Bayesian geostatistics in health cartography: the perspective of malaria

摘要: Maps of parasite prevalences and other aspects infectious diseases that vary in space are widely used parasitology. However, spatial parasitological datasets rarely, if ever, have sufficient coverage to allow exact determination such maps. Bayesian geostatistics (BG) is a method for finding large sample maps can explain dataset, which do better job explaining the data more likely be represented. This represents knowledge analyst has gained from about unknown true map. BG provides conceptually simple way convert these samples predictions features map, example regional averages. These account each map sample, yielding an appropriate level predictive precision.