Publications
1.
Darin, Edith; Boo, Gianluca; Tatem, Andrew J
A bottom-up population modelling approach to complement the population and housing census Conference
IUSSP , International Population Conference 2021, 2021.
Abstract | Links | BibTeX | Tags: Africa, bottom-up modelling, census, Democratic Republic of Congo
@conference{nokey,
title = {A bottom-up population modelling approach to complement the population and housing census},
author = {Darin, Edith and Boo, Gianluca and Tatem, Andrew J},
url = {https://ipc2021.popconf.org/abstracts/210325},
year = {2021},
date = {2021-12-07},
urldate = {2021-12-07},
booktitle = {IUSSP , International Population Conference 2021},
abstract = {The population and housing census provides essential demographic information for decision-making and action at local, national and international levels. However, census data in the most vulnerable countries is often outdated or partial because political instability, conflict and natural disasters prevent a national count. The bottom-up modeling approach helps supplement outdated or incomplete census data by estimating population counts and age/sex structures in approximately 100m grid cells using population data collected over a set fully enumerated places and auxiliary geospatial covariates. We present the modeling effort carried out in the Democratic Republic of Congo — the last census was carried out in 1984 — and in Burkina Faso — the last census was carried out in 2020 but only covered 70% of the country. Both models showed good predictive performance, indicated by R2 values of 0.73 and 0.63 for the respective out-of-sample predictions of population counts. The resulting bottom-up, gridded population estimates are currently used for census support and humanitarian response in both countries. This work highlights the flexibility of the bottom-up modeling approach, in terms of input population data, model specification, and aggregation of population estimates to support specific use cases.},
keywords = {Africa, bottom-up modelling, census, Democratic Republic of Congo},
pubstate = {published},
tppubtype = {conference}
}
The population and housing census provides essential demographic information for decision-making and action at local, national and international levels. However, census data in the most vulnerable countries is often outdated or partial because political instability, conflict and natural disasters prevent a national count. The bottom-up modeling approach helps supplement outdated or incomplete census data by estimating population counts and age/sex structures in approximately 100m grid cells using population data collected over a set fully enumerated places and auxiliary geospatial covariates. We present the modeling effort carried out in the Democratic Republic of Congo — the last census was carried out in 1984 — and in Burkina Faso — the last census was carried out in 2020 but only covered 70% of the country. Both models showed good predictive performance, indicated by R2 values of 0.73 and 0.63 for the respective out-of-sample predictions of population counts. The resulting bottom-up, gridded population estimates are currently used for census support and humanitarian response in both countries. This work highlights the flexibility of the bottom-up modeling approach, in terms of input population data, model specification, and aggregation of population estimates to support specific use cases.
