Consequences of geographical accessibility to post-exposure treatment for rabies and snakebite in Africa: a mini review.

Introduction: Rabies and snakebite envenoming are two zoonotic neglected tropical diseases (NTDs) transmitted to humans by animal bites, causing each year around 179,000 deaths and are most prevalent in Asia and Africa. Improving geographical accessibility to treatment is crucial in reducing the time from bite to treatment. This mini review aims to identify and synthesize recent studies on the consequences of distance and travel time on the victims of these diseases in African countries, in order to discuss potential joint approaches for health system strengthening targeting both diseases. Methods: A literature review was conducted separately for each disease using Pubmed, Google Scholar, and snowball searching. Eligible studies, published between 2017 and 2022, had to discuss any aspect linked to geographical accessibility to treatments for either disease in Africa. Results: Twenty-two articles (8 on snakebite and 14 on rabies) were eligible for data extraction. No study targeted both diseases. Identified consequences of low accessibility to treatment were classified into 6 categories: (1) Delay to treatment; (2) Outcome; (3) Financial impacts; (4) Under-reporting; (5) Compliance to treatment, and (6) Visits to traditional healers. Discussion and conclusion: Geographical access to treatment significantly influences the burden of rabies and snakebite in Africa. In line with WHO's call for integrating approaches among NTDs, there are opportunities to model disease hotspots, assess population coverage, and optimize geographic access to care for both diseases, possibly jointly. This could enhance the management of these NTDs and contribute to achieving the global snakebite and rabies roadmaps by 2030.

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.

Estimating the Carbon Footprint of Healthcare in the Canton of Geneva and Reduction Scenarios for 2030 and 2040.

Switzerland, a wealthy country, has a cutting-edge healthcare system, yet per capita, it emits over one ton of CO2, ranking among the world's most polluting healthcare systems. To estimate the carbon footprint of the healthcare system of Geneva's canton, we collected raw data on the activities of its stakeholders. Our analysis shows that when excluding medicines and medical devices, hospitals are the main greenhouse gas emitter by far, accounting for 48% of the healthcare system's emission, followed by nursing homes (20%), private practice (18%), medical analysis laboratories (7%), dispensing pharmacies (4%), the homecare institution (3%), and the ambulance services (<1%). The most prominent emission items globally are medicines and medical devices by far, accounting for 59%, followed by building operation (19%), transport (11%), and catering (4%), among others. To actively reduce Geneva's healthcare carbon emissions, we propose direct and indirect measures, either with an immediate impact or implementing systemic changes concerning medicine prescription, building heating and cooling, low-carbon means of transport, less meaty diets, and health prevention. This study, the first of its kind in Switzerland, deciphers where most of the greenhouse gas emissions arise and proposes action levers to pave the way for ambitious emission reduction policies. We also invite health authorities to engage pharmaceutical and medical suppliers in addressing their own responsibilities, notably through the adaptation of procurement processes and requirements.

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.

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.

[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.

Vulnerability to snakebite envenoming and access to healthcare in the Terai region of Nepal: a geospatial analysis.

Background: Snakebite envenoming is a neglected tropical disease that mainly affects poor populations in rural areas. In hyperendemic regions, prevention could partially reduce the constant risk, but the population still needs timely access to adequate treatment. In line with WHO's snakebite roadmap, we aim to understand snakebite vulnerability through modelling of risk and access to treatment, and propose plausible solutions to optimise resource allocation. Methods: We combined snakebite-risk distribution rasters with travel-time accessibility analyses for the Terai region of Nepal, considering three vehicle types, two seasons, two snakebite syndromes, and uncertainty intervals. We proposed localised and generalised optimisation scenarios to improve snakebite treatment coverage for the population, focusing on the neurotoxic syndrome. Findings: In the Terai, the neurotoxic syndrome is the main factor leading to high snakebite vulnerability. For the most common scenario of season, syndrome, and transport, an estimated 2.07 (15.3%) million rural people fall into the high vulnerability class. This ranges between 0.3 (2.29%) and 6.8 (50.43%) million people when considering the most optimistic and most pessimistic scenarios, respectively. If all health facilities treating snakebite envenoming could optimally treat both syndromes, treatment coverage of the rural population could increase from 65.93% to 93.74%, representing a difference of >3.8 million people. Interpretation: This study is the first high-resolution analysis of snakebite vulnerability, accounting for uncertainties in both risk and travel speed. The results can help identify populations highly vulnerable to snakebite envenoming, optimise resource allocation, and support WHO's snakebite roadmap efforts. Funding: Swiss National Science Foundation.

