Adegbite, Gbenga and Edeki, S.O. and Isewon, Itunuoluwa and Emmanuel, Jerry and Dokunmu, Titilope M. and Rotimi, S. O and Oyelade, O. J. and Adebiyi, E. F. (2023) Mathematical modeling of malaria transmission dynamics in humans with mobility and control states. Infectious Disease Modelling, 8. pp. 1015-1031.
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Abstract
Malaria importation is one of the hypothetical drivers of malaria transmission dynamics across the globe. Several studies on malaria importation focused on the effect of the use of conventional malaria control strategies as approved by the World Health Organization (WHO) on malaria transmission dynamics but did not capture the effect of the use of traditional malaria control strategies by vigilant humans. In order to handle the aforementioned situation, a novel system of Ordinary Differential Equations (ODEs) was developed comprising the human and the malaria vector compartments. Analysis of the system was carried out to assess its quantitative properties. The novel computational algorithm used to solve the developed system of ODEs was implemented and benchmarked with the existing Runge-Kutta numerical solution method. Furthermore, simulations of different vigilant conditions useful to control malaria were carried out. The novel system of malaria models was well-posed and epidemiologically meaningful based on its quantitative properties. The novel algorithm performed relatively better in terms of model simulation accuracy than Runge-Kutta. At the best model-fit condition of 98% vigilance to the use of conventional and traditional malaria control strategies, this study revealed that malaria importation has a persistent impact on malaria transmission dynamics. In lieu of this, this study opined that total vigilance to the use of the WHO-approved and traditional malaria management tools would be the most effective control strategy against malaria importation.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Malaria importation Traditional malaria control Ordinary differential equation Quantitative properties Novel algorithm Runge-Kutta |
| Subjects: | Q Science > QA Mathematics > QA76 Computer software Q Science > QH Natural history > QH301 Biology |
| Divisions: | Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science Faculty of Medicine, Health and Life Sciences > School of Biological Sciences |
| Depositing User: | Patricia Nwokealisi |
| Date Deposited: | 31 Jul 2024 10:31 |
| Last Modified: | 31 Jul 2024 10:31 |
| URI: | http://eprints.covenantuniversity.edu.ng/id/eprint/18332 |
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