- H1N1 Influenza
- Epidemic Model
- Comparison Principle
- Endemic Equilibrium
- Basic Reproduction Number
The development of economic globalization and the progression of science and technology yield more and more frequent contact and communication between people in different countries and regions, which further directly accelerates the development of global economy and fosters the prosperity and flourishing of a society. However, the bad things may occur simultaneously, such as, the spread of 2003 SARS and 2009 H1N1 influenza almost throughout the world. SARS involved 30 countries and regions, caused more than 8,000 patients, and 774 deaths [19, 20]. The H1N1 influenza virus quickly spread worldwide due to airplane travel. As of May 6, 2009, the virus had invaded in 23 countries including Mexico and the United States, and a total of 1,882 people were confirmed to be infected by it . It then follows that the studies on the influence of infectious diseases transmission on the global population that formulates patchy models are more and more significant and practical.
A great number of mathematical patchy models have been proposed and analyzed to illustrate the influence of the transmission of infectious diseases on the local population among many countries and regions [1, 2, 7, 12, 18]. But for many mathematical models of infectious diseases in a patchy environment, the global stability of the endemic equilibrium is still an open problem. Motivated by this, in the present paper, a class of simple models with susceptibles dispersal in a patchy environment is to be formulated and investigated the stability of the endemic equilibrium by constructing the Lyapunov function (also see [5, 6, 9–11, 13, 14]).
The rest of this paper is organized as follows. In Sect. 2, the model with susceptibles dispersal between two disjoint patches is formulated, and the existence, uniqueness, and boundedness of the solutions are analyzed. The existence of equilibria and the basic reproduction numbers are derived in Sect. 3. In Sect. 4, the long-term behavior of the model is studied. The brief conclusions and discussions are given in Sect. 5.
() is the recruitment constant rate of the population in the i th patch. () represents the transmission rate in the i th patch. () represents the natural death rate in the i th patch. () is the induced-death rate in the i th patch. () is the recovery rate of the infectious persons in the i th patch. represents the dispersal rate of susceptible individuals from the second patch to the first patch. represents the dispersal rate of susceptible individuals from the first patch to the second patch. All the parameters considered in the present paper are nonnegative. () denotes the number of the total population in the i th patch at time t. Therefore, ().
By applying the Theorem 5.2.1 of , it then follows that for any , system (1) exists a unique local nonnegative solution through the initial value .
System (2) implies . Therefore, is ultimately bounded and all the solutions of system (1) globally exists on the interval . The aforementioned discussions can be summarized into the following results.
is a positively invariant set and attracts all positive orbits in .
Note that the long-time behaviors of the solutions of system (1) are investigated in region Ω instead of the space .
where denotes for the spectral radius of the matrix M, and correspond to the basic reproduction numbers of the first and the second patch when there is no dispersal between two patches, respectively. The proof process of , Theorem 2 implies the following statements.
Let and be the maximum real part of all the eigenvalues of the matrix . Then if and only if , and if and only if ;
Let and be the maximum real part of all the eigenvalues of the matrix . Then if and only if , and if and only if .
In this section, the stability of equilibria is to be formulated. First of all, the global stability of the disease-free equilibrium is to be discussed. There holds the following result.
Theorem 4.1 If the basic reproduction number is less than one, the disease-free equilibrium is globally asymptotically stable; while if the basic reproduction number is greater than one, the disease-free equilibrium is unstable.
tends to the zero solution as t goes to infinity. Let , and . implies and . Lemma 3.1 implies and . By the continuity of and in ε, ε can be chosen small enough so that and . Consequently, the solutions of system (4) approach to zero with t going to infinity. The comparison principle of cooperative systems , Theorem B.1, implies and as . Therefore, the theory of asymptotically autonomous systems , Theorem 1.2, shows that ().
In the case of , , Theorem 2, admits that is unstable, which finishes the theorem. □
Next, the two results regarding the stability of the boundary equilibria are given by applying the so-called Routh-Hurwitz criterion.
Theorem 4.2 If and , the boundary equilibrium is stable when ; while the boundary equilibrium is unstable when .
Routh-Hurwitz criterion implies all the roots of Eq. (5) have a negative real part.
Therefore, yields the boundary equilibrium is locally stable; while demonstrates the boundary equilibrium is unstable. □
Theorem 4.3 If and , the boundary equilibrium is stable when ; while the boundary equilibrium is unstable when .
by using the Routh-Hurwitz criterion, it then follows that the real part of all the solutions of (6) is negative.
Furthermore, it is easier to see that if , the boundary equilibrium is locally stable; while if , the boundary equilibrium is unstable. □
Now we are in the position to discuss the global stability of the endemic equilibrium.
then the endemic equilibrium is globally asymptotically stable.
Proof Conditions (i)-(iv) imply system (1) exists the endemic equilibrium . Next, we study the stability of the endemic equilibrium by using the Lyapunov approach.
