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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.

The facets of an African economy based on wildlife resources

Impacts of the COVID-19 pandemic on migration flows

Substantial crop losses occur at various stages along the postharvest value chain. Losses result from poor handling and storage practices combined with limited awareness, infrastructure, and knowledge. The African Postharvest Losses Information System (APHLIS) (www.aphlis.net) is the foremost international effort to collect, analyse and disseminate data on postharvest losses of cereal grains in sub-Saharan Africa. The cumulative % loss in weight incurred during harvesting, drying, threshing/shelling, winnowing, household-level storage, transport and market-level storage for the selected crop, location, and year is presented. Complimentary data sets are collected and used to convert this % loss into absolute loss values in tonnes, US$ and nutrients, along with the nutritional and financial impacts of these losses by province and country. Understanding the magnitude of postharvest loss, the points in the value chain where losses occur, and the causes and impacts of loss helps decision-makers formulate effective policies and invest in successful postharvest loss programmes.
Substantial crop losses occur at various stages along the postharvest value chain. Losses result from poor handling and storage practices combined with limited awareness, infrastructure, and knowledge. The African Postharvest Losses Information System (APHLIS) (www.aphlis.net) is the foremost international effort to collect, analyse and disseminate data on postharvest losses of cereal grains in sub-Saharan Africa. The cumulative % loss in weight incurred during harvesting, drying, threshing/shelling, winnowing, household-level storage, transport and market-level storage for the selected crop, location, and year is presented. Complimentary data sets are collected and used to convert this % loss into absolute loss values in tonnes, US$ and nutrients, along with the nutritional and financial impacts of these losses by province and country. Understanding the magnitude of postharvest loss, the points in the value chain where losses occur, and the causes and impacts of loss helps decision-makers formulate effective policies and invest in successful postharvest loss programmes.
Substantial crop losses occur at various stages along the postharvest value chain. Losses result from poor handling and storage practices combined with limited awareness, infrastructure, and knowledge. The African Postharvest Losses Information System (APHLIS) (www.aphlis.net) is the foremost international effort to collect, analyse and disseminate data on postharvest losses of cereal grains in sub-Saharan Africa. The cumulative % loss in weight incurred during harvesting, drying, threshing/shelling, winnowing, household-level storage, transport and market-level storage for the selected crop, location, and year is presented. Complimentary data sets are collected and used to convert this % loss into absolute loss values in tonnes, US$ and nutrients, along with the nutritional and financial impacts of these losses by province and country. Understanding the magnitude of postharvest loss, the points in the value chain where losses occur, and the causes and impacts of loss helps decision-makers formulate effective policies and invest in successful postharvest loss programmes.
Substantial crop losses occur at various stages along the postharvest value chain. Losses result from poor handling and storage practices combined with limited awareness, infrastructure, and knowledge. The African Postharvest Losses Information System (APHLIS) (www.aphlis.net) is the foremost international effort to collect, analyse and disseminate data on postharvest losses of cereal grains in sub-Saharan Africa. The cumulative % loss in weight incurred during harvesting, drying, threshing/shelling, winnowing, household-level storage, transport and market-level storage for the selected crop, location, and year is presented. Complimentary data sets are collected and used to convert this % loss into absolute loss values in tonnes, US$ and nutrients, along with the nutritional and financial impacts of these losses by province and country. Understanding the magnitude of postharvest loss, the points in the value chain where losses occur, and the causes and impacts of loss helps decision-makers formulate effective policies and invest in successful postharvest loss programmes.
Substantial crop losses occur at various stages along the postharvest value chain. Losses result from poor handling and storage practices combined with limited awareness, infrastructure, and knowledge. The African Postharvest Losses Information System (APHLIS) (www.aphlis.net) is the foremost international effort to collect, analyse and disseminate data on postharvest losses of cereal grains in sub-Saharan Africa. The cumulative % loss in weight incurred during harvesting, drying, threshing/shelling, winnowing, household-level storage, transport and market-level storage for the selected crop, location, and year is presented. Complimentary data sets are collected and used to convert this % loss into absolute loss values in tonnes, US$ and nutrients, along with the nutritional and financial impacts of these losses by province and country. Understanding the magnitude of postharvest loss, the points in the value chain where losses occur, and the causes and impacts of loss helps decision-makers formulate effective policies and invest in successful postharvest loss programmes.
Fire is a natural part of all ecosystems. Wildfires have been burning vegetation and shaping landscapes far longer than people have been on Earth. However, changes in fire frequency and timing can result in degradation if the vegetation is not adapted to the new fire regimes. This can cause long-term damage to land biomass components affecting soil structure, nutrients and water cycling. This layer displays the areas of concern for fires related issues derived from the convergence of global evidence of human-environment interactions that can have consequences on land degradation. This layer is part of the World Altas of Desertification
Aridity represents the ‘dryness’ of the climate. Dry areas have a higher potential for land degradation. This layer displays the areas of concern for aridity related issues derived from the convergence of global evidence of human-environment interactions that can lead to land degradation. It highlights dryland areas, where the Aridity Index (ratio of precipitation to evapotranspiration) is inferior to 0.65. This layer is part of the World Altas of Desertification
Smallholder farmers and pastoralists have restricted access to capital and may not have the capacity to invest in management practices that mitigate land degradation. This layer displays the areas of concern for the issues related to income level derived from the convergence of global evidence of human-environment interactions that can lead to land degradation. This layer is part of the World Altas of Desertification
The INFORM Risk Index 2021 is a composite model structured into a hierarchy of dimensions, categories, and components. All scores are normalized on a scale of 0 to 10 (10 being the highest risk).Below is the clear breakdown of the index's architecture based on your descriptions:The Composite IndexThe top-level score representing a country's overall risk of humanitarian crisis. It is used to assign countries into Risk Classes:Low: ≤3.5Medium: 3.5−5.0High: 5.0−6.5Very High: ≥6.5Dimension: VulnerabilityThis dimension measures the predisposition of a population to be affected by a hazard based on economic, political, and social characteristics.Sub-Index: Socio-Economic VulnerabilityAn aggregate index covering three main components of systemic instability:Development Deprivation: Measures poverty using the Human Development Index (HDI) and Multidimensional Poverty Index (MPI).Inequality: Captures the dispersion of human development, including the Gender Inequality Index and the Gini Coefficient.Aid Dependency: Measures economic instability through reliance on public aid, development assistance, and remittances.Sub-Index: Vulnerable GroupsCaptures social groups with limited access to care and heightened susceptibility:Uprooted People: Tracks refugees, IDPs, and returnees.Children Under 5: Specifically monitors child malnutrition and mortality rates.Recent Shocks: Factors in populations already affected by natural disasters in the last 3 years.Food Security: Captures trends in chronic hunger and nutritional balance.Health Conditions: Monitors the prevalence of pandemics (HIV, TB, Malaria) and neglected tropical diseases.Dimension: Lack of Coping CapacityThis dimension measures the ability of a country to manage and recover from disasters through its infrastructure and government effort.Sub-Index: Institutional CapacityMeasures the "soft" infrastructure of a country's disaster management:Governance: Captures government effectiveness, resilience-building, and political integrity (lack of corruption).DRR Implementation: Quantifies how well Disaster Risk Reduction activities are actually put into practice.Sub-Index: InfrastructureMeasures the "hard" assets and systems available during a crisis:Communication: Evaluates the efficiency of early warning dissemination and the literacy/education of the recipients.Physical Connectivity: Assesses the accessibility of transport and the quality/availability of water and sanitation services.Access to Healthcare: Captures health system strength, including physician density and maternal/infant health services.