About this Journal Submit a Manuscript Table of Contents
Abstract and Applied Analysis
Volume 2014 (2014), Article ID 631658, 12 pages
Research Article

Mathematical Modelling of the Spread and Control of Onchocerciasis in Tropical Countries: Case Study in Nigeria

Department of Mathematics and Applied Mathematics, Faculty of Natural and Agricultural Sciences, University of the Free State, Bloemfontein 9300, South Africa

Received 2 May 2014; Accepted 2 June 2014; Published 22 October 2014

Academic Editor: Abdon Atangana

Copyright © 2014 Ikechukwu Chiwueze Oguoma and Thomas Mbah Acho. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Onchocerciasis, also known as river blindness and Robles disease, is a parasitic disease caused by Onchocerca volvulus, a nematode (roundworm), and it is endemic in tropical countries like Nigeria. The objective of this paper is to discuss the mathematical formulation underpinning the spread and control of this disease on one hand. On the other hand, we make use of some new analytical methods to derive the solution of the resulting set of equations. The numerical results are presented to test the efficiency and the accuracy of both methods. The techniques used for solving these problems are friendly, very easy, and less time consuming. The numerical solutions in both cases display the biological behaviour of the real life situation.

1. Introduction

Onchocerciasis is a country-wide public health problem in Nigeria. The present estimates had suggested that 7–10 million Nigerians are infected with Onchocerca volvulus, and approximately 40 million are at risk of the disease [1]. More than 120,000 cases of Onchocerciasis related blindness have been reported [24], and thousands of people suffer from disabling complications of this disease [5]. Onchocerciasis, which is the world’s second-leading infectious cause of blindness, is a parasitic disease caused by the filarial nematode, Onchocerca volvulus. It is termed as “river blindness” because it is spread by the bite of the blackfly vector that breads near oxygen-high fast-flowing streams and rivers people rely on for washing, drinking, and farming which results in depopulation of the fertile river valleys. The lifespan of blackflies is short, lasting only 2-3 weeks. The disease affects rural communities in Nigeria and is the major cause of blindness and skin disease in endemic areas with serious socioeconomic effects. It has been identified by the World Health Organization as one of the neglected tropical diseases (NTD) [6, 7], “Neglected” because they are not mentioned in the millennium Development Goals. This implied that they are not usually included among the important development discussions, and as such they do not receive adequate attention or funding.

Figure 1 explains the life cycle of the parasite Onchocerca volvulus.

Figure 1: Life cycle of Onchocerca volvulus [8].

Onchocerca volvulus is transmitted to humans through the bite of a blackfly which introduces immature larva forms of the parasite (infective larvae) into their human host.

The larvae migrate to the subcutaneous tissue where they undergo further development and form skin nodules as they mature into adult worms (macrofilaria). The adult worms mate and produce millions of microscopic larvae (microfilaria). This continues for years of the adult worm’s life. Although the infection with larvae begins immediately, the disease may not become apparent in an individual for months to years. In most individuals, it develops slowly in the skin, while some patients may show symptoms initially with eye problems, ocular involvement, and general debilitation.

The blackflies absorb the microfilariae as they feed during the day, which further undergo developmental stages within the blackflies into infective larvae, which are then transmitted to the next human victim.

A study was carried out in Imo River Basin, Imo State, Southeastern Nigeria, to assess the prevalence and intensity of microfilaria of Onchocerca volvulus in the area [9]. The survey coverage was about 91.8% of the study population and it was found by EC. Uttah found that thirty-seven percent of those examined was positive for Onchocerca volvulus microfilariae (39.2% of males and 34.9% of females). The microfilariae (mf) prevalence increased steadily with increasing age to reach 70.4% in the oldest age group.

Going towards the northern part of Nigeria, the endemicity of human onchocerciasis was assessed by Anosike and Onwuliri [10] in eight rural communities at risk, in Ningi Local Government Area, Bauchi State, Nigeria, between July 1990 and March 1991. Of the 1536 subjects skin-snipped, 334 (21.7%) were positive for Onchocerca volvulus microfilariae.

Wogu and Okaka investigated the overall prevalence of onchocerciasis in Okpuje, Owan West L.G.A. of Edo State, Nigeria. The figure recorded in their study of 47.5% compares favourably with the 48.6% prevalence reported by Edungbola and Asaolu [11] in Kwara State, Nigeria, but higher than the 26.9% recorded by Nwaorgu et al. [12] in an onchocerciasis mesoendemic area of Enugu State, Nigeria. However, Akinbo and Okaka [13] reported a high overall prevalence (83%) of the disease in Ovia North East L.G.A., Edo State, Nigeria [14]. These reports suggest that we need a well-thought mathematical formulation of a simple and appropriate model for the spread and control of this disease.

2. Model Formulation

In this section, we define the parameters used in the model below as follows: is the contact rate between and ; is the contact rate between and ; is the contact rate between and ; is the contact rate between and ; is the contact rate between and ; is the transmission rate from to ; and are the proportions of Ivermectin/Mectizan treatment that cured the patient; is the rate of movement of humans from the infective compartment into the human susceptible compartment; is the rate of movement of human from the human infective compartment into the latent (incubation) period compartment.

3. Model Diagram

Figure 2 shows the model diagram which consists of five sets of ordinary differential equations highlighting the rate of change with respect to time of human susceptible compartment ; human latent (incubation) period compartment ; human infective compartment ; vector susceptible compartment ; and the vector infective compartment .

Figure 2: Model transfer diagram for onchocerciasis.

4. Mathematical Formulation of the Model

From the model transfer diagram (Figure 2), we have the following set of equations: To find the steady state, we assume that the compartments , , , , and do not depend on time. Therefore, We now solve the differential equations to find the value for , , , , and .

From (4), From (5), From (1), But From (2), Lastly, from (3), We have that provided that .

Therefore, the disease free equilibrium (DFE) is given as and the endemic equilibrium is given as

5. Stability Analysis

To assess the stability of the (DFE), we solve the model characteristics equation using the Jacobean matrix formulated from (1), (2), (3), (4), and (5) above as follows: Applying the eigenvalue we have

Hence, we obtain from From , From , From , From , Given that the results of , , , , and are all negative and considering the principles of linearized stability which says that the systems are asymptotically stable if and only if all the eigenvalues of the system have negative real parts, we say that the disease-free equilibrium (DFE) is asymptotically stable.

6. Application of the Homotopy Decomposition Method (HDM)

In this section, we apply the HDM [1517] to solve these mathematical sets of equations representing the onchocerciasis disease model as follows: We then assume that the solutions of the above integral equations can be put in the following form, for , Replacing the above expressions in the integral equations, we obtain the following expressions: We compared the terms of the same power of and obtained the following: Continuing for , we have We now integrate the above equations to obtain the following: