Impact of traffic variability on geographic accessibility to 24/7 emergency healthcare for the urban poor: A GIS study in Dhaka, Bangladesh

Optimization of the emergency obstetric and neonatal care network in Benin through expert-based sub-national prioritizations

Introduction

To reduce maternal mortality by 2030, Benin needs to implement strategies for improving access to high quality emergency obstetric and neonatal care (EmONC). This study applies an expert-based approach using sub-national travel specificities to identify and prioritize a network of EmONC maternities that maximizes both population coverage and functionality.

Methods

We conducted a series of workshops involving international, national, and department experts in maternal health to prioritize a set of EmONC facilities that meet international standards. Geographical accessibility modeling was used together with EmONC availability to inform the process. For women in need of EmONC, experts provided insights into travel characteristics (i.e., modes and speeds of travel) specific to each department, enabling more realistic travel times estimates modelled with the AccessMod software.

Results

The prioritization approach resulted in the selection of 109 EmONC maternities from an initial group of 125 designated maternities. The national coverage of the population living within an hour's drive of the nearest EmONC maternity increased slightly from 92.6% to 94.1% after prioritization. This increase in coverage was achieved by selecting maternities with sufficient obstetrical activities to be upgraded to EmONC maternities in the Plateau and Atlantique departments.

Conclusion

The prioritization approach enabled Benin to achieve the minimum EmONC availability, while ensuring very good geographical accessibility to the prioritized network. Limited human and financial resources can now be targetted towards a smaller number of EmONC facilities to make them fully functioning in the medium-term. By implementing this strategy, Benin aims to reduce maternal mortality rates and deliver effective, high-quality obstetric and neonatal care, especially during emergencies.

Measuring geographic access to emergency obstetric care: a comparison of travel time estimates modelled using Google Maps Directions API and AccessMod in three Nigerian conurbations

Google 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.

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.

Quality of life and its predictors among patients with metastatic cancer in Bangladesh: the APPROACH survey

BACKGROUND

This study aimed to assess the health-related quality of life (HRQOL) (physical, functional, emotional, social, spiritual) and psychological (anxiety and depression) well-being and their associations with patient characteristics among patients with metastatic cancer in Bangladesh.

METHODS

A convenience sample of 386 Bangladeshi patients with stage IV solid cancers was recruited from a palliative care outpatient department and an inpatient palliative center. Dependent variables included the physical, functional, emotional, social, and overall scores of the Functional Assessment of Cancer Therapy-General (FACT-G) scale, the Functional Assessment of Chronic Illness Therapy-Spiritual Well-being (FACIT-SP) scale, the anxiety, depression, and overall scores of the Hospital Anxiety and Depression (HADS) scale. Linear regressions examined the association between dependent variables and patient characteristics.

RESULTS

A substantial proportion of Bangladeshi patients reported anxiety (59% of outpatients and 55% of inpatients) and depression (60% of outpatients and 73% of inpatients) symptoms. Generally, greater financial difficulty and symptom burden scores were associated with worse health outcomes. Older patients reported poorer functional and spiritual well-being but better anxiety scores. Females reported worse anxiety and depressive symptoms and physical well-being but better spiritual outcomes.

CONCLUSIONS

Additional efforts must be directed at improving the HRQOL of patients with metastatic cancer in Bangladesh. Furthermore, assistance should be made more accessible to vulnerable groups, including women, the elderly, and those with financial difficulty.

Estimated travel time and staffing constraints to accessing the Ethiopian health care system: A two-step floating catchment area analysis

Background

Despite large investments in the public health care system, disparities in health outcomes persist between lower- and upper-income individuals, as well as rural vs urban dwellers in Ethiopia. Evidence from Ethiopia and other low- and middle-income countries suggests that challenges in health care access may contribute to poverty in these settings.

Methods

We employed a two-step floating catchment area to estimate variations in spatial access to health care and in staffing levels at health care facilities. We estimated the average travel time from the population centers of administrative areas and adjusted them with provider-to-population ratios. To test hypotheses about the role of travel time vs staffing, we applied Spearman's rank tests to these two variables against the access score to assess the significance of observed variations.

Results

Among Ethiopia's 11 first-level administrative units, Addis Ababa, Dire Dawa, and Harari had the best access scores. Regions with the lowest access scores were generally poorer and more rural/pastoral. Approximately 18% of the country did not have access to a public health care facility within a two-hour walk. Our results suggest that spatial access and staffing issues both contribute to access challenges.

