Quantifying aggregated uncertainty in Plasmodim falciparum malaria prevalence and populations at risk via efficient space-time geostatistical joint simulation

Risk maps estimating the spatial distribution of infectious diseases are required to guide public health policy from local to global scales. The advent of model-based geostatistics (MBG) has allowed these maps to be generated in a formal statistical framework, providing robust metrics of map uncerta...

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Bibliographic Details
Main Authors: Gething, P, Patil, A, Hay, S
Format: Journal article
Language:English
Published: Public Library of Science 2010
Subjects: