Please use this identifier to cite or link to this item: https://cris.library.msu.ac.zw//handle/11408/6241
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dc.contributor.authorPeter M. Machariaen_US
dc.contributor.authorKerry L.M. Wongen_US
dc.contributor.authorLenka Beňováen_US
dc.contributor.authorJia Wangen_US
dc.contributor.authorPrestige Tatenda Makangaen_US
dc.contributor.authorNicolas Rayen_US
dc.contributor.authorAduragbemi Banke-Thomasen_US
dc.date.accessioned2024-08-07T08:31:01Z-
dc.date.available2024-08-07T08:31:01Z-
dc.date.issued2024-05-27-
dc.identifier.urihttps://cris.library.msu.ac.zw//handle/11408/6241-
dc.description.abstractGoogle Maps Directions Application Programming Interface (the API) and AccessMod tools are increasingly being used to estimate travel time to healthcare. However, no formal comparison of estimates from the tools has been conducted. We modelled and compared median travel time (MTT) to comprehensive emergency obstetric care (CEmOC) using both tools in three Nigerian conurbations (Kano, Port-Harcourt, and Lagos). We compiled spatial layers of CEmOC healthcare facilities, road network, elevation, and land cover and used a least-cost path algorithm within AccessMod to estimate MTT to the nearest CEmOC facility. Comparable MTT estimates were extracted using the API for peak and non-peak travel scenarios. We investigated the relationship between MTT estimates generated by both tools at raster celllevel (0.6 km resolution). We also aggregated the raster cell estimates to generate administratively relevant ward-level MTT. We compared ward-level estimates and identified wards within the same conurbation falling into different 15-minute incremental categories (<15/15-30/30-45/45-60/+60). Of the 189, 101 and 375 wards, 72.0%, 72.3% and 90.1% were categorised in the same 15- minute category in Kano, Port-Harcourt, and Lagos, respectively. Concordance decreased in wards with longer MTT. AccessMod MTT were longer than the API’s in areas with ≥45min. At the raster cell-level, MTT had a strong positive correlation (≥0.8) in all conurbations. Adjusted R2 from a linear model (0.624-0.723) was high, increasing marginally in a piecewise linear model (0.677-0.807). In conclusion, at <45-minutes, ward-level estimates from the API and AccessMod are marginally different, however, at longer travel times substantial differences exist, which are amenable to conversion factors.en_US
dc.language.isoenen_US
dc.publisherPAGEpressen_US
dc.relation.ispartofGeospatial Healthen_US
dc.subjectSpatial accessibilityen_US
dc.subjectleast cost pathen_US
dc.subjectAccessModen_US
dc.subjectGoogle Maps Directions APIen_US
dc.subjecturban areaen_US
dc.subjectmaternal healthen_US
dc.titleMeasuring geographic access to emergency obstetric care: a comparison of travel time estimates modelled using Google Maps Directions API and AccessMod in three Nigerian conurbationsen_US
dc.typeresearch articleen_US
dc.identifier.doihttps://doi.org/10.4081/gh.2024.1266-
dc.contributor.affiliationPopulation and Health Impact Surveillance Group, Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya; Department of Public Health, Institute of Tropical Medicine, Antwerp, Belgiumen_US
dc.contributor.affiliationFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdomen_US
dc.contributor.affiliationDepartment of Public Health, Institute of Tropical Medicine, Antwerp, Belgium; Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdomen_US
dc.contributor.affiliationSchool of Computing and Mathematical Sciences, University of Greenwich, London, United Kingdomen_US
dc.contributor.affiliationSurveying and Geomatics Department, Midlands State University Faculty of the Built Environment, Gweru, Midlands, Zimbabwe; Climate, Environment and Health Department, Centre for Sexual Health and HIV/AIDS Research, Harare, Zimbabwe; Department of International Public Health, Liverpool School of Tropical Medicine, Liverpool, Zimbabwe.en_US
dc.contributor.affiliationGeoHealth Group, Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland; Institute for Environmental Sciences, University of Geneva, Geneva, Switzerlanden_US
dc.contributor.affiliationFaculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom; School of Human Sciences, University of Greenwich, London, United Kingdom; Maternal and Reproductive Health Research Collective, Surulere, Lagos, Nigeria.en_US
dc.relation.issn1970-7096en_US
dc.description.volume19en_US
dc.description.issue1en_US
dc.description.startpage1en_US
dc.description.endpage17en_US
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item.cerifentitytypePublications-
item.grantfulltextopen-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.openairetyperesearch article-
item.languageiso639-1en-
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