Measuring the availability and geographical accessibility of maternal health services across sub-Saharan Africa

Spatial Access to Continuous Maternal and Perinatal Health Care Services in Low-Resource Settings: Cross-Sectional Study

BACKGROUND

Maternal and perinatal health are fundamental to human development. However, in low-resource settings such as sub-Saharan Africa (SSA), significant challenges persist in reducing maternal, newborn, and child mortality. To achieve the targets of the sustainable development goal 3 (SDG3) and universal health coverage (UHC), improving access to continuous maternal and perinatal health care services (CMPHS) has been addressed as a critical strategy.

OBJECTIVE

This study aims to provide a widely applicable procedure to illuminate the current challenges in ensuring access to CMPHS for women of reproductive age. The findings are intended to inform targeted recommendations for prioritizing resource allocation and policy making in low-resource settings.

METHODS

In accordance with the World Health Organization guidelines and existing literature, and taking into account the local context of CMPHS delivery to women of reproductive age in Mozambique, we first proposed the identification of CMPHS as the continuum of 3 independent service packages, namely antenatal care (ANC), institutional delivery (ID), and postnatal care (PNC). Then, we used the nearest-neighbor method (NNM) to assess spatial access to each of the 3 service packages. Lastly, we carried out an overlap analysis to identify 8 types of resource-shortage zones.

RESULTS

The median shortest travel times for women of reproductive age to access ANC, ID, and PNC were 2.38 (IQR 1.38-3.89) hours, 3.69 (IQR 1.87-5.82) hours, and 4.16 (IQR 2.48-6.67) hours, respectively. Spatial barriers for women of reproductive age accessing ANC, ID, and PNC demonstrated large variations both among and within regions. Maputo City showed the shortest travel time and the best equity within the regions (0.46, IQR 0.26-0.69 hours; 0.74, IQR 0.47-1.04 hours; and 1.34, IQR 0.83-1.85 hours, respectively), while the provinces of Niassa (4.07, IQR 2.41-6.63 hours; 18.20, IQR 11.67-24.65 hours; and 7.69, IQR 4.74-13.05 hours, respectively) and Inhambane (2.69, IQR 1.49-3.91 hours; 4.43, IQR 2.37-7.16 hours; and 10.76, IQR 7.73-13.66 hours, respectively) lagged behind significantly in both aspects. In general, more than 51% of the women of reproductive age, residing in 83.25% of Mozambique's land area, were unable to access any service package of CMPHS in time (within 2 hours), while only about 21%, living in 2.69% of Mozambique's land area, including Maputo, could access timely CMPHS.

CONCLUSIONS

The spatial accessibility and equity of CMPHS in Mozambique present significant challenges in achieving SDG3 and UHC, especially in the Inhambane and Niassa regions. For Inhambane, policy makers should prioritize the implementation of a decentralization allocation strategy to increase coverage and equity through upgrading existing health care facilities. For Niassa, the cultivation of well-trained midwives who can provide door-to-door ANC and PNC at home should be prioritized, with an emphasis on strengthening communities' engagement. The proposed 2-step procedure should be implemented in other low-resource settings to promote the achievement of SDG3.

Does oral iron and folate supplementation during pregnancy protect against adverse birth outcomes and reduced neonatal and infant mortality in Africa: A protocol for a systematic review and meta-analysis?

BACKGROUND

Globally, one-third of pregnant women are at risk of iron deficiency, particularly in the African region. While recent findings show that iron and folate supplementation can lower the risk of adverse birth outcomes and childhood mortality, our understanding of its impact in Africa remains incomplete due to insufficient evidence. This protocol outlines the systematic review steps to investigate the impact of oral iron and folate supplementation during pregnancy on adverse birth outcomes, neonatal mortality and infant mortality in Africa.

METHODS AND ANALYSIS

MEDLINE, PsycINFO, Embase, Scopus, CINAHL, Web of Science, and Cochrane databases were searched for published articles. Google Scholar and Advanced Google Search were used for gray literature and nonindexed articles. Oral iron and/or folate supplementation during pregnancy is the primary exposure. The review will focus on adverse birth outcomes, neonatal mortality and infant mortality. Both Cochrane Effective Practice and Organization of Care and Newcastle-Ottawa Scale risk of bias assessment tools will be used. Meta-analysis will be conducted if design and data analysis methodologies permit. This systematic review and meta-analysis will provide up-to-date evidence about iron and folate supplementation's role in adverse birth outcomes, neonatal mortality and infant mortality in the African region.

ETHICS AND DISSEMINATION

This review will provide insights that help policymakers, program planners, researchers, and public health practitioners interested in working in the region.

PROSPERO REGISTRATION NUMBER

CRD42023452588.

COVID-19 Vaccination Site Accessibility, United States, December 11, 2020-March 29, 2022

During December 11, 2020-March 29, 2022, the US government delivered ≈700 million doses of COVID-19 vaccine to vaccination sites, resulting in vaccination of ≈75% of US adults during that period. We evaluated accessibility of vaccination sites. Sites were accessible by walking within 15 minutes by 46.6% of persons, 30 minutes by 74.8%, 45 minutes by 82.8%, and 60 minutes by 86.7%. When limited to populations in counties with high social vulnerability, accessibility by walking was 55.3%, 81.1%, 86.7%, and 89.4%, respectively. By driving, lowest accessibility was 96.5% at 15 minutes. For urban/rural categories, the 15-minute walking accessibility between noncore and large central metropolitan areas ranged from 27.2% to 65.1%; driving accessibility was 79.9% to 99.5%. By 30 minutes driving accessibility for all urban/rural categories was >95.9%. Walking time variations across jurisdictions and between urban/rural areas indicate that potential gains could have been made by improving walkability or making transportation more readily available.

Assessing the accuracy of health facility typology in representing the availability of health services: a case study in Mali

INTRODUCTION

Using health facility types as a measure of service availability is a common approach in international standards for health system policy and planning. However, this proxy may not accurately reflect the actual availability of specific health services.

OBJECTIVE

This study aims to evaluate the reliability of health facility typology as an indicator of specific health service availability and explore whether certain facility types consistently provide particular services.

DESIGN

We analysed a comprehensive dataset containing information from 1725 health facilities in Mali. To uncover and visualise patterns within the dataset, we used two analytical techniques: Multiple Correspondence Analysis and Between-Class Analysis. These analyses allowed us to quantitatively measure the influence of health facility types on the variation in health service provisioning. Additionally, we developed and calculated a Consistency Index, which assesses the consistency of a health facility type in providing specific health services. By examining various health facilities and services, we sought to determine the accuracy of facility types as indicators of service availability.

SETTING

The study focused on the health system in Mali as a case study.

RESULTS

Our findings indicate that using health facility types as a proxy for service availability in Mali is not an accurate representation. We observed that most of the variation in service provision does not stem from differences between facility types but rather within facility types. This suggests that relying solely on health facility typology may lead to an incomplete understanding of health service availability.

CONCLUSIONS

These results have significant implications for health policy and planning. The reliance on health facility types as indicators for health system policy and planning should be reconsidered. A more nuanced and evidence-based understanding of health service availability is crucial for effective health policy and planning, as well as for the assessment and monitoring of health systems.

Informal health sector and routine immunization: making the case for harnessing the potentials of patent medicine vendors for the big catch-up to reduce zero-dose children in sub-Saharan Africa

The COVID-19 pandemic caused a surge in the number of unimmunized and under-immunized children in Africa. The majority of unimmunized (or zero-dose) children live in hard-to-reach rural areas, urban slums, and communities affected by conflict where health facilities are usually unavailable or difficult to access. In these settings, people mostly rely on the informal health sector for essential health services. Therefore, to reduce zero-dose children, it is critical to expand immunization services beyond health facilities to the informal health sector to meet the immunization needs of children in underserved places. In this perspective article, we propose a framework for the expansion of immunization services through the informal health sector as one of the pillars for the big catch-up plan to improve coverage and equity. In African countries like Nigeria, Ethiopia, Tanzania, and the Democratic Republic of Congo, patent medicine vendors serve as an important informal health sector provider group, and thus, they can be engaged to provide immunization services. A hub-and-spoke model can be used to integrate patent medicine vendors into the immunization system. A hub-and-spoke model is a framework for organization design where services that are provided by a central facility (hub) are complimented by secondary sites (spokes) to optimize access to care. Systems thinking approach should guide the design, implementation, and evaluation of this model.

Revealed versus potential spatial accessibility of healthcare and changing patterns during the COVID-19 pandemic

BACKGROUND

Timely access to healthcare is essential but measuring access is challenging. Prior research focused on analyzing potential travel times to healthcare under optimal mobility scenarios that do not incorporate direct observations of human mobility, potentially underestimating the barriers to receiving care for many populations.

METHODS

We introduce an approach for measuring accessibility by utilizing travel times to healthcare facilities from aggregated and anonymized smartphone Location History data. We measure these revealed travel times to healthcare facilities in over 100 countries and juxtapose our findings with potential (optimal) travel times estimated using Google Maps directions. We then quantify changes in revealed accessibility associated with the COVID-19 pandemic.

RESULTS

We find that revealed travel time differs substantially from potential travel time; in all but 4 countries this difference exceeds 30 minutes, and in 49 countries it exceeds 60 minutes. Substantial variation in revealed healthcare accessibility is observed and correlates with life expectancy (⍴=-0.70) and infant mortality (⍴=0.59), with this association remaining significant after adjusting for potential accessibility and wealth. The COVID-19 pandemic altered the patterns of healthcare access, especially for populations dependent on public transportation.

CONCLUSIONS

Our metrics based on empirical data indicate that revealed travel times exceed potential travel times in many regions. During COVID-19, inequitable accessibility was exacerbated. In conjunction with other relevant data, these findings provide a resource to help public health policymakers identify underserved populations and promote health equity by formulating policies and directing resources towards areas and populations most in need.

A geospatial analysis of accessibility and availability to implement the primary healthcare roadmap in Ethiopia

BACKGROUND

Primary healthcare (PHC) is a crucial strategy for achieving universal health coverage. Ethiopia is working to improve its primary healthcare system through the Optimization of Health Extension Program (OHEP), which aims to increase accessibility, availability and performance of health professionals and services. Measuring current accessibility of healthcare facilities and workforce availability is essential for the success of the OHEP and achieving universal health coverage in the country.

METHODS

In this study we use an innovative mixed geospatial approach to assess the accessibility and availability of health professionals and services to provide evidence-based recommendations for the implementation of the OHEP. We examined travel times to health facilities, referral times between health posts and health centers, geographical coverage, and the availability and density of health workers relative to the population.

RESULTS

Our findings show that the accessibility and availability of health services in Somali region of Ethiopia is generally low, with 65% of the population being unable to reach a health center or a health post within 1 h walking and referral times exceeding 4 h walking on average. The density of the health workforce is low across Somali region, with no health center being adequately staffed as per national guidelines.

CONCLUSIONS

Improving accessibility and addressing healthcare worker scarcity are challenges for implementing the primary care roadmap in Ethiopia. Upgrading health posts and centers, providing comprehensive services, and training healthcare workers are crucial. Effective outreach strategies are also needed to bridge the gap and improve accessibility and availability.

Impacts of seasonal flooding on geographical access to maternal healthcare in the Barotse Floodplain, Zambia

BACKGROUND

Seasonal floods pose a commonly-recognised barrier to women's access to maternal services, resulting in increased morbidity and mortality. Despite their importance, previous GIS models of healthcare access have not adequately accounted for floods. This study developed new methodologies for incorporating flood depths, velocities, and extents produced with a flood model into network- and raster-based health access models. The methodologies were applied to the Barotse Floodplain to assess flood impact on women's walking access to maternal services and vehicular emergency referrals for a monthly basis between October 2017 and October 2018.

METHODS

Information on health facilities were acquired from the Ministry of Health. Population density data on women of reproductive age were obtained from the High Resolution Settlement Layer. Roads were a fusion of OpenStreetMap and data manually delineated from satellite imagery. Monthly information on floodwater depth and velocity were obtained from a flood model for 13-months. Referral driving times between delivery sites and EmOC were calculated with network analysis. Walking times to the nearest maternal services were calculated using a cost-distance algorithm.

RESULTS

The changing distribution of floodwaters impacted the ability of women to reach maternal services. At the peak of the dry season (October 2017), 55%, 19%, and 24% of women had walking access within 2-hrs to their nearest delivery site, EmOC location, and maternity waiting shelter (MWS) respectively. By the flood peak, this dropped to 29%, 14%, and 16%. Complete inaccessibility became stark with 65%, 76%, and 74% unable to access any delivery site, EmOC, and MWS respectively. The percentage of women that could be referred by vehicle to EmOC from a delivery site within an hour also declined from 65% in October 2017 to 23% in March 2018.

CONCLUSIONS

Flooding greatly impacted health access, with impacts varying monthly as the floodwave progressed. Additional validation and application to other regions is still needed, however our first results suggest the use of a hydrodynamic model permits a more detailed representation of floodwater impact and there is great potential for generating predictive models which will be necessary to consider climate change impacts on future health access.

Predicting health services utilization using a score of perceived barriers to medical care: evidence from rural Senegal

BACKGROUND

Ensuring access to healthcare services is a key element to achieving the Sustainable Development Goal 3 of "promoting healthy lives and well-being for all" through Universal Health Coverage (UHC). However, in the context of low- and middle-income countries, most studies focused on financial protection measured through catastrophic health expenditures (CHE), or on health services utilization among specific populations exhibiting health needs (such as pregnancy or recent sickness).

METHODS

This study aims at building an individual score of perceived barriers to medical care (PBMC) in order to predict primary care utilization (or non-utilization). We estimate the score on six items: (1) knowing where to go, (2) getting permission, (3) having money, (4) distance to the facility, (5) finding transport, and (6) not wanting to go alone, using individual data from 1787 adult participants living in rural Senegal. We build the score via a stepwise descendent explanatory factor analysis (EFA), and assess its internal consistency. Finally, we assess the construct validity of the factor-based score by testing its association (univariate regressions) with a wide range of variables on determinants of healthcare-seeking, and evaluate its predictive validity for primary care utilization.

RESULTS

EFA yields a one-dimensional score combining four items with a 0.7 Cronbach's alpha indicating good internal consistency. The score is strongly associated-p-values significant at the 5% level-with determinants of healthcare-seeking (including, but not limited to, sex, education, marital status, poverty, and distance to the health facility). Additionally, the score can predict non-utilization of primary care at the household level, utilization and non-utilization of primary care following an individual's episode of illness, and utilization of primary care during pregnancy and birth. These results are robust to the use of a different dataset.

CONCLUSION

As a valid, sensitive, and easily documented individual-level indicator, the PBMC score can be a complement to regional or national level health services coverage to measure health services access and predict utilization. At the individual or household level, the PBMC score can also be combined with conventional metrics of financial risk protection such as CHE to comprehensively document deficits in, and progress towards UHC.

Demand–supply-side barriers affecting maternal health service utilization among rural women of West Shoa Zone, Oromia, Ethiopia: A qualitative study

Introduction

Despite the efforts and strategies being applied by the government and the partner organizations to increase maternal health service utilization, maternal health service utilization is low in the general population and very low in rural communities of the West Shoa Zone specifically.

Objective

This study intended to identify and describe barriers contributing to low maternal health service utilization in selected rural districts of the West Shoa Zone of Oromia regional state, Ethiopia, by 2021.

Methods

The study was conducted from February 01 to April 30/2021 in three districts of the West Shoa Zone. The districts were selected purposively based on the report of their last year’s (2020) performance on maternal health service utilization obtained from the Zonal health office, where the ANC follow-up and Institutional delivery were the lowest among the Districts in the Zone. A community-based qualitative phenomenological approach was used to explore the demand-supply side barriers affecting the utilization of maternal health services. Six Focus Group discussions, 9 In-depth Interviews, and 12 Key Informants Interviews were conducted with women who gave birth at home in the last 12 months and with health care providers at different health offices and health institutions. Data were tape-recorded, transcribed verbatim, translated, and analyzed thematically using MAXQDA software.

Results

Our findings revealed that though women strongly agree on the importance and advantage of maternal health services utilization, both demand and supply side barriers such as low awareness on when to use the services, not knowing ANC schedule, misinformation about ANC and institutional delivery, not knowing their estimated date of delivery and precipitated labor, shortage of manpower at health institutions, far distance health facilities, and unavailability or un-accessibility of ambulance services during an emergency time, lack of transportation to health facilities were hindering them not to use the services.

Conclusion

In general, rural women are facing many challenges yet to accessing and utilizing maternal health services. To achieve the SDG targets, addressing barriers prohibiting a woman from using MCH should be critically addressed.

Differences between gridded population data impact measures of geographic access to healthcare in sub-Saharan Africa

Background

Access to healthcare is imperative to health equity and well-being. Geographic access to healthcare can be modeled using spatial datasets on local context, together with the distribution of existing health facilities and populations. Several population datasets are currently available, but their impact on accessibility analyses is unknown. In this study, we model the geographic accessibility of public health facilities at 100-meter resolution in sub-Saharan Africa and evaluate six of the most popular gridded population datasets for their impact on coverage statistics at different administrative levels.

Methods

Travel time to nearest health facilities was calculated by overlaying health facility coordinates on top of a friction raster accounting for roads, landcover, and physical barriers. We then intersected six different gridded population datasets with our travel time estimates to determine accessibility coverages within various travel time thresholds (i.e., 30, 60, 90, 120, 150, and 180-min).

Results

Here we show that differences in accessibility coverage can exceed 70% at the sub-national level, based on a one-hour travel time threshold. The differences are most notable in large and sparsely populated administrative units and dramatically shape patterns of healthcare accessibility at national and sub-national levels.

Conclusions

The results of this study show how valuable and critical a comparative analysis between population datasets is for the derivation of coverage statistics that inform local policies and monitor global targets. Large differences exist between the datasets and the results underscore an essential source of uncertainty in accessibility analyses that should be systematically assessed.

Distance is “a big problem”: a geographic analysis of reported and modelled proximity to maternal health services in Ghana

Background

Geographic barriers to healthcare are associated with adverse maternal health outcomes. Modelling travel times using georeferenced data is becoming common in quantifying physical access. Multiple Demographic and Health Surveys ask women about distance-related problems accessing healthcare, but responses have not been evaluated against modelled travel times. This cross-sectional study aims to compare reported and modelled distance by socio-demographic characteristics and evaluate their relationship with skilled birth attendance. Also, we assess the socio-demographic factors associated with self-reported distance problems in accessing healthcare.

Methods

Distance problems and socio-demographic characteristics reported by 2210 women via the 2017 Ghana Maternal Health Survey were included in analysis. Geospatial methods were used to model travel time to the nearest health facility using roads, rivers, land cover, travel speeds, cluster locations and health facility locations. Logistic regressions were used to predict skilled birth attendance and self-reported distance problems.

Results

Women reporting distance challenges accessing healthcare had significantly longer travel times to the nearest health facility. Poverty significantly increased the odds of reporting challenges with distance. In contrast, living in urban areas and being registered with health insurance reduced the odds of reporting distance challenges. Women with a skilled attendant at birth, four or more skilled antenatal appointments and timely skilled postnatal care had shorter travel times to the nearest health facility. Generally, less educated, poor, rural women registered with health insurance had longer travel times to their nearest health facility. After adjusting for socio-demographic characteristics, the following factors increased the odds of skilled birth attendance: wealth, health insurance, higher education, living in urban areas, and completing four or more antenatal care appointments.

Conclusion

Studies relying on modelled travel times to nearest facility should recognise the differential impact of geographic access to healthcare on poor rural women. Physical access to maternal health care should be scaled up in rural areas and utilisation increased by improving livelihoods.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12884-022-04998-0.

How applicable is geospatial analysis in maternal and neonatal health in sub-Saharan Africa? A systematic review

Background

Sub-Saharan Africa (SSA) has the world's highest maternal and neonatal morbidity and mortality and has shown the slowest progress in reducing them. In addition, there is substantial inequality in terms of maternal and neonatal morbidity and mortality in the region. Geospatial studies can help prioritize scarce resources by pinpointing priority areas for implementation. This systematic review was conducted to explore the application of geospatial analysis to maternal and neonatal morbidity and mortality in SSA.

Methods

A systematic search of PubMed, SCOPUS, EMBASE, and Web of Science databases was performed. All observational and qualitative studies that reported on maternal or neonatal health outcomes were included if they used a spatial analysis technique and were conducted in a SSA country. After removing duplicates, two reviewers independently reviewed each study's abstract and full text for inclusion. Furthermore, the quality of the studies was assessed using the Joanna Briggs Institute (JBI) critical appraisal checklists. Finally, due to the heterogeneity of studies, narrative synthesis was used to summarize the main findings, and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline was strictly followed to report the review results. A total of 56 studies were included in the review.

Results

We found that geospatial analysis was used to identify inequalities in maternal and neonatal morbidity, mortality, and health care utilization and to identify gaps in the availability and geographic accessibility of maternal health facilities. In addition, we identified a few studies that used geospatial analysis for modelling intervention areas. We also detected challenges and shortcomings, such as unrealistic assumptions used by geospatial models and a shortage of reliable, up-to-date, small-scale georeferenced data.

Conclusions

The use of geospatial analysis for maternal and neonatal health in SSA is still limited, and more detailed spatial data are required to exploit the potential of geospatial technologies fully.

Geospatial mapping of timely access to inpatient neonatal care and its relationship to neonatal mortality in Kenya

Globally, 2.4 million newborns die in the first month of life, with neonatal mortality rates (NMR) per 1,000 livebirths being highest in sub-Saharan Africa. Improving access to inpatient newborn care is necessary for reduction of neonatal deaths in the region. We explore the relationship between distance to inpatient hospital newborn care and neonatal mortality in Kenya. Data on service availability from numerous sources were used to map hospitals that care for newborns with very low birth weight (VLBW). Estimates of livebirths needing VLBW services were mapped from population census data at 100 m spatial resolution using a random forest algorithm and adjustments using a systematic review of livebirths needing these services. A cost distance algorithm that adjusted for proximity to roads, road speeds, land use and protected areas was used to define geographic access to hospitals offering VLBW services. County-level access metrics were then regressed against estimates of NMR to assess the contribution of geographic access to VLBW services on newborn deaths while controlling for wealth, maternal education and health workforce. 228 VLBW hospitals were mapped, with 29,729 births predicted as requiring VLBW services in 2019. Approximately 80.3% of these births were within 2 hours of the nearest VLBW hospital. Geographic access to these hospitals, ranged from less than 30% in Wajir and Turkana to as high as 80% in six counties. Regression analysis showed that a one percent increase in population within 2 hours of a VLBW hospital was associated with a reduction of NMR by 0.24. Despite access in the country being above the 80% threshold, 17/47 counties do not achieve this benchmark. To reduce inequities in NMR in Kenya, policies to improve care must reduce geographic barriers to access and progressively improve facilities' capacity to provide quality care for VLBW newborns.

