Geographical accessibility to functional emergency obstetric care facilities in urban Nigeria using closer-to-reality travel time estimates: a population-based spatial analysis
Banke-Thomas, Aduragbemi ORCID: 0000-0002-4449-0131 , Wong, Kerry L.M., Olubodun, Oluwatosin, Macharia, Peter M, Sundararajan, Narayanan, Shah, Yash, Prasad, Gautam, Kansal, Mansi, Vispute, Swapnil, Shekel, Tomer, Ogunyemi, Olakunmi, Gwacham-Anisiobi, Uchenna, Wang, Jia ORCID: 0000-0003-4379-9724 , Omolade Abejirinde, Ibukun-Oluwa, Makanga, Prestige Tatenda, Azodoh, Ngozi, Nzelu, Charles, Afolabi, Bosede B, Stanton, Charlotte and Beňová, Lenka (2024) Geographical accessibility to functional emergency obstetric care facilities in urban Nigeria using closer-to-reality travel time estimates: a population-based spatial analysis. The Lancet Global Health, 12 (5). e848-e858. ISSN 2214-109X (doi:https://doi.org/10.1016/S2214-109X(24)00045-7)
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Abstract
Better accessibility for emergency obstetric care facilities can substantially reduce maternal and perinatal deaths. However, pregnant women and girls living in urban settings face additional complex challenges travelling to facilities. We aimed to assess the geographical accessibility of the three nearest functional public and private comprehensive emergency obstetric care facilities in the 15 largest Nigerian cities via a novel approach that uses closer-to-reality travel time estimates than traditional model-based approaches. In this population-based spatial analysis, we mapped city boundaries, verified and geocoded functional comprehensive emergency obstetric care facilities, and mapped the population distribution for girls and women aged 15–49 years (ie, of childbearing age). We used the Google Maps Platform's internal Directions Application Programming Interface to derive driving times to public and private facilities. Median travel time and the percentage of women aged 15–49 years able to reach care were summarised for eight traffic scenarios (peak and non-peak hours on weekdays and weekends) by city and within city under different travel time thresholds (≤15 min, ≤30 min, ≤60 min).
Findings
As of 2022, there were 11·5 million girls and women aged 15–49 years living in the 15 studied cities, and we identified the location and functionality of 2020 comprehensive emergency obstetric care facilities. City-level median travel time to the nearest comprehensive emergency obstetric care facility ranged from 18 min in Maiduguri to 46 min in Kaduna. Median travel time varied by location within a city. The between-ward IQR of median travel time to the nearest public comprehensive emergency obstetric care varied from the narrowest in Maiduguri (10 min) to the widest in Benin City (41 min). Informal settlements and peripheral areas tended to be worse off compared to the inner city. The percentages of girls and women aged 15–49 years within 60 min of their nearest public comprehensive emergency obstetric care ranged from 83% in Aba to 100% in Maiduguri, while the percentage within 30 min ranged from 33% in Aba to over 95% in Ilorin and Maiduguri. During peak traffic times, the median number of public comprehensive emergency obstetric care facilities reachable by women aged 15–49 years under 30 min was zero in eight (53%) of 15 cities.
Interpretation
Better access to comprehensive emergency obstetric care is needed in Nigerian cities and solutions need to be tailored to context. The innovative approach used in this study provides more context-specific, finer, and policy-relevant evidence to support targeted efforts aimed at improving comprehensive emergency obstetric care geographical accessibility in urban Africa.
Item Type: | Article |
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Uncontrolled Keywords: | geographical accessibility; emergency obstetric care; urban Nigeria; close-to-reality; spatial analysis |
Subjects: | Q Science > QA Mathematics R Medicine > R Medicine (General) R Medicine > RG Gynecology and obstetrics |
Faculty / School / Research Centre / Research Group: | Faculty of Education, Health & Human Sciences Faculty of Education, Health & Human Sciences > School of Human Sciences (HUM) Faculty of Engineering & Science Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS) |
Last Modified: | 09 Aug 2024 14:54 |
URI: | http://gala.gre.ac.uk/id/eprint/47548 |
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