Multiple Endemic Solutions in an Epidemic Hepatitis B Model without Vertical Transmission

Abstract

This paper examines the dynamics of Hepatitis B via a Susceptible Exposed Infectious Recovered (SEIR) type epidemic model. Previous studies have shown that Hepatitis B is characterized by multiple endemic solutions, a matter which may be of concern in developing control strategies. We identify the possible causes of multiple endemic solutions in a Hepatitis B model and conclude that the dependance of the probability of carriage development  (q(Λ)) on the force of infection (Λ) is the main reason for multiple endemicity. Other factors such as a large proportion of infants that are not vaccinated (ω) may also enhance the possibility of multiple endemicity. The role of carriers may also play a key role in the possibility of such complex dynamics, i.e., when infectiousness of carriers-(α) is high, the probability of existence of multiple endemic equilibrium solutions is increased. In our arguments, the traditional reproduction number R0< 1 which we define here by a function G(0) < 1 does not imply stability of disease-free equilibrium.

Share and Cite:

Onyango, N. (2014) Multiple Endemic Solutions in an Epidemic Hepatitis B Model without Vertical Transmission. Applied Mathematics, 5, 2518-2529. doi: 10.4236/am.2014.516242.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] Kuznetsov, A.Y. (2004) Elements of Applied Bifurcation Theory. 3rd Edition, Springer, Berlin.
http://dx.doi.org/10.1007/978-1-4757-3978-7
[2] Guckenheimer, J. and Holmes, P. (1983) Nonlinear Oscillations, Dynamical Systems and Bifurcations of Vector Fields. Springer, Berlin.
http://dx.doi.org/10.1007/978-1-4612-1140-2
[3] Edmunds, W.J., Medley, G.F. and Nokes, D.J. (1996) The Transmission Dynamics and Control of Hepatitis-B Virus in the Gambia. Statistics in Medicine, 15, 2215-2233.
http://dx.doi.org/10.1002/(SICI)1097-0258(19961030)15:20<2215::AID-SIM369>3.0.CO;2-2
[4] Medley, G.F., Lindop, N.A., Edmunds, W.J. and Nokes, D.J. (1996) Hepatitis-B Virus Endemicity: Heterogeneity, Catastrophic Dynamics and Control. Nature Medicine, 7, 916-624.
[5] Zhao, S., Xu, Z. and Lu, Y. (2000) A Mathematical Model of Hepatitis B Virus Transmission and Its Application for Vaccination Strategy in China. International Journal of Epidemiology, 29, 744-752.
http://dx.doi.org/10.1093/ije/29.4.744
[6] Inaba, H. (2006) Mathematical Analysis of an Age Structured SIR Epidemic Model with Vertical Transmission. Discrete and Continuous Dynamical Systems, Series B, 6, 69-96.
http://dx.doi.org/10.3934/dcdsb.2006.6.69
[7] Webb, G.F. (1985) Theory of Non-Linear Age Dependent Population Dynamics. Marcel Dekker Inc., New York.
[8] Pruess, J. and Schappacher, W. (1984) Semigroup Methods for Age-Structured Population Dynamics. In: Chatterji, S., Fuchstainer, B., Kulisch, U. and Liedl, R., Eds., Jarbuch überblicke Mathematik, Viewing Verlag.
[9] Thieme, H.R. (2003) Mathematics in Population Biology. Princeton University Press, New Jersey.
[10] Dietz, K. and Schlenze, D. (1985) Mathematical Models for Infectious Disease Statistics, a Celebration of Statistics. In: Atkinson, A.C. and Fienberg, S.E., Eds., The ISI Centenary Volume, Springer-Verlag, New York.
[11] Müller, J. (1998) Optimal Vaccination Patterns in Age-Structured Populations. SIAM Journal on Applied Mathematics, 59, 222-241.
http://dx.doi.org/10.1137/S0036139995293270
[12] Grippenberg, G. (1983) On a Non-Linear Intergral Equation Modeling an Epidemic in an Age-Structured Population. Journal for Pure and Applied Mathematics, 341, 56-67.
[13] Inaba, H. (1990) Threshold and Stability Results for an Age-Structured Epidemic Model. Journal of Mathematical Biology, 28, 411-434.
http://dx.doi.org/10.1007/BF00178326
[14] Diekmann, O., Heesterbeek, J.A.P. and Metz, J.A.J. (1990) On the Definition and the Computation of the Basic Reproduction Ratio R0 in Models for Infectious Diseases in Heterogeneous Populations. Journal of Mathematical Biology, 28, 365-382.
http://dx.doi.org/10.1007/BF00178324
[15] Li, J., Blakeley, D. and Smith, R.J. (2011) The Failure of R0. Computational and Mathematical Methods in Medicine, 2011, Article ID: 527610.
[16] Chavez, C.C. and Song, B. (2004) Dynamical Models of Tuberculosis and Their Applications. Mathematical Bioscience and Engineering, 1, 361-404.
http://dx.doi.org/10.3934/mbe.2004.1.361
[17] Hadeler, K.P. and Van den Driessche, P. (1997) Backward Bifurcation in Epidemic Control. Mathematical Biosciences, 146, 15-35.
http://dx.doi.org/10.1016/S0025-5564(97)00027-8
[18] Sharomi, O., Podder, C.N., Gumel, A.B., Elbasha, E.H. and Watmough, J. (2000) Role of Incidence Function in Vaccine-Induced Backward Bifurcation in Some HIV Models. Mathematical Biosciences, 210, 436-463.
http://dx.doi.org/10.1016/j.mbs.2007.05.012
[19] Garba, S.M., Gumel, A.B. and Bakar, M.R.A. (2008) Backward Bifurcations in Dengue Transmission Dynamics. Mathematical Biosciences, 215, 11-25.
http://dx.doi.org/10.1016/j.mbs.2008.05.002
[20] Reluga, T.C., Medlock, J. and Perelson, A.S. (2008) Backward Bifurcations and Multiple Equilibria in Epidemic Models with Structured Immunity. Journal of Theoretical Biology, 252, 155-165.
http://dx.doi.org/10.1016/j.jtbi.2008.01.014
[21] Robotin, M.C. (2011) Hepatitis B Prevention and Control: Lessons from the East and the West. World Journal of Hepatology, 3, 31-37.
http://dx.doi.org/10.4254/wjh.v3.i2.31

Copyright © 2023 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.