The inequality of arithmetic-geometric mean implies . The equality holds if and only if . That is, when and , . By using the LaSalle invariant principle , the endemic equilibrium is globally asymptotically stable. □
In this paper, an infectious diseases model with susceptibles dispersal between two disjoint patches has been proposed and analyzed to investigate the impact of susceptibles dispersal on diseases transmission in the whole population. The existence of equilibria is obtained and the basic reproduction numbers , , and are defined. It is indicated that and are two important threshold parameters to determine the long-term behavior of the solutions of system (1). The disease-free equilibrium is globally asymptotically stable and the disease ultimately dies out by applying the comparison principle of cooperative systems if the basic reproduction numbers both and are below unity. The disease persists in patch one and can be eradicated in patch two if is above one, is below one, and . The disease persists in patch two and can be eradicated in patch one if is above one, is below one, and . While the disease uniformly persists in the whole population and the endemic equilibrium is globally asymptotically stable by using the Lyapunov approach if the conditions , , , and are satisfied.
System (1) almost shares the same qualitative behavior as the simple epidemic model if dispersal can not be considered in the population. The patchy models need not be considered if only susceptibles disperse among patches. Furthermore, all the patches can be thought of as just one patch and susceptibles dispersal has no influence on disease transmission.
The authors are grateful to the referee for her/his valuable remarks which led to improvement of the article. This work was supported in part by the National Nature Science Foundation of China (NSFC 11001215, 11101126, and 11101127), the Scientific Research Foundation for Doctoral Scholars of Haust (09001535), and the Foundation of Shaanxi Educational Committee (12JK0859).
- Brauer F, van den Driessche P: Models for transmission of disease with immigration of infectives. Math. Biosci. 2001, 171: 143–154. 10.1016/S0025-5564(01)00057-8MathSciNetView ArticleGoogle Scholar
- Brauer F, van den Driessche P, Wang L: Oscillations in a patchy environment disease model. Math. Biosci. 2008, 215: 1–10. 10.1016/j.mbs.2008.05.001MathSciNetView ArticleGoogle Scholar
- Centers for Disease Control and Prevention: Update: Novel influenza A (H1N1) virus infections-worldwide, May 6, 2009. Morb. Mort. Wkly. Rep. 2009, 58: 453–458.Google Scholar
- van den Driessche P, Watmough J: Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission. Math. Biosci. 2002, 180: 29–48. 10.1016/S0025-5564(02)00108-6MathSciNetView ArticleGoogle Scholar
- Guo H, Li MY: Global dynamics of a staged progression model for infectious diseases. Math. Biosci. Eng. 2006, 3: 513–525.MathSciNetView ArticleGoogle Scholar
- Guo H, Li MY: Global dynamics of a staged-progression model with amelioration for infectious diseases. J. Biol. Dyn. 2008, 2: 154–168. 10.1080/17513750802120877MathSciNetView ArticleGoogle Scholar
- Hethcote HW: Qualitative analysis of communicable disease models. Math. Biocsi. 1976, 28: 335–356.MathSciNetView ArticleGoogle Scholar
- LaSalle JP: The Stability of Dynamical Systems. SIAM, Philadelphia; 1976.View ArticleGoogle Scholar
- Li M, Shuai Z: Global-stability problem for coupled systems of differential equations on networks. J. Differ. Equ. 2010, 248: 1–20. 10.1016/j.jde.2009.09.003MathSciNetView ArticleGoogle Scholar
- Li MY, Shuai Z, Wang C: Global stability of multi-group epidemic models with distributed delays. J. Math. Anal. Appl. 2010, 361: 38–47. 10.1016/j.jmaa.2009.09.017MathSciNetView ArticleGoogle Scholar
- Liu L, Zhou Y, Wu J: Global dynamics in a TB model incorporating case detection and two treatment stages. Rocky Mt. J. Math. 2008, 38: 1541–1559. 10.1216/RMJ-2008-38-5-1541MathSciNetView ArticleGoogle Scholar
- Lloyd A, May RM: Spatial heterogeneity in epidemic models. J. Theor. Biol. 1996, 179: 1–11. 10.1006/jtbi.1996.0042View ArticleGoogle Scholar
- Mccluskey CC: Lyapunov functions for tuberculosis models with fast and slow progression. Math. Biosci. Eng. 2006, 3: 603–614.MathSciNetView ArticleGoogle Scholar
- O’Regan SM, Kelly TC, Korobeinikov A, O’Callaghan MJA, Pokrovskii AV:Lyapunov functions for and epidemic models. Appl. Math. Lett. 2010, 23: 446–448. 10.1016/j.aml.2009.11.014MathSciNetView ArticleGoogle Scholar
- Smith HL Mathematical Surveys and Monographs 41. In Monotone Dynamical Systems: An Introduction to the Theory of Competitive and Cooperative Systems. Am. Math. Soc, Providence; 1995.Google Scholar
- Smith HL, Walman P: The Theory of the Chemostat. Cambridge Univ. Press, Cambridge; 1995.View ArticleGoogle Scholar
- Thieme HR: Convergence results and a Poincaré-Bendison trichotomy for asymptotical autonomous differential equations. J. Math. Biol. 1992, 30: 755–763.MathSciNetView ArticleGoogle Scholar
- Wang W, Zhao X-Q: An epidemic model in a patchy environment. Math. Biosci. 2004, 190: 97–112. 10.1016/j.mbs.2002.11.001MathSciNetView ArticleGoogle Scholar
- World Health Organization: Summary table of SARS cases by country, 1 November 2002–7 August 2003, http://www.who.int/csr/sars/country/2003_8_5/en. Accessed 15 August 2003
- World Health Organization: WHO guidelines for the global surveillance of severe acute respiratory syndrome (SARS). http://www.who.int/csr/resources/publications/WHO_CDS_CSR_ARO_2004_1/en/index.html
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