Geographical accessibility to functional emergency obstetric care facilities in urban Nigeria using closer-to-reality travel time estimates: a population-based spatial analysis.

BACKGROUND: 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. METHODS: 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. FUNDING: Google.

Socio-spatial equity analysis of relative wealth index and emergency obstetric care accessibility in urban Nigeria.

BACKGROUND: Better geographical accessibility to comprehensive emergency obstetric care (CEmOC) facilities can significantly improve pregnancy outcomes. However, with other factors, such as affordability critical for care access, it is important to explore accessibility across groups. We assessed CEmOC geographical accessibility by wealth status in the 15 most-populated Nigerian cities. METHODS: We mapped city boundaries, verified and geocoded functional CEmOC facilities, and assembled population distribution for women of childbearing age and Meta's Relative Wealth Index (RWI). We used the Google Maps Platform's internal Directions Application Programming Interface to obtain driving times to public and private facilities. City-level median travel time (MTT) and number of CEmOC facilities reachable within 60 min were summarised for peak and non-peak hours per wealth quintile. The correlation between RWI and MTT to the nearest public CEmOC was calculated. RESULTS: We show that MTT to the nearest public CEmOC facility is lowest in the wealthiest 20% in all cities, with the largest difference in MTT between the wealthiest 20% and least wealthy 20% seen in Onitsha (26 vs 81 min) and the smallest in Warri (20 vs 30 min). Similarly, the average number of public CEmOC facilities reachable within 60 min varies (11 among the wealthiest 20% and six among the least wealthy in Kano). In five cities, zero facilities are reachable under 60 min for the least wealthy 20%. Those who live in the suburbs particularly have poor accessibility to CEmOC facilities. CONCLUSIONS: Our findings show that the least wealthy mostly have poor accessibility to care. Interventions addressing CEmOC geographical accessibility targeting poor people are needed to address inequities in urban settings.

Access to critical obstetric care can be lifesaving for pregnant women and their offspring. However, socioeconomic factors are known to affect accessibility to health services across different groups. Here, we assessed peak and off-peak travel times to functional health facilities for women from 15 Nigerian cities, using travel time estimates produced by Google Maps and stratified by wealth status. Travel time to the nearest hospital and the number of hospitals reachable within 60 min varied across cities. The wealthiest 20% across all cities had the shortest travel time and vice versa for the least wealthy 20%. Women who live in the suburbs particularly have poor accessibility. Tailored action is needed to improve access for vulnerable populations living in urban settings.

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 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.

Prevalence, indications, and complications of caesarean section in health facilities across Nigeria: a systematic review and meta-analysis.

BACKGROUND: Over 80,000 pregnant women died in Nigeria due to pregnancy-related complications in 2020. Evidence shows that if appropriately conducted, caesarean section (CS) reduces the odds of maternal death. In 2015, the World Health Organization (WHO), in a statement, proposed an optimal national prevalence of CS and recommended the use of Robson classification for classifying and determining intra-facility CS rates. We conducted this systematic review and meta-analysis to synthesise evidence on prevalence, indications, and complications of intra-facility CS in Nigeria. METHODS: Four databases (African Journals Online, Directory of Open Access Journals, EBSCOhost, and PubMed) were systematically searched for relevant articles published from 2000 to 2022. Articles were screened following the PRISMA guidelines, and those meeting the study's inclusion criteria were retained for review. Quality assessment of included studies was conducted using a modified Joanna Briggs Institute's Critical Appraisal Checklist. Narrative synthesis of CS prevalence, indications, and complications as well as a meta-analysis of CS prevalence using R were conducted. RESULTS: We retrieved 45 articles, with most (33 (64.4%)) being assessed as high quality. The overall prevalence of CS in facilities across Nigeria was 17.6%. We identified a higher prevalence of emergency CS (75.9%) compared to elective CS (24.3%). We also identified a significantly higher CS prevalence in facilities in the south (25.5%) compared to the north (10.6%). Furthermore, we observed a 10.7% increase in intra-facility CS prevalence following the implementation of the WHO statement. However, none of the studies adopted the Robson classification of CS to determine intra-facility CS rates. In addition, neither hierarchy of care (tertiary or secondary) nor type of facility (public or private) significantly influenced intra-facility CS prevalence. The commonest indications for a CS were previous scar/CS (3.5-33.5%) and pregnancy-related hypertensive disorders (5.5-30.0%), while anaemia (6.4-57.1%) was the most reported complication. CONCLUSION: There are disparities in the prevalence, indications, and complications of CS in facilities across the geopolitical zones of Nigeria, suggestive of concurrent overuse and underuse. There is a need for comprehensive solutions to optimise CS provision tailor-made for zones in Nigeria. Furthermore, future research needs to adopt current guidelines to improve comparison of CS rates.

Prevalence, influencing factors, and outcomes of emergency caesarean section in public hospitals situated in the urban state of Lagos, Nigeria.

Background: Caesarean section (CS) performed in an emergency can be life-saving for both the pregnant woman and her baby. In Nigeria, CS rates have been estimated to be 2.7% nationally, with the highest regional rate of 7.0% reported in the South-West of the country. Our objective in this facility-based retrospective cross-sectional study was to describe patterns and assess factors, obstetric indications, and outcomes of emergency CS in Lagos, Nigeria. Methods: Socio-demographic, travel, and obstetric data of pregnant women were extracted from case notes. Travel data was inputted in Google Maps to extract travel time from the pregnant women' home to the hospital. Univariate, bivariate and multivariable logistic regression analyses were conducted. Results: Of the 3,134 included pregnant women, 1,923 (61%) delivered via emergency CS. The odds of an emergency CS were significantly higher among women who were booked (OR=1.97, 95%CI 1.64-2.35), presented with obstructed labour (OR=2.59, 95%CI 1.68-3.99), pre-eclampsia/eclampsia (OR=1.67, 95%CI 1.08-2.56), multiple gestations (OR=2.71, 95%CI 1.72-4.28) and travelled from suburban areas (OR=1.43, 95%CI 1.15-1.78). There was an increasing dose-effect response between travel time to the hospital and emergency CS. Conclusion: Optimisation of CS rates requires a multi-pronged approach during pregnancy and childbirth, with particular emphasis on supporting pregnant women living in the suburbs.

Leveraging big data for improving the estimation of close to reality travel time to obstetric emergency services in urban low- and middle-income settings.

Maternal and perinatal mortality remain huge challenges globally, particularly in low- and middle-income countries (LMICs) where >98% of these deaths occur. Emergency obstetric care (EmOC) provided by skilled health personnel is an evidence-based package of interventions effective in reducing these deaths associated with pregnancy and childbirth. Until recently, pregnant women residing in urban areas have been considered to have good access to care, including EmOC. However, emerging evidence shows that due to rapid urbanization, this so called "urban advantage" is shrinking and in some LMIC settings, it is almost non-existent. This poses a complex challenge for structuring an effective health service delivery system, which tend to have poor spatial planning especially in LMIC settings. To optimize access to EmOC and ultimately reduce preventable maternal deaths within the context of urbanization, it is imperative to accurately locate areas and population groups that are geographically marginalized. Underpinning such assessments is accurately estimating travel time to health facilities that provide EmOC. In this perspective, we discuss strengths and weaknesses of approaches commonly used to estimate travel times to EmOC in LMICs, broadly grouped as reported and modeled approaches, while contextualizing our discussion in urban areas. We then introduce the novel OnTIME project, which seeks to address some of the key limitations in these commonly used approaches by leveraging big data. The perspective concludes with a discussion on anticipated outcomes and potential policy applications of the OnTIME project.