Conclusion

Investments both in new health facilities and staffing in existing facilities will be necessary to improve health care access within Ethiopia. Because rural and low-income areas are more likely to have poor access, future strategies for expanding and strengthening the health care system should strongly emphasize equity and the role of improved access in reducing poverty.

The Contributions of Population Distribution, Healthcare Resourcing, and Transportation Infrastructure to Spatial Accessibility of Health Care

Population demand, healthcare resourcing, and transportation linkage are considered as major determinants of spatial access to health care. Temporal changes of the 3 determinants would result in gain or loss of spatial access to health care. As a remarkable milestone achieved by Targeted Poverty Reduction Project launched in China, the significant improvements in spatial access to health care served as an ideal context for investigating the relative contributions of these 3 determinants to the changes in spatial access to health care in a rural county. A national level poverty-stricken county, Chishui county from Guizhou province, China, was chosen as our study area. The enhanced two-step floating catchment area model and the chain substitution method were employed for analysis. The relative contributions of the 3 determinants demonstrated variations with villages. The relative contributions of healthcare resourcing were positive in all villages as indicated by sharp increases in healthcare resources. Population changes and transportation infrastructure expansion had both negative and positive effects on spatial access to health care for different villages. Decisionmakers should take into account the duration of travel time spent between where people live, where transport hubs are located, and where healthcare services are delivered in the process of formulating policies toward rural healthcare planning. For villages with poorly-established infrastructure, the optimization of population distribution and healthcare resourcing should be considered as the priority. A stronger marginal effect would be induced by transportation infrastructure expansion with increased spatial accessibility. This study provides empirical evidences to inform healthcare planning in low- and middle-income countries.

Mapping population access to essential surgical care in Liberia using equipment, personnel, and bellwether capability standards

BACKGROUND

Accurate surveillance of population access to essential surgery is key for strategic healthcare planning. This study aimed to estimate population access to surgical facilities meeting standards for safe surgery equipment, specialized surgical personnel, and bellwether capability, cesarean delivery, emergency laparotomy, and long-bone fracture fixation and to evaluate the validity of using these standards to describe the full breadth of essential surgical care needs in Liberia.

METHOD

An observational study of surgical facilities was conducted in Liberia between 20 September and 8 November 2018. Facility data were combined with geospatial data and analysed in an online visualization platform.

RESULTS

Data were collected from 51 of 52 surgical facilities. Nationally, 52.9 per cent of the population (2 392 000 of 4 525 000 people) had 2-h access to their closest surgical facility, whereas 41.1 per cent (1 858 000 people) and 48.6 per cent (2 199 000 people) had 2-h access to a facility meeting the personnel and equipment standards respectively. Six facilities performed all bellwether procedures; 38.7 per cent of the population (1 751 000 people) had 2-h access to one of these facilities. Bellwether-capable facilities were more likely to perform other essential surgical procedures (OR 3.13, 95 per cent c.i. 1.28 to 7.65; P = 0.012). These facilities delivered a median of 13.0 (i.q.r. 11.3-16.5) additional essential procedures.

CONCLUSION

Population access to essential surgery is limited in Liberia; strategies to reduce travel times ought to be part of healthcare policy. Policymakers should also be aware that bellwether capability might not be a valid proxy for the full breadth of essential surgical care in low-income settings.

Impact of traffic congestion on spatial access to healthcare services in Nairobi

Background

Geographic accessibility is an important determinant of healthcare utilization and is critical for achievement of universal health coverage. Despite the high disease burden and severe traffic congestion in many African cities, few studies have assessed how traffic congestion impacts geographical access to healthcare facilities and to health professionals in these settings. In this study, we assessed the impact of traffic congestion on access to healthcare facilities, and to the healthcare professionals across the healthcare facilities.

Methods

Using data on health facilities obtained from the Ministry of Health in Kenya, we mapped 944 primary, 94 secondary and four tertiary healthcare facilities in Nairobi County. We then used traffic probe data to identify areas within a 15-, 30- and 45-min drive from each health facility during peak and off-peak hours and calculated the proportion of the population with access to healthcare in the County. We employed a 2-step floating catchment area model to calculate the ratio of healthcare and healthcare professionals to population during these times.

Results

During peak hours, <70% of Nairobi's 4.1 million population was within a 30-min drive from a health facility. This increased to >75% during off-peak hours. In 45 min, the majority of the population had an accessibility index of one health facility accessible to more than 100 people (<0.01) for primary health care facilities, one to 10,000 people for secondary facilities, and two health facilities per 100,000 people for tertiary health facilities. Of people with access to health facilities, a sub-optimal ratio of <4.45 healthcare professionals per 1,000 people was observed in facilities offering primary and secondary healthcare during peak and off-peak hours.

