On the Homotopy Analysis Method for an Seir Tuberculosis Model

M.O. Ibrahim, S.A. Egbetade

  Open Access OPEN ACCESS  Peer Reviewed PEER-REVIEWED

On the Homotopy Analysis Method for an Seir Tuberculosis Model

M.O. Ibrahim1, S.A. Egbetade2,

1Department of Mathematics, University of Ilorin, Ilorin, Nigeria

2Department of Mathematics & Statistics, The Polytechnic, Ibadan, Nigeria


In this paper, we provide a very accurate, non-perturbative, semi-analytical solution to a system of nonlinear first-order differential equations modeling the transmission of tuberculosis (TB) in a homogeneous population. Our analysis is based on Homotopy Analysis Method (HAM). Maple 15 software is used to carry out the computations. Our results show the validity and potential of HAM for computing the solution of nonlinear equations.

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Cite this article:

  • Ibrahim, M.O., and S.A. Egbetade. "On the Homotopy Analysis Method for an Seir Tuberculosis Model." American Journal of Applied Mathematics and Statistics 1.4 (2013): 71-75.
  • Ibrahim, M. , & Egbetade, S. (2013). On the Homotopy Analysis Method for an Seir Tuberculosis Model. American Journal of Applied Mathematics and Statistics, 1(4), 71-75.
  • Ibrahim, M.O., and S.A. Egbetade. "On the Homotopy Analysis Method for an Seir Tuberculosis Model." American Journal of Applied Mathematics and Statistics 1, no. 4 (2013): 71-75.

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1. Introduction

Infection with tuberculosis (TB) is caused by a bacterial known as Mycobacterium Tuberculosis [1, 2, 3]. Globally, TB is one of the greatest diseases of public concern because the pandemic is a substantial threat to socio-economic development imposing a heavy burden on families, communities and economies [4, 5, 6]. In 1993, the World Health Organisation (WHO) declared TB a global emergency and about 2 billion people were estimated to be globally infected with TB that year [7]. However, with drastic global treatment measures, the incidence of TB has reduced across the globe. According to a recent global TB reports, 9.4 million people acquired the disease in 2008 resulting in 1.8 million deaths while the number of active cases has reduced to 5.7 million in 2011 with 1.4 million deaths showing that TB mortality has decreased by 22% globally since 2008 [8, 9].

Mathematical models have been widely used in different forms for studying the transmission dynamics of TB epidemics [10-17][10]. However, the dilemma with many models in epidemiology is sometimes how to obtain analytic solutions of the nonlinear equations describing the dynamics of these diseases [18].

In 1992, a non-perturbative method known as homotopy analysis method (HAM) was proposed by Liao [19].This method was based on homotopy, an important part of topology [20]. HAM is a general analytic technique developed for the purpose of obtaining approximate analytic series solutions to different types of nonlinear equations especially those with strong nonlinearity. This method has been successfully applied to solve many types of nonlinear problems arising in the field of science, engineering and finance [21-38][21]. The HAM offers certain advantages over previous non-perturbative methods. Firstly, its validity does not depend upon small parameters of the considered nonlinear problem. Secondly, it provides a simple way to ensure the convergence of series solutions. Furthermore, we have great freedom to choose auxiliary linear operator so that one can approximate a nonlinear equation more efficiently by means of better base functions. Equal importantly, a few new solutions of some nonlinear problems which are neglected by all other analytic and numerical techniques are found using HAM. In addition, as proved in [25], HAM logically contains the three traditional non-perturbation methods such as Lyapunov artificial small parameter method [39], δ-expansion method [40] and Adomian decomposition method [41]. The homotopy perturbation method developed in [42] is also a special case of HAM as pointed out by Sajid and Hayat [43], Liang and Jeffery [44] and other researchers.

2. Mathematical Formulation

In this paper, we consider the following TB epidemic model proposed by Egbetade and Ibrahim [45]


where S= number of susceptible who do not have the disease but could get it

E= number of exposed who are infected but are yet to show any sign of symptoms

I= number of infectives who have the disease and can transmit it to others

R= number of recovered or removed who can not get the disease or transmit it.

γ= proportion of recruitment due to immigration

π= rate of recruitment of susceptible individuals

S= treatment rate of TB

β= transmission rate of TB

μ natural death rate

μT= death rate of TB

ν rate of slow progression

ρ rate of fast progression

D= detection rate of TB

ε= rate at which susceptible individuals recover.

In section 3, we shall apply the homotopy analysis method described in the next section to solve equations (2.1) – (2.4).

