Evidence map›Paper›PMID 33069304›Full record

ArticleThe Lancet. Global health2020

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

Kent Garber, Charles Fox, Moustafa Abdalla, Andrew Tatem, Naseeb Qirbi, Laura Lloyd-Braff, Kahtan Al-Shabi, Kennedy Ongwae, Meredith Dyson, Kebir Hassen

Open access · goldAbstract read
In one paragraph

Article in The Lancet. Global health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
5.6field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 1 synthesis or guideline pooled it, 56 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 5 institutions in 5 countries.

Kent GarberHealth, Nutrition, and Population Sector, Middle East and North Africa, World Bank, Washington, DC, USA. Electronic address: kgarber@worldbank.org.
Charles FoxDepartment of Sustainable Development, World Bank, Washington, DC, USA.
Moustafa AbdallaHealth, Nutrition, and Population Sector, Middle East and North Africa, World Bank, Washington, DC, USA.
Andrew TatemWorldPop, School of Geography and Environmental Science, University of Southampton, Southampton, UK.
Naseeb QirbiWHO, Sana'a, Yemen.
Laura Lloyd-BraffWHO, Sana'a, Yemen.
Kahtan Al-ShabiWHO, Sana'a, Yemen.
Kennedy OngwaeHealth and Nutrition Department for UNICEF Yemen, Amman, Jordan.
Meredith DysonHealth and Nutrition Department for UNICEF Yemen, Amman, Jordan.
Kebir HassenHealth and Nutrition Department for UNICEF Sudan, Khartoum, Sudan.
Sana'a University · YEWorld Bank · USUnited Nations Relief and Works Agency for Palestine Refugees in the Near East · JOFederal Ministry of Health · SDUniversity of Southampton · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn 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.

methodsWe 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.

findingsIn 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.

interpretationThese 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.

fundingGlobal 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.

Indexed as

Health Services AccessibilityHumansModels, StatisticalRelief WorkSpatial AnalysisYemen

Identifiers

PMID33069304
PMCPMC7561303
OpenAlexW3092671884

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.