---
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.