National population mapping from sparse survey data: A hierarchical Bayesian modeling framework to account for uncertainty.

ABSTRACT: Population estimates are critical for government services, development projects, and public health campaigns. Such data are typically obtained through a national population and housing census. However, population estimates can quickly become inaccurate in localized areas, particularly where migration or displacement has occurred. Some conflict-affected and resource-poor countries have not conducted a census in over 10 y. We developed a hierarchical Bayesian model to estimate population numbers in small areas based on enumeration data from sample areas and nationwide information about administrative boundaries, building locations, settlement types, and other factors related to population density. We demonstrated this model by estimating population sizes in every 10- m grid cell in Nigeria w

SUBMITTER: Leasure DR 

PROVIDER: S-EPMC7533662 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature