Cargando…
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 emer...
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
World Health Organization; licensee Elsevier.
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7561303/ https://www.ncbi.nlm.nih.gov/pubmed/33069304 http://dx.doi.org/10.1016/S2214-109X(20)30359-4 |
_version_ | 1783595241636364288 |
---|---|
author | Garber, Kent Fox, Charles Abdalla, Moustafa Tatem, Andrew Qirbi, Naseeb Lloyd-Braff, Laura Al-Shabi, Kahtan Ongwae, Kennedy Dyson, Meredith Hassen, Kebir |
author_facet | Garber, Kent Fox, Charles Abdalla, Moustafa Tatem, Andrew Qirbi, Naseeb Lloyd-Braff, Laura Al-Shabi, Kahtan Ongwae, Kennedy Dyson, Meredith Hassen, Kebir |
author_sort | Garber, Kent |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7561303 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | World Health Organization; licensee Elsevier. |
record_format | MEDLINE/PubMed |
spelling | pubmed-75613032020-10-16 Estimating access to health care in Yemen, a complex humanitarian emergency setting: a descriptive applied geospatial analysis Garber, Kent Fox, Charles Abdalla, Moustafa Tatem, Andrew Qirbi, Naseeb Lloyd-Braff, Laura Al-Shabi, Kahtan Ongwae, Kennedy Dyson, Meredith Hassen, Kebir Lancet Glob Health Articles 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. World Health Organization; licensee Elsevier. 2020-11 2020-10-15 /pmc/articles/PMC7561303/ /pubmed/33069304 http://dx.doi.org/10.1016/S2214-109X(20)30359-4 Text en © 2020 World Health Organization Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Articles Garber, Kent Fox, Charles Abdalla, Moustafa Tatem, Andrew Qirbi, Naseeb Lloyd-Braff, Laura Al-Shabi, Kahtan Ongwae, Kennedy Dyson, Meredith Hassen, Kebir Estimating access to health care in Yemen, a complex humanitarian emergency setting: a descriptive applied geospatial analysis |
title | Estimating access to health care in Yemen, a complex humanitarian emergency setting: a descriptive applied geospatial analysis |
title_full | Estimating access to health care in Yemen, a complex humanitarian emergency setting: a descriptive applied geospatial analysis |
title_fullStr | Estimating access to health care in Yemen, a complex humanitarian emergency setting: a descriptive applied geospatial analysis |
title_full_unstemmed | Estimating access to health care in Yemen, a complex humanitarian emergency setting: a descriptive applied geospatial analysis |
title_short | Estimating access to health care in Yemen, a complex humanitarian emergency setting: a descriptive applied geospatial analysis |
title_sort | estimating access to health care in yemen, a complex humanitarian emergency setting: a descriptive applied geospatial analysis |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7561303/ https://www.ncbi.nlm.nih.gov/pubmed/33069304 http://dx.doi.org/10.1016/S2214-109X(20)30359-4 |
work_keys_str_mv | AT garberkent estimatingaccesstohealthcareinyemenacomplexhumanitarianemergencysettingadescriptiveappliedgeospatialanalysis AT foxcharles estimatingaccesstohealthcareinyemenacomplexhumanitarianemergencysettingadescriptiveappliedgeospatialanalysis AT abdallamoustafa estimatingaccesstohealthcareinyemenacomplexhumanitarianemergencysettingadescriptiveappliedgeospatialanalysis AT tatemandrew estimatingaccesstohealthcareinyemenacomplexhumanitarianemergencysettingadescriptiveappliedgeospatialanalysis AT qirbinaseeb estimatingaccesstohealthcareinyemenacomplexhumanitarianemergencysettingadescriptiveappliedgeospatialanalysis AT lloydbrafflaura estimatingaccesstohealthcareinyemenacomplexhumanitarianemergencysettingadescriptiveappliedgeospatialanalysis AT alshabikahtan estimatingaccesstohealthcareinyemenacomplexhumanitarianemergencysettingadescriptiveappliedgeospatialanalysis AT ongwaekennedy estimatingaccesstohealthcareinyemenacomplexhumanitarianemergencysettingadescriptiveappliedgeospatialanalysis AT dysonmeredith estimatingaccesstohealthcareinyemenacomplexhumanitarianemergencysettingadescriptiveappliedgeospatialanalysis AT hassenkebir estimatingaccesstohealthcareinyemenacomplexhumanitarianemergencysettingadescriptiveappliedgeospatialanalysis |