Application of optimal control strategies to HIV-malaria co-infection dynamics

• Main Authors: Fatmawati, .-, Windarto, .-, Lathifah Hanif, .-
• Format: Book Section PeerReviewed
• Language: English; English; English; English
• Published: IOP Publishing 2018
• Subjects: Q Science; QA Mathematics; QA370-387 Differential Equations
• Online Access: https://repository.unair.ac.id/114301/1/C34.%20Fulltext.pdf; https://repository.unair.ac.id/114301/2/C34.%20Reviewer%20dan%20validasi.pdf; https://repository.unair.ac.id/114301/3/C34.%20Similarity.pdf; https://repository.unair.ac.id/114301/4/C34.%20Submission.pdf; https://repository.unair.ac.id/114301/; https://iopscience.iop.org/article/10.1088/1742-6596/974/1/012057
• Institution: Universitas Airlangga

This paper presents a mathematical model of HIV and malaria co-infection transmission dynamics. Optimal control strategies such as malaria preventive, anti-malaria and antiretroviral (ARV) treatments are considered into the model to reduce the co-infection. First, we studied the existence and stability of equilibria of the presented model without control variables. The model has four equilibria, namely the disease-free equilibrium, the HIV endemic equilibrium, the malaria endemic equilibrium, and the co-infection equilibrium. We also obtain two basic reproduction ratios corresponding to the diseases. It was found that the disease-free equilibrium is locally asymptotically stable whenever their respective basic reproduction numbers are less than one. We also conducted a sensitivity analysis to determine the dominant factor controlling the transmission. sic reproduction numbers are less than one. We also conducted a sensitivity analysis to determine the dominant factor controlling the transmission. Then, the optimal control theory for the model was derived analytically by using Pontryagin Maximum Principle. Numerical simulations of the optimal control strategies are also performed to illustrate the results. From the numerical results, we conclude that the best strategy is to combine the malaria prevention and ARV treatments in order to reduce malaria and HIV co-infection populations.