Optimal Control Strategies for Minimizing Malaria Transmission in Kenya

Abstract

Malaria remains a leading cause of mortality and morbidity among children under five and pregnant women in sub-Saharan Africa. It is however preventable and controllable provided current recommended interventions are properly implemented. Malaria transmission is highly variable across Kenya because of the different transmission intensities. The challenges posed by malaria and the targets for a malaria-free world call for the understanding of malaria dynamics and determining the effective and optimal strategies for preventing and controlling the spread of malaria. Better utilization of malaria intervention strategies will ensure the gain in the value for money by developing a better understanding (and better articulation) of costs and results so that more informed, evidence-based choices are made. The study formulated and analyzed a deterministic model for malaria transmission dynamics with four malaria control strategies used in Kenya namely: Insecticide Treated Nets (ITNs), treatment, Indoor Residual Spraying (IRS) and Intermittent Prevention Treatment for pregnant women (IPTp). The study further formulated an optimal control problem and derived expressions for the optimal control for the malaria model with four control variables, with the aim of minimizing total mosquito population, infected individuals and exposed individuals while keeping the cost low for different transmission settings in Kenya. Cost effective analysis of one or all possible combinations of malaria control strategies for different transmission settings was carried out to assess the extent to which the intervention strategies were beneficial and cost effective. Collected data from both published and hospital records (in Kisumu, Kisii, Chuka and Nyeri representing the four different transmission settings/ epidemiological zones in Kenya) were used to estimate the parameters for the malaria model. Numerical simulations were done in the R Statistical Computing platform. Numerical simulations indicated that malaria control strategies have effect in lowering exposed and infected members of both human and mosquito population. The most sensitive parameters were mosquito death rate and mosquito biting rate. The optimal control strategies for malaria control in both endemic and epidemic-prone areas was the combined use of treatment andIRS; in seasonal areas it was the use of treatment; and in low risk areas was the use of ITNs and treatment. The most cost-effective intervention strategies in endemic areas was the combination of treatment, IRS and IPTp; in epidemic-prone areas it was the use of treatment and IRS; for seasonal areas it was the use of ITNs and treatment, and for the low risk areas it was the use of treatment. In order to minimize malaria transmission in Kenya, the study recommends interventions strategies targeting to reduce mosquito population and mosquito bitting rates. Strategies targeting to reduce mosquito population and mosquito biting rates (vector control) such as ITNs and IRS should be implemented. The study recommends optimal use of treatment and IRS for both endemic and epidemic prone areas, treatment for seasonal areas, and ITNs and treatment for low risk areas. The recommended cost effective strategies for malaria control are use of IRS and IPTp for endemic area, use of treatment and IRS for epidemic-prone areas, use of ITNs and treatment for seasonal and use of treatment for low risk areas. This study provided useful tools that can guide policy makers in designing interventions that suits the groups most at risk for malaria (i.e. under five year-olds and the pregnant women) for different transmission settings, post-2015 malaria eradication strategies and achievement of the UN Sustainable Development Goals.