Conclusion

Our study shows access to healthcare being negatively impacted by traffic congestion, highlighting the need for multisectoral collaborations between urban planners, health sector and policymakers to optimize health access for the city residents. Additionally, growing availability of traffic probe data in African cities should enable similar analysis and understanding of healthcare access for city residents in other countries on the continent.

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.

Factors associated with accessing and utilisation of healthcare and provision of health services for residents of slums in low and middle-income countries: a scoping review of recent literature

OBJECTIVE

To identify factors associated with accessing and utilisation of healthcare and provision of health services in slums.

DESIGN

A scoping review incorporating a conceptual framework for configuring reported factors.

DATA SOURCES

MEDLINE, Embase, CINAHL, Web of Science and the Cochrane Library were searched from their inception to December 2021 using slum-related terms.

ELIGIBILITY CRITERIA

Empirical studies of all designs reporting relevant factors in slums in low and middle-income countries.

DATA EXTRACTION AND SYNTHESIS

Studies were categorised and data were charted according to a preliminary conceptual framework refined by emerging findings. Results were tabulated and narratively summarised.

RESULTS

Of the 15 469 records retrieved from all years, 4368 records dated between 2016 and 2021 were screened by two independent reviewers and 111 studies were included. The majority (63 studies, 57%) were conducted in Asia, predominantly in India. In total, 104 studies examined healthcare access and utilisation from slum residents' perspective while only 10 studies explored provision of health services from providers/planners' perspective (three studies included both). A multitude of factors are associated with accessing, using and providing healthcare in slums, including recent migration to slums; knowledge, perception and past experience of illness, healthcare needs and health services; financial constraint and competing priorities between health and making a living; lacking social support; unfavourable physical environment and locality; sociocultural expectations and stigma; lack of official recognition; and existing problems in the health system.

CONCLUSION

The scoping review identified a significant body of recent literature reporting factors associated with accessing, utilisation and provision of healthcare services in slums. We classified the diverse factors under seven broad categories. The findings can inform a holistic approach to improving health services in slums by tackling barriers at different levels, taking into account local context and geospatial features of individual slums. SYSTEMATIC REVIEW REGISTRATION NUMBER: https://osf.io/694t2.

Access to care following injury in Northern Malawi, a comparison of travel time estimates between Geographic Information System and community household reports

INTRODUCTION

Injuries disproportionately impact low- and middle-income countries like Malawi. The Lancet Commission on Global Surgery's indicators include the population proportion accessing laparotomy and open fracture care, key trauma interventions, within two hours. The "Golden Hour" for receiving facility-based resuscitation also guides injury care system strengthening. Firstly, we estimated the proportion of the local population able to reach primary, secondary and tertiary facility care within two and one hours using Geographic Information System (GIS) analysis. Secondly, we compared community household-reported with GIS-estimated travel time.

METHODS

Using information from a Health and Demographic Surveillance Site (Karonga, Malawi) on road network, facility location, and local staff-estimated travel speeds, we used a GIS-generated friction surface to calculate the shortest travel time from all households to each facility serving the population. We surveyed community households who reported travel time to their preferred, closest, government secondary and tertiary facilities. For recently injured community members, time to reach facility care was recorded. To assess the relationship between community household-reported travel time and GIS-estimated travel time, we used linear regression to generate a proportionality constant. To assess associations and agreement between injured patient-reported and GIS-estimated travel time, we used Kendall rank and Cohen's kappa tests.

RESULTS

Using GIS, we estimated 79.1% of households could reach any secondary facility, 20.5% the government secondary facility, and 0% the government tertiary facility, within two hours. Only 28.2% could reach any secondary facility within one hour, 0% for the government secondary facility. Community household-reported travel time exceeded GIS-estimated travel time. The proportionality constant was 1.25 (95%CI 1.21-1.30) for the closest facility, 1.28 (95%CI 1.23-1.34) for the preferred facility, 1.45 (95%CI 1.33-1.58) for the government secondary facility, and 2.12 (95%CI 1.84-2.41) for tertiary care. Comparing injured patient-reported with GIS-estimated travel time, the correlation coefficient was 0.25 (SE 0.047) and Cohen's kappa was 0.15 (95%CI 0.078-0.23), suggesting poor agreement.

DISCUSSION

Most households couldn't reach government secondary care within recognised thresholds indicating poor temporal access. Since GIS-estimated travel time was shorter than community-reported travel time, the true proportion may be lower still. GIS derived estimates of population emergency care access in similar contexts should be interpreted accordingly.