3. Homotopy Analysis Method

For the sake of completeness and readability of the present work, we give below a systematic description of the procedures of HAM.

Consider a nonlinear equation of the form


where N is a nonlinear operator, t denotes the time and u(t) is an unknown function. Let u0(t) denote an initial approximation of u(t) and L denote an auxiliary linear operator, Liao [21] constructs the zero-order deformation equation.


where p∈[0,1][, 1] is the embedding parameter, h≠0 is a nonzero auxiliary parameter, H(t)≠0 is a non-zero auxiliary function.

When p=0 and p=1, the zero-order deformation equations becomes respectively




Thus, as p increases from 0 to 1, the solution (t; p) varies continuously from the initial approximation u0(t) to the exact solution u(t). Such a kind of continuous variation is called deformation in topology. Expanding (t; p) by Taylor’s series in power series of p, we have




is the deformation derivative.

If the auxiliary linear operator N, the initial approximation u0(t) , the auxiliary parameter h and the auxiliary function H(t) are properly chosen so that

(1) the solution of the zero-order deformation equation (3.2) exists for all .

(2) the deformation derivative (3.6) exists for all

(3) the series (3.5) converges at p=1.

Then, we have the series solution


According to the definition (3.6), the governing equation can be derived from the zero-order deformation equation (3.2). Differentiating (3.2) times with respect to the embedding parameter , then setting and finally dividing by , we obtain the th order deformation equation






Note that according to the definition (3.10), the right hand side of (3.9) depends only on . Thus, we easily gain the series by solving the linear high-order deformation equation (3.9) using symbolic computation software such as Matlab, Maple or Mathematica.

4. Solution of SEIR Model by HAM

To solve the model equation (2.1) – (2.4) by HAM, we consider equation (2.1) and choose the linear operator


with the property that


where is a constant of integration. The inverse operator is given by


Let the nonlinear operator be defined as


By constructing the zero-order deformation equation


we have that for

, then

, then

Then, we have the th order deformation equation




The solution of the th order deformation equation (4.6) for and using and is given by


Following earlier steps, we get


5. Numerical Results and Discussion

For numerical results, the following values for parameters are considered.

Table 1. Parameter values for the series solutions

For high accuracy of results, we use Maple 15 computation software [46].For the graphs, dot lines: Susceptibles; dash lines: Exposed; dashdot lines: Infectives; longdash lines: Recovered. The 5th, 6th, 7th and 8th terms approximations for S(t), E(t), I(t) and R(t) are calculated and presented below.

5th terms approximations

6th terms approximations

7th terms approximations

8th terms approximations

Figure 1. Plots of 5th terms approximations for S(t), I(t) and R(t) against time(t)
Figure 2. Plots of 6th terms approximations for S(t), I(t) and R(t) against time(t)
Figure 3. Plots of 7th terms approximations for S(t), E(t), I(t) and R(t) against time(t)
Figure 4. Plots of 8th terms approximations for S(t), E(t), I(t) and R(t) against time(t)

From the various order of approximations, the HAM yields convergent series solutions that are reasonable and easy to express. The plots show that while the number of susceptible (S) decreases the population who are infectives (I) increases in the period of the epidemic. Meanwhile, the number of exposed (E) increases while the number of recovered (R) decreases. However, from figure 4, as the infection dies out (i.e. as I→0, the number of susceptible, exposed and recovered increases. In particular, as I→0, S approaches some positive value S=6.0513 which is the eventual population who were never infective.

6. Conclusion

In this paper, the HAM has been successfully applied to approximately solve a system of nonlinear equations in tuberculosis dynamics. The results show the potential and efficiency of HAM in solving nonlinear problems. We thus conclude that, combined with high performance computer and symbolic computation software such as Maple and so on, the homotopy analysis method might become a new powerful analytic tool to get satisfactory approximations for nonlinear problems in science and engineering.


