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A review of geospatial methods for population estimation and their use in constructing reproductive, maternal, newborn, child and adolescent health service indicators

A review of geospatial methods for population estimation and their use in constructing reproductive, maternal, newborn, child and adolescent health service indicators
A review of geospatial methods for population estimation and their use in constructing reproductive, maternal, newborn, child and adolescent health service indicators
Household survey data are frequently used to measure reproductive, maternal, newborn, child and adolescent health (RMNCAH) service utilisation in low and middle income countries. However, these surveys are typically only undertaken every 5 years and tend to be representative of larger geographical administrative units. Investments in district health management information systems (DHMIS) have increased the capability of countries to collect continuous information on the provision of RMNCAH services at health facilities. However, reliable and recent data on population distributions and demographics at subnational levels necessary to construct RMNCAH coverage indicators are often missing. One solution is to use spatially disaggregated gridded datasets containing modelled estimates of population counts. Here, we provide an overview of various approaches to the production of gridded demographic datasets and outline their potential and their limitations. Further, we show how gridded population estimates can be used as alternative denominators to produce RMNCAH coverage metrics in combination with data from DHMIS, using childhood vaccination as examples.
Denominators, Geospatial modelling, Gridded data sets, RMNCAH, Subnational estimation, Universal coverage
1472-6963
Nilsen, Kristine
306e0bd5-8139-47db-be97-47fe15f0c03b
Tejedor-Garavito, Natalia
26fd242c-c882-4210-a74d-af2bb6753ee3
Leasure, Douglas R.
c025de11-3c61-45b0-9b19-68d1d37959cd
Utazi, C. Edson
91982e3d-d79b-4e0e-ba23-7bdfa417b10b
Ruktanonchai, Corrine W.
44e6fcd0-246b-480e-8940-9557dbb7c0cc
Wigley, Adelle S.
21b38ae2-ffd3-4d45-bf29-843e6d62807f
Dooley, Claire A.
8caf4d90-5b57-4f92-a6e6-ff2399114af1
Matthews, Zoe
ebaee878-8cb8-415f-8aa1-3af2c3856f55
Tatem, Andrew J.
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Nilsen, Kristine
306e0bd5-8139-47db-be97-47fe15f0c03b
Tejedor-Garavito, Natalia
26fd242c-c882-4210-a74d-af2bb6753ee3
Leasure, Douglas R.
c025de11-3c61-45b0-9b19-68d1d37959cd
Utazi, C. Edson
91982e3d-d79b-4e0e-ba23-7bdfa417b10b
Ruktanonchai, Corrine W.
44e6fcd0-246b-480e-8940-9557dbb7c0cc
Wigley, Adelle S.
21b38ae2-ffd3-4d45-bf29-843e6d62807f
Dooley, Claire A.
8caf4d90-5b57-4f92-a6e6-ff2399114af1
Matthews, Zoe
ebaee878-8cb8-415f-8aa1-3af2c3856f55
Tatem, Andrew J.
6c6de104-a5f9-46e0-bb93-a1a7c980513e

Nilsen, Kristine, Tejedor-Garavito, Natalia, Leasure, Douglas R., Utazi, C. Edson, Ruktanonchai, Corrine W., Wigley, Adelle S., Dooley, Claire A., Matthews, Zoe and Tatem, Andrew J. (2021) A review of geospatial methods for population estimation and their use in constructing reproductive, maternal, newborn, child and adolescent health service indicators. BMC Health Services Research, 21 (1), [370]. (doi:10.1186/s12913-021-06370-y).

Record type: Article

Abstract

Household survey data are frequently used to measure reproductive, maternal, newborn, child and adolescent health (RMNCAH) service utilisation in low and middle income countries. However, these surveys are typically only undertaken every 5 years and tend to be representative of larger geographical administrative units. Investments in district health management information systems (DHMIS) have increased the capability of countries to collect continuous information on the provision of RMNCAH services at health facilities. However, reliable and recent data on population distributions and demographics at subnational levels necessary to construct RMNCAH coverage indicators are often missing. One solution is to use spatially disaggregated gridded datasets containing modelled estimates of population counts. Here, we provide an overview of various approaches to the production of gridded demographic datasets and outline their potential and their limitations. Further, we show how gridded population estimates can be used as alternative denominators to produce RMNCAH coverage metrics in combination with data from DHMIS, using childhood vaccination as examples.

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More information

Accepted/In Press date: 9 April 2021
Published date: 13 September 2021
Keywords: Denominators, Geospatial modelling, Gridded data sets, RMNCAH, Subnational estimation, Universal coverage

Identifiers

Local EPrints ID: 451440
URI: http://eprints.soton.ac.uk/id/eprint/451440
ISSN: 1472-6963
PURE UUID: 806fd6b7-ccff-45fe-a650-2848fc96d22d
ORCID for Kristine Nilsen: ORCID iD orcid.org/0000-0003-2009-4019
ORCID for Natalia Tejedor-Garavito: ORCID iD orcid.org/0000-0002-1140-6263
ORCID for Douglas R. Leasure: ORCID iD orcid.org/0000-0002-8768-2811
ORCID for Zoe Matthews: ORCID iD orcid.org/0000-0003-1533-6618
ORCID for Andrew J. Tatem: ORCID iD orcid.org/0000-0002-7270-941X

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Date deposited: 27 Sep 2021 16:33
Last modified: 17 Mar 2024 03:53

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Contributors

Author: Kristine Nilsen ORCID iD
Author: Douglas R. Leasure ORCID iD
Author: C. Edson Utazi
Author: Corrine W. Ruktanonchai
Author: Adelle S. Wigley
Author: Claire A. Dooley
Author: Zoe Matthews ORCID iD
Author: Andrew J. Tatem ORCID iD

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