Tale of 22 cities: utilisation patterns and content of maternal care in large African cities

Introduction

Globally, the majority of births happen in urban areas. Ensuring that women and their newborns benefit from a complete package of high-quality care during pregnancy, childbirth and the postnatal period present specific challenges in large cities. We examine health service utilisation and content of care along the maternal continuum of care (CoC) in 22 large African cities.

Methods

We analysed data from the most recent Demographic and Health Survey (DHS) since 2013 in any African country with at least one city of ≥1 million inhabitants in 2015. Women with live births from survey clusters in the most populous city per country were identified. We analysed 17 indicators capturing utilisation, sector and level of health facilities and content of three maternal care services: antenatal care (ANC), childbirth care and postnatal care (PNC), and a composite indicator capturing completion of the maternal CoC. We developed a categorisation of cities according to performance on utilisation and content within maternal CoC.

Results

The study sample included 25 326 live births reported by 19 217 women. Heterogeneity in the performance in the three services was observed across cities and across the three services within cities. ANC utilisation was high (>85%); facility-based childbirth and PNC ranged widely, 77%–99% and 29%–94%, respectively. Most cities showed inconsistent levels of utilisation and content across the maternal CoC, Cotonou and Accra showed relatively best and Nairobi and Ndjamena worst performance.

Conclusion

This exploratory analysis showed that many DHS can be analysed on the level of large African cities to provide actionable information about the utilisation and content of the three maternal health services. Our comparative analysis of 22 cities and proposed typology of best and worst-performing cities can provide a starting point for extracting lessons learnt and addressing critical gaps in maternal health in rapidly urbanising contexts.

Assessing Trauma Center Accessibility for Healthcare Equity Using an Anti-Covering Approach

Motor vehicle accidents are one of the most prevalent causes of traumatic injury in patients needing transport to a trauma center. Arrival at a trauma center within an hour of the accident increases a patient's chances of survival and recovery. However, not all vehicle accidents in Tennessee are accessible to a trauma center within an hour by ground transportation. This study uses the anti-covering location problem (ACLP) to assess the current placement of trauma centers and explore optimal placements based on the population distribution and spatial pattern of motor vehicle accidents in 2015 through 2019 in Tennessee. The ACLP models seek to offer a method of exploring feasible scenarios for locating trauma centers that intend to provide accessibility to patients in underserved areas who suffer trauma as a result of vehicle accidents. The proposed ACLP approach also seeks to adjust the locations of trauma centers to reduce areas with excessive service coverage while improving coverage for less accessible areas of demand. In this study, three models are prescribed for finding optimal locations for trauma centers: (a) TraCt: ACLP model with a geometric approach and weighted models of population, fatalities, and spatial fatality clusters of vehicle accidents; (b) TraCt-ESC: an extended ACLP model mitigating excessive service supply among trauma center candidates, while expanding services to less served areas for more beneficiaries using fewer facilities; and (c) TraCt-ESCr: another extended ACLP model exploring the optimal location of additional trauma centers.

Hospital Site Suitability Assessment Using Three Machine Learning Approaches: Evidence from the Gaza Strip in Palestine

Palestinian healthcare institutions face difficulties in providing effective service delivery, particularly in times of crisis. Problems arising from inadequate healthcare service delivery are traceable to issues such as spatial coverage, emergency response time, infrastructure, and manpower. In the Gaza Strip, specifically, there is inadequate spatial distribution and accessibility to healthcare facilities due to decades of conflicts. This study focuses on identifying hospital site suitability areas within the Gaza Strip in Palestine. The study aims to find an optimal solution for a suitable hospital location through suitability mapping using relevant environmental, topographic, and geodemographic parameters and their variable criteria. To find the most significant parameters that reduce the error rate and increase the efficiency for the suitability analysis, this study utilized machine learning methods. Identification of the most significant parameters (conditioning factors) that influence a suitable hospital location was achieved by employing correlation-based feature selection (CFS) with the search algorithm (greedy stepwise). Thus, the suitability map of potential hospital sites was modeled using a support vector machine (SVM), multilayer perceptron (MLP), and linear regression (LR) models. The results of the predicted sites were validated using CFS cross-validation and the receiver operating characteristic (ROC) curve metrics. The CFS analysis shows very high correlations with R2 values of 0.94, 0. 93, and 0.75 for the SVM, MLP, and LR models, respectively. Moreover, based on areas under the ROC curve, the MLP model produced a prediction accuracy of 84.90%, SVM of 75.60%, and LR of 64.40%. The findings demonstrate that the machine learning techniques used in this study are reliable, and therefore are a promising approach for assessing a suitable location for hospital sites for effective health delivery planning and implementation.

