Version 1
: Received: 31 October 2024 / Approved: 31 October 2024 / Online: 1 November 2024 (10:38:22 CET)
How to cite:
Helikumi, M.; Thobias Bisaga, T.; Kimulu, A. M.; Mhlanga, A. Modeling the Impact of Human Awareness and Insecticide Use on Malaria Control: A Fractional-Order Approach. Preprints2024, 2024110052. https://doi.org/10.20944/preprints202411.0052.v1
Helikumi, M.; Thobias Bisaga, T.; Kimulu, A. M.; Mhlanga, A. Modeling the Impact of Human Awareness and Insecticide Use on Malaria Control: A Fractional-Order Approach. Preprints 2024, 2024110052. https://doi.org/10.20944/preprints202411.0052.v1
Helikumi, M.; Thobias Bisaga, T.; Kimulu, A. M.; Mhlanga, A. Modeling the Impact of Human Awareness and Insecticide Use on Malaria Control: A Fractional-Order Approach. Preprints2024, 2024110052. https://doi.org/10.20944/preprints202411.0052.v1
APA Style
Helikumi, M., Thobias Bisaga, T., Kimulu, A. M., & Mhlanga, A. (2024). Modeling the Impact of Human Awareness and Insecticide Use on Malaria Control: A Fractional-Order Approach. Preprints. https://doi.org/10.20944/preprints202411.0052.v1
Chicago/Turabian Style
Helikumi, M., Ancent Makau Kimulu and Adquate Mhlanga. 2024 "Modeling the Impact of Human Awareness and Insecticide Use on Malaria Control: A Fractional-Order Approach" Preprints. https://doi.org/10.20944/preprints202411.0052.v1
Abstract
In this research work, we developed a fractional-order model for the transmission dynamics of malaria, incorporating two control strategies: health education campaigns, and use of insecticides. The theoretical analysis of the model was presented, including the computation of disease-free equilibrium and basic reproduction number. We analyzed the stability of the proposed model using well formulated Lyapunov function. Furthermore, model parameter estimation was carried out using real data on malaria cases reported in Zimbabwe. We found that the fractional-order model provided a better fit to the real data compared to the classical integer-order model. Sensitivity analysis of the basic reproduction number was performed using computed partial rank correlation coefficients to assess the effect of each parameter on malaria transmission. Additionally, we conducted numerical simulations to evaluate the impact of memory effects on the spread of malaria. The simulation results indicated that the order of derivatives significantly influences the dynamics of malaria transmission. Moreover, we simulated the model to assess the effectiveness of the proposed control strategies. Overall, the interventions were found to have the potential to significantly reduce the spread of malaria within the population.
Computer Science and Mathematics, Applied Mathematics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