Delineating natural catchment health districts with routinely collected health data from women's travel to give birth in Ghana

Background

Health service areas are essential for planning, policy and managing public health interventions. In this study, we delineate health service areas from routinely collected health data as a robust geographic basis for presenting access to maternal care indicators.

Methods

A zone design algorithm was adapted to delineate health service areas through a cross-sectional, ecological study design. Health sub-districts were merged into health service areas such that patient flows across boundaries were minimised. Delineated zones and existing administrative boundaries were used to provide estimates of access to maternal health services. We analysed secondary data comprising routinely collected health records from 32,921 women attending 27 hospitals to give birth, spatial demographic data, a service provision assessment on the quality of maternal healthcare and health sub-district boundaries from Eastern Region, Ghana.

Results

Clear patterns of cross border movement to give birth emerged from the analysis, but more women originated closer to the hospitals. After merging the 250 sub-districts in 33 districts, 11 health service areas were created. The minimum percent of internal flows of women giving birth within any health service area was 97.4%. Because the newly delineated boundaries are more “natural” and sensitive to observed flow patterns, when we calculated areal indicator estimates, they showed a marked improvement over the existing administrative boundaries, with the inclusion of a hospital in every health service area.

Conclusion

Health planning can be improved by using routine health data to delineate natural catchment health districts. In addition, data-driven geographic boundaries derived from public health events will improve areal health indicator estimates, planning and interventions.

Pooled Prevalence and Determinants of Completion of Maternity Continuum of Care in Sub-Saharan Africa: A Multi-Country Analysis of Recent Demographic and Health Surveys

Background

Improving the coverage of completion of the maternity continuum of care is the priority area of sub-Saharan African countries to achieve the sustainable development goal. Despite this, information is scant about the pooled prevalence of completion of the maternity continuum of care and its determinants in sub-Saharan African countries. Therefore, this study aimed to assess the pooled prevalence of completion of the maternity continuum of care and its determinants among women in sub-Saharan African countries.

Methods

The study was conducted based on Demographic and Health Survey (DHS) data from 33 sub-Saharan African countries from 2010 to 2020. The total sample size of 337,297 postpartum period women with children aged 0–36 months (about 3 years) was employed in the analysis by STATA version 14. A multilevel logistic regression model was fitted, and intraclass correlation coefficient (ICC), median odds ratio (MOR), proportion change in variance (PCV), and deviance were used for model fitness and comparison. Adjusted odds ratio (AOR) with its 95% confidence interval (CI) was presented. Variables with a value of p < 0.05 were declared significant determinants of completion of the maternity continuum of care.

Results

The pooled prevalence of completion of the maternity continuum of care was 35.81%; [95% CI, 35.64%, 35.9%]. Higher educational level [AOR = 3.62; 95% CI 2.25, 4.46], wanted pregnancy [AOR = 2.51; 95% CI 1.82, 3.12], history of terminated pregnancy [AOR = 3.21; 95% CI 2.86, 4.21], distance to the nearby health facility [AOR = 2.11; 95% CI 1.68, 2.36], women as primary decision maker [AOR = 2.15; 95% CI 2.02, 2.87], nouse of traditional medication during pregnancy [AOR = 1.01; 95% CI 1.00, 1.45], antenatal care (ANC) visit within second trimester [AOR = 2.76; 95% CI 2.01, 3.47], informed about pregnancy complication [AOR = 2.73; 95% CI 2.10, 3.21], healthcare provider support [AOR = 1.77; 95% CI 1.02, 2.44], and being eastern and western African [AOR = 1.55; 95% CI 1.11, 2.44 and AOR = 2.01; 95% CI 1.88, 2.76, respectively] were determinant factors of completion of maternity continuum of care.

Conclusions

The completion of the maternity continuum of care in sub-Sahara African countries was low. Emphasis on women's education, type, history of pregnancy, distance to the nearby health facility, region, assessing the exposure of traditional medication, and informed about pregnancy complications, healthcare provider's support can improve the prevalence of completion of the maternity continuum of care.

Toward Equitable Access to Tertiary Cancer Care in Rwanda: A Geospatial Analysis

PURPOSE

Geographic access to care is an important measure of health equity. In this study, we describe geographic access to cancer care centers (CCCs) in Rwanda with the current facilities providing care and examine how access could change with expanded care infrastructure.

METHODS

Health facilities included are public hospitals administered by the Rwanda Ministry of Health. The WorldPop Project was used to estimate population distribution, and OpenStreetMap was used to determine travel routes. On the basis of geolocations of the facilities, AccessMod 5 was used to estimate the percentage of the population that live within 1 hour, 2 hours, and 4 hours of CCCs under the current (two facilities) and expanded care (seven facilities) scenarios. Variations in access by region, poverty, and level of urbanization were described.

RESULTS

Currently, 13%, 41%, and 85% of Rwandans can access CCCs within one, two, and 4 hours of travel, respectively. With expansion of CCCs to seven facilities, access increases to 37%, 84%, and 99%, respectively. There is a substantial variation in current geographic access by province, with 1-hour access in Kigali at 98%, whereas access in the Western Province is 0%; care expansion could increase 2-hour access in the Western Province from 1% to 71%. Variation in access is also seen across the level of urbanization, with current 1-hour access in urban versus rural areas of 45% and 8%, respectively. Expanded care results in improvement of 1-hour access to 67% and 33%, respectively. Similar trends were also noted across poverty levels.