Disparities in Healthcare Services and Spatial Assessments of Mobile Health Clinics in the Border Regions of Thailand

Reducing the disparities in healthcare access is one of the important goals in healthcare services and is significant for national health. However, measuring the complexity of access in truly underserved areas is the critical step in designing and implementing healthcare policy to improve those services and to provide additional support. Even though there are methods and tools for modeling healthcare accessibility, the context of data is challenging to interpret at the local level for targeted program implementation due to its complexity. Therefore, the purpose of this study is to develop a concise and context-specific methodology for assessing disparities for a remote province in Thailand to assist in the development and expansion of the efficient use of additional mobile health clinics. We applied the geographic information system (GIS) methodology with the travel time-based approach to visualize and analyze the concealed information of spatial data in the finer analysis resolution of the study area, which was located in the border region of the country, Ubon Ratchathani, to identify the regional differences in healthcare allocation. Our results highlight the significantly inadequate level of accessibility to healthcare services in the regions. We found that over 253,000 of the population lived more than half an hour away from a hospital. Moreover, the relationships of the vulnerable residents and underserved regions across the province are underlined in the study and substantially discussed in terms of expansion of mobile health delivery to embrace the barrier of travel duration to reach healthcare facilities. Accordingly, this research study addresses regional disparities and provides valuable references for governmental authorities and health planners in healthcare strategy design and intervention to minimize the inequalities in healthcare services.

An assessment of geographical access and factors influencing travel time to emergency obstetric care in the urban state of Lagos, Nigeria

Previous efforts to estimate the travel time to comprehensive emergency obstetric care (CEmOC) in low- and middle-income countries (LMICs) have either been based on spatial models or self-reported travel time, both with known inaccuracies. The study objectives were to estimate more realistic travel times for pregnant women in emergency situations using Google Maps, determine system-level factors that influence travel time and use these estimates to assess CEmOC geographical accessibility and coverage in Lagos state, Nigeria. Data on demographics, obstetric history and travel to CEmOC facilities of pregnant women with an obstetric emergency, who presented between 1st November 2018 and 31st December 2019 at a public CEmOC facility were collected from hospital records. Estimated travel times were individually extracted from Google Maps for the period of the day of travel. Bivariate and multivariate analyses were used to test associations between travel and health system-related factors with reaching the facility >60 minutes. Mean travel times were compared and geographical coverage mapped to identify ‘hotspots’ of predominantly >60 minutes travel to facilities. For the 4005 pregnant women with traceable journeys, travel time ranges were 2–240 minutes (without referral) and 7–320 minutes (with referral). Total travel time was within the 60 and 120 minute benchmark for 80 and 96% of women, respectively. The period of the day of travel and having been referred were significantly associated with travelling >60 minutes. Many pregnant women living in the central cities and remote towns typically travelled to CEmOC facilities around them. We identified four hotspots from which pregnant women travelled >60 minutes to facilities. Mean travel time and distance to reach tertiary referral hospitals were significantly higher than the secondary facilities. Our findings suggest that actions taken to address gaps need to be contextualized. Our approach provides a useful guide for stakeholders seeking to comprehensively explore geographical inequities in CEmOC access within urban/peri-urban LMIC settings.

Addressing the global snakebite crisis with geo-spatial analyses - Recent advances and future direction

Venomous snakebite is a neglected tropical disease that annually leads to hundreds of thousands of deaths or long-term physical and mental ailments across the developing world. Insufficient data on spatial variation in snakebite risk, incidence, human vulnerability, and accessibility of medical treatment contribute substantially to ineffective on-ground management. There is an urgent need to collect data, fill knowledge gaps and address on-ground management problems. The use of novel, and transdisciplinary approaches that take advantage of recent advances in spatio-temporal models, 'big data', high performance computing, and fine-scale spatial information can add value to snakebite management by strategically improving our understanding and mitigation capacity of snakebite. We review the background and recent advances on the topic of snakebite related geospatial analyses and suggest avenues for priority research that will have practical on-ground applications for snakebite management and mitigation. These include streamlined, targeted data collection on snake distributions, snakebites, envenomings, venom composition, health infrastructure, and antivenom accessibility along with fine-scale models of spatio-temporal variation in snakebite risk and incidence, intraspecific venom variation, and environmental change modifying human exposure. These measures could improve and 'future-proof' antivenom production methods, antivenom distribution and stockpiling systems, and human-wildlife conflict management practices, while simultaneously feeding into research on venom evolution, snake taxonomy, ecology, biogeography, and conservation.