Present and Future Drinking Water Security and Its Impacts on Maternities: A Multi-Scale Assessment of Sudan.

Adequate access to drinking water for hydration and hygiene depends on many factors. We developed the Drinking Water Security Index (DWSI) to assess relative multifactorial drinking water security at different spatial and temporal scales. DWSI is a function of four key indicators of drinking water security: water quality, water accessibility, water continuity, and water availability. We built DWSI with a total of 10 variables and applied the new index in Sudan to assess historical and future drinking water security at state, local, and maternity levels. Analyses at the state level found that the Red Sea and River Nile states are most vulnerable, with the lowest DWSI for both historical and future periods. The 1 km2 pixel level analysis shows large differences in water security within the major states. Analyses at the maternity level showed that nearly 18.97 million people are affected by the 10% of maternities with the lowest DWSI, a number projected to increase by 60% by 2030. Current and future DWSI of maternities providing Emergency Obstetric and Newborn Care was assessed to identify those where urgent action is needed to ensure quality health care in water-secure conditions. This work provides useful information for stakeholders in the health and drinking water sectors in Sudan, to improve public health, reduce preventable mortality, and make the population more resilient to projected environmental changes.

Balancing Public & Economic Health in Japan during the COVID-19 Pandemic: A Descriptive Analysis.

Despite loose restrictions and a low mortality rate due to COVID-19, Japan faced the challenge of stabilizing its economy during the pandemic. Here, we analyzed how the Japanese government attempted to maintain a balance between the health of the population and the health of the economy. We used a mix of quantitative data, information from policy documents, and news agency publications. Features of the Japanese government's handling of the pandemic include the lack of constitutional authority to enforce a lockdown, the laxer restrictions compared with other countries in which citizens were advised only to exercise self-restraint and avoid close social contact, and the existence of expert panels that had only an advisory role. Our findings address the slow initial response of the government, which feared that the 2020 Tokyo Olympics would be canceled, and the increased testing when the Olympics were postponed, as well as the expansion of vaccination efforts after the Olympics. In addition, there was a targeted campaign to promote national travel to increase economic revenue in the tourism sector, but this led to an increase in COVID-19 cases.

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.

Combining school-catchment area models with geostatistical models for analysing school survey data from low-resource settings: Inferential benefits and limitations.

School-based sampling has been used to inform targeted responses for malaria and neglected tropical diseases. Standard geostatistical methods for mapping disease prevalence use the school location to model spatial correlation, which is questionable since exposure to the disease is more likely to occur in the residential location. In this paper, we propose to overcome the limitations of standard geostatistical methods by introducing a modelling framework that accounts for the uncertainty in the location of the residence of the students. By using cost distance and cost allocation models to define spatial accessibility and in absence of any information on the travel mode of students to school, we consider three school catchment area models that assume walking only, walking and bicycling and, walking and motorized transport. We illustrate the use of this approach using two case studies of malaria in Kenya and compare it with the standard approach that uses the school locations to build geostatistical models. We argue that the proposed modelling framework presents several inferential benefits, such as the ability to combine data from multiple surveys some of which may also record the residence location, and to deal with ecological bias when estimating the effects of malaria risk factors. However, our results show that invalid assumptions on the modes of travel to school can worsen the predictive performance of geostatistical models. Future research in this area should focus on collecting information on the modes of transportation to school which can then be used to better parametrize the catchment area models.

Corrigendum to "What is the impact of snakebite envenoming on domestic animals? A nation-wide community-based study in Nepal and Cameroon" [Toxicon: X 9 (2021) 100068].

