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This report presents new and updated baseline profiles of 34 livelihood zones—33 rural and one peri-urban—in the Democratic Republic of the Congo (DRC). The information was gathered during fieldwork from February to September 2024.
Using the Household Economy Analysis (HEA) framework, the livelihood zone baseline profiles include detailed information about local livelihoods—sources of food, sources of income, expenditures, and coping strategies—that allow FEWS NET and other acute food insecurity early warning analysts to understand the basic components of household economies in typical years, determine which hazards are most likely to undermine these economies, and identify ways to support local livelihoods so households can survive and recover from future shocks.
Livelihood zone baseline profile information is disaggregated by geography and by wealth. This is because people’s access to food and cash income and their expenditure requirements depend on where they live and on their wealth status.
Key determinants of wealth in the DRC include the amount of land cultivated by the household, the types and numbers of livestock owned by the household, and the amount of other off-farm productive assets (e.g., boats and fishing equipment in fishing zones). Assets generally increase with wealth, as does household size, with wealthier people typically living in larger households.
Agriculture is the basis of household livelihoods in all rural zones in the country, even where the importance of fishing or mining differentiates a zone from its neighbors. The vast and varied rural landscape in the DRC induces caution about generalizing, but four kinds of environments fundamentally influence local livelihoods:
- Sparsely populated great forests of the north and center with cultivated clearings, forest gathering, and hunting
- Savannah areas of roughly the southern half of the country, characterized by cassava and maize production and generally moderate population densities
- Riverine and lacustrine areas, with a successful mix of fishing and cultivation supporting denser populations
- Eastern highlands, characterized by far denser populations than in nearly all other zones in the country, with varying balances of crops and livestock
To view the full report as a PDF, including a national-level overview of livelihoods in the DRC, click 'Download Report' at the top of this page.
To view a webinar recording on the release of 2026 livelihood zone baseline profiles for the Democratic Republic of the Congo or view slides from the event, click 'Watch Event Video' or 'Download Resource' at the top of this page.
Each livelihood zone baseline profile is divided up into several sections: zone description, markets, timeline and reference year, seasonal calendar, wealth breakdown, sources of food, sources of cash income, expenditure patterns, food access calendars, poor female-headed households, response strategies, and key parameters for monitoring.
To jump to the livelihood zone baseline profile for a specific zone, click on the bookmarks below:
Fact sheets provide a summary of the most relevant data from the DRC livelihood zone baseline profiles. They include the livelihood zone description; seasonal calendar; key parameters for monitoring; wealth breakdown and productive assets; and sources of food, cash income, and expenditure patterns.
To view the 2024 DRC Livelihood Zone Baseline Profile Fact Sheets, click HERE.
Recommended citation: Famine Early Warning Systems Network (FEWS NET). Livelihood Zone Baseline Profiles Report, Democratic Republic of the Congo (2024). Washington, DC: FEWS NET, 2026. https://fews.net/southernafrica/democratic-republic-congo/livelihood-baseline/october-2024.
Livelihood Baselines provide quantitative analysis of household livelihood options. They include a detailed breakdown of food, cash income, and expenditure patterns. The baseline also highlights market patterns, seasonality, and coping strategies. Baselines can be used to quantify and measure the impact of shocks on households when used in outcome analysis. They are also useful in planning humanitarian assistance, particularly in forecasting whether and when assistance will be needed, how many people might be affected, and what types of assistance will be most impactful.