A Stochastic, Individual-Based Mathematical Model of Onchocerciasis Transmission in North-Eastern Nigeria

In Nigeria, onchocerciasis (river blindness), which is caused by the filarial worm Onchocerca volvulus and spread by Simulium blackflies, is still a significant public health concern, especially in riverine populations in the northeastern states of Adamawa, Bauchi, Borno, Gombe, Taraba, and Yobe. Due to non-compliance, drug ineligibility, migration of infected individuals and gaps in vector control, transmission continues in a number of endemic foci despite thirty years of mass drug administration (MDA) with ivermectin. In order to overcome major shortcomings of previous deterministic models that assumed homogenous human and vector populations, this study offers a stochastic, individual-based, geographically explicit, and time-dependent mathematical model to represent the heterogeneous transmission dynamics of onchocerciasis. Incorporating temperature and rainfall as climatic drivers of vector breeding and disease transmission, the model divides the human population into compliant and non-compliant susceptible, exposed, infectious, treated, and recovered compartments and the blackfly vector population into larval, susceptible, and infectious stages. Proofs of positivity and boundedness of solutions were used to establish the well-posedness of the model, and a disease-free equilibrium was obtained. R0 = 0.0202 was the result of applying the Next Generation Matrix technique to calculate the fundamental reproduction number (R0) and parameterizing it with values taken from the literature and estimation. The model indicates a long-term decrease in disease incidence and prevalence because this value is much less than unity, which is in accordance with Nigeria's goal of eradicating onchocerciasis by 2030. With an exponential decay pattern shared by all classes, simulations conducted over a five-year projection period (2026–2030) revealed decreasing trends in infected non-compliant, infected compliant, and treated populations along with decreased vector infection rates shown in Figures 1 to 4. Comparative intervention scenarios showed that when ivermectin treatment is combined with public health education, the disease is eliminated more quickly than when either technique is applied independently. The findings underscore that sustained ivermectin distribution, improved compliance through education, and integration of climatic variables into predictive models are critical to achieving elimination targets, while highlighting that any relaxation of intervention efforts could allow disease resurgence.