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README.md

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+---
+license: cc-by-4.0
+task_categories:
+  - tabular-classification
+  - tabular-regression
+language:
+  - en
+tags:
+  - mining
+  - occupational-health
+  - tuberculosis
+  - silicosis
+  - hiv
+  - epidemiology
+  - africa
+  - synthetic-data
+pretty_name: African Mining Occupational Health Dataset
+size_categories:
+  - 1K<n<10K
+---
+
+# African Mining Occupational Health Dataset
+
+## Dataset Description
+
+### Overview
+
+This dataset models the silicosis-tuberculosis-HIV syndemic affecting mining populations across sub-Saharan Africa. It provides synthetic screening records capturing the complex interplay between occupite dust exposure, infectious disease burden, and occupational health outcomes in both formal and artisanal mining contexts.
+
+The dataset encodes epidemiologically-validated prevalence rates, risk factor associations, and comorbidity patterns derived from cross-sectional health screening studies conducted in Zimbabwe and South Africa.
+
+### Dataset Statistics
+
+| Attribute | Value |
+|-----------|-------|
+| Records | 5,000 |
+| Variables | 16 |
+| Geographic Scope | South Africa, Zimbabwe, Ghana, Tanzania, DRC |
+| Format | CSV, Parquet |
+
+## Data Schema
+
+### Variable Dictionary
+
+| Variable | Type | Description | Value Range/Categories |
+|----------|------|-------------|----------------------|
+| `record_id` | string | Unique screening record identifier | OCC-XXXXXXXX |
+| `mine_type` | categorical | Mining operation type | formal_gold, formal_platinum, formal_coal, artisanal |
+| `country` | categorical | Country of screening | south_africa, zimbabwe, ghana, tanzania, drc |
+| `age` | integer | Worker age in years | 18-65 |
+| `gender` | categorical | Worker gender | male, female |
+| `employment_years` | float | Duration of mining employment | 0.5-40 years |
+| `silica_exposed` | boolean | History of respirable silica exposure | True/False |
+| `job_category` | categorical | Occupational role | driller, winch_operator, blaster, loader_operator, maintenance, supervisor, digger, processor, transporter, general, other |
+| `hiv_status` | categorical | HIV serostatus | positive, negative |
+| `silicosis_status` | categorical | Radiological silicosis diagnosis | positive, negative |
+| `tb_history` | categorical | Previous tuberculosis diagnosis | yes, no |
+| `tb_current` | categorical | Current active tuberculosis | positive, negative |
+| `silico_tb` | boolean | Combined silico-tuberculosis diagnosis | True/False |
+| `respiratory_symptoms` | categorical | Self-reported respiratory symptoms | yes, no |
+| `comorbidities` | categorical | Other chronic conditions present | yes, no |
+| `screening_year` | integer | Year of health screening | 2018-2024 |
+
+## Methodology
+
+### Epidemiological Framework
+
+This dataset models the well-documented syndemic interaction between:
+
+1. **Silicosis**: Chronic fibrotic lung disease from crystalline silica inhalation
+2. **Tuberculosis**: Both primary infection and reactivation, amplified by silica-induced immunosuppression
+3. **HIV/AIDS**: Further immunocompromise increasing susceptibility to both silicosis progression and TB
+
+### Primary Literature Sources
+
+| Source ID | Citation | Parameters Extracted |
+|-----------|----------|---------------------|
+| ZWE_001-007 | Moyo, D., et al. (2021). Prevalence of silicosis, pulmonary tuberculosis and their co-morbidities among artisanal and small-scale gold miners in Zimbabwe. *Occupational and Environmental Medicine*. [PMC8583466](https://pmc.ncbi.nlm.nih.gov/articles/PMC8583466/) | HIV prevalence (23.5%), silicosis prevalence (11.2%), TB prevalence (4.0%), silica exposure (95%), HIV-silicosis OR (2.79) |
+| SA_001-004 | teWaterNaude, J.M., et al. (2006). Tuberculosis and silica exposure in South African gold miners. *Occupational and Environmental Medicine*, 63(3), 187-192. [PMC2078150](https://pmc.ncbi.nlm.nih.gov/articles/PMC2078150/) | PTB prevalence (19.4-35.2%), high-risk occupations, exposure-response relationships |
