The University of Southampton
University of Southampton Institutional Repository

Estimating access to health care in Yemen, a complex humanitarian emergency setting: a descriptive applied geospatial analysis

Estimating access to health care in Yemen, a complex humanitarian emergency setting: a descriptive applied geospatial analysis
Estimating access to health care in Yemen, a complex humanitarian emergency setting: a descriptive applied geospatial analysis
Background
In conflict settings, data to guide humanitarian and development responses are often scarce. Although geospatial analyses have been used to estimate health-care access in many countries, such techniques have not been widely applied to inform real-time operations in protracted health emergencies. Doing so could provide a more robust approach for identifying and prioritising populations in need, targeting assistance, and assessing impact. We aimed to use geospatial analyses to overcome such data gaps in Yemen, the site of one of the world's worst ongoing humanitarian crises.
Methods
We derived geospatial coordinates, functionality, and service availability data for Yemen health facilities from the Health Resources and Services Availability Monitoring System assessment done by WHO and the Yemen Ministry of Public Health and Population. We modelled population spatial distribution using high-resolution satellite imagery, UN population estimates, and census data. A road network grid was built from OpenStreetMap and satellite data and modified using UN Yemen Logistics Cluster data and other datasets to account for lines of conflict and road accessibility. Using this information, we created a geospatial network model to deduce the travel time of Yemeni people to their nearest health-care facilities.
Findings
In 2018, we estimated that nearly 8·8 million (30·6%) of the total estimated Yemeni population of 28·7 million people lived more than 30-min travel time from the nearest fully or partially functional public primary health-care facility, and more than 12·1 million (42·4%) Yemeni people lived more than 1 h from the nearest fully or partially functional public hospital, assuming access to motorised transport. We found that access varied widely by district and type of health service, with almost 40% of the population living more than 2 h from comprehensive emergency obstetric and surgical care. We identified and ranked districts according to the number of people living beyond acceptable travel times to facilities and services. We found substantial variability in access and that many front-line districts were among those with the poorest access.
Interpretation
These findings provide the most comprehensive estimates of geographical access to health care in Yemen since the outbreak of the current conflict, and they provide proof of concept for how geospatial techniques can be used to address data gaps and rigorously inform health programming. Such information is of crucial importance for humanitarian and development organisations seeking to improve effectiveness and accountability.
Funding
Global Financing Facility for Women, Children, and Adolescents Trust Fund; Development and Data Science grant; and the Yemen Emergency Health and Nutrition Project, a partnership between the World Bank, UNICEF, and WHO.
2214-109X
E1435-E1443
Garber, Kent
9577c132-65de-48b8-92e0-56830f83ba2c
Fox, Charles
3adc117a-3734-4474-a05f-53218ce54c3a
Abdalla, Moustafa
51937c57-33f1-4a9b-8736-fc9b84b267c2
Tatem, Andrew
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Qirbi, Naseeb
d01c0d19-d0ee-4c03-93d1-1fbc15110256
Lloyd-Braff, Laura
111ad9f2-411f-4eb9-8452-d125b1334cd1
Al-Shobi, Kahtan
0e9c828f-2f8c-4f70-9683-46a832f40a71
Ongwae, Kennedy
15f6b60f-c221-4527-8cff-a135e2ebc43d
Dyson, Meredith
97f56b57-5dc1-4260-8fe9-fdb1b58f70f9
Hassen, Kebir
0813d108-9ef8-4609-8b1b-7a69353b50c4
Garber, Kent
9577c132-65de-48b8-92e0-56830f83ba2c
Fox, Charles
3adc117a-3734-4474-a05f-53218ce54c3a
Abdalla, Moustafa
51937c57-33f1-4a9b-8736-fc9b84b267c2
Tatem, Andrew
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Qirbi, Naseeb
d01c0d19-d0ee-4c03-93d1-1fbc15110256
Lloyd-Braff, Laura
111ad9f2-411f-4eb9-8452-d125b1334cd1
Al-Shobi, Kahtan
0e9c828f-2f8c-4f70-9683-46a832f40a71
Ongwae, Kennedy
15f6b60f-c221-4527-8cff-a135e2ebc43d
Dyson, Meredith
97f56b57-5dc1-4260-8fe9-fdb1b58f70f9
Hassen, Kebir
0813d108-9ef8-4609-8b1b-7a69353b50c4