CONCLUSION

Geographical access to CCCs varies substantially by province, level of urbanization, and poverty. These disparities can be alleviated by strategic care expansion to other tertiary care facilities across Rwanda.

The causal effect of delivery volume on severe maternal morbidity: an instrumental variable analysis in Sichuan, China

Objective

Findings regarding the association between delivery volume and maternal health outcomes are mixed, most of which explored their correlation. This study aims to demonstrate the causal effect of delivery volume on severe maternal morbidity (SMM) in China.

Methods

We analysed all women giving birth in the densely populated Sichuan province with 83 million residents in China, during the fourth quarters of each of 4 years (from 2016 to 2019). The routinely collected discharge data, the health institutional annual report data and road network data were used for analysis. The maternal health outcome was measured by SMM. Instrumental variable (IV) methods were applied for estimation, while the surrounding average number of delivery cases per institution was used as the instrument.

Results

The study included 4545 institution-years of data from 1456 distinct institutions with delivery services, reflecting 810 049 associated delivery cases. The average SMM rate was approximately 33.08 per 1000 deliveries during 2016 and 2019. More than 86% of delivery services were provided by a third of the institutions with the highest delivery volume (≥143 delivery cases quarterly). In contrast, less than 2% of delivery services were offered by a third of the institutions with the lowest delivery volume (<19 delivery cases quarterly). After adjusting the confounders in the IV-logistic models, the average marginal effect of per 1000 cases in delivery volume was −0.162 (95% CI −0.169 to –0.155), while the adjusted OR of delivery volume was 0.005 (95% CI 0.004 to 0.006).

Conclusion

Increased delivery volume has great potential to improve maternal health outcomes, while the centralisation of delivery services might facilitate maternal health promotion in China. Our study also provides implications for other developing countries confronted with similar challenges to China.

Availability and Utilization of Postabortion Care Services in Burkina Faso, Côte d'Ivoire, and Guinea: A Secondary Analysis of Emergency Obstetric and Neonatal Care Needs Assessments (EmONC)

SYNOPSIS: Generally, there are disparities in the availability and utilization of postabortion care services within the different regions at the national level in Burkina Faso, Cote d’Ivoire, and Guinea and between the 3 countries. Access to postabortion care at the primary level must be improved and the adoption of family planning when providing postabortion care.

Unsafe abortion remains one of the leading causes of maternal mortality in sub-Sahara Africa, with relatively poor access to quality postabortion care (PAC) services. This study evaluated the quantity and distribution as well as the utilization of PAC services in Burkina Faso, Cote d’Ivoire, and Guinea. We conducted a secondary data analysis using the most recent EmONC surveys in the 3 countries between 2016 and 2017. We used PAC signal functions approach to assess facilities’ capacity to provide basic PAC at both primary and referral level of care and comprehensive PAC at the referral level. We illustrated population coverage of PAC services based on the WHO benchmark, and then assessed the utilization of PAC services. Basic PAC capacity at primary level was low (36.6%), ranging from 16.2% in Burkina Faso to 36% in Cote d’Ivoire. About 82.0% of hospitals could provide comprehensive PAC. There were disparities in the geographical distribution of PAC services at both national and subnational levels. Abortion complications represented 16.2% of all obstetric emergencies, and uptake of PAC modern contraceptive was low (37.1%) in all countries. There is a need to focus on access to PAC at the primary level of care in the 3 countries.

Impact of newly constructed primary healthcare centres on antenatal care attendance, facility delivery and all-cause mortality: quasi-experimental evidence from Taabo health and demographic surveillance system, Côte d'Ivoire

OBJECTIVES

Access to quality care remains limited, particularly in low-income and middle-income countries. Although better health outcomes for families living in close proximity to healthcare facilities have been documented in cross-sectional studies, evidence on the extent to which additional health facilities can contribute to improved population health remains scanty. We aimed to estimate the causal impact of newly constructed primary healthcare facilities within a health and demographic surveillance (HDSS) site in Côte d'Ivoire.

DESIGN

We conducted a quasi-experimental study. Logistic and Cox proportional hazards regression models were used to estimate the impact of new healthcare facilities on healthcare-seeking behaviour and all-cause mortality.

SETTING

Data were collected prospectively through the Taabo HDSS located in south-central Côte d'Ivoire between 2010 and 2018.

PARTICIPANTS

We analysed 2957 deaths across 440 973 person-year observations as well as 14 132 live births.

PRIMARY OUTCOME MEASURES

The primary outcomes were antenatal care (ANC) attendance, facility delivery and mortality. Logistic and Cox proportional hazards models were employed to estimate the impact of the new health facilities on ANC attendance, facility delivery and child as well as adult mortality.

RESULTS

Average distance to the nearest healthcare facility declined from 5.5 km before to 2.8 km after opening of four new healthcare facilities in targeted villages. No improvement was observed for ANC attendance, institutional deliveries and adult mortality. New facilities reduced the risk of post-neonatal infant mortality by 46% (HR 0.54, 95% CI 0.31 to 0.94, p<0.05), suggesting a mortality gradient of 2 deaths per 1000 for each additional km (Coef=0.002, 95% CI 0.000 to 0.004, p<0.05).

CONCLUSIONS

Our results suggest that new facilities do not necessarily improve healthcare utilisation and health outcomes. Further research is needed to identify the best ways to ensure access to quality care in resource-constrained settings.

