Onchocerciasis leaves immunological and epidemiological memory in humans; hence, effective future control requires understanding its current and past states. However, existing models rely largely on integer-order derivative (IOD) formulations, which often fail to capture memory and non-local effects observed in infectious diseases, or on fractional-order derivative (FOD) formulations with singular kernels, which may inadequately represent memory effects due to their singularity. Moreover, previous models did not examine the impact of isolation as a control strategy. Hence, we propose a non-local, non-singular kernel FOD model for onchocerciasis in the Caputo–Fabrizio sense, incorporating vector control and isolation strategies. Using fixed-point theory and iterative methods, we establish the existence and uniqueness of solutions, and conditions for both onchocerciasis-free and endemic equilibrium points. All analytic solutions confirm the model’s biological feasibility. Sensitivity analysis shows that human-to-vector and vector-to-human contact rates significantly increase the effective reproduction number, while early treatment and isolation are the most influential factors in reducing it. Fitting via the three-step fractional Adams–Bashforth method yielded a coefficient determination R2=0.9960 and mean absolute percentage error (MAPE) = 7.68%, with fraction order β=0.6432. Numerical simulations demonstrated that IOD models will lead to an untimely relaxation of control measures compared with FOD models. Based on the numerical simulation dataset, the fractional-order model further suggests that at least 75% early treatment and isolation intensity are effective intervention strategies for onchocerciasis control/elimination. It also highlights that policymakers should reduce the epidemiological mechanisms (such as delayed treatment and repeated exposure to blackfly) that sustain the disease memory index.
BT - Scientific African DA - 09/2026 DO - 10.1016/j.sciaf.2026.e03630 LA - ENG M3 - Article N2 -Onchocerciasis leaves immunological and epidemiological memory in humans; hence, effective future control requires understanding its current and past states. However, existing models rely largely on integer-order derivative (IOD) formulations, which often fail to capture memory and non-local effects observed in infectious diseases, or on fractional-order derivative (FOD) formulations with singular kernels, which may inadequately represent memory effects due to their singularity. Moreover, previous models did not examine the impact of isolation as a control strategy. Hence, we propose a non-local, non-singular kernel FOD model for onchocerciasis in the Caputo–Fabrizio sense, incorporating vector control and isolation strategies. Using fixed-point theory and iterative methods, we establish the existence and uniqueness of solutions, and conditions for both onchocerciasis-free and endemic equilibrium points. All analytic solutions confirm the model’s biological feasibility. Sensitivity analysis shows that human-to-vector and vector-to-human contact rates significantly increase the effective reproduction number, while early treatment and isolation are the most influential factors in reducing it. Fitting via the three-step fractional Adams–Bashforth method yielded a coefficient determination R2=0.9960 and mean absolute percentage error (MAPE) = 7.68%, with fraction order β=0.6432. Numerical simulations demonstrated that IOD models will lead to an untimely relaxation of control measures compared with FOD models. Based on the numerical simulation dataset, the fractional-order model further suggests that at least 75% early treatment and isolation intensity are effective intervention strategies for onchocerciasis control/elimination. It also highlights that policymakers should reduce the epidemiological mechanisms (such as delayed treatment and repeated exposure to blackfly) that sustain the disease memory index.
PB - Elsevier BV PY - 2026 SP - 1 EP - 20 T2 - Scientific African TI - Caputo–Fabrizio fractional dynamics of onchocerciasis: Assessing the impact of disease memory effects, isolation and vector control strategies on onchocerciasis transmission dynamics UR - https://www.sciencedirect.com/science/article/pii/S2468227626004552/pdfft?md5=ebf774634dd5ba2c190b150133439d04&pid=1-s2.0-S2468227626004552-main.pdf VL - 34 SN - 2468-2276 ER -