New diagnostics and treatments for malaria have renewed hope in the developing world as they promise relief from the debilitating effects of this illness. Accompanying these interventions are a growing number of economic evaluations assessing their efficiency. To ensure the relevance of economic evaluations to decision making purposes it is imperative that they use best available computational and statistical approaches. This thesis initially discusses the necessary requirements for economic evaluations to ensure they provide appropriate decision recommendations. This is followed by four evaluations of malaria diagnostics and treatments using methods new to the context of malaria. The first study expands the range of factors included in the evaluation of diagnostic tests, addressing compromised adherence to test results and societal costs associated with antimalarial use. The second analysis demonstrates how models can be designed as decision support tools allowing stakeholders to enter local data along with other parameter estimates, priorities and values. Both Bayesian and deterministic models are presented for comparison. The third analysis demonstrates the use of multilevel models for economic evaluations based on multi-centre trials. The chapter compares the results of a multilevel model evaluating treatments for severe malaria with those obtained in a standard analysis. The fourth study uses a Markov model to evaluate the efficiency of Home Management of Malaria programmes. The use of a Markov model addresses the restricted portrayal of malaria infection and illness that has characterised many previous evaluations. In addition to contributing to a better understanding of the cost-effectiveness of the latest malaria treatments and diagnostic tests, this thesis seeks to bridge the growing gap between recent methodological advances in the field of economic evaluation, and the relative paucity of evaluations producing practical and effective policy recommendations for areas of the world where the burden of malaria and other diseases is heaviest.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:536822 |
| Date | January 2009 |
| Creators | Lubell, Yoel |
| Contributors | Mills, A. |
| Publisher | London School of Hygiene and Tropical Medicine (University of London) |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://researchonline.lshtm.ac.uk/1343273/ |
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