Evidence map›Paper›PMID 37872185›Full record

ArticleScientific data2023

A geospatial database of close-to-reality travel times to obstetric emergency care in 15 Nigerian conurbations.

Peter M Macharia, Kerry L M Wong, Tope Olubodun, Lenka Beňová, Charlotte Stanton, Narayanan Sundararajan, Yash Shah, Gautam Prasad, Mansi Kansal, Swapnil Vispute and 8 more

Abstract readDataset
In one paragraph

Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
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

9 citing papers in PubMed.

  1. Article
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  4. The Burden of Plastic Surgery in Rural Kenya: The Kapsowar Hospital Experience.Plastic and reconstructive surgery. Global open · 2024
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Peter M MachariaDepartment of Public Health, Institute of Tropical Medicine, Antwerp, Belgium.ORCID http://orcid.org/0000-0003-3410-1881
Kerry L M WongFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK.
Tope OlubodunDepartment of Community Medicine and Primary Care, Federal Medical Centre Abeokuta, Abeokuta, Ogun, Nigeria.
Lenka BeňováDepartment of Public Health, Institute of Tropical Medicine, Antwerp, Belgium.
Charlotte StantonGoogle LLC, California, USA. chstanton@google.com.
Narayanan SundararajanGoogle LLC, California, USA.
Yash ShahGoogle LLC, California, USA.
Gautam PrasadGoogle LLC, California, USA.
Mansi KansalGoogle LLC, California, USA.
Swapnil VisputeGoogle LLC, California, USA.
Tomer ShekelGoogle LLC, California, USA.
Uchenna Gwacham-AnisiobiNuffield Department of Population Health, University of Oxford, Oxford, UK.
Olakunmi OgunyemiLagos State Ministry of Health, Ikeja, Lagos, Nigeria.
Jia WangSchool of Computing & Mathematical Sciences, University of Greenwich, London, UK.
Ibukun-Oluwa Omolade AbejirindeDalla Lana School of Public Health, University of Toronto, Toronto, Canada.
Prestige Tatenda MakangaSurveying and Geomatics Department, Midlands State University Faculty of Science and Technology, Gweru, Midlands, Zimbabwe.
Bosede B AfolabiMaternal and Reproductive Health Research Collective, Lagos, Nigeria.
Aduragbemi Banke-ThomasFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK. aduragbemi.banke-thomas@lshtm.ac.uk.ORCID http://orcid.org/0000-0002-4449-0131

Funding

Wellcome Trust
6 · The paper itself

Abstract

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.

Identifiers

PMID37872185
PMCPMC10593805

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.