Approximate solutions to malaria transmission models with seasonality and awareness: A comparative analysis of ADM and HPM
Keywords:
Mathematical Modeling, Semi-Analytic Method, Non-linear Differential Equations, Epidemiology, Intervention Strategies, Seasonality. 2010 MSC: 34A34, 65L70, 93A30, 93C15.Abstract
Mathematical modelling provides critical insights into malaria transmission dynamics and interven tion efficacy. While standard numerical solvers provide quantitative solutions, semi-analytical methods yield closed-form series approximations that enhance qualitative and parametric understanding. This study com paratively investigates two prominent semi-analytical techniques, the Adomian Decomposition Method (ADM) and the Homotopy Perturbation Method (HPM), applied to a seasonally-forced malaria transmission model. The underlying formulation encompasses human behavioral awareness, a structured mosquito life cycle, and seasonal forcing, resulting in a twelve-dimensional coupled non-autonomous nonlinear system. Explicit recur sive algorithms for ADM and HPM are derived and validated against fourth-fifth order Runge–Kutta numeri cal benchmarks using biologically realistic parameters. The comparative evaluation indicates compartment dependent performance: HPM exhibits high precision for human epidemiological classes over short intervals, while ADM demonstrates superior stability across mosquito developmental stages and awareness dynam ics over extended time periods. Numerical experiments further show that intensified awareness campaigns significantly curtail infection prevalence across both host and vector populations. The methods remain com putationally tractable for 12D systems. Our findings therefore provide practical guidance for selecting semi analytical schemes according to compartment and time-scale in high-dimensional epidemiological systems.
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Abioye, A. I., Peter, O. J., Ayoade, A. A., Uwaheren, O. A., & Ibrahim, M. O. (2020). Application of Adomian decomposition method on a mathematical model of malaria. Advances in Mathematics: Scientific Journal, 9(1), 417–435.
Adomian, G. (1994). Solving frontier problems of physics: The decomposition method. Kluwer Academic Publishers.
Akdim K, Ez-Zetouni A & Zahid M. (2022). The influence of awareness campaigns on the spread of an infectious disease: a qualitative analysis of a fractional epidemic model. Model Earth Syst Environ., 8(1):1311-1319.
Bakare, E.A., Hoskova-Mayerova, S. (2023). Numerical treatment of optimal control the- ory applied to malaria transmission dynamic model. Qual Quant., 57 (Suppl 3), 409-431. https://doi.org/10.1007/s11135-020-01092-5
Basir, F.A., Nieto, J.J., Raezah, A.A. et al. (2025) Impact of local and global awareness campaigns on malaria transmission: A mathematical model with protected human class and optimal control approach. Eur. Phys. J. Plus, 140, 262 (2025). https://doi.org/10.1140/epjp/s13360-025-06206-2
Chitnis, N., Hyman, J. M., & Cushing, J. M. (2010). Determining important parameters in the spread of malaria through the sensitivity analysis of a mathematical model. Bulletin of Mathematical Biology, 72(1), 1–27. https://doi.org/10.1007/s11538-009-9424-8
Cowman, A. F., Healer, J., Marapana, D., & Marsh, K. (2016). Malaria: Biology and disease. Cell, 167(3), 610–624. https://doi.org/10.1016/j.cell.2016.07.055
Geethamalini, S., Sangeetha, S., Anandhababu, D., & Venkataraman, P. (2024). A numerical & analyt- ical study of SIRC epidemic model using HPM. Journal of Computational Analysis and Applications, 33(7), 1097–1104.
Haringo, A.T., Obsu, L.L. & Bushu, F.K. (2024). A mathematical model of malaria transmis- sion with media-awareness and treatment interventions. J. Appl. Math. Comput. 70, 4715-4753. https://doi.org/10.1007/s12190-024-02154-9
Haringo, A.T., Obsu, L.L. & Bushu, F.K. (2025). Optimal control and cost-effectiveness analysis of malaria transmission dynamics. Int. J. Dynam. Control, 13, 230. https://doi.org/10.1007/s40435-025- 01719-1
He, J. H. (1999). Homotopy perturbation technique. Computer Methods in Applied Mechanics and Engineering, 178(3–4), 257–262. https://doi.org/10.1016/S0045-7825(99)00018-3
He, J. H. (2000). A coupling method of a homotopy technique and a perturbation tech- nique for non-linear problems. International Journal of Non-Linear Mechanics, 35(1), 37–43. https://doi.org/10.1016/S0020-7462(98)00085-7
Helikumi, M. (2024). Modeling the impact of human awareness and insecticide usage on malaria control: A fractional-order approach. Mathematics, 12(22), Article 3607. https://doi.org/10.3390/math12223607
Ibrahim, M. O., Yusuf, T. T., & Abubakar, U. (2020). Impact of awareness to control malaria disease.
Journal of Applied Mathematics, 2020, 1–12. https://doi.org/10.1155/2020/8657410
Ibrahim, M. M. , Byun, J. H. , Mannan, M.M. , Jung, H., & Kim, K. S. (2020). Impact of Awareness to Control Malaria Disease: A Mathematical Modeling Approach. Complexity. 01 (2020).
https://doi.org/10.1155/2020/8657410
Mandal, S., Sarkar, R. R., & Sinha, S. (2011). Mathematical models of malaria - a review. Malaria
Journal, 10(1), 202. https://doi.org/10.1186/1475-2875-10-202
Ochieng, F. O. (2023). SEIRS model for malaria transmission dynamics incorporat-
ing seasonality and awareness campaign. Infectious Disease Modelling, 9(1), 84–102.
https://doi.org/10.1016/j.idm.2023.11.010
Senthamarai, R., & Balamuralitharan, S. (2016). Analytical solutions of SIRS-SI malaria disease model
using HPM. Journal of Chemical and Pharmaceutical Research, 8(7), 651–666.
Srivastav, A.K. & Ghosh, M. (2021). Modeling the transmission dynamics of malaria with saturated treatment: a case study of India. J. Appl. Math. Comput. 67, 519540 (2021).
https://doi.org/10.1007/s12190-020-01469-7
White, N. J., Pukrittayakamee, S., Hien, T. T., Faiz, M. A., Mokuolu, O. A., & Dondorp, A. M. (2014).
Malaria. The Lancet, 383(9918), 723–735. https://doi.org/10.1016/S0140-6736(13)60024-0
World Health Organization. (2023). World malaria report 2023. WHO.
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