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High-resolution population mapping and estimation in the western part of the Democratic Republic of Congo

High-resolution population mapping and estimation in the western part of the Democratic Republic of Congo
High-resolution population mapping and estimation in the western part of the Democratic Republic of Congo
According to the United Nations, the Democratic Republic of Congo (DRC) is the fourth most populous country in Africa. Yet, accurate demographic figures are currently unavailable because the last national census was conducted over three decades ago. This situation has shown to be critical to policymaking and intervention planning in the domain of public health. In the western part of the country, for instance, human African trypanosomiasis is highly endemic but accurate sub-national population figures are required for effective disease mapping. This work aims at producing gridded population estimates with a 100 meters spatial resolution for the five most western provinces of DRC. In doing so, we adopt a bottom-up modeling approach incorporating demographic data from recent micro-census surveys and various geospatial datasets in a Bayesian hierarchical framework. The resulting high-resolution population estimates and associated uncertainty measures are meant to inform spatial epidemiological applications in the region and foster the use of similar modeling approaches in other parts of the country.
Darin, Edith
868fa688-2567-4dbd-aa12-3dcc91f2aa8d
Boo, Gianluca
d49f7aaa-6d95-4e36-b9be-e469911c4a3d
Leasure, Douglas
c025de11-3c61-45b0-9b19-68d1d37959cd
Tatem, Andrew
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Darin, Edith
868fa688-2567-4dbd-aa12-3dcc91f2aa8d
Boo, Gianluca
d49f7aaa-6d95-4e36-b9be-e469911c4a3d
Leasure, Douglas
c025de11-3c61-45b0-9b19-68d1d37959cd
Tatem, Andrew
6c6de104-a5f9-46e0-bb93-a1a7c980513e

Darin, Edith, Boo, Gianluca, Leasure, Douglas and Tatem, Andrew (2019) High-resolution population mapping and estimation in the western part of the Democratic Republic of Congo. GEOMED 2019: XI international, interdisciplinary conference on spatial statistics, geographical epidemiology and geographical aspects of public health, United Kingdom. 27 - 29 Aug 2020. (doi:10.13140/RG.2.2.24975.94880).

Record type: Conference or Workshop Item (Poster)

Abstract

According to the United Nations, the Democratic Republic of Congo (DRC) is the fourth most populous country in Africa. Yet, accurate demographic figures are currently unavailable because the last national census was conducted over three decades ago. This situation has shown to be critical to policymaking and intervention planning in the domain of public health. In the western part of the country, for instance, human African trypanosomiasis is highly endemic but accurate sub-national population figures are required for effective disease mapping. This work aims at producing gridded population estimates with a 100 meters spatial resolution for the five most western provinces of DRC. In doing so, we adopt a bottom-up modeling approach incorporating demographic data from recent micro-census surveys and various geospatial datasets in a Bayesian hierarchical framework. The resulting high-resolution population estimates and associated uncertainty measures are meant to inform spatial epidemiological applications in the region and foster the use of similar modeling approaches in other parts of the country.

Full text not available from this repository.

More information

Published date: August 2019
Venue - Dates: GEOMED 2019: XI international, interdisciplinary conference on spatial statistics, geographical epidemiology and geographical aspects of public health, United Kingdom, 2020-08-27 - 2020-08-29

Identifiers

Local EPrints ID: 442932
URI: http://eprints.soton.ac.uk/id/eprint/442932
PURE UUID: 3a0dc34f-a2cc-4186-b62a-aca0d0bbc412
ORCID for Edith Darin: ORCID iD orcid.org/0000-0002-8176-092X
ORCID for Gianluca Boo: ORCID iD orcid.org/0000-0002-4078-8221
ORCID for Andrew Tatem: ORCID iD orcid.org/0000-0002-7270-941X

Catalogue record

Date deposited: 03 Aug 2020 16:30
Last modified: 04 Aug 2020 01:52

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