en Year joined GFF
2017
Investment Case timeframe
2017-2021
World Bank co-financed project effective
2018
World Bank co-financed project effective
2019

Core RMNCAH-N Impact Indicators

The 8 GFF core impact indicators reflect updates aligned with the in-country survey schedule which optimally occurs once every three to five years to determine population-based changes in important health and nutrition outcomes. These indicators are core to the GFF Logic Model, to reflect impact of aligned interventions over time.  Collected by governments and development partners, these indicators are also used to monitor the Every Woman Every Child Initiative and the 2030 Sustainable Development Goals (SDGs) for RMNCAH-N. The country survey data includes Demographic Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS), which are funded by domestic resources as well as by the World Health Organization (WHO), UNICEF, USAID and other multi- and bilateral organizations. The Covid-19 pandemic forced several countries to cancel or re-schedule plans for survey data collection in early 2020 to early 2022.

CORE RMNCAH-N IMPACT INDICATORS
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The GFF highlights progress between the two most recent point estimates from population-based surveys approved by countries.  The timing of the data points is dependent on when survey data are available, which introduces lags.  In addition, it has been demonstrated that stillbirths tend to be under-reported in population based surveys1.  For many of the indicators highlighted in this table, annual estimates are produced through global processes.  The globally produced estimates can be found through the following sites:

Core Health Financing Indicators

The six GFF core health financing indicators track changes to country budget and expenditures with a focus on health spending, to monitor the expected impact of increasing the total volume and value of funding allocated to health and nutrition. The GFF partnership supports financing reforms by engaging with ministries of finance and ministries of health to strengthen mobilization of domestic resources as well as allocative and technical efficiency. These indicators are tracked through country-specific data sources such as BOOST, NHA, and budget reports. Expenditure data are tracked through the Global Health Expenditure Database (GHED), for which data are available through the end of 2018. Through measurement of budgets and expenditures, the GFF partnership aims to accelerate the expansion of interventions that are high-impact, cost-effective, affordable, and feasible to accelerate progress on universal health coverage and in achieving SDG targets.

CORE HEALTH FINANCING INDICATORS
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Survey and Estimated RMNCAH-N Coverage

The RMNCAH-N coverage data includes a standard set of 9 RMNCAH-N coverage indicators from available population-based surveys from 2010 to the most recent available survey. These indicators show progress towards key goals across maternal, child, and adolescent health and nutrition outcomes. Additional key nutrition-specific and/or education-specific coverage indicators are presented for countries where the GFF co-finances a nutrition-focused World Bank project or where education is a strong focus of the IC. 

The RMNCAH-N coverage data are sourced from the most recent available population-based surveys. Data on immunization are presented from the WHO/UNICEF joint reporting process and recent population-based surveys. 

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Population-Based Survey Coverage Indicators
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Resource Mapping

Resource mapping is a key component of the GFF approach. The resource mapping exercise helps countries assess funding gaps, align donor and government resources, and improve the efficiency and equity of health spending. Resource mapping data for each country varies based on whether countries have completed one or more resource mapping exercises.

The MoH of Mauritania has conducted a RMET with the support of GFF. It shows that in 2021, total financing amounted to 6.05 billion MRU, which represents about 2/3 from the public budget and 1/3 from development partners. The funding gap for the new national health strategy is estimated at MRU 145 million in 2021. Out of the four pillars in the national health strategy, the majority of external funding is allocated to Axis 1) Accelerating the reduction of maternal, neonatal and infant/child mortality and Axis 4) Strengthening the pillars of the system to achieve UHC. Within Axis 1 there seems to be an overfunding of maternal and neonatal health in comparison with child health.

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Resource Mapping
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Monitoring The Country-led Process

The GFF Logic Model highlights key elements of a GFF co-financed country-led process that contribute to the expected impact of improved RMNCAH-N outcomes over time. The GFF has developed a core set of indicators to monitor implementation of the GFF approach, considered as inputs and activities in the model, that emphasize prioritization and alignment to capitalize on efficiencies to improve transparency and accountability as well as health outcomes. Process monitoring includes tracking investment case development, country stakeholder engagement, health financing and the inclusion of gender and equity approaches.

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Monitoring The Country-led Process
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Implementation Progress

The data in this section is provided for a selection of indicators from the Investment Case Results Framework, Health Financing priorities, and the World Bank Project as applicable. Please select indicators from the dropdown menu to view the data for each indicator. Where subnational data is available, the map will display subnational trends over time or the latest data available. Hovering over the map will display additional data for the select indicator. Clicking on a region will add it to the chart on the right. All data, including source information, may be downloaded by selecting the arrow to the right of the indicator dropdown menu.

Implementation Progress
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* National data only.
Source:
Note: Levels of quality and completeness of data from national HMIS systems vary substantially across and within countries. The GFF is working closely with partner countries and other technical partners to improve the quality and completeness of national HMIS systems and other key country-led data systems.