Geographic barriers to establishing a successful hospital referral system in rural Madagascar

Background

The provision of emergency and hospital care has become an integral part of the global vision for universal health coverage. To strengthen secondary care systems, we need to accurately understand the time necessary for populations to reach a hospital. The goal of this study was to develop methods that accurately estimate referral and prehospital time for rural districts in low and middle-income countries. We used these estimates to assess how local geography can limit the impact of a strengthened referral programme in a rural district of Madagascar.

Methods

We developed a database containing: travel speed by foot and motorised vehicles in Ifanadiana district; a full mapping of all roads, footpaths and households; and remotely sensed data on terrain, land cover and climatic characteristics. We used this information to calibrate estimates of referral and prehospital time based on the shortest route algorithms and statistical models of local travel speed. We predict the impact on referral numbers of strategies aimed at reducing referral time for underserved populations via generalised linear mixed models.

Results

About 10% of the population lived less than 2 hours from the hospital, and more than half lived over 4 hours away, with variable access depending on climatic conditions. Only the four health centres located near the paved road had referral times to the hospital within 1 hour. Referral time remained the main barrier limiting the number of referrals despite health system strengthening efforts. The addition of two new referral centres is estimated to triple the population living within 2 hours from a centre with better emergency care capacity and nearly double the number of expected referrals.

Conclusion

This study demonstrates how adapting geographic accessibility modelling methods to local scales can occur through improving the precision of travel time estimates and pairing them with data on health facility use.

How did micro-mobility change in response to COVID-19 pandemic? A case study based on spatial-temporal-semantic analytics

Cities worldwide adopted lockdown policies in response to the outbreak of coronavirus disease 2019 (COVID-19), significantly influencing people's travel behavior. In particular, micro-mobility, an emerging mode of urban transport, is profoundly shaped by this crisis. However, there is limited research devoted to understanding the rapidly evolving trip patterns of micro-mobility in response to COVID-19. To fill this gap, we analyze the changes in micro-mobility usage before and during the lockdown period exploiting high-resolution micro-mobility trip data collected in Zurich, Switzerland. Specifically, docked bike, docked e-bike, and dockless e-bike are evaluated and compared from the perspective of space, time and semantics. First, the spatial and temporal analysis results uncover that the number of trips decreased remarkably during the lockdown period. The striking difference between the normal and lockdown period is the decline in the peak hours of workdays. Second, the origin-destination flows are used to construct spatially embedded networks. The results suggest that the origin-destination pairs remain similar during the lockdown period, while the numbers of trips between each origin-destination pair is reduced due to COVID-19 pandemic. Finally, the semantic analysis is conducted to uncover the changes in trip purpose. It is revealed that the proportions of Home, Park, and Grocery activities increase, while the proportions of Leisure and Shopping activities decrease during the lockdown period. The above results can help planners and policymakers better make evidence-based policies regarding micro-mobility in the post-pandemic society.

Achieving universal electrification of rural healthcare facilities in sub-Saharan Africa with decentralized renewable energy technologies

A potential response to the COVID-19 pandemic in sub-Saharan Africa (SSA) with long-term benefits is to provide electricity for medical equipment in rural health centers and communities. This study identifies a large gap in the electrification of healthcare facilities in SSA, and it shows that decentralized photovoltaic systems can offer a clean, reliable, quick, and cost-effective solution. The cost of providing renewable electricity to each health facility by a stand-alone PV system is analyzed for a given location (incorporating operational costs). The upfront investment cost for providing electricity with PV to >50,000 facilities (mostly primary health posts) currently without electricity is estimated at EUR 484 million. Analysis of the accessibility and population distribution shows that 281 million people could reduce their travel time to healthcare facilities (by an average of 50 min) if all facilities were electrified.

A review of geospatial methods for population estimation and their use in constructing reproductive, maternal, newborn, child and adolescent health service indicators

Background

Household survey data are frequently used to measure reproductive, maternal, newborn, child and adolescent health (RMNCAH) service utilisation in low and middle income countries. However, these surveys are typically only undertaken every 5 years and tend to be representative of larger geographical administrative units. Investments in district health management information systems (DHMIS) have increased the capability of countries to collect continuous information on the provision of RMNCAH services at health facilities. However, reliable and recent data on population distributions and demographics at subnational levels necessary to construct RMNCAH coverage indicators are often missing. One solution is to use spatially disaggregated gridded datasets containing modelled estimates of population counts. Here, we provide an overview of various approaches to the production of gridded demographic datasets and outline their potential and their limitations. Further, we show how gridded population estimates can be used as alternative denominators to produce RMNCAH coverage metrics in combination with data from DHMIS, using childhood vaccination as examples.

Methods

We constructed indicators on the percentage of children one year old for diphtheria, pertussis and tetanus vaccine dose 3 (DTP3) and measles vaccine dose (MCV1) in Zambia and Nigeria at district levels. For the numerators, information on vaccines doses was obtained from each country’s respective DHMIS. For the denominators, the number of children was obtained from 3 different sources including national population projections and aggregated gridded estimates derived using top-down and bottom-up geospatial methods.

Results

In Zambia, vaccination estimates utilising the bottom-up approach to population estimation substantially reduced the number of districts with > 100% coverage of DTP3 and MCV1 compared to estimates using population projection and the top-down method. In Nigeria, results were mixed with bottom-up estimates having a higher number of districts > 100% and estimates using population projections performing better particularly in the South.

Conclusions

Gridded demographic data utilising traditional and novel data sources obtained from remote sensing offer new potential in the absence of up to date census information in the estimation of RMNCAH indicators. However, the usefulness of gridded demographic data is dependent on several factors including the availability and detail of input data.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-06370-y.

"In cities, it's not far, but it takes long": comparing estimated and replicated travel times to reach life-saving obstetric care in Lagos, Nigeria

BACKGROUND

Travel time to comprehensive emergency obstetric care (CEmOC) facilities in low-resource settings is commonly estimated using modelling approaches. Our objective was to derive and compare estimates of travel time to reach CEmOC in an African megacity using models and web-based platforms against actual replication of travel.

