Articles

MATHEMATICAL ANALYSIS OF WEST NILE VIRUS MODEL WITH DISCRETE DELAYS

  • Salisu M. GARBA ,
  • Mohammad A. SAFI
Expand
  • Department of Mathematics and Applied Mathematics, University of Pretoria, Pretoria 0002, South Africa; Department of Mathematics, The Hashemite University, Zarqa, Jordan

Received date: 2011-05-31

  Revised date: 2012-09-13

  Online published: 2013-09-20

Abstract

The paper presents the basic model for the transmission dynamics of West Nile virus (WNV). The model, which consists of seven mutually-exclusive compartments representing the birds and vector dynamics, has a locally-asymptotically stable disease-free equilibrium whenever the associated reproduction number (R0) is less than unity.
As reveal in [3, 20], the analyses of the model show the existence of the phenomenon of backward bifurcation (where the stable disease-free equilibrium of the model co-exists with a stable endemic equilibrium when the reproduction number of the disease is less than unity). It is shown, that the backward bifurcation phenomenon can be removed by substituting the associated standard incidence function with a mass action incidence. Analysis of the reproduction number of the model shows that, the disease will persist, whenever R0 > 1, and increase in the length of incubation period can help reduce WNV burden in the community if a certain threshold quantities, denoted by Δb and Δv are  negative. On the other hand, increasing the length of the incubation period increases disease burden if Δb > 0 and Δv > 0. Furthermore, it is shown that adding time delay to the corresponding autonomous model with standard incidence (considered in [2]) does not alter the qualitative dynamics of the autonomous system (with respect to the elimination or persistence of the disease).

Cite this article

Salisu M. GARBA , Mohammad A. SAFI . MATHEMATICAL ANALYSIS OF WEST NILE VIRUS MODEL WITH DISCRETE DELAYS[J]. Acta mathematica scientia, Series B, 2013 , 33(5) : 1439 -1462 . DOI: 10.1016/S0252-9602(13)60095-8

References

[1] Bender K, Thompson F E. West Nile virus: a growing challenge. Amer J Nursing, 2003, 103(6): 32–39

[2] Bowman C, Gumel A B, van den Drissche P, Wu J, Zhu H. Mathematical model for assessing control strategies against West Nile virus. Bull Math Biol, 2005, 67: 1107–1133

[3] Blayneh KW, Gumel A B, Lenhart S, Clayton T. Backward bifurcation and optimal control in transmission dynamics of West Nile Virus. Bull Math Biol, 2010, 72(4): 1006–1028

[4] Brauer F. Backward bifurcation in simple vaccination models. J Math Anal Appl, 2004, 298(2): 418–431

[5] Centers for Disease Control and Prevention. Update: West Nile-like virus encephalitis-New York. Morb Mortal Wkly Rep, 2001, 48: 890–892

[6] Centers for Disease Control and Prevention. West Nile virus: virus history and distribution. 2002,
http://www.cdc.gov/ncidod/dvbid/westnile/background.htm (Accessed March 2010)

[7] Conway John B. Functions of One Complex Variable I. Berlin, Heidelrberg, New York: Springer-Verlag, 1978

[8] Cruz-Pacheco G, Esteva L, Montano-Hirose J A, Vargas D. Modelling the dynamics of West Nile virus. Bull Math Biol, 2005, 67: 1157–1172

[9] Darensburg T, Kocic V. On the discrete model of West Nile-like epidemics. Proc Dyn Appl, 2004, 4: 358–366

[10] Diekmann O, Heesterbeek J A P. Mathematical Epidemiology of Infectious Diseases: Model Building, Analysis and Interpretation. New York: Wiley, 2000

[11] Garba S M, Gumel A B, Abu Bakar M R. Backward bifurcations in dengue transmission dynamics. Math Biosci, 2008, 215(1): 11–25

[12] Garba S M, Gumel A B. Effect of cross-immunity on the transmission dynamics of two strains of dengue. Int J Comp Math, 2007, 87(10): 2361–2384

[13] Garba S M, Safi M A, Gumel A B. Cross-immunity-induced backward bifurcation for a model of trans-mission dynamics of two strains of influenza. Nonlinear Analysis: Real World Applications, 2013, 14: 1384–1403

[14] Gourley S A, Liu R, Wu J. Eradicating vector-borne diseases via age-structured culling. J Math Biol, 2007, 54: 309–335

[15] Gourley S A, Liu R, Wu J. Some vector borne diseases with structured host populations: extinction and spatial spread. SIAM J Appl Math, 2007, 67(2): 408–433

[16] Hale J. Theory of Functional Differential Equations. Heidelberg: Springer-Verlag, 1977

[17] Hayes C G. West Nile fever. In the Arboviruses: Epidemiology and Ecology, 1988, 5: 59–88

[18] Health Canada General information on West Nile virus. 2003, http://www.hc-sc.gc.ca/english/westnile/
general.html (Accessed April 2010)

[19] Hethcote H W. The mathematics of infectious diseases. SIAM Review, 2000, 42: 599–653

[20] Hui W, Huaiping Z. The backward bifurcation in compartmental models for West Nile virus. Math Biosci, 2010, 227: 20–28

[21] Jang S R -J. On a discrete West Nile epidemic model. Comp Appl Math, 2007, 26: 397–414

[22] Kenkre V M, Parmenter R R, Peixoto I D, Sadasiv L. A theoretic framework for the analysis of the West Nile virus epidemic. Comp Math, 2006, 42: 313–324

[23] Lewis M, Renclawowicz J, van den Driessche P. Traveling waves and spread rates for a West Nile virus model. Bull Math Biol, 2006, 66: 3–23

[24] Lewis M A, Renclawowicz J, van den Driesssche P, Wonham M. A comparison of continuous and discrete-time West Nile virus models. Bull Math Biol, 2006, 68: 491–509

[25] Mickens R E. Calculation of denominator functions for nonstandard finite difference schemes for differential
equations satisfying a positivity condition. Numer Methods Partial Differ Equ, 2007, 23: 672–691

[26] Mukandavire Z, Garira W. Age and sex structured model for assessing the demographic impact of mother-to child transmission of HIV/AIDS. Bull Math Biol, 2007, 69(6): 2061–2092

[27] Nosal B, Pellizzari R. West Nile virus. Canad Medical Assoc J, 2003, 168(11): 1443–1444

[28] Rappole J, Derrickson S R, Hubalek Z. Migratory birds and spread of West Nile Virus in the western hemisphere. Emerging Infectious Diseases, 2000, 6: 1–16

[29] Ross R. The Prevention of Malaria. London: John Murray, 1911

[30] Sharomi O, Podder C N, Gumel A B, Elbasha E H, Watmough J. Role of incidence function in vaccine-induced backward bifurcation in some HIV models. Math Biosci, 2007, 210: 436–463

[31] Stuart A M, Humphries A R. Dynamical Systems and Numerical Analysis. New York: Cambridge Uni-versity Press, 1998

[32] Thomas D M, Urena B. A model describing the evolution of West Nile-like encephalitis in New York City. Math Comp Model, 2001, 34: 771–781

[33] van den Driessche P, Watmough J. Reproduction numbers and sub-threshold endemic equilibria for com-
partmental models of disease transmission. Math Biosci, 2002, 180: 29–48

[34] Wang W, Ma Zhien. Global dynamics of an epidemic model with time delay. Nonlinear Analysis: Real World Applications, 2002, 3: 365–373

Outlines

/