[Improving access to maternities: a key challenge in low-resource settings]. / Améliorer l'accès aux maternités : un enjeu clé lorsque les ressources manquent.

In low- and middle-income countries, pregnant women face considerable challenges in accessing emergency obstetric and neonatal care services. Several factors contribute to this, such as insufficient availability of services, their inadequate geographical distribution, and a lack of qualified staff and infrastructure. The United Nations Population Fund, in collaboration with the University of Geneva, has deployed an innovative approach in 14 countries to optimise service quality and geographical accessibility. This approach has formed the basis for a new global indicator contributing to the reduction of maternal mortality. Calculating this indicator requires various types of data, going beyond traditional indicators, but allowing for a more comprehensive consideration of the different facets of access to services.

Dans les pays à revenu faible ou intermédiaire, les femmes enceintes sont confrontées à des défis importants pour accéder aux services obstétricaux et néonatals d'urgence. Plusieurs facteurs y contribuent, tels qu'une disponibilité insuffisante des services, leur répartition géographique inadéquate et un manque de personnel qualifié ainsi que d'infrastructure. Le Fonds des Nations Unies pour la population, en collaboration avec l'Université de Genève, a déployé dans 14 pays une approche innovante optimisant la qualité des services et l'accessibilité géographique. Elle a été la base d'un nouvel indicateur global participant à la réduction de la mortalité maternelle. Le calcul de cet indicateur requiert des données allant au-delà des indicateurs classiques, permettant une meilleure considération des différentes facettes de l'accès aux services.

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.

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.

Access to primary healthcare, which encompasses essential healthcare services and often the initial point of contact between individuals and the healthcare system, is crucial for addressing the health needs of a population. In Ethiopia, ongoing efforts to reform the primary healthcare system aim to increase geographic access to health services and improve the availability of healthcare workers. This study focuses on the Somali region of Ethiopia and finds that 65% of the population is unable to reach a health center within 1 h of walking, and none of the health centers meet national and international staffing guidelines. These results play an important role in identifying areas where mobile outreach, involving trained service providers traveling to communities with limited access to healthcare facilities, can bridge gaps in healthcare accessibility and availability. Furthermore, the findings inform the implementation of primary healthcare reforms.

Travel scenario workshops for geographical accessibility modeling of health services: A transdisciplinary evaluation study.

Introduction: Limited geographical access to quality Emergency Obstetric and Newborn Care (EmONC) is a major driver of high maternal mortality. Geographic access to EmONC facilities is identified by the global community as a critical issue for reducing maternal mortality and is proposed as a global indicator by the Ending Preventable Maternal Mortality (EPMM) initiative. Geographic accessibility models can provide insight into the population that lacks adequate access and on the optimal distribution of facilities and resources. Travel scenarios (i.e., modes and speed of transport) used to compute geographical access to healthcare are a key input to these models and should approximate reality as much as possible. This study explores strategies to optimize and harmonize knowledge elicitation practices for developing travel scenarios. Methods: Knowledge elicitation practices for travel scenario workshops (TSW) were studied in 14 African and South-Asian countries where the United Nations Population Fund supported ministries of health and governments in strengthening networks of EmONC facilities. This was done through a mixed methods evaluation study following a transdisciplinary approach, applying the four phases of the Interactive Learning and Action methodology: exploration, in-depth, integration, and prioritization and action planning. Data was collected in November 2020-June 2021 and involved scoping activities, stakeholder identification, semi-structured interviews (N = 9), an evaluation survey (N = 31), and two co-creating focus group discussions (N = 8). Results: Estimating realistic travel speeds and limited time for the workshop were considered as the largest barriers. The identified opportunities were inclusively prioritized, whereby preparation; a favorable composition of attendees; validation practices; and evaluation were anticipated to be the most promising improvement strategies, explaining their central place on the co-developed initial standard operating procedure (SOP) for future TSWs. Mostly extensive preparation-both on the side of the organization and the attendees-was anticipated to address nearly all of the identified TSW challenges. Conclusion: This study showed that the different identified stakeholders had contradicting, complementing and overlapping ideas about strategies to optimize and harmonize TSWs. Yet, an initial SOP was inclusively developed, emphasizing practices for before, during and after each TSW. This SOP is not only relevant in the context of the UNFPA EmONC development approach, but also for monitoring the newly launched EPMM indicator and even in the broader field of geographic accessibility modeling.

Constructing and validating a transferable epidemic risk index in data scarce environments using open data: A case study for dengue in the Philippines.

Epidemics are among the most costly and destructive natural hazards globally. To reduce the impacts of infectious disease outbreaks, the development of a risk index for infectious diseases can be effective, by shifting infectious disease control from emergency response to early detection and prevention. In this study, we introduce a methodology to construct and validate an epidemic risk index using only open data, with a specific focus on scalability. The external validation of our risk index makes use of distance sampling to correct for underreporting of infections, which is often a major source of biases, based on geographical accessibility to health facilities. We apply this methodology to assess the risk of dengue in the Philippines. The results show that the computed dengue risk correlates well with standard epidemiological metrics, i.e. dengue incidence (p = 0.002). Here, dengue risk constitutes of the two dimensions susceptibility and exposure. Susceptibility was particularly associated with dengue incidence (p = 0.048) and dengue case fatality rate (CFR) (p = 0.029). Exposure had lower correlations to dengue incidence (p = 0.193) and CFR (p = 0.162). Highest risk indices were seen in the south of the country, mainly among regions with relatively high susceptibility to dengue outbreaks. Our findings reflect that the modelled epidemic risk index is a strong indication of sub-national dengue disease patterns and has therefore proven suitability for disease risk assessments in the absence of timely epidemiological data. The presented methodology enables the construction of a practical, evidence-based tool to support public health and humanitarian decision-making processes with simple, understandable metrics. The index overcomes the main limitations of existing indices in terms of construction and actionability.

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.

The winding road to health: A systematic scoping review on the effect of geographical accessibility to health care on infectious diseases in low- and middle-income countries.

BACKGROUND: Geographical accessibility to healthcare is an important component of infectious disease dynamics. Timely access to health facilities can prevent disease progression and enables disease notification through surveillance systems. The importance of accounting for physical accessibility in response to infectious diseases is increasingly recognized. Yet, there is no comprehensive review of the literature available on infectious diseases in relation to geographical accessibility to care. Therefore, we aimed at evaluating the current state of knowledge on the effect of geographical accessibility to health care on infectious diseases in low- and middle-income countries. METHODS AND FINDINGS: A search strategy was developed and conducted on Web of Science and PubMed on 4 March 2019. New publications were checked until May 28, 2020. All publication dates were eligible. Data was charted into a tabular format and descriptive data analyses were carried out to identify geographical regions, infectious diseases, and measures of physical accessibility among other factors. Search queries in PubMed and Web of Science yielded 560 unique publications. After title and abstract screening 99 articles were read in full detail, from which 64 articles were selected, including 10 manually. Results of the included publications could be broadly categorized into three groups: (1) decreased spatial accessibility to health care was associated with a higher infectious disease burden, (2) decreased accessibility was associated to lower disease reporting, minimizing true understanding of disease distribution, and (3) the occurrence of an infectious disease outbreak negatively impacted health care accessibility in affected regions. In the majority of studies, poor geographical accessibility to health care was associated with higher disease incidence, more severe health outcomes, higher mortality, and lower disease reporting. No difference was seen between countries or infectious diseases. CONCLUSIONS: Currently, policy-makers and scientists rely on data collected through passive surveillance systems, introducing uncertainty on disease estimates for remote communities. Our results highlight the need for increasing integration of geographical accessibility measures in disease risk modelling, allowing more realistic disease estimates and enhancing our understanding of true disease burden. Additionally, disease risk estimates could be used in turn to optimize the allocation of health services in the prevention and detection of infectious diseases.

How geographic access to care shapes disease burden: The current impact of post-exposure prophylaxis and potential for expanded access to prevent human rabies deaths in Madagascar.

