Percentage of cohort of young people three to five years older than the intended age for the last grade of upper secondary level of education who have completed that level of education. This indicator measures the potential impact of electricity on youth education, that represents a crucial pillar for the development of a country.

Percentage of children aged 6-8 that currently attends, or in the current school year attended, school. This indicator measures the potential educational impact of bringing electricity to schools; therefore, the impact of binging electricity will be higher where the educational attendance is low.

Percentage of schools in Africa reporting to have no electricity. The lower the education facilities with access to electricity the greater the potential for decentralised renewable energies to improve electricity access in these facilities and thus educational outcomes.

Poverty affects billions of people around the globe. On a daily basis, they face low wages and substandard health, education, and living standards. Because of this, poverty must be understood and approached as a multidimensional issue. The Multidimensional Poverty Index (MPI) acknowledges that poverty has many faces. The second dimension in the MIP is the Education dimension. This includes years of schooling and child school attendance. This map shows the percentage contribution of the education dimension to overall poverty. The lower percentages are shown in darker blues while the higher percentages are shown as brighter, lighter blues.

Priority areas are identified using local coefficients estimated through Geographically Weighted Regression (GWR), which measures the spatially varying relationship between access to sanitation infrastructure and education using the indicator of percentage of population with secondary education . The tool highlights locations where the local association between electricity access and the selected nutrition indicator is both negative and statistically significant. The identified areas are classified as having strong, moderate, or mild associations according to the magnitude of the local GWR coefficient. This classification helps users determine the appropriate intensity of intervention. The spatially varying coefficients therefore allow users to identify areas where limited sanitation access is most strongly associated with lower education, supporting targeted interventions, programme planning, and place-based development strategies.

Priority areas are identified using local coefficients estimated through Geographically Weighted Regression (GWR), which measures the spatially varying relationship between access to sanitation infrastructure and gender using the indicator of percentage of women with secondary education. The tool highlights locations where the local association between sanitation access and the selected gender indicator is both negative and statistically significant. The identified areas are classified as having strong, moderate, or mild associations according to the magnitude of the local GWR coefficient. This classification helps users determine the appropriate intensity of intervention. The spatially varying coefficients therefore allow users to identify areas where limited sanitation access is most strongly associated with lower women education, supporting targeted interventions, programme planning, and place-based development strategies.

Priority areas are identified using local coefficients estimated through Geographically Weighted Regression (GWR), which measures the spatially varying relationship between access to Water infrastructure and education using the indicator of percentage of population with secondary education. The tool highlights locations where the local association between access to piped water s and the selected education indicator is both negative and statistically significant. The identified areas are classified as having strong, moderate, or mild associations according to the magnitude of the local GWR coefficient. This classification helps users determine the appropriate intensity of intervention. The spatially varying coefficients therefore allow users to identify areas where limited sanitation access is most strongly associated with lower education, supporting targeted interventions, programme planning, and place-based development strategies.

Priority areas are identified using local coefficients estimated through Geographically Weighted Regression (GWR), which measures the spatially varying relationship between access to water infrastructure and gender using the indicator of percentage of women with secondary education. The tool highlights locations where the local association between access to piped water and the selected gender indicator is both negative and statistically significant. The identified areas are classified as having strong, moderate, or mild associations according to the magnitude of the local GWR coefficient. This classification helps users determine the appropriate intensity of intervention. The spatially varying coefficients therefore allow users to identify areas where limited water access is most strongly associated with lower women education, supporting targeted interventions, programme planning, and place-based development strategies.

This layer shows the percentage of people with access to any improved sanitation facility, including both piped systems (such as sewer or septic tanks) and non-piped improved options (like ventilated improved pit latrines or composting toilets), in 2017. Improved sanitation is essential for public health, reducing the spread of waterborne diseases and supporting safe and dignified living conditions. Areas with low access highlight the need for expanded basic services and targeted investments in infrastructure.

Priority areas are identified using local coefficients estimated through Geographically Weighted Regression (GWR), which measures the spatially varying relationship between access to electricity and education using the indicator of percentage of population with secondary education .
The tool highlights locations where the local association between electricity access and the selected nutrition indicator is both negative and statistically significant. In this application, priority areas are further restricted to locations where electricity access is below 80%, ensuring that the results remain relevant for policy intervention.
The identified areas are classified as having strong, moderate, or mild associations according to the magnitude of the local GWR coefficient. This classification helps users determine the appropriate intensity of intervention. The spatially varying coefficients therefore allow users to identify areas where limited electricity access is most strongly associated with higher education, supporting targeted interventions, programme planning, and place-based development strategies.

Priority areas are identified using local coefficients estimated through Geographically Weighted Regression (GWR), which measures the spatially varying relationship between access to electricity and gender using the indicator of proportion of women with secondary school. The tool highlights locations where the local association between electricity access and the selected nutrition indicator is both negative and statistically significant. In this application, priority areas are further restricted to locations where electricity access is below 80%, ensuring that the results remain relevant for policy intervention. The identified areas are classified as having strong, moderate, or mild associations according to the magnitude of the local GWR coefficient. This classification helps users determine the appropriate intensity of intervention. The spatially varying coefficients therefore allow users to identify areas where limited electricity access is most strongly associated with lower proportion of women at secondary school, supporting targeted interventions, programme planning, and place-based development strategies.

This layer shows the estimated number of deaths per 1,000 live births among children under 5 years of age (in 2017) — a key indicator of child survival and overall health system performance. High under-5 mortality rates often reflect limited access to essential health services, clean water, sanitation, and adequate nutrition. Expanding decentralized systems can play a key role in improving child survival outcomes in underserved areas.