[This corrects the article DOI: 10.1016/j.toxcx.2021.100068.].

Optimising scale and deployment of community health workers in Sierra Leone: a geospatial analysis.

BACKGROUND: Little is known about strategies for optimising the scale and deployment of community health workers (CHWs) to maximise geographic accessibility of primary healthcare services. METHODS: We used data from a national georeferenced census of CHWs and other spatial datasets in Sierra Leone to undertake a geospatial analysis exploring optimisation of the scale and deployment of CHWs, with the aim of informing implementation of current CHW policy and future plans of the Ministry of Health and Sanitation. RESULTS: The per cent of the population within 30 min walking to the nearest CHW with preservice training increased from 16.1% to 80.4% between 2000 and 2015. Contrary to current national policy, most of this increase occurred in areas within 3 km of a health facility where nearly two-thirds (64.5%) of CHWs were deployed. Ministry of Health and Sanitation-defined 'easy-to-reach' and 'hard-to-reach' areas, geographic areas that should be targeted for CHW deployment, were less well covered, with 19.2% and 34.6% of the population in 2015 beyond a 30 min walk to a CHW, respectively. Optimised CHW networks in these areas were more efficiently deployed than existing networks by 22.4%-71.9%, depending on targeting metric. INTERPRETATIONS: Our analysis supports the Ministry of Health and Sanitation plan to rightsize and retarget the CHW workforce. Other countries in sub-Saharan Africa interested in optimising the scale and deployment of their CHW workforce in the context of broader human resources for health and health sector planning may look to Sierra Leone as an exemplar model from which to learn.

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.

Snakebite epidemiology in humans and domestic animals across the Terai region in Nepal: a multicluster random survey.

BACKGROUND: Each year, 2 million people worldwide are bitten by snakes, resulting in an estimated 81 000-138 000 deaths. WHO has added snakebite envenoming to the list of neglected tropical diseases, highlighting the need for stronger epidemiological evidence in endemic countries, such as Nepal. METHODS: We conducted a cross-sectional survey in villages randomly geospatially selected from aerial images from across the Nepal's Terai lowlands region (excluding towns and cities). We collected data between Nov 30, 2018 and May 7, 2019, and analysed snakebite incidence rates and outcomes in humans and domestic animals. FINDINGS: Among 63 454 human participants living in 13 879 households (249 villages), 166 were bitten by a snake over the previous 12 months; 48·8% were envenomed and 7·8% died. This corresponded to an annual crude incidence rate of 262 snakebites (adjusted incidence of 251·1 [95% CI 201·7-312·6]) and 20 deaths (22·4 [11·9-42·1]) per 100 000 people, extrapolating to 26 749-37 661 yearly bitten people and 2386-3225 deaths. Bitten people had a median age of 30 years (IQR 20-45) and with available data, 64% were female. Children younger than 15 years (n=6; 46%) and females (n=10; 77%) were disproportionately affected among the 13 people who died. The incidence was higher in the Eastern region, and mortality was higher in the Central region. Of 183 949 animals, owners reported 144 snakebites, with an annual incidence rate of 42-202 per 100 000 and mortality of 79-100%, varying by animal type. Spatial and seasonal incidence were similar in humans and in animals. INTERPRETATION: This study provides the first epidemiological estimates of snakebite envenoming in humans and domestic animals across Nepal's Terai lowlands. It was also the first to use a community-based, transdisciplinary, and One Health design. These findings call for a strengthening of preventive measures and better access to life-saving treatments. FUNDING: Swiss National Science Foundation project 315130_176271 (SNAKE-BYTE).

Assessment of the effect of snakebite on health and socioeconomic factors using a One Health perspective in the Terai region of Nepal: a cross-sectional study.