[1]  Blower, S.M., McLean, A.R., Porco, T.C., Small, P.M., Hopewell, P.C., Sanchez, M.A. and Moss, A.R., “ The intrinsic transmission dynamics of tuberculosis epidemics,” Nat. Med., 1(8). 815-821. 1995. doi:
In article      CrossRefPubMed/NCBI
[2]  Song, B., Castillo-Chavez, C. and Aparicio, J-P., “Tuberculosis with fast and slow dynamics: the role of close and casual contact,” Math. Biosci., 180. 187-205. 2002. doi:
In article      CrossRef
[3]  Egbetade, S.A. and Ibrahim, M.O., “Global stability results for a tuberculosis epidemic model,” Res. J. Maths & Stat., 4(1). 14-20. 2012.
In article      
[4]  Colijn, C., Cohen, T. and Murray, M. (2006) Mathematical models of tuberculosis: accomplishments and future challenges. Proc. Natl. Acad. USA 103(18), 1-28.
In article      
[5]  World Health Organisation . Tuberculosis factsheet. 2010. http://www.who.int/medicenter/factsheet/html.
In article      
[6]  Ibrahim, M.O., Ejieji, C.N. and Egbetade, S.A., “A mathematical model for the epidemiology of tuberculosis with estimate of the basic reproduction number,” IOSR J. of Maths., 5(5). 46-52. 2013. doi:
In article      CrossRef
[7]  World Health Organisation. Tuberculosis control. 2009. http://who/globalreport2009/pdf.
In article      
[8]  World Health Organisation. WHO global TB report.2012.www.int/tb/publications/factsheet.
In article      
[9]  Egbetade, S.A., Ibrahim, M.O. and Ejieji, C.N., “On existence of a vaccination model of tuberculosis disease pandemic,” Int. J. Engrg. and Sc., 2(7). 41-44. 2013.
In article      
[10]  Waaler, H., Geser, A. and Anderson, S., “The use of mathematical models in the study of the epidemiology of tuberculosis,” Am. J. Public Health, 52. 1002-1013.1062.
In article      
[11]  Castillo-Chavez, C. and Feng, Z., “To treat or not to treat: the case of tuberculosis,” J. Math. Biol., 35(6). 629-656. 1997. doi:
In article      CrossRefPubMed/NCBI
[12]  Aparicio, J.P., Capurro, A.F. and Castillo-Chavez, C., “Transmission and dynamics of tuberculosis on generalized households,” J. Theor. Biol., 206. 327-341. 2000. doi:
In article      CrossRefPubMed/NCBI
[13]  Dye, C., “Global epidemiology of tuberculosis,” Lancet, 367(9514). 938-940.2006.
In article      
[14]  Cohen, T., Colijn, C., Finklea, B. and Murray, M. “Exogeneous re-infection and the dynamics of tuberculosis epidemics: local effects in a network model of transmission,” J.R. Soc. Interface, 4(14). 523-531.2007.
In article      
[15]  Roeger, L.W., Feng, Z. and Castillo-Chavez, C. “Modeling TB and HIV co-infections,” Mathematical Biosciences and Engineering, 6(4). 815-837. 2009. doi:
In article      CrossRefPubMed/NCBI
[16]  White, P.J. and Garnett, G.P., “Mathematical modeling of the epidemiology of tuberculosis,” In: Michael, E., Speer, R.C. eds. Advances in Experimental Medicines and Biology Vol. 673, Modeling Parasite Transformation and Control. NY:Springer+Business Media, LLC Landes Biosciences, 127-140.
In article      
[17]  Oxlade, O., Sterling, T.R. and Schwartzman, K., “Developing a tuberculosis transmission model that accounts for changes in population health,” Medical Decision Making, 31. 53-68. 2011. doi:
In article      CrossRefPubMed/NCBI
[18]  Brauer, F., “Basic ideas of mathematical epidemiology. Mathematical approaches for energy and re-emerging infectious diseases: Models, Methods and Theory,” (eds. Castillo-Chavez, C., Blower, S., van der Driessche, P., Kirschner, D. and Yakubu, A.A.). Berlin, Springer-Verlag.
In article      
[19]  Liao, S.J., The proposed homotopy analysis method for the solutions of nonlinear problems. Ph.D. Thesis. Shanghai Jiao Tong University, Shanghai, China.1992.
In article      
[20]  Alexander, J.L. and York, J.A., “The homotopy continuation method: numerically implementable topological procedures,” Trans Am. Math. Soc., 242. 271-284. 1978. doi:
In article      CrossRef
[21]  Liao, S.J., “A kind of approximate solution technique which does not depend upon small parameters (II): an application in fluid mechanics,” Int. J. Nonlinear Mech., 32(5). 815-822. 1997. doi:
In article      CrossRef
[22]  Liao, S.J. and Chwang, A.T., “Application of homotopy analysis method in nonlinear oscillations,” Trans. ASME J. Appl. Mech., 65. 914-922. 1998. doi:
In article      CrossRef
