Synthetic Stroke Rehabilitation and Disability Data for Sub-Saharan Africa

70% of stroke survivors have disability and less than 5% access rehabilitation in Sub-Saharan Africa, according to the dataset's abstract. This synthetic dataset models stroke types, acute care, post-stroke disability, rehabilitation access, and functional recovery across three care tiers. It was created by electricsheepafrica and parameterized from published Sub-Saharan Africa literature, not from real observations.

Use Cases

• Simulating healthcare system strain based on modelled stroke incidence and rehabilitation access rates.
• Testing machine learning models for predicting functional recovery based on synthetic patient pathways.
• Educational demonstrations of health disparities using modelled data on post-stroke disability and care tiers.

Strengths

• Explicitly states it is synthetic, parameterized from published literature, preventing misuse for empirical analysis.
• Models multiple specific healthcare concepts: stroke types, acute care, disability, rehabilitation access, and functional recovery.

Limitations

• Synthetic data not suitable for empirical analysis or policy inference, as stated in the description.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

Parameterized from published Sub-Saharan Africa literature.

Collection Method

Synthetic generation.

Freshness

Last updated 2026-04-14 22:49:33; freshness should be verified.

Geography

Sub-Saharan Africa