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Backward Bifurcation and Optimal Control in Transmission Dynamics of West Nile Virus

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Abstract

The paper considers a deterministic model for the transmission dynamics of West Nile virus (WNV) in the mosquito-bird-human zoonotic cycle. The model, which incorporates density-dependent contact rates between the mosquito population and the hosts (birds and humans), is rigorously analyzed using dynamical systems techniques and theories. These analyses reveal 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) in WNV transmission dynamics. The epidemiological consequence of backward bifurcation is that the classical requirement of having the reproduction number less than unity, while necessary, is no longer sufficient for WNV elimination from the population. It is further shown that the model with constant contact rates can also exhibit this phenomenon if the WNV-induced mortality in the avian population is high enough. The model is extended to assess the impact of some anti-WNV control measures, by re-formulating the model as an optimal control problem with density-dependent demographic parameters. This entails the use of two control functions, one for mosquito-reduction strategies and the other for personal (human) protection, and redefining the demographic parameters as density-dependent rates. Appropriate optimal control methods are used to characterize the optimal levels of the two controls. Numerical simulations of the optimal control problem, using a set of reasonable parameter values, suggest that mosquito reduction controls should be emphasized ahead of personal protection measures.

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References

  • Adams, B.M., Banks, H.T., Davidian, M., Kwon, H.-D., Tran, H.T., Wynne, S.N., Rosenberg, E.S., 2005. HIV dynamics: Modeling, data analysis and optimal treatment protocols. J. Comput. Appl. Math. 184, 10–49.

    Article  MATH  MathSciNet  Google Scholar 

  • Bowman, C., Gumel, A.B., van den Driessche, P., Wu, J., Zhu, H., 2005. A mathematical model for assessing control strategies against West Nile virus. Bull. Math. Biol. 67, 1107–1133.

    Article  MathSciNet  Google Scholar 

  • Blayneh, K., Cao, Y., Kwon, Hee-Dae, 2009. Optimal control of vector-borne diseases: treatment and prevention. Discrete Contin. Dyn. Syst. Ser. 11(3), 587–611.

    Article  MATH  MathSciNet  Google Scholar 

  • Burt, F.J., Grobbelaar, A.A., Leman, P.A., Anthony, F.S., Gibson, G.V.F., Swanepoel, R., 2002. Phylogenetic Relationships of Southern African West Nile virus isolates. CDC: Emerging Infectious Diseases 8(8). http://www.medscape.com/viewarticle/440765

  • Carr, J., 1981. Applications of Centre Manifold Theory. Springer, New York.

    MATH  Google Scholar 

  • Castillo-Chavez, C., Song, B., 2004. Dynamical models of tuberculosis and their applications. Math. Biosci. Eng. 1(2), 361–404.

    MATH  MathSciNet  Google Scholar 

  • Castillo-Chavez, C., Feng, Z., Huang, W., 2002. In: Castillo-Chavez, C., Blower, S., van den Driessche, P., Kirschner, D., Yakubu, A.-A. (Eds.), Mathematical Approaches for Emerging and Reemerging Infectious Diseases. Springer, New York

    Google Scholar 

  • Center for Disease Control and Prevention (2005). West Nive Virus Fact Sheet, September 27, 2005. www.cdc.gov/ncidod/westnile/wnv_factsheet.htm

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

    Article  MathSciNet  Google Scholar 

  • Culshaw, R.V., 2004. Optimal HIV treatment by maximising immune response. J. Math. Biol. 48, 545–562.

    Article  MATH  MathSciNet  Google Scholar 

  • Cushing, J.M., 1998. An Introduction to Structured Population Dynamics. CBMS-NSF Regional Conference Series in Applied Mathematics, vol. 71, SIAM, Philadelphia.

    MATH  Google Scholar 

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

    MathSciNet  Google Scholar 

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

    Google Scholar 

  • Dushoff, J., Wenzhang, H., Castillo-Chavez, C., 1998. Backwards bifurcations and catastrophe in simple models of fatal diseases. J. Math. Biol. 36, 227–248.

    Article  MATH  MathSciNet  Google Scholar 

  • Fleming, W.H., Rishel, R.W., 1975. Deterministic and Stochastic Optimal Control. Springer, New York.

    MATH  Google Scholar 

  • Gourley, S.A., Liu, L.R., Wu, J., 2007. Some vector borne diseases with structured host populations: Extinction and spatial spread. SIAM J. Appl. Math. 67, 408–433.