BACKGROUND: Post-exposure prophylaxis (PEP) is highly effective at preventing human rabies deaths, however access to PEP is limited in many rabies endemic countries. The 2018 decision by Gavi to add human rabies vaccine to its investment portfolio should expand PEP availability and reduce rabies deaths. We explore how geographic access to PEP impacts the rabies burden in Madagascar and the potential benefits of improved provisioning. METHODOLOGY & PRINCIPAL FINDINGS: We use spatially resolved data on numbers of bite patients seeking PEP across Madagascar and estimates of travel times to the closest clinic providing PEP (N = 31) in a Bayesian regression framework to estimate how geographic access predicts reported bite incidence. We find that travel times strongly predict reported bite incidence across the country. Using resulting estimates in an adapted decision tree, we extrapolate rabies deaths and reporting and find that geographic access to PEP shapes burden sub-nationally. We estimate 960 human rabies deaths annually (95% Prediction Intervals (PI): 790-1120), with PEP averting an additional 800 deaths (95% PI: 640-970) each year. Under these assumptions, we find that expanding PEP to one clinic per district (83 additional clinics) could reduce deaths by 19%, but even with all major primary clinics provisioning PEP (1733 additional clinics), we still expect substantial rabies mortality. Our quantitative estimates are most sensitive to assumptions of underlying rabies exposure incidence, but qualitative patterns of the impacts of travel times and expanded PEP access are robust. CONCLUSIONS & SIGNIFICANCE: PEP is effective at preventing rabies deaths, and in the absence of strong surveillance, targeting underserved populations may be the most equitable way to provision PEP. Given the potential for countries to use Gavi funding to expand access to PEP in the coming years, this framework could be used as a first step to guide expansion and improve targeting of interventions in similar endemic settings where PEP access is geographically restricted and baseline data on rabies risk is lacking. While better PEP access should save many lives, improved outreach, surveillance, and dog vaccination will be necessary, and if rolled out with Gavi investment, could catalyze progress towards achieving zero rabies deaths.

Modelling geographical accessibility to support disaster response and rehabilitation of a healthcare system: an impact analysis of Cyclones Idai and Kenneth in Mozambique.

OBJECTIVES: Modelling and assessing the loss of geographical accessibility is key to support disaster response and rehabilitation of the healthcare system. The aim of this study was therefore to estimate postdisaster travel times to functional health facilities and analyse losses in accessibility coverage after Cyclones Idai and Kenneth in Mozambique in 2019. SETTING: We modelled travel time of vulnerable population to the nearest functional health facility in two cyclone-affected regions in Mozambique. Modelling was done using AccessMod V.5.6.30, where roads, rivers, lakes, flood extent, topography and land cover datasets were overlaid with health facility coordinates and high-resolution population data to obtain accessibility coverage estimates under different travel scenarios. OUTCOME MEASURES: Travel time to functional health facilities and accessibility coverage estimates were used to identify spatial differences between predisaster and postdisaster geographical accessibility. RESULTS: We found that accessibility coverage decreased in the cyclone-affected districts, as a result of reduced travel speeds, barriers to movement, road constraints and non-functional health facilities. In Idai-affected districts, accessibility coverage decreased from 78.8% to 52.5%, implying that 136 941 children under 5 years of age were no longer able to reach the nearest facility within 2 hours travel time. In Kenneth-affected districts, accessibility coverage decreased from 82.2% to 71.5%, corresponding to 14 330 children under 5 years of age having to travel >2 hours to reach the nearest facility. Damage to transport networks and reduced travel speeds resulted in the most substantial accessibility coverage losses in both Idai-affected and Kenneth-affected districts. CONCLUSIONS: Postdisaster accessibility modelling can increase our understanding of spatial differences in geographical access to care in the direct aftermath of a disaster and can inform targeting and prioritisation of limited resources. Our results reflect opportunities for integrating accessibility modelling in early disaster response, and to inform discussions on health system recovery, mitigation and preparedness.