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Preventive Strategies to Reduce Malaria Burden: Epidemiological Surveillance and Modeling for New Control and Elimination Methodologies
- Dixit, Amruta
- Advisor(s): Ogunseitan, Oladele
Abstract
Malaria epidemiology around the world is changing at a rapid pace due to intensive malaria control campaigns in the past decade. In spite of major progress in malaria control, new strategies are needed to reduce the malaria disease burden and reach global eradication goals. Within the framework of translational medicine, this interdisciplinary dissertation used a multilevel approach to describe and evaluate strategies seen as imperative to achieving the goal of malaria elimination set forth by the World Health Organization. We used a combination of field surveys and mathematical modeling methodologies to examine malaria epidemiology from the individual, the community, and the bench-side perspectives in countries aiming at control (Kenya) and elimination (Thailand). In Kenya, the combination of consumer, healthcare provider, and pharmaceutical retailer surveys revealed that the high cost of diagnosis and treatment at a healthcare facility may be inhibiting positive health-seeking behavior and may be incongruent with the goals of
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current subsidization policies. In Thailand, field surveys identified cross-border human movement patterns and important migration parameters between Thailand and Myanmar. The multi-node model simulations found an indirect impact of interventions on the side of the border that did not receive the intervention. Sensitivity analyses showed that the indirect impact of vector control was stronger with increased migration rates. Therefore, in this border region that harbors a constant and unmonitored flow of people, the regional malaria elimination strategies need to be accommodative of highly mobile populations. Lastly, we used a combination of field survey data from Kenya and the mathematical model to explore potential added benefits of including a long-lasting microbial larvicide as a supplemental vector control strategy in endemic regions of sub-Saharan Africa where insecticide resistance and changes in vector behavior present significant challenges to control. The model results indicated that larviciding has the potential to provide significant added benefits to malaria control in the context of prevailing pyrethroid resistance and outdoor transmission. In conclusion, parameterizing mathematical models with field-derived entomological and epidemiological data framed within individual, community, and bench-side perspectives, can represent a valuable approach to assist malaria control and elimination efforts.
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