×

Modeling approach to assess the transmission dynamics of hepatitis B infection in Africa. (English) Zbl 1467.92220

Summary: Hepatitis B virus infection remains a major public health concern in many developing countries in the world. In this paper, we formulate and analyse a simple deterministic model to assess the dynamics and control of the disease using ordinary differential equations. To analyse the effect of the initial transmission of the disease we compute the basic reproduction number \(\mathscr{R}_0\) and perform stability analysis. The results show that both the disease-free equilibrium and the endemic equilibrium are globally stable with respect to the value of \(\mathscr{R}_0\). Results also show that \(\mathscr{R}_0\) is highly affected by the vertical transmission and the recovery rate of the chronic carriers after screening and treatment. Therefore, effective mechanisms which will reduce vertical transmission are needed as well as effective screening of individuals, so that those who will be found infected get treated. Further results from numerical analysis show that when the disease is introduced in the population it is persistent and therefore effective control mechanisms are required.

MSC:

92D30 Epidemiology
34D20 Stability of solutions to ordinary differential equations

References:

[1] S. Locarnini, Molecular virology of hepatitis B virus, Semin. Liver Dis. 24(suppl. 1)(2014) 3-10.
[2] CDC (2016), Hepatitis B General information. Retrieved on May 21st, 2018.
[3] A. V. Kamyad,R. Akhari, A. A. Heydari, A. Heydari, Mathematical modeling of transmission dynamics and optimal control ovaccination and treatment for hepatitis B virus, Comput. and Math. Methods in Med. 2014 (2014) 1-15. · Zbl 1307.92275
[4] J. Mann, M. Roberts, Modeling the epidemiology of hepatitis B in New Zealand, J. Theor. Bio. 269(1)(2001) 266 272. · Zbl 1307.92348
[5] R. Williams, Global challenges in liver disease, Hepatology 44(3)(2006) 521 - 526.
[6] R. M. Anderson, R. M. May, Infectious disease of humans: dynamics and control. Oxford University Press, Oxford, 1991.
[7] R. M. Anderson, R. M. May, D. J. Nokes, Preliminary analyses of the predicted impacts of various vaccination strategies on the transmission of hepatis B virus. In: Berner (Ed.), The control of hepatitis B: The Role of Prevention in Adolescence. Gower Medical Publishing, L;ndon, 1992.
[8] J. R. Williams, D. J. Nokes, G. F. Medley, R. M. Anderson, The transmission dynamics of hepatitis B in the UK: A mathematical modle for evaluating costs and effectivenss of immunisation programmes, Epidemiol Infect 116(1)(1996) 71 - 89.
[9] W. J. Edmunds, C. F. Medley, D. J. Nokes, A. J. Hall, H. C. Whittle, The influence of age on the development of the hepatitis B carrier state, Proc. R. Soc. 253 (1993) 197 - 201.
[10] G. F. Medley, N. A. Lindop, W. J. Edmunds, D. J. Nokes, Hepatitis B virus endimicity: Heterogeneity, catastrophic dynamics and control, Nat. Med. 7(5)(2001) 619 - 624.
[11] S. Zhao, Z. Xu, Y. Lu, A mathematical model of hepatitis B virus transmission and its application for vaccination strategy in China, Int. J. Epid. 29(14)(2000) 744- 752.
[12] X. Zhou, Q. Sun, Stability of a fractional-order HBV infection model, Int. J. Adv. Appl. Math. and Mech., 2(2)(2016) 1-6. · Zbl 1359.92113
[13] X.J. Wang, R.Z. Zhang, Y.S. Hu, X.F. Liang,. Analysis on epidemic status of viral hepatitis in China: the report from Chinese Center for Disease Control and Prevention, Dis. Surveillance 19(2004), 290 - 292.
[14] R. Xu, Z. Ma, An HBV model with diffusion and time delay, J. Theor. Bio. 257(3)(2009) 499 - 509. · Zbl 1400.92560
[15] L. Zou, W. Zhang, S. Ruan,. Modeling the transmission dynamics and control of hepatitis B virus in China, J. Theor. Bio. 262(2010) 330 - 338. · Zbl 1403.92316
[16] Z. Zhang, Y. Zhou, The analysis and application of an HBV model, Appl. Math. Model. 36(3)(2012) 1302 - 1312. · Zbl 1243.34054
[17] A. M. Elaiw, M. A. Alghamdi, S. Aly,. Hepatitis B virus dynamics: modeling, analysis, and optimal treatment scheduling, Dis. Dyn. Nat. and Soc. 2013. · Zbl 1264.91102
[18] I. K. Adu, A. Y. Aidoo, I. O. Darko, E. Osei-Frimpong, Mathematical model of hepatitis B in the Bosomtwe district of Ashanti region, Ghana, Appl. Math. Sc. 8(67)(2014) 3343 - 3358.
[19] S. C. Mpeshe, N. Nyerere, S. Sanga, Modeling approach to investigate the dynamics of Zika virus fever: a neglected disease in Africa, J. Adv. Appl. Math. and Mech. 4(3)(2017) 14-21. · Zbl 1382.92244
[20] C. Castillo-Chavez, Z. Feng, W. Huang, On the computation ofR0and its role in global stability. In: CastilloChavez, C., van den Driessche, P., Kirschner, D., Yakubu, A. A. (Eds.), Mathematical approaches for emerging and reemerging infection diseases: an introduction, The IMA Volumes in Mathematics and its Applications, vol.125:31-65. New York: Springer, 2002. · Zbl 0989.00065
[21] A. Korobeinikov, Lyapunov Functions and Global Properties for SEIR and SEIS Epidemic Models, Math. Med. and Bio. 21(2)(2004), 75-83. · Zbl 1055.92051
[22] A. Korobeinikov, Global properties of infectious disease models with nonlinear incidence, Bull. Math. Bio. 69(2007) 1871 - 1886. · Zbl 1298.92101
[23] M. Y. Li, J. S. Muldowney, A geometric approach to global stability problems, SIAM J. Math. Analy. 27(4)(1996) 1070-1083. · Zbl 0873.34041
[24] M.A. Khan, A. Walid, S. Islam, I. Khan, S. Shafie, T. Gul, Stability analysis of an SEIR epidemic nodel with nonlinear saturated incidence and temporary immunity, Int. J. Adv. Appl. Math. and Mech., 2(3)(2015) 1-14 · Zbl 1359.93395
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.