[23]  Liao, S.J., “An explicit totally analytic approximate solution for Blasius viscous flow problems,” Int. J. Nonlinear Mechanics, 34. 759-778. 1999. doi:
In article      CrossRef
[24]  Liao, S.J., “Analytic approximation of the drag coefficient for the viscous flow past a sphere,” Int. J. Nonlinear Mech., 37, 1-18.2002.
In article      
[25]  Liao, S.J.2003 Beyond Perturbation: Introduction to the homotopy analysis method. Chapman and Hall, CRC Press, Boca Raton. doi:
In article      CrossRef
[26]  Liao, S.J., “On the analytic solution of magnetohydrodynamic flow of non-Newtonian fluids over a stretching sheets,” J. Fluid Mech., 488, 189-212. 2003. doi:
In article      CrossRef
[27]  Liao, S.J. and Magyari, E., “Exponentially decaying boundary layers and limiting cases of families of algebraically decaying ones,” ZAMP, 57(5). 777-792. 2006. doi:
In article      CrossRef
[28]  Hayat, T., Khan, M. and Asghar, S., “Homotopy analysis of MHD flows of an Oldroyd 8-constant fluid,” Acta. Mech., 168. 213-232. 2004. doi:
In article      CrossRef
[29]  Zhu, S.P., “An exact explicit solution for the evaluation of American put options,” Quantitative Finance, 6. 229-242. 2006. doi:
In article      CrossRef
[30]  Zhu, S.P., “A closed form analytical solution for the evaluation of convertible bonds with constant dividend yield,” Anzian J., 47, 477-494. 2006. doi:
In article      CrossRef
[31]  Song, H. and Tao, L., “Homotopy analysis of 1D unsteady nonlinear ground water flow through porous media,” J. Coastal Res., 50. 292-295. 2007.
In article      
[32]  Abbasbandy, S., “Application of homotopy analysis method to solve a generalized Hirota-Satsuma coupled KdV equation,” Phys. Lett. A, 361. 478-483. 2007. doi:
In article      CrossRef
[33]  Awawdeh, F., Adawi, A. and Mustafa, Z., “Solutions of the SIR models of epidemics using HAM,” Chaos, Solitons and Fractals, 42. 3047-3052. 2009. doi:
In article      CrossRef
[34]  Matinfar, M. and Saeidy, M., “Application of homotopy analysis method to fourth order parabolic partial differential equations,” Applications and Applied Mathematics, 5(9).70-80. 2010.
In article      
[35]  Li, Y., Nohara, B.T. and Liao, S.J., “Series solutions of coupled Van der Pol equation by means of homotopy analysis method,” Journal of Mathematical Physics, 51. 063517. 2010. doi:
In article      CrossRef
[36]  Hassan, H.N. and El-Tawil, M.A., “A new technique of using homotopy analysis method for solving high-order nonlinear differential equations,” Mathematical methods in Applied Science, 34. 728-742. 2011. doi:
In article      CrossRef
[37]  Arafa, A.A.M., Rida, S.Z. and Khalil, M., “Solutions of fractional order model of childhood diseases with constant variation strategy,” Math. Sc. Lett., 1(1). 17-23. 2012. doi:
In article      CrossRef
[38]  Vahdati, S., Tavassoli, K.M. and Ghasemi, M., “Application of homotopy analysis method to SIR epidemic model,” Research Journal of Recent Sciences, 2(1). 91-96. 2013.
In article      
[39]  Lyapunov, A.M., “General problems on stability of motion,” Taylor and Francis, London.
In article      
[40]  Awrejcewicz, J., Andrianov, I.V. and Manevitch, L.I., “Asymptotic approaches in nonlinear dynamics,” Springer-Verlag, Berlin.
In article      
[41]  Adomian, G., “A review of the decomposition method and some recent results for nonlinear equations,” Comp. Math. Appl., 21. 101-127. 1991. doi:
In article      CrossRef
[42]  He, J.H., “Homotopy perturbation techniques,” Comput. Methods Appl. Mech. Engrg., 178. 257-262. 1999. doi:
In article      CrossRef
[43]  Sajid, M. and Hayat, T., “Comparison of HAM and HPM methods for nonlinear heat conduction and convection equations,” Nonlinear Anal.: Real World Appl., 9. 2296-2301. 2008. doi:
In article      CrossRef
[44]  Liang, S.X. and Jeffery, D.J., “Comparison of homotopy analysis method and homotopy perturbation method through an evaluation equation,” Comm. Nonlinear Sci. Numer. Simul., 14. 4057-4064. 2009. doi:
In article      CrossRef
[45]  Egbetade, S.A. and Ibrahim, M.O., “Stability analysis of equilibrium states of an SEIR tuberculosis model,” Journal of the Nigerian Association of Mathematical Physics, 20. 119-124. 2012.
In article      
[46]  Maplesoft 15, Waterloo Maple Inc. Ontario, Canada. 2011.
In article      
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