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A geospatial database of close-to-reality travel times to obstetric emergency care in 15 Nigerian conurbations
Travel 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 ma...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10593805/ https://www.ncbi.nlm.nih.gov/pubmed/37872185 http://dx.doi.org/10.1038/s41597-023-02651-9 |
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author | Macharia, Peter M. Wong, Kerry L. M. Olubodun, Tope Beňová, Lenka Stanton, Charlotte Sundararajan, Narayanan Shah, Yash Prasad, Gautam Kansal, Mansi Vispute, Swapnil Shekel, Tomer Gwacham-Anisiobi, Uchenna Ogunyemi, Olakunmi Wang, Jia Abejirinde, Ibukun-Oluwa Omolade Makanga, Prestige Tatenda Afolabi, Bosede B. Banke-Thomas, Aduragbemi |
author_facet | Macharia, Peter M. Wong, Kerry L. M. Olubodun, Tope Beňová, Lenka Stanton, Charlotte Sundararajan, Narayanan Shah, Yash Prasad, Gautam Kansal, Mansi Vispute, Swapnil Shekel, Tomer Gwacham-Anisiobi, Uchenna Ogunyemi, Olakunmi Wang, Jia Abejirinde, Ibukun-Oluwa Omolade Makanga, Prestige Tatenda Afolabi, Bosede B. Banke-Thomas, Aduragbemi |
author_sort | Macharia, Peter M. |
collection | PubMed |
description | Travel 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. |
format | Online Article Text |
id | pubmed-10593805 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-105938052023-10-25 A geospatial database of close-to-reality travel times to obstetric emergency care in 15 Nigerian conurbations Macharia, Peter M. Wong, Kerry L. M. Olubodun, Tope Beňová, Lenka Stanton, Charlotte Sundararajan, Narayanan Shah, Yash Prasad, Gautam Kansal, Mansi Vispute, Swapnil Shekel, Tomer Gwacham-Anisiobi, Uchenna Ogunyemi, Olakunmi Wang, Jia Abejirinde, Ibukun-Oluwa Omolade Makanga, Prestige Tatenda Afolabi, Bosede B. Banke-Thomas, Aduragbemi Sci Data Data Descriptor Travel 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. Nature Publishing Group UK 2023-10-23 /pmc/articles/PMC10593805/ /pubmed/37872185 http://dx.doi.org/10.1038/s41597-023-02651-9 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Data Descriptor Macharia, Peter M. Wong, Kerry L. M. Olubodun, Tope Beňová, Lenka Stanton, Charlotte Sundararajan, Narayanan Shah, Yash Prasad, Gautam Kansal, Mansi Vispute, Swapnil Shekel, Tomer Gwacham-Anisiobi, Uchenna Ogunyemi, Olakunmi Wang, Jia Abejirinde, Ibukun-Oluwa Omolade Makanga, Prestige Tatenda Afolabi, Bosede B. Banke-Thomas, Aduragbemi A geospatial database of close-to-reality travel times to obstetric emergency care in 15 Nigerian conurbations |
title | A geospatial database of close-to-reality travel times to obstetric emergency care in 15 Nigerian conurbations |
title_full | A geospatial database of close-to-reality travel times to obstetric emergency care in 15 Nigerian conurbations |
title_fullStr | A geospatial database of close-to-reality travel times to obstetric emergency care in 15 Nigerian conurbations |
title_full_unstemmed | A geospatial database of close-to-reality travel times to obstetric emergency care in 15 Nigerian conurbations |
title_short | A geospatial database of close-to-reality travel times to obstetric emergency care in 15 Nigerian conurbations |
title_sort | geospatial database of close-to-reality travel times to obstetric emergency care in 15 nigerian conurbations |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10593805/ https://www.ncbi.nlm.nih.gov/pubmed/37872185 http://dx.doi.org/10.1038/s41597-023-02651-9 |
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