Dataset Information

National optimisation of accessibility to emergency obstetrical and neonatal care in Togo: a geospatial analysis.

ABSTRACT:

Objectives

Improving access to emergency obstetrical and neonatal care (EmONC) is a key strategy for reducing maternal and neonatal mortality. Access is shaped by several factors, including service availability and geographical accessibility. In 2013, the Ministry of Health (MoH) of Togo used service availability and other criteria to designate particular facilities as EmONC facilities, facilitating efficient allocation of limited resources. In 2018, the MoH further revised and rationalised this health facility network by applying an innovative methodology using health facility characteristics and geographical accessibility modelling to optimise timely access to EmONC services. This study compares the geographical accessibility of the network established in 2013 and the smaller network developed in 2018.

Design

We used data regarding travel modes and speeds, geographical barriers and topographical and urban constraints, to estimate travel times to the nearest EmONC facilities. We compared the EmONC network of 109 facilities established in 2013 with the one composed of 73 facilities established in 2018, using three travel scenarios (walking and motorised, motorcycle-taxi and walking-only).

Results

When walking and motorised travel is considered, the 2013 EmONC network covers 81% and 96.6% of the population at the 1-hour and 2-hour limit, respectively. These figures are slightly higher when motorcycle-taxis are considered (82.8% and 98%), and decreased to 34.7% and 52.3% for the walking-only scenario. The 2018 prioritised EmONC network covers 78.3% (1-hour) and 95.5% (2-hour) of the population for the walking and motorised scenario.

Conclusions

By factoring in geographical accessibility modelling to our iterative EmONC prioritisation process, the MoH was able to decrease the designated number of EmONC facilities in Togo by about 30%, while still ensuring that a high proportion of the population has timely access to these services. However, the physical access to EmONC for women unable to afford motorised transport remains inequitable.

SUBMITTER: Curtis A

PROVIDER: S-EPMC8327815 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundGhana did not meet the Millennium Development Goal 4 of reducing child mortality by two-thirds and may not meet SDG (2030). There is a need to direct scarce resources to mitigate the impact of the most important risk factors influencing high neonatal deaths. This study applied both spatial and non-spatial regression models to explore the differential impact of environmental, maternal, and child associated risk factors on neonatal deaths in Ghana.MethodsThe study relied on data from the Ghana Demographic and Health Surveys (GDHS) and the Ghana Maternal Health Survey (GMHS) conducted between 1998 and 2017 among 49,908 women of reproductive age and 31,367 children under five (GDHS-1998 = 3298, GDHS-2003 = 3844, GDHS-2008 = 2992, GDHS-2014 = 5884, GMHS-2017 = 15,349). Spatial Autoregressive Models that account for spatial autocorrelation in the data at the cluster-level and non-spatial statistical models with appropriate sampling weight adjustment were used to study factors associated with neonatal deaths, and a p-value less than 0.05 was considered statistically significant.ResultsPopulation density, multiple births, smaller household sizes, high parity, and low birth weight significantly increased the risk of neonatal deaths over the years. Among mothers who had multiple births, the risk of having neonatal deaths was approximately four times as high as the risk of neonatal deaths among mothers who had only single birth [aRR = 3.42, 95% CI: 1.63-7.17, p < 0.05]. Neonates who were perceived by their mothers to be small were at a higher risk of neonatal death compared to very large neonates [aRR = 2.08, 95% CI: 1.19-3.63, p < 0.05]. A unit increase in the number of children born to a woman of reproductive age was associated with a 49% increased risk in neonatal deaths [aRR = 1.49, 95% CI: 1.30-1.69, p < 0.05].ConclusionNeonatal mortality in Ghana remains relatively high, and the factors that predisposed children to neonatal death were birth size that were perceived to be small, low birth weight, higher parity, and multiple births. Improving pregnant women's nutritional patterns and providing special support to women who have multiple deliveries will reduce neonatal mortality in Ghana.

Project description:BackgroundIn conflict settings, data to guide humanitarian and development responses are often scarce. Although geospatial analyses have been used to estimate health-care access in many countries, such techniques have not been widely applied to inform real-time operations in protracted health emergencies. Doing so could provide a more robust approach for identifying and prioritising populations in need, targeting assistance, and assessing impact. We aimed to use geospatial analyses to overcome such data gaps in Yemen, the site of one of the world's worst ongoing humanitarian crises.MethodsWe derived geospatial coordinates, functionality, and service availability data for Yemen health facilities from the Health Resources and Services Availability Monitoring System assessment done by WHO and the Yemen Ministry of Public Health and Population. We modelled population spatial distribution using high-resolution satellite imagery, UN population estimates, and census data. A road network grid was built from OpenStreetMap and satellite data and modified using UN Yemen Logistics Cluster data and other datasets to account for lines of conflict and road accessibility. Using this information, we created a geospatial network model to deduce the travel time of Yemeni people to their nearest health-care facilities.FindingsIn 2018, we estimated that nearly 8·8 million (30·6%) of the total estimated Yemeni population of 28·7 million people lived more than 30-min travel time from the nearest fully or partially functional public primary health-care facility, and more than 12·1 million (42·4%) Yemeni people lived more than 1 h from the nearest fully or partially functional public hospital, assuming access to motorised transport. We found that access varied widely by district and type of health service, with almost 40% of the population living more than 2 h from comprehensive emergency obstetric and surgical care. We identified and ranked districts according to the number of people living beyond acceptable travel times to facilities and services. We found substantial variability in access and that many front-line districts were among those with the poorest access.InterpretationThese findings provide the most comprehensive estimates of geographical access to health care in Yemen since the outbreak of the current conflict, and they provide proof of concept for how geospatial techniques can be used to address data gaps and rigorously inform health programming. Such information is of crucial importance for humanitarian and development organisations seeking to improve effectiveness and accountability.FundingGlobal Financing Facility for Women, Children, and Adolescents Trust Fund; Development and Data Science grant; and the Yemen Emergency Health and Nutrition Project, a partnership between the World Bank, UNICEF, and WHO.