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 emerg...

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Autores:
Tipo de recurso:
Article of investigation
Fecha de publicación:
2020
Institución:
Universidad de Bogotá Jorge Tadeo Lozano
Repositorio:
Expeditio: repositorio UTadeo
Idioma:
eng
OAI Identifier:
oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/14563
Acceso en línea:
https://doi.org/10.1016/S2214-109X(20)30359-4
http://hdl.handle.net/20.500.12010/14563
Palabra clave:
Humanitarian emergency
Geospatial analysis
Health care
Yemen
Síndrome respiratorio agudo grave
COVID-19
SARS-CoV-2
Coronavirus
Rights
License
Abierto (Texto Completo)
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oai_identifier_str oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/14563
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dc.title.spa.fl_str_mv 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
spellingShingle Estimating access to health care in Yemen, a complex humanitarian emergency setting: a descriptive applied geospatial analysis
Humanitarian emergency
Geospatial analysis
Health care
Yemen
Síndrome respiratorio agudo grave
COVID-19
SARS-CoV-2
Coronavirus
title_short 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_sort Estimating access to health care in Yemen, a complex humanitarian emergency setting: a descriptive applied geospatial analysis
dc.subject.spa.fl_str_mv Humanitarian emergency
Geospatial analysis
Health care
Yemen
topic Humanitarian emergency
Geospatial analysis
Health care
Yemen
Síndrome respiratorio agudo grave
COVID-19
SARS-CoV-2
Coronavirus
dc.subject.lemb.spa.fl_str_mv Síndrome respiratorio agudo grave
COVID-19
SARS-CoV-2
Coronavirus
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.
publishDate 2020
dc.date.accessioned.none.fl_str_mv 2020-10-19T14:39:00Z
dc.date.available.none.fl_str_mv 2020-10-19T14:39:00Z
dc.date.created.none.fl_str_mv 2020
dc.type.local.spa.fl_str_mv Artículo
dc.type.coar.spa.fl_str_mv http://purl.org/coar/resource_type/c_2df8fbb1
format http://purl.org/coar/resource_type/c_2df8fbb1
dc.identifier.issn.spa.fl_str_mv 0140-6736
dc.identifier.other.spa.fl_str_mv https://doi.org/10.1016/S2214-109X(20)30359-4
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/20.500.12010/14563
dc.identifier.doi.spa.fl_str_mv https://doi.org/10.1016/S2214-109X(20)30359-4
identifier_str_mv 0140-6736
url https://doi.org/10.1016/S2214-109X(20)30359-4
http://hdl.handle.net/20.500.12010/14563
dc.language.iso.spa.fl_str_mv eng
language eng
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.local.spa.fl_str_mv Abierto (Texto Completo)
rights_invalid_str_mv Abierto (Texto Completo)
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dc.format.extent.spa.fl_str_mv 9 páginas
dc.format.mimetype.spa.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv The Lancet
dc.source.spa.fl_str_mv reponame:Expeditio Repositorio Institucional UJTL
instname:Universidad de Bogotá Jorge Tadeo Lozano
instname_str Universidad de Bogotá Jorge Tadeo Lozano
institution Universidad de Bogotá Jorge Tadeo Lozano
reponame_str Expeditio Repositorio Institucional UJTL
collection Expeditio Repositorio Institucional UJTL
bitstream.url.fl_str_mv https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/14563/3/Estimating-access-to-health-care-in-Yemen--a-complex-humani_2020_The-Lancet-.pdf.jpg
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spelling 2020-10-19T14:39:00Z2020-10-19T14:39:00Z20200140-6736https://doi.org/10.1016/S2214-109X(20)30359-4http://hdl.handle.net/20.500.12010/14563https://doi.org/10.1016/S2214-109X(20)30359-4Background 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.9 páginasapplication/pdfengThe Lancetreponame:Expeditio Repositorio Institucional UJTLinstname:Universidad de Bogotá Jorge Tadeo LozanoHumanitarian emergencyGeospatial analysisHealth careYemenSíndrome respiratorio agudo graveCOVID-19SARS-CoV-2CoronavirusEstimating access to health care in Yemen, a complex humanitarian emergency setting: a descriptive applied geospatial analysisArtículohttp://purl.org/coar/resource_type/c_2df8fbb1Abierto (Texto Completo)http://purl.org/coar/access_right/c_abf2Garber, KentFox, CharlesAbdalla, MoustafaTatem, AndrewQirbi, NaseebLloyd-Braff, LauraAl-Shabi, KahtanOngwae, KennedyDyson, MeredithHassen, KebirTHUMBNAILEstimating-access-to-health-care-in-Yemen--a-complex-humani_2020_The-Lancet-.pdf.jpgEstimating-access-to-health-care-in-Yemen--a-complex-humani_2020_The-Lancet-.pdf.jpgIM Thumbnailimage/jpeg24611https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/14563/3/Estimating-access-to-health-care-in-Yemen--a-complex-humani_2020_The-Lancet-.pdf.jpg384d6f4fdda1085e1241e530ce85ec01MD53open accessLICENSElicense.txtlicense.txttext/plain; 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