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Title: Capturing diagnostic error in geostatistical models of Malaria survey data Authors:  Eleni Verykouki - Swiss Tropical and Public Health Institute (Switzerland) [presenting]
Andres Cardona Gavaldon - Swiss Tropical and Public Health Institute (Switzerland)
Penelope Vounatsou - Swiss Tropical and Public Health Institute (Switzerland)
Abstract: Malaria is a blood disease that is caused by parasites that are transmitted to humans via the Anopheles mosquito. It is usually found in tropical and subtropical climates where the parasites that cause it live, and it is most prevalent in the African region. Children under five years of age are one of most vulnerable groups affected by malaria. Early and accurate diagnosis of malaria is essential for effective disease management and malaria surveillance. There are two main diagnostic tools to test for malaria, Microscopic diagnosis and Rapid Diagnostic Test (RDT). The aim concerns the estimation of the prevalence of malaria in children under five in Africa. Data consist of environmental and socio economic parameters. Data of microscopy tests and RDT are also used to measure for diagnostic error in the case where neither tests can be considered as a gold standard. Bayesian inference and spatial statistical methodology are employed to obtain high spatial resolution maps of malaria transmission risk in children under five in African countries.