The fifth Millennium Development target of reducing infant mortality by two thirds by the year 2015 can only be achieved if mortality due to malaria is significantly reduced. WHO recommends early detection and treatment among high-risk groups as one of the strategies for reducing the malaria burden. To be effective, this approach requires an early warning system which enables the health care system to be well-prepared and to allocate scarce resources effectively. Unfortunately, such a system is still not available at the appropriate scale. This book addresses this issue by developing a dynamic malaria transmission model at a local (district) scale using appropriate environmental factors. This dynamic model, driven by temperature and rainfall, successfully simulates seasonal vector abundance and also predicts successfully the monthly malaria incidence. Additionally through a detailed and innovative methodology this pioneering book enables scientists to replicate the study elsewhere in different settings.
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Yazoumé Yé African Population and Health Research Centre, Kenya. Osman Sankoh INDEPTH Network, Ghana. Bocar Kouyaté Centre National de Recherche et de Formation sur le Paludisme, Burkina Faso. Rainer Sauerborn University of Heidelberg, Germany.
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