Please use this identifier to cite or link to this item: https://cris.library.msu.ac.zw//handle/11408/6012
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dc.contributor.authorPeter M. Machariaen_US
dc.contributor.authorKerry L. M. Wongen_US
dc.contributor.authorTope Olubodunen_US
dc.contributor.authorLenka Beňováen_US
dc.contributor.authorCharlotte Stantonen_US
dc.contributor.authorNarayanan Sundararajanen_US
dc.contributor.authorYash Shahen_US
dc.contributor.authorGautam Prasaden_US
dc.contributor.authorMansi Kansalen_US
dc.contributor.authorSwapnil Visputeen_US
dc.contributor.authorTomer Shekelen_US
dc.contributor.authorUchenna Gwacham-Anisiobien_US
dc.contributor.authorOlakunmi Ogunyemien_US
dc.contributor.authorJia Wangen_US
dc.contributor.authorIbukun-Oluwa Omolade Abejirindeen_US
dc.contributor.authorPrestige Tatenda Makangaen_US
dc.contributor.authorBosede B. Afolabien_US
dc.contributor.authorAduragbemi Banke-Thomasen_US
dc.date.accessioned2024-03-27T10:40:39Z-
dc.date.available2024-03-27T10:40:39Z-
dc.date.issued2023-10-23-
dc.identifier.urihttps://cris.library.msu.ac.zw//handle/11408/6012-
dc.description.abstractTravel time estimation accounting for on-the-ground realities between the location where a need for emergency obstetric care (EmOC) arises and the health facility capable of providing EmOC is essential for improving pregnancy outcomes. Current understanding of travel time to care is inadequate in many urban areas of Africa, where short distances obscure long travel times and travel times can vary by time of day and road conditions. Here, we describe a database of travel times to comprehensive EmOC facilities in the 15 most populated extended urban areas of Nigeria. The travel times from cells of approximately 0.6 × 0.6 km to facilities were derived from Google Maps Platform’s internal Directions Application Programming Interface, which incorporates traffic considerations to provide closer-to-reality travel time estimates. Computations were done to the first, second and third nearest public or private facilities. Travel time for eight traffic scenarios (including peak and non-peak periods) and number of facilities within specific time thresholds were estimated. The database offers a plethora of opportunities for research and planning towards improving EmOC accessibility.en_US
dc.language.isoenen_US
dc.publisherNature Researchen_US
dc.relation.ispartofScientific Dataen_US
dc.subjectgeospatialen_US
dc.subjectdatabaseen_US
dc.subjectclose-to-realityen_US
dc.subjecttravel timesen_US
dc.subjectobstetric emergency careen_US
dc.subjectNigeriaen_US
dc.titleA geospatial database of close- to-reality travel times to obstetric emergency care in 15 Nigerian conurbationsen_US
dc.typeresearch articleen_US
dc.identifier.doihttps://doi.org/10.1038/s41597-023-02651-9-
dc.contributor.affiliationDepartment of Public Health, Institute of Tropical Medicine, Antwerp, Belgium; Population & Health Impact Surveillance Group, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya and Centre for Health Informatics, Computing, and Statistics, Lancaster Medical School, Lancaster University, Lancaster, UKen_US
dc.contributor.affiliationFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UKen_US
dc.contributor.affiliationDepartment of Community Medicine and Primary Care, Federal Medical Centre Abeokuta, Abeokuta, Ogun, Nigeriaen_US
dc.contributor.affiliationDepartment of Public Health, Institute of Tropical Medicine, Antwerp, Belgiumen_US
dc.contributor.affiliationGoogle LLC, California, USAen_US
dc.contributor.affiliationGoogle LLC, California, USAen_US
dc.contributor.affiliationGoogle LLC, California, USAen_US
dc.contributor.affiliationGoogle LLC, California, USAen_US
dc.contributor.affiliationGoogle LLC, California, USAen_US
dc.contributor.affiliationGoogle LLC, California, USAen_US
dc.contributor.affiliationGoogle LLC, California, USAen_US
dc.contributor.affiliationNuffield Department of Population Health, University of Oxford, Oxford, UKen_US
dc.contributor.affiliationLagos State Ministry of Health, Ikeja, Lagos, Nigeriaen_US
dc.contributor.affiliationSchool of Computing & Mathematical Sciences, University of Greenwich, London, UKen_US
dc.contributor.affiliationDalla Lana School of Public Health, University of Toronto, Toronto, Canada; Women’s College Hospital Institute for Health System Solutions and Virtual Care, Toronto, Canadaen_US
dc.contributor.affiliationSurveying and Geomatics Department, Midlands State University Faculty of Science and Technology, Gweru, Midlands, Zimbabwe; Climate and Health Division, Centre for Sexual Health and HIV/AIDS Research, Harare, Zimbabween_US
dc.contributor.affiliationMaternal and Reproductive Health Research Collective, Lagos, Nigeria; Department of Obstetrics and Gynaecology, College of Medicine of the University of Lagos, Lagos, Nigeriaen_US
dc.contributor.affiliationFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK; Maternal and Reproductive Health Research Collective, Lagos, Nigeria; School of Human Sciences, University of Greenwich, London, UKen_US
dc.relation.issn2052-4463en_US
dc.description.volume10en_US
dc.description.startpage1en_US
dc.description.endpage8en_US
item.grantfulltextopen-
item.cerifentitytypePublications-
item.openairetyperesearch article-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextWith Fulltext-
item.languageiso639-1en-
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