Datasets:

electricsheepafrica
/

africa-synth-disability-stroke-rehabilitation-recovery-all

license: cc-by-4.0
task_categories:
  - tabular-classification
language:
  - en
tags:
  - disability
  - stroke
  - rehabilitation
  - hemiplegia
  - physiotherapy
  - synthetic
  - sub-saharan-africa
pretty_name: Stroke Rehabilitation & Recovery (SSA)
size_categories:
  - 10K<n<100K
configs:
  - config_name: urban_stroke_unit
    data_files: data/stroke_urban.csv
    default: true
  - config_name: district_hospital
    data_files: data/stroke_district.csv
  - config_name: rural_community
    data_files: data/stroke_rural.csv
data_type: synthetic

⚠️ Synthetic dataset — Parameterized from published SSA literature, not real observations. Not suitable for empirical analysis or policy inference.

Stroke Rehabilitation & Recovery in Sub-Saharan Africa

Abstract

Synthetic dataset modelling stroke types, acute care, post-stroke disability, rehabilitation access, and functional recovery across three care tiers in SSA. 70% of stroke survivors have disability; <5% access rehabilitation in SSA.

Parameterization Evidence

Parameter	Value	Source	Year
Stroke incidence increasing; youngest patients globally	Burden	Lancet Neurology	2022
70% survivors disabled; <5% access rehab	Access	WHO	2023
Physiotherapy <10% coverage in most SSA	Workforce	PMC	2022

Validation

Usage

from datasets import load_dataset
ds = load_dataset("electricsheepafrica/stroke-rehabilitation-recovery", "urban_stroke_unit")

References

Lancet Neurology. Stroke in SSA. 2022.
WHO. Stroke fact sheet. 2023.

Citation

@dataset{electricsheepafrica_stroke_rehabilitation_recovery_2025,
  title={Stroke Rehabilitation and Recovery in Sub-Saharan Africa},
  author={Electric Sheep Africa},
  year={2025},
  publisher={HuggingFace},
  url={https://huggingface.co/datasets/electricsheepafrica/stroke-rehabilitation-recovery}
}

License

CC-BY-4.0