Journal article
High-resolution population estimation using household survey data and building footprints
- Abstract:
- The national census is an essential data source to support decision-making in many areas of public interest. However, this data may become outdated during the intercensal period, which can stretch up to several decades. In this study, we develop a Bayesian hierarchical model leveraging recent household surveys and building footprints to produce up-to-date population estimates. We estimate population totals and age and sex breakdowns with associated uncertainty measures within grid cells of approximately 100 m in five provinces of the Democratic Republic of the Congo, a country where the last census was completed in 1984. The model exhibits a very good fit, with an R2 value of 0.79 for out-of-sample predictions of population totals at the microcensus-cluster level and 1.00 for age and sex proportions at the province level. This work confirms the benefits of combining household surveys and building footprints for high-resolution population estimation in countries with outdated censuses.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 2.8MB, Terms of use)
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- Publisher copy:
- 10.1038/s41467-022-29094-x
Authors
- Publisher:
- Springer Nature
- Journal:
- Nature Communications More from this journal
- Volume:
- 13
- Article number:
- 1330
- Publication date:
- 2022-03-14
- Acceptance date:
- 2022-02-23
- DOI:
- EISSN:
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2041-1723
- Language:
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English
- Keywords:
- Pubs id:
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1276595
- Local pid:
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pubs:1276595
- Deposit date:
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2022-09-01
Terms of use
- Copyright holder:
- Boo et al.
- Copyright date:
- 2022
- Rights statement:
- Copyright © 2022 The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
- Licence:
- CC Attribution (CC BY)
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