Mapping malaria by sharing spatial information between incidence and prevalence datasets
Mapping malaria by sharing spatial information between incidence and prevalence datasets
Summary As malaria incidence decreases and more countries move towards elimination, maps of malaria risk in low prevalence areas are increasingly needed. For low burden areas, disaggregation regression models have been developed to estimate risk at high spatial resolution from routine surveillance reports aggregated by administrative unit polygons. However, in …