BACKGROUND: Snakebite envenoming has a substantial health and socioeconomic effect in rural communities. However, there are insufficient epidemiological and animal data, which prevents accurate assessment on the effects of snakebite. We aimed to assess the health and socioeconomic effect of snakebite using a One Health perspective. METHODS: In this cross-sectional survey-based study, we assessed the health and socioeconomic effects of snakebite data using a multicluster survey that was previously done as part of the SNAKE-BYTE project in the Terai region, Nepal. Health effect was measured in terms of disability-adjusted life years (DALYs). Livelihood losses encompassed out-of-pocket health-care expenditures, losses of productivity due to days off work, and the losses due to mortality and treatment costs in domestic animals. Mortality losses in domestic animals were also estimated as animal loss equivalents, and overall human and animal health effect expressed using modified DALYs for zoonotic disease (zDALYs). FINDINGS: We estimate an annual snakebite burden of 200 799 DALYs (95% CI 103 137-357 805), mostly due to mortality in children and women. Snakebite is estimated to lead to US$2·8 million in yearly livelihood losses associated with human and animal cases. Overall, we estimate a yearly human and animal health burden of 202 595 zDALYs (104 300-360 284). INTERPRETATION: These findings present robust evidence on the extent of snakebite's health and socioeconomic effect and emphasise the need for a One Health perspective. The results also stress how improved data collection at the community level is crucial for improved assessments of its effect. FUNDING: Swiss National Science Foundation.

Use of Physical Accessibility Modelling in Diagnostic Network Optimization: A Review.

Diagnostic networks are complex systems that include both laboratory-tested and community-based diagnostics, as well as a specimen referral system that links health tiers. Since diagnostics are the first step before accessing appropriate care, diagnostic network optimization (DNO) is crucial to improving the overall healthcare system. The aim of our review was to understand whether the field of DNO, and especially route optimization, has benefited from the recent advances in geospatial modeling, and notably physical accessibility modeling, that have been used in numerous health systems assessment and strengthening studies. All publications published in English between the journal's inception and 12 August 2021 that dealt with DNO, geographical accessibility and optimization, were systematically searched for in Web of Science and PubMed, this search was complemented by a snowball search. Studies from any country were considered. Seven relevant publications were selected and charted, with a variety of geospatial approaches used for optimization. This paucity of publications calls for exploring the linkage of DNO procedures with realistic accessibility modeling framework. The potential benefits could be notably better-informed travel times of either the specimens or population, better estimates of the demand for diagnostics through realistic population catchments, and innovative ways of considering disease epidemiology to inform DNO.

Improving the efficiency of scale-up and deployment of community health workers in Mali: A geospatial analysis.

Optimising the scale and deployment of community health workers (CHWs) is important for maximizing geographical accessibility of integrated primary health care (PHC) services. Yet little is known about approaches for doing so. We used geospatial analysis to model optimised scale-up and deployment of CHWs in Mali, to inform strategic and operational planning by the Ministry of Health and Social Development. Accessibility catchments were modelled based on travel time, accounting for barriers to movement. We compared geographic coverage of the estimated population, under-five deaths, and plasmodium falciparum (Pf) malaria cases across different hypothetical optimised CHW networks and identified surpluses and deficits of CHWs compared to the existing CHW network. A network of 15 843 CHW, if optimally deployed, would ensure that 77.3% of the population beyond 5 km of the CSCom (community health centre) and CSRef (referral health facility) network would be within a 30-minute walk of a CHW. The same network would cover an estimated 59.5% of U5 deaths and 58.5% of Pf malaria cases. As an intermediary step, an optimised network of 4 500 CHW, primarily filling deficits of CHW in the regions of Kayes, Koulikoro, Sikasso, and Ségou would ensure geographic coverage for 31.3% of the estimated population. There were no important differences in geographic coverage percentage when prioritizing CHW scale-up and deployment based on the estimated population, U5 deaths, or Pf malaria cases. Our geospatial analysis provides useful information to policymakers and planners in Mali for optimising the scale-up and deployment of CHW and, in turn, for maximizing the value-for-money of resources of investment in CHWs in the context of the country's health sector reform. Countries with similar interests in optimising the scale and deployment of their CHW workforce may look to Mali as an exemplar model from which to learn.

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.