+
+### Key Epidemiological Parameters
+
+**HIV Prevalence** (Moyo et al., 2021):
+- ASM workers: 23.5% (90/373 tested)
+- 95% CI: 19.4-28.1%
+
+**Silicosis Prevalence** (Moyo et al., 2021):
+- Overall: 11.2% (52/464)
+- 95% CI: 8.6-14.4%
+
+**Tuberculosis Burden**:
+- Current TB (Zimbabwe ASM): 4.0% (95% CI: 2.5-6.4%)
+- TB history (SA gold miners): 19.4% (95% CI: 16.0-22.8%)
+- TB with radiological evidence (SA): 35.2% (95% CI: 31.1-39.3%)
+
+**HIV-Silicosis Association** (Moyo et al., 2021):
+- HIV+ workers have 2.79x increased silicosis risk
+- 95% CI: 1.48-5.24
+
+**Silica Exposure** (Moyo et al., 2021):
+- 95% of ASM workers report dust exposure
+- 27% have ≥10 years mining duration
+
+### Conditional Dependencies Modeled
+
+```
+Silicosis Risk = f(silica_exposure, employment_years, hiv_status)
+TB Risk = f(silicosis_status, hiv_status, employment_years)
+Current TB = f(silicosis_status, hiv_status, tb_history)
+Symptoms = f(silicosis_status, tb_current)
+```
+
+## Limitations
+
+1. **Cross-sectional Design**: Source studies are cross-sectional; temporal relationships are inferred
+2. **Selection Effects**: Mining populations in studies may not represent all workers
+3. **Diagnostic Heterogeneity**: TB and silicosis definitions vary across source studies
+4. **Treatment Effects**: ART coverage and TB treatment effects not fully modeled
+5. **Exposure Quantification**: Silica exposure is binary rather than dose-response
+
+## Ethical Considerations
+
+- **Sensitive Health Data**: HIV status is highly sensitive; synthetic nature mitigates privacy risks
+- **Stigmatization**: Results should not stigmatize mining communities or countries
+- **Health Equity**: Dataset highlights occupational health disparities requiring policy attention
+- **Clinical Limitations**: Not suitable for individual diagnostic or prognostic decisions
+
+## Intended Uses
+
+### Appropriate Uses
+
+- Epidemiological modeling of occupational lung disease
+- Machine learning for screening program optimization
+- Health economics and cost-effectiveness research
+- Educational demonstrations of syndemic frameworks
+- Methods development for comorbidity analysis
+
+### Inappropriate Uses
+
+- Individual clinical diagnosis or prognosis
+- Insurance underwriting or risk stratification
+- Occupational health compliance certification
+- Policy decisions without validation against local data
+
+## Citation
+
+```bibtex
+@dataset{electric_sheep_africa_occupational_health_2024,
+  title = {African Mining Occupational Health Dataset: Silicosis-TB-HIV Syndemic},
+  author = {Electric Sheep Africa},
+  year = {2024},
+  publisher = {Hugging Face},
+  url = {https://huggingface.co/datasets/electricsheepafrica/african-mining-occupational-health},
+  note = {Synthetic dataset derived from epidemiological studies of African mining populations}
+}
+```
+
+## References
+
+1. Moyo, D., Zishiri, C., Ncube, R., Madziva, G., & Sandy, C. (2021). Prevalence of silicosis and pulmonary tuberculosis among artisanal and small-scale gold miners in Zimbabwe. *Occupational and Environmental Medicine*, 78(Suppl 1), A1-A173.
+
+2. teWaterNaude, J.M., Ehrlich, R.I., Churchyard, G.J., Pemba, L., Dekker, K.,"; M., White, N.W., Thompson, M.L., & Myers, J.E. (2006). Tuberculosis and silica exposure in South African gold miners. *Occupational and Environmental Medicine*, 63(3), 187-192.
+
+3. Rees, D., & Murray, J. (2007). Silica, silicosis and tuberculosis. *International Journal of Tuberculosis and Lung Disease*, 11(5), 474-484.
+
+## License
+
+This dataset is released under the [Creative Commons Attribution 4.0 International License](https://creativecommons.org/licenses/by/4.0/) (CC-BY-4.0).
+
+## Contact
+
+For questions or feedback, please open an issue on the dataset repository or contact Electric Sheep Africa.