Garber, Kent, Fox, Charles, Abdalla, Moustafa, Tatem, Andrew, Qirbi, Naseeb, Lloyd-Braff, Laura, Al-Shobi, Kahtan, Ongwae, Kennedy, Dyson, Meredith and Hassen, Kebir (2020) Estimating access to health care in Yemen, a complex humanitarian emergency setting: a descriptive applied geospatial analysis. Lancet Global Health, 8 (11), E1435-E1443. (doi:10.1016/S2214-109X(20)30359-4).

Record type: Article

Abstract

Background
In conflict settings, data to guide humanitarian and development responses are often scarce. Although geospatial analyses have been used to estimate health-care access in many countries, such techniques have not been widely applied to inform real-time operations in protracted health emergencies. Doing so could provide a more robust approach for identifying and prioritising populations in need, targeting assistance, and assessing impact. We aimed to use geospatial analyses to overcome such data gaps in Yemen, the site of one of the world's worst ongoing humanitarian crises.
Methods
We derived geospatial coordinates, functionality, and service availability data for Yemen health facilities from the Health Resources and Services Availability Monitoring System assessment done by WHO and the Yemen Ministry of Public Health and Population. We modelled population spatial distribution using high-resolution satellite imagery, UN population estimates, and census data. A road network grid was built from OpenStreetMap and satellite data and modified using UN Yemen Logistics Cluster data and other datasets to account for lines of conflict and road accessibility. Using this information, we created a geospatial network model to deduce the travel time of Yemeni people to their nearest health-care facilities.
Findings
In 2018, we estimated that nearly 8·8 million (30·6%) of the total estimated Yemeni population of 28·7 million people lived more than 30-min travel time from the nearest fully or partially functional public primary health-care facility, and more than 12·1 million (42·4%) Yemeni people lived more than 1 h from the nearest fully or partially functional public hospital, assuming access to motorised transport. We found that access varied widely by district and type of health service, with almost 40% of the population living more than 2 h from comprehensive emergency obstetric and surgical care. We identified and ranked districts according to the number of people living beyond acceptable travel times to facilities and services. We found substantial variability in access and that many front-line districts were among those with the poorest access.
Interpretation
These findings provide the most comprehensive estimates of geographical access to health care in Yemen since the outbreak of the current conflict, and they provide proof of concept for how geospatial techniques can be used to address data gaps and rigorously inform health programming. Such information is of crucial importance for humanitarian and development organisations seeking to improve effectiveness and accountability.
Funding
Global Financing Facility for Women, Children, and Adolescents Trust Fund; Development and Data Science grant; and the Yemen Emergency Health and Nutrition Project, a partnership between the World Bank, UNICEF, and WHO.

This record has no associated files available for download.

More information

Published date: 1 November 2020
Additional Information: © 2020 World Health Organization

Identifiers

Local EPrints ID: 457937
URI: http://eprints.soton.ac.uk/id/eprint/457937
ISSN: 2214-109X
PURE UUID: c0c3cff1-7fea-4a58-8d04-319a3433c37d
ORCID for Andrew Tatem: ORCID iD orcid.org/0000-0002-7270-941X

Catalogue record

Date deposited: 23 Jun 2022 16:41
Last modified: 17 Mar 2024 03:29

Export record

Altmetrics

Contributors

Author: Kent Garber
Author: Charles Fox
Author: Moustafa Abdalla
Author: Andrew Tatem ORCID iD
Author: Naseeb Qirbi
Author: Laura Lloyd-Braff
Author: Kahtan Al-Shobi
Author: Kennedy Ongwae
Author: Meredith Dyson
Author: Kebir Hassen

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×