--- license: cc-by-4.0 task_categories: - tabular-classification - tabular-regression language: - en tags: - healthcare - supply-chain - medical-oxygen - hypoxemia - pulse-oximetry - concentrator - PSA-plant - pneumonia - neonatal - sub-saharan-africa - lmic pretty_name: "Medical Oxygen Supply (Availability, Equipment, Hypoxemia Mortality, Supply Chain)" size_categories: - 10K Validation Report

### 4.1 Key Validation Results | Metric | Referral | District | Rural | Literature | | --- | --- | --- | --- | --- | | Oxygen available | 82% | 50% | 12% | ~50% lack oxygen [6] | | Sufficient supply | 65% | 35% | 8% | <10% volume [1] | | Pulse ox functional | 85% | 14% | 0.4% | Limited periphery [4] | | Mean patients needing O2 | 40 | 12 | 3 | Facility volume | | Mean patients receiving O2 | 26 | 2.5 | 0 | Coverage gap | | Mean deaths/observation | 5.0 | 4.3 | 1.7 | High mortality [4] | ## 5. Usage ```python from datasets import load_dataset dataset = load_dataset( "electricsheepafrica/medical-oxygen-supply", "district_hospital" ) df = dataset["train"].to_pandas() # Oxygen coverage gap analysis df['coverage_pct'] = df['patients_received_oxygen'] / df['patients_needing_oxygen'].clip(lower=1) * 100 print(df.groupby('primary_oxygen_source')['coverage_pct'].mean()) ``` ### 5.1 Suggested Analyses - **Oxygen access prediction**: Classify facilities at risk of stockout from infrastructure and logistics features. - **Mortality modelling**: Quantify the relationship between oxygen availability, pulse oximetry, and hypoxemia deaths. - **Equipment investment**: Compare cost-effectiveness of concentrators vs cylinders vs PSA plants by facility type. - **Power dependency**: Model the impact of electrification and solar deployment on oxygen availability. ## 6. Limitations - **Simulated**: Not from real oxygen surveys or health management information systems. - **No temporal dynamics**: Cross-sectional observations, not longitudinal supply chain tracking. - **Simplified mortality**: Deaths are modelled from a single probability rather than full clinical pathways. - **No ambient conditions**: Altitude, temperature, and humidity effects on concentrator performance not modelled. - **No cost granularity**: Unit costs for cylinders, concentrators, and PSA are approximated, not market-specific. ## 7. References 1. Oxygen Hub / ITT (2021). Closing the medical oxygen gap in sub-Saharan Africa. oxygenhub.org/psaplants 2. PMC (2022). Oxygen inequity in the COVID-19 pandemic and beyond. PMC9972372. 3. PMC (2022). A comprehensive approach to medical oxygen ecosystem building. 151/165 broken PSA plants in SSA. PMC9771461. 4. PMC (2021). Oxygen delivery systems for adults in sub-Saharan Africa: A scoping review. Hypoxemia prevalence 11–89%. PMC8109278. 5. BMC Health Services Research (2025). Design and maintenance of medical oxygen concentrators in SSA. WHO distributed >30,000 OCs. doi:10.1186/s12913-025-12315-6 6. PMC (2024). Functional availability of medical oxygen for management of pneumonia. ~50% facilities lack oxygen. PMC11082622. 7. WHO (2023). Model List of Essential Medicines, 23rd list. Medical oxygen included. ## Citation ```bibtex @dataset{esa_medical_oxygen_supply_2025, title = {Medical Oxygen Supply Dataset: Availability, Equipment, Hypoxemia Mortality, and Supply Chain Across Three Tiers of Healthcare in Sub-Saharan Africa}, author = {{Electric Sheep Africa}}, year = {2025}, publisher = {Hugging Face}, url = {https://huggingface.co/datasets/electricsheepafrica/medical-oxygen-supply}, note = {Simulated dataset. Not for clinical or procurement use.} } ``` ## License [CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/)