"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.

Modelling geographical accessibility to urban centres in Kenya in 2019

BACKGROUND

Access to major services, often located in urban centres, is key to the realisation of numerous Sustainable Development Goals (SDGs). In Kenya, there are no up-to-date and localised estimates of spatial access to urban centres. We estimate the travel time to urban centres and identify marginalised populations for prioritisation and targeting.

METHODS

Urban centres were mapped from the 2019 Kenya population census and combined with spatial databases of road networks, elevation, land use and travel barriers within a cost-friction algorithm to compute travel time. Seven travel scenarios were considered: i) walking only (least optimistic), ii) bicycle only, iii) motorcycle only, iv) vehicle only (most optimistic), v) walking followed by motorcycle transport, vi) walking followed by vehicle transport, and vii) walking followed by motorcycle and then vehicle transport (most pragmatic). Mean travel time, and proportion of the population within 1-hour and 2-hours of the urban centres were summarized at sub-national units (counties) used for devolved planning. Inequities were explored and correlations between the proportion of the population within 1-hour of an urban centre and ten SDG indicators were computed.

RESULTS

A total of 307 urban centres were digitised. Nationally, the mean travel time was 4.5-hours for the walking-only scenario, 1.0-hours for the vehicle only (most optimistic) scenario and 1.5-hours for the walking-motorcycle-vehicle (most pragmatic) scenario. Forty-five per cent (21.3 million people) and 87% (41.6 million people) of Kenya's population resided within 1-hour of the nearest urban centre for the least optimistic and most pragmatic scenarios respectively. Over 3.2 million people were considered marginalised or living outside the 2-hour threshold in the pragmatic scenario, 16.0 million Kenyans for walking only, and 2.2 million for the most optimistic scenario. County-level spatial access was highly heterogeneous ranging between 8%-100% and 32%-100% of people within the 1-hour threshold for the least and most optimistic scenarios, respectively. Counties in northern and eastern parts of Kenya were generally most marginalised. The correlation coefficients for nine SDG indicators ranged between 0.45 to 0.78 and were statistically significant.

CONCLUSION

Travel time to urban centres in Kenya is heterogeneous. Therefore, marginalised populations should be prioritised during resource allocation and policies should be formulated to enhance equitable access to public services and opportunities in urban areas.

An integrated analysis of spatial access to the three-tier healthcare delivery system in China: a case study of Hainan Island

BACKGROUND

Access to healthcare is critical for the implementation of Universal Health Coverage. With the development of healthcare insurance systems around the world, spatial impedance to healthcare institutions has attracted increasing attention. However, most spatial access methodologies have been developed in Western countries, whose healthcare systems are different from those in Low- and Middle-Income Countries (LMICs).

METHODS

Hainan Island was taken as an example to explore the utilization of modern spatial access techniques under China's specialized Three-Tier Health Care Delivery System. Healthcare institutions were first classified according to the three tiers. Then shortest travel time was calculated for each institution's tier, overlapped to identify eight types of multilevel healthcare access zones. Spatial access to doctors based on the Enhanced Two-Step Floating Catchment Area Method was also calculated.

RESULTS

On Hainan Island, about 90% of the population lived within a 60-min service range for Tier 3 (hospital) healthcare institutions, 80% lived within 30 min of Tier 2 (health centers), and 75% lived within 15 min of Tier 1 (clinics). Based on local policy, 76.36% of the population living in 48.52% of the area were able to receive timely services at all tiers of healthcare institutions. The weighted average access to doctors was 2.31 per thousand residents, but the regional disparity was large, with 64.66% being contributed by Tier 3 healthcare institutions.

CONCLUSION

Spatial access to healthcare institutions on Hainan Island was generally good according to travel time and general abundance of doctors, but inequity between regions and imbalance between different healthcare institution tiers exist. Primary healthcare institutions, especially in Tier 2, should be strengthened.

First Description of a Helicopter-Borne ECPR Team for Remote Refractory Out-of-Hospital Cardiac Arrest

