National population mapping from sparse survey data: A hierarchical Bayesian modeling framework to account for uncertainty
Leasure DR., Jochem WC., Weber EM., Seaman V., Tatem AJ.
Significance High-resolution population estimates are essential for government planning, development projects, and public health campaigns, but countries where this information is most needed are often where recent national census data are least available. We present a modeling framework that combines recent neighborhood-scale microcensus surveys with national-scale data from satellite images and digital maps to estimate population sizes for every 100-m grid square nationally. We present a case study from Nigeria where population estimates with national coverage were produced using household survey data from 1,141 locations. This work represents a significant step toward achieving high-resolution population estimates with national coverage from sparse population data while providing reliable estimates of uncertainty at any spatial scale.