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Transversal Component

Title: Transversal Component. 

Main Objective: Operate through the JRC’s Africa Knowledge Platform and serve as an integration engine, connecting thematic sectors and aligning the contributions of the RCoEs around a unified and coherent vision.

Specific Objectives:

  1. Ensure effective coordination of the ArcX programme through a robust and well-managed transversal mechanism;
  2. Enhance the science–policy interface by providing targeted support services that facilitate evidence-based decision-making;
  3. Strengthen knowledge circulation and collective learning across ArcX through an efficient and interoperable knowledge management mechanism;
  4. Promote inter-sectoral networking and partnership opportunities by delivering tailored support services that connect actors across thematic and regional domains.

Starting Year: 2023
Implementation Duration: 6 years

Areas of Impact:

  1. Strategic coherence;
  2. Programme efficiency;
  3. Reduced duplication;
  4. Evidence-based decisions;
  5. Policy harmonisation;
  6. Uptake of scientific insights;
  7. Knowledge circulation;
  8. Collective learning;
  9. Scaling of innovations;
  10. Innovation ecosystems;
  11. Cross-sector alliances;
  12. Private-sector + Africa–Europe cooperation

Target Groups: Regional Centers of Excellence.

ArcX Partners: See ArcX Partners card and the ArcX Partnership Map.

Component Coordinator: Agriconsulting Europe S.A. (AESA).

Scientific and Technical Support from EC - DG JRC: DG-JRC Directorate D (Sustainable Resources) Unit D6 (Nature Conservation and Observations).


Available Resources
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This layer shows the percentage of children under 6 months who are exclusively breastfed, meaning they receive only breast milk without any additional food or drink. Exclusive breastfeeding is a key determinant of child survival, growth, and development.
This layer provides estimates of the percentage of children aged 2 to 10 years (PfPR2–10) with detectable Plasmodium falciparum parasites in 2022. The estimates are generated using geostatistical models based on point prevalence surveys, routine surveillance data, and a wide range of geospatial covariates representing mosquito habitat and environmental conditions. The data are available annually from 2000 onward, covering all malaria-endemic countries, at a spatial resolution of 5 × 5 km.
This layer represents the estimated travel time (in hours) by foot to the nearest primary school. The accessibility map is generated using a well-established geospatial methodology that integrates road and rail networks, land cover, and topographic features. The resulting gridded "friction surface" represents the time required to traverse each ~1 km × 1 km pixel of Africa.
This layer represents the estimated travel time (in hours) by foot to the nearest healthcare facility. The underlying methodology is described in Weiss et al. (2020), which leverages major data collection efforts from OpenStreetMap, Google Maps, and academic sources to compile the most comprehensive global inventory of healthcare facility locations to date. The approach is based on the creation of friction surfaces that quantify the time required to traverse each ~1 km × 1 km pixel of the Earth's surface.
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.
This layer shows the percentage of children under 5 experiencing severe wasting (in 2019) — the most critical form of acute malnutrition. These children face a significantly higher risk of mortality and require immediate therapeutic support. This indicator helps prioritize emergency nutrition interventions and monitor high-risk areas in need of health and food system strengthening.
This layer shows the percentage of children under 5 years of age (in 2019) who are underweight, based on low weight-for-age. Underweight is a composite indicator capturing both chronic and acute undernutrition. It is useful for identifying vulnerable populations and informing multisectoral strategies to improve child health, food access, and caregiving practices.
This layer shows the prevalence of wasting among children under 5 years of age (in 2019), a sign of acute undernutrition indicated by low weight-for-height. Wasting reflects recent and severe weight loss, often caused by food shortage, infection, or crisis conditions. Mapping areas with high wasting rates can help target urgent humanitarian and nutrition assistance.
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.
Access to piped water reflects the availability of improved water sources directly delivered to households. This layer shows the percentage of people with access to piped water in 2017. Low coverage may signal the need for targeted interventions, potentially supported by decentralized energy systems to power water pumping and distribution.
The Armed Conflict Location & Event Data Project (ACLED) dataset is a disaggregated conflict event dataset designed for real-time monitoring and analysis. It records the specific dates, locations, actors, and types of all reported political violence and protest events to facilitate local and scale-dependant research on war patterns and processes. This layer show the ACLED data relative to the African continent recorded between 2020 and 2025. ACLED updates the dataset every Monday here.
This dataset provides estimates of the total number of under-5 children per grid cell, for Uganda. The data come from the WorldPop R2025A, version v1 release. The dataset is available in GeoTIFF format at a spatial resolution of 30 arc-seconds (approximately 1 km at the equator). All layers use the WGS84 Geographic Coordinate System.
Constrained estimates of the total number of people per spatial unit, derived from high-resolution population distribution data produced by the WorldPop Global Demographic Data project. These estimates are based on a 30-arcsecond (~1 km) resolution modeling framework and incorporate official census counts, administrative boundaries, and a suite of geospatial covariates.
The Global Gridded Relative Deprivation Index (GRDI) characterizes the relative levels of multidimensional deprivation and poverty, where a value of 100 represents the highest level of deprivation and a value of 0 the lowest. GRDI is built from sociodemographic and satellite data inputs that were spatially harmonized, indexed, and weighted into six main components to produce the final GRDI layer.
This layer shows the percentage of stunting among children under 5 years of age, a form of chronic undernutrition reflected in low height-for-age. Stunting can result from prolonged food insecurity, poor maternal health, or inadequate early childhood care. Areas with high stunting rates indicate long-term development challenges and can help guide interventions aimed at improving nutrition, health services, and water and sanitation infrastructure.