Introduction: Access time to extracorporeal cardiopulmonary resuscitation (ECPR) refractory out of hospital cardiac arrest (OHCA) is a crucial factor. In our region, some patients are not eligible to this treatment due to the impossibility to reach the hospital with reasonable delay (ideally 60 min). In order to increase accessibility for patients far from ECPR centers, we developed a helicopter-borne ECPR-team which is sent out to the patient for ECPR implementation on the scene of the OHCA.Methods: We conducted a retrospective monocentric study to evaluate this strategy. The team is triggered by the local emergency medical service and heliborne on the site of the OHCA. All consecutive patients implemented with ECPR by our heliborne ECPR team from January 2014 to December 2017 were included. We analyzed usual CA characteristics, different times (no-flow, low-flow, time between OHCA and dispatch…), and patient outcome.Results: During this 4-year study period, 33 patients were included. Mean age was 43.9 years. Mean distance from the ECPR-team base to OHCA location was 41 km. Mean low-flow time was 110 minutes. Five patients survived with good neurological outcome; 6 patients developed brain death and became organ donors.Conclusion: These results show the possibility to make ECPR accessible for patients far from ECPR centers. Survival rate is non negligible, especially in the absence of therapeutic alternative. An earlier trigger of the ECPR-team could reduce the low-flow time and probably increase survival. This strategy improves equity of access to ECPR and needs to be confirmed by further studies.

Analysis of Location Selection of Public Service Facilities Based on Urban Land Accessibility

Urbanization has been a flourishing process in a wide range of developing countries. The planning and construction of public service facilities is a crucial component of this process. Existing planning methods of public service facilities focused on macroscopic indicators like population and GDP. In this way, accessibility and transportation conditions were neglected. Four typical counties in China were selected as samples where travel surveys and questionnaire surveys on public service facilities were conducted. Taking education and medical care as representative public service facilities, this study used geographic information processing to connect the locations of public service facilities at all levels with the urban land accessibility. Then, analysis of variance was used to obtain correlations between the level of public service facilities and the urban land accessibility. The results showed that the urban land accessibility of locations of public service facilities follows a normal distribution. Categories of facilities showed significant difference on urban land accessibility. Therefore, intervals of urban land accessibility of locations of public service facilities within one standard deviation from the mean were constructed by category. These intervals built a connection between transportation conditions with locations of public service facilities. Corresponding relation of carbon emission of facility-related trips and urban land accessibility was established as an example of an application. Carbon emissions caused by facility-related trips can be reduced by locating facilities at locations with appropriate urban land accessibility.

Travel time and perinatal mortality after emergency caesarean sections: an evaluation of the 2-hour proximity indicator in Sierra Leone

INTRODUCTION

Longer travel times are associated with increased adverse maternal and perinatal outcomes. Geospatial modelling has been increasingly used to estimate geographic proximity in emergency obstetric care. In this study, we aimed to assess the correlation between modelled and patient-reported travel times and to evaluate its clinical relevance.

METHODS

Women who delivered by caesarean section in nine hospitals were followed up with home visits at 1 month and 1 year. Travel times between the location before the delivery and the facility where caesarean section was performed were estimated, based on two models (model I Ouma et al; model II Munoz et al). Patient-reported and modelled travel times were compared applying a univariable linear regression analysis, and the relation between travel time and perinatal mortality was assessed.

RESULTS

The median reported travel time was 60 min, compared with 13 and 34 min estimated by the two models, respectively. The 2-hour access threshold correlated with a patient-reported travel time of 5.7 hours for model I and 1.8 hours for model II. Longer travel times were associated with transport by boat and ambulance, visiting one or two facilities before reaching the final facility, lower education and poverty. Lower perinatal mortality was found both in the group with a reported travel time of 2 hours or less (193 vs 308 per 1000 births, p<0.001) and a modelled travel time of 2 hours or less (model I: 209 vs 344 per 1000 births, p=0.003; model II: 181 vs 319 per 1000 births, p<0.001).

CONCLUSION

The standard model, used to estimate geographical proximity, consistently underestimated the travel time. However, the conservative travel time model corresponded better to patient-reported travel times. The 2-hour threshold as determined by the Lancet Commission on Global Surgery, is clinically relevant with respect to reducing perinatal death, not a clear cut-off.

Modelling improved efficiency in healthcare referral systems for the urban poor using a geo-referenced health facility data: the case of Sylhet City Corporation, Bangladesh

Background

An effective referral system is critical to ensuring access to appropriate and timely healthcare services. In pluralistic healthcare systems such as Bangladesh, referral inefficiencies due to distance, diversion to inappropriate facilities and unsuitable hours of service are common, particularly for the urban poor. This study explores the reported referral networks of urban facilities and models alternative scenarios that increase referral efficiency in terms of distance and service hours.

Methods

Road network and geo-referenced facility census data from Sylhet City Corporation were used to examine referral linkages between public, private and NGO facilities for maternal and emergency/critical care services, respectively. Geographic distances were calculated using ArcGIS Network Analyst extension through a “distance matrix” which was imported into a relational database. For each reported referral linkage, an alternative referral destination was identified that provided the same service at a closer distance as indicated by facility geo-location and distance analysis. Independent sample t-tests with unequal variances were performed to analyze differences in distance for each alternate scenario modelled.

