Urban Slum and Housing Affordability Indicators for the Democratic Republic of the Congo

Proportion and total count of the urban population living in slums or informal settlements in the Democratic Republic of the Congo, based on four UN-Habitat household shelter deprivation indicators. The data also includes the proportion of the urban population living in housing that costs more than 30% of their monthly income. This dataset was produced by the United Nations Human Settlements Programme (UN-Habitat) Data and Analytics Section and was last updated on 2026-05-06.

Use Cases

• Assess the prevalence of slum conditions based on UN-Habitat's deprivation indicators for lack of water, sanitation, living area, and structural quality.
• Analyze housing cost burden by identifying urban populations spending over 30% of income on housing.
• Estimate the total urban population living in informal settlements for regional or national planning.
• Monitor progress towards SDG 11.1 (access to adequate, safe, and affordable housing) using standardized UN metrics.

Strengths

• Data is based on a standardized UN-Habitat methodology using four key shelter deprivation indicators.
• Includes two distinct metrics: slum population proportion and housing cost overburden proportion.
• Produced by the authoritative United Nations Human Settlements Programme (UN-Habitat).

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Excludes the 'security of tenure' deprivation indicator due to stated data limitations.

Provenance

Source

United Nations Human Settlements Programme (UN-Habitat), Data and Analytics Section

Collection Method

Likely derived from national surveys and UN-Habitat's analysis of household shelter deprivations.

Freshness

Last updated 2026-05-06 22:56:38.158690; freshness should be verified.

Geography

Democratic Republic of the Congo, likely with sub-national regional breakdowns.