Optimal control in a model of malaria with differential susceptibility

Doracelly Hincapié; Juan Ospina

doi:10.1117/12.2049782

5 June 2014 Optimal control in a model of malaria with differential susceptibility

Doracelly Hincapié, Juan Ospina

Proceedings Volume 9112, Sensing Technologies for Global Health, Military Medicine, and Environmental Monitoring IV; 91121P (2014) https://doi.org/10.1117/12.2049782
Event: SPIE Sensing Technology + Applications, 2014, Baltimore, MD, United States

Abstract

A malaria model with differential susceptibility is analyzed using the optimal control technique. In the model the human population is classified as susceptible, infected and recovered. Susceptibility is assumed dependent on genetic, physiological, or social characteristics that vary between individuals. The model is described by a system of differential equations that relate the human and vector populations, so that the infection is transmitted to humans by vectors, and the infection is transmitted to vectors by humans. The model considered is analyzed using the optimal control method when the control consists in using of insecticide-treated nets and educational campaigns; and the optimality criterion is to minimize the number of infected humans, while keeping the cost as low as is possible. One first goal is to determine the effects of differential susceptibility in the proposed control mechanism; and the second goal is to determine the algebraic form of the basic reproductive number of the model. All computations are performed using computer algebra, specifically Maple. It is claimed that the analytical results obtained are important for the design and implementation of control measures for malaria. It is suggested some future investigations such as the application of the method to other vector-borne diseases such as dengue or yellow fever; and also it is suggested the possible application of free software of computer algebra like Maxima.

Citation Download Citation

Doracelly Hincapié and Juan Ospina "Optimal control in a model of malaria with differential susceptibility", Proc. SPIE 9112, Sensing Technologies for Global Health, Military Medicine, and Environmental Monitoring IV, 91121P (5 June 2014); https://doi.org/10.1117/12.2049782

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