Results

The large majority of reported referrals were received by public facilities. Taking into account distance, cost and hours of service, alternative scenarios for emergency services can augment referral efficiencies by 1.5–1.9 km (p < 0.05) compared to 2.5–2.7 km in the current scenario. For maternal health services, modeled alternate referrals enabled greater referral efficiency if directed to private and NGO-managed facilities, while still ensuring availability after working-hours. These referral alternatives also decreased the burden on Sylhet City’s major public tertiary hospital, where most referrals were directed. Nevertheless, associated costs may be disadvantageous for the urban poor.

Conclusions

For both maternal and emergency/critical care services, significant distance reductions can be achieved for public, NGO and private facilities that avert burden on Sylhet City’s largest public tertiary hospital. GIS-informed analyses can help strengthen coordination between service providers and contribute to more effective and equitable referral systems in Bangladesh and similar countries.

Spatial access inequities and childhood immunisation uptake in Kenya

BACKGROUND

Poor access to immunisation services remains a major barrier to achieving equity and expanding vaccination coverage in many sub-Saharan African countries. In Kenya, the extent to which spatial access affects immunisation coverage is not well understood. The aim of this study was to quantify spatial accessibility to immunising health facilities and determine its influence on immunisation uptake in Kenya while controlling for potential confounders.

METHODS

Spatial databases of immunising facilities, road network, land use and elevation were used within a cost friction algorithim to estimate the travel time to immunising health facilities. Two travel scenarios were evaluated; (1) Walking only and (2) Optimistic scenario combining walking and motorized transport. Mean travel time to health facilities and proportions of the total population living within 1-h to the nearest immunising health facility were computed. Data from a nationally representative cross-sectional survey (KDHS 2014), was used to estimate the effect of mean travel time at survey cluster units for both fully immunised status and third dose of diphtheria-tetanus-pertussis (DPT3) vaccine using multi-level logistic regression models.

RESULTS

Nationally, the mean travel time to immunising health facilities was 63 and 40 min using the walking and the optimistic travel scenarios respectively. Seventy five percent of the total population were within one-hour of walking to an immunising health facility while 93% were within one-hour considering the optimistic scenario. There were substantial variations across the country with 62%(29/47) and 34%(16/47) of the counties with < 90% of the population within one-hour from an immunising health facility using scenarios 1 and 2 respectively. Travel times > 1-h were significantly associated with low immunisation coverage in the univariate analysis for both fully immunised status and DPT3 vaccine. Children living more than 2-h were significantly less likely to be fully immunised [AOR:0.56(0.33-0.94) and receive DPT3 [AOR:0.51(0.21-0.92) after controlling for household wealth, mother's highest education level, parity and urban/rural residence.

CONCLUSION

Travel time to immunising health facilities is a barrier to uptake of childhood vaccines in regions with suboptimal accessibility (> 2-h). Strategies that address access barriers in the hardest to reach communities are needed to enhance equitable access to immunisation services in Kenya.

Epidemiological profile and mapping geographical distribution of road traffic accidents reported to a tertiary care hospital, Mangaluru using quantum geographic information system (QGIS)

Background:

The worldwide annual average of road traffic accident (RTA) is approximately 7,00,000 and out of that 10% occur in India. It is estimated that in India, by 2020 RTA would have its fatal effect on about 5,50,000 people annually. This study was conducted to describe the epidemiological profile and spatial distribution of RTAs using quantum geographic information system (QGIS) software reported to a tertiary care hospital in Mangaluru.

Methods:

It was a record based descriptive study conducted in a tertiary care hospital of Mangaluru. The complete enumeration of all RTAs reported to Yenepoya Medical College Hospital (YMCH) during January 2018 to June 2018 was followed. QGIS software was used to depict spatial distribution of the road traffic accident on open street map.

Results:

A total of 180 cases of RTA was reported to the hospital during the study period, of which 86.1% were males. The mean age of the study participants was 33.99 years. The lower limb was the most common site of injury (48.3%) and fractures were the most common type of injury (55.6%). As per the type of RTA majority (55.6%) was motorbike accidents and drivers (47.8%) were the most common RTA victims. Predominantly RTAs occurred during evening hours of the day (40%). QGIS plotting revealed clustering of RTAs in Dakshina Kannada district, North Karnataka and neighboring districts of Kerala.

Conclusion:

QGIS can be used at the health care system level as an important tool to plan preventive measures and early intervention measures at the site of RTA.