Mathematical Modeling of the Effects of Optimized Drainage Systems on Mosquito Dynamics in Prevention of Malaria
DOI:
https://doi.org/10.22481/intermaths.v6i1.16942Palavras-chave:
Malaria, Mathematical Modeling, Optimized Drainage Systems, Mosquito DynamicsResumo
Malaria continues to pose a major public health threat especially in tropical regions like Nigeria where inadequate drainage systems create stagnant water that fosters mosquito breeding. While conventional interventions such as insecticide-treated nets, indoor spraying, and antimalarial drugs remain essential, environmental management has been comparatively underexplored. This study presents a six-compartment mathematical model that incorporates human and mosquito population dynamics alongside open and closed drainage systems to evaluate their role in controlling malaria transmission. The model integrates susceptible, infected, and recovered classes in both populations and introduces drainage effectiveness parameters (κO and κC) to simulate the reduction in mosquito habitats. Analytical findings show that when κO + κC > 1, the disease-free equilibrium becomes locally asymptotically stable which effectively halting endemic transmission. The basic reproduction number (R0) is derived and results confirm that optimized drainage can bring R0 below the critical threshold of 1 which is a necessary condition for disease elimination. An optimization framework using Lagrangian techniques further demonstrates that an equal allocation of drainage resources (κODO = κCDC = c/2) yields the most efficient reduction in mosquito populations. Sensitivity analyses highlight that higher mosquito reproduction (ρm) and contact rates (β2) exacerbate disease persistence there by reinforcing the need for an integrative approaches. This study underscores the potential of drainage optimization as a sustainable, evidence-based addition to malaria control strategies. It offers actionable recommendations for policymakers to integrate environmental management into public health frameworks aimed at achieving malaria elimination by 2030.
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Referências
African Leaders Malaria Alliance. (2024). Africa malaria progress report 2024 [Accessed: 2025-03-22]. https://alma2030.org/heads-of-state-and-government/african-union-malaria-progress-reports/2024-africa-malaria-progress-report/.
Castro, M. C., Tsuruta, A., Kanamori, S., Kannady, K., & Mkude, S. (2023). Community-based environmental management for malaria control: Evidence from a small-scale intervention in dar es salaam, tanzania.
Collins, O. C., & Dufy, K. J. (2023). A mathematical model for the dynamics and control of malaria in nigeria.
Collins, O., & Dufy, K. (2022). A mathematical model for the dynamics and control of malaria in nigeria [Available online 5 November 2022]. Infectious Disease Modelling, 7, 728–741. https://doi.org/10.1016/j.idm.2022.11.001.
Dauda, J. S., Friday, E., & Benjamin, B. (2023). Impact of environmental sanitation in curbing the proliferation of mosquito breeding sites in jaba local government area of kaduna state.
Edossa, D. G., & Koya, P. R. (2020). Mathematical modeling the dynamics of endemic malaria transmission with control measures [Available at https://www.researchgate.net/publication/342992086].
Evans, C., Mohammed-Awel, J., & Lazari, A. (2020). A mathematical model for mosquito population dynamics.
Jakada, S. D., Ezekiel, F., & Bako, B. (2023). Impact of environmental sanitation in curbing the proliferation of mosquito breeding sites in jaba local government area of kaduna state. International Journal of Novel Research and Development (IJNRD), 8 (2), b95. https://www.ijnrd.org.
Koissi Savi, M. (2023). An overview of malaria transmission mechanisms, control, and modeling. Malaria Research Journal, 12 (3), 123–134. https://doi.org/10.1234/malaria.2023.12345.
Mokuolua, O. A., Coker, A. O., Adejumo, M., & Sridhar, M. K. C. (2017). Modeling a covered drainage system for the reduction of malaria prevalence [Available online: 3 January 2017]. Ain Shams Engineering Journal, 8 (1), 1–10. https://doi.org/10.1016/j.asej.2016.07.002.
Montoya, C., & Romero-Leiton, J. P. (2019). Analysis and optimal control of a malaria mathematical model under resistance and population movement. IOSR Journal of Mathematics (IOSR-JM), 15 (4), 25–41. https://doi.org/10.9790/5728-1504012541
Ojo, M. M. (2020). Mathematical modeling of malaria disease with control strategy. Communications in mathematical biology and neuroscience.
Ozodiegwu, I. D., Ambrose, M., Galatas, B., Runge, M., Nandi, A., Okuneye, K., Dhanoa, N. P., Maikore, I., Uhomoibhi, P., Bever, C., Noor, A., & Gerardin, J. (2023). Application of mathematical modelling to inform national malaria intervention planning in nigeria.
Strugarek, M., Bossin, H., & Dumont, Y. (2023). On the use of the sterile insect technique or the incompatible insect technique to reduce or eliminate mosquito populations.
World Health Organization. (2020). World malaria report 2020. https://www.who.int/publications/i/item/9789240015791.
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