METHODS

We extracted data from patient files of all 732 pregnant women who presented in emergency in the four publicly owned tertiary CEmOC facilities in Lagos, Nigeria, between August 2018 and August 2019. For a systematically selected subsample of 385, we estimated travel time from their homes to the facility using the cost-friction surface approach, Open Source Routing Machine (OSRM) and Google Maps, and compared them to travel time by two independent drivers replicating women's journeys. We estimated the percentage of women who reached the facilities within 60 and 120 min.

RESULTS

The median travel time for 385 women from the cost-friction surface approach, OSRM and Google Maps was 5, 11 and 40 min, respectively. The median actual drive time was 50-52 min. The mean errors were >45 min for the cost-friction surface approach and OSRM, and 14 min for Google Maps. The smallest differences between replicated and estimated travel times were seen for night-time journeys at weekends; largest errors were found for night-time journeys at weekdays and journeys above 120 min. Modelled estimates indicated that all participants were within 60 min of the destination CEmOC facility, yet journey replication showed that only 57% were, and 92% were within 120 min.

CONCLUSIONS

Existing modelling methods underestimate actual travel time in low-resource megacities. Significant gaps in geographical access to life-saving health services like CEmOC must be urgently addressed, including in urban areas. Leveraging tools that generate 'closer-to-reality' estimates will be vital for service planning if universal health coverage targets are to be realised by 2030.

Evaluating the Accuracy of Gridded Population Estimates in Slums: A Case Study in Nigeria and Kenya

Low- and middle-income country cities face unprecedented urbanization and growth in slums. Gridded population data (e.g., ~100 × 100 m) derived from demographic and spatial data are a promising source of population estimates, but face limitations in slums due to the dynamic nature of this population as well as modelling assumptions. In this study, we compared field-referenced boundaries and population counts from Slum Dwellers International in Lagos (Nigeria), Port Harcourt (Nigeria), and Nairobi (Kenya) with nine gridded population datasets to assess their statistical accuracy in slums. We found that all gridded population estimates vastly underestimated population in slums (RMSE: 4958 to 14,422, Bias: −2853 to −7638), with the most accurate dataset (HRSL) estimating just 39 per cent of slum residents. Using a modelled map of all slums in Lagos to compare gridded population datasets in terms of SDG 11.1.1 (percent of population living in deprived areas), all gridded population datasets estimated this indicator at just 1–3 per cent compared to 56 per cent using UN-Habitat’s approach. We outline steps that might improve that accuracy of each gridded population dataset in deprived urban areas. While gridded population estimates are not yet sufficiently accurate to estimate SDG 11.1.1, we are optimistic that some could be used in the future following updates to their modelling approaches.

When distance matters: Mapping HIV health care underserved communities in sub-Saharan Africa

Despite efforts to increase the proportion of individuals diagnosed with HIV who receive anti-retroviral therapy, 28% of people living with HIV (PLHIV) aged 15 years and older in eastern and southern Africa and 42% in western and central Africa were not receiving anti-retroviral therapy in 2019. Therefore, improving access to health care services is key to reduce HIV incidence and prevalence. The main aim of this study was to generate high-resolution maps of underserved areas where people cannot access the closest health care facilities within appropriate travel time in sub-Saharan Africa (SSA). Main sources of data for this study were the estimated number of PLHIV for adults aged 15-49 years in 47 countries in SSA and the global map of travel time to the nearest health care facility by motorized and non-motorized transportation. These data were used to estimate and map the number of PLHIV in underserved areas at a travel distance of 10, 30, and 60 minutes from the nearest healthcare facility. We identified and mapped more than 7 million PLHIV in the areas with a lack of access to health care within 10-minute travel time and 1.5 million PLHIV in the areas with a lack of access to health care within 60-minute travel time. The identified locations of underserved areas are an indicator of the challenge faced by PLHIV in accessing health services in SSA, a situation that is likely worsened by the COVID-19 pandemic. These findings can contribute to developing cost-effective geospatial policies for interventions aimed at underserved areas at a finer resolution for communities that have usually been identified in aggregated spatial areas. Further development and implementation of tailored intervention and treatment programs, especially in areas identified as underserved for PLHIV, should be explored. Geospatial analyses could complement the decision-making process with stakeholders to enhance healthcare access for PLHIV in SSA.

Planning universal accessibility to public health care in sub-Saharan Africa

Achieving universal health care coverage-a key target of the United Nations Sustainable Development Goal number 3-requires accessibility to health care services for all. Currently, in sub-Saharan Africa, at least one-sixth of the population lives more than 2 h away from a public hospital, and one in eight people is no less than 1 h away from the nearest health center. We combine high-resolution data on the location of different typologies of public health care facilities [J. Maina et al., Sci. Data 6, 134 (2019)] with population distribution maps and terrain-specific accessibility algorithms to develop a multiobjective geographic information system framework for assessing the optimal allocation of new health care facilities and assessing hospitals expansion requirements. The proposed methodology ensures universal accessibility to public health care services within prespecified travel times while guaranteeing sufficient available hospital beds. Our analysis suggests that to meet commonly accepted universal health care accessibility targets, sub-Saharan African countries will need to build ∼6,200 new facilities by 2030. We also estimate that about 2.5 million new hospital beds need to be allocated between new facilities and ∼1,100 existing structures that require expansion or densification. Optimized location, type, and capacity of each facility can be explored in an interactive dashboard. Our methodology and the results of our analysis can inform local policy makers in their assessment and prioritization of health care infrastructure. This is particularly relevant to tackle health care accessibility inequality, which is not only prominent within and between countries of sub-Saharan Africa but also, relative to the level of service provided by health care facilities.