    Article  MATH  MathSciNet  Google Scholar 

  • Huhn, D.G., James, J.S., Montgomery, P.S., Dworkin, S.M., 2003. West Nile virus in the United States: an update on an emerging infectious disease. Am. Fam. Phys. 68(4), 653–675.

    Google Scholar 

  • Jang, S.R.-J., 2007. On a discrete West Nile epidemic model. Comput. Appl. Math. 26, 397–414.

    Article  MathSciNet  Google Scholar 

  • Joshi, H.R., 2003. Optimal control of HIV immunology model. Optim. Control Appl. Methods 23(4), 199–213.

    Article  Google Scholar 

  • Jianga, J., Qiub, Z., Wu, J., Zhu, H., 2009. Threshold conditions for West Nile virus outbreaks. Bull. Math. Biol. doi:10.1007/s11538-008-9374-6

    Google Scholar 

  • Jung, E., Lenhart, S., Feng, Z., 2002. Optimal control of treatments in a two-strain tuberculosis model. Discrete Contin. Dyn. Syst. Ser. 2(4), 473–482.

    Article  MATH  MathSciNet  Google Scholar 

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

    MathSciNet  Google Scholar 

  • Kilpatric, A.M., Kramer, L.D., Jones, M.J., Marra, P.P., Daszak, P., Fonseca, D.M., 2007. Genetic influences on mosquito feeding behavior and the emergence of zoonotic pathogens. Am. J. Trop. Med. Hyg. 77(4), 667–671.

    Google Scholar 

  • Kirschner, E.D., Lenhart, S., Serbin, S., 1997. Optimal control of the chemotherapy of HIV. J. Math. Biol. 35, 775–792.

    Article  MATH  MathSciNet  Google Scholar 

  • Lenhart, S., Workman, J.T., 2007. Optimal Control Applied to Biological Models. Mathematical and Computational Biology Series. Chapman & Hall/CRC Press, London/Boca Raton.

    MATH  Google Scholar 

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

    Article  Google Scholar 

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

    Article  MathSciNet  Google Scholar 

  • Lukes, D.L., 1982. Differential Equations: Classical to Controlled. Mathematics in Science and Engineering. Academic Press, New York.

    MATH  Google Scholar 

  • NGwa, G.A., Shu, W.S., 2000. A mathematical model for endemic malaria with variable human and mosquito populations. Math. Comput. Model. 32, 747–763.

    Article  MATH  MathSciNet  Google Scholar 

  • Nosal, B., Pellizzari, R., 2003. West Nile virus. CMAJ 168(11), 1443–1444.

    Google Scholar 

  • Ontero, J., Anderson, F., Andreadis, T.G., Main, A.J., Kline, D.L., 2004. Prevalence of West Nile virus in tree canopy-in habiting Culex pipiens and associated mosquitoes. Am. J. Trop. Med. Hyg. 71(1), 112–119.

    Google Scholar 

  • Pontryagin, L.S., Boltyanskii, V.G., Gamkrelidze, R.V., Mishchenko, E.F., 1986. The Mathematical Theory of Optimal Process, vol. 4. Gordon & Breach, New York.

    Google Scholar 

  • Peterson, L.R., Marfin, A.A., 2002. West Nile virus: a primer for the clinician. Ann. Intern. Med. 137(3), 173–179.

    Google Scholar 

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

    Article  MATH  MathSciNet  Google Scholar 

  • Thomas, D.M., Urena, B., 2001. A model describing the evolution of West Nile-like encephalitis in New York city. Math. Comput. Model. 34, 771–781.

    Article  MATH  MathSciNet  Google Scholar 

  • van den Driessche, P., Watmough, J., 2002. Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission. Math. Biosci. 180, 29–48.

    Article  MATH  MathSciNet  Google Scholar 

  • Wonham, M.J., de-Camino-Beck, T., Lewis, M.A., 2004. An epidemiological model for West Nile virus: Invasion analysis and control applications. Proc. R. Soc. Lond. 271, 501–507.

    Article  Google Scholar 

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Correspondence to Abba B. Gumel.

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Blayneh, K.W., Gumel, A.B., Lenhart, S. et al. Backward Bifurcation and Optimal Control in Transmission Dynamics of West Nile Virus. Bull. Math. Biol. 72, 1006–1028 (2010). https://doi.org/10.1007/s11538-009-9480-0

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  • DOI: https://doi.org/10.1007/s11538-009-9480-0

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