Fine resolution mapping of population age-structures for health and development applications.

摘要: The age-group composition of populations varies considerably across the world, and obtaining accurate, spatially detailed estimates numbers children under 5 years is important in designing vaccination strategies, educational planning or maternal healthcare delivery. Traditionally, such are derived from population censuses, but these can often be unreliable, outdated coarse resolution for resource-poor settings. Focusing on Nigeria, we use nationally representative household surveys their cluster locations to predict proportion under-five 1 × km using a Bayesian hierarchical spatio-temporal model. Results showed that land cover, travel time major settlements, night-time lights vegetation index were good predictors accounting fine-scale variation, rather than assuming uniform year olds result significant differences health metrics. largest gaps estimated bednet coverage Kano, Katsina Jigawa. Geolocated valuable resource providing detailed, contemporary regularly updated age-structure data absence recent census data. By combining with covariate layers, maps unprecedented detail produced guide targeting interventions