Datasets:

electricsheepafrica
/

africa-synth-mining-occupational-health-all

record_id stringlengths 12 12	mine_type stringclasses 4 values	country stringclasses 5 values	age int64 18 65	gender stringclasses 2 values	employment_years float64 0.5 40	silica_exposed bool 2 classes	job_category stringclasses 11 values	hiv_status stringclasses 2 values	silicosis_status stringclasses 2 values	tb_history stringclasses 2 values	tb_current stringclasses 2 values	silico_tb bool 2 classes	respiratory_symptoms stringclasses 2 values	comorbidities stringclasses 2 values	screening_year int64 2.02k 2.02k
OCC-0A975D4F	artisanal	south_africa	30	male	14	true	processor	negative	negative	no	negative	false	yes	yes	2,020
OCC-D89067C3	formal_platinum	ghana	25	male	7	true	supervisor	negative	negative	no	negative	false	yes	no	2,024
OCC-09A1AE4D	artisanal	tanzania	23	male	6.7	true	general	negative	negative	yes	negative	false	no	no	2,024
OCC-118F48BC	artisanal	south_africa	18	male	2	true	processor	negative	negative	yes	negative	false	no	no	2,023
OCC-20D762E7	formal_gold	south_africa	55	male	5.7	true	winch_operator	positive	negative	no	negative	false	yes	yes	2,024
OCC-A889BAB7	artisanal	zimbabwe	36	male	3.3	true	processor	negative	negative	no	positive	false	yes	yes	2,023
OCC-3B8E184D	artisanal	tanzania	47	male	1	true	general	positive	positive	yes	positive	true	yes	no	2,020
OCC-F1A064DD	artisanal	ghana	19	male	0.7	true	digger	negative	negative	no	positive	false	yes	no	2,023
OCC-DBBD6BF4	formal_gold	ghana	56	male	19.6	true	driller	negative	positive	yes	negative	false	yes	no	2,024
OCC-AEF9A1B3	formal_coal	zimbabwe	39	female	21	true	loader_operator	negative	negative	no	negative	false	no	no	2,024
OCC-66F21E4D	formal_platinum	south_africa	49	male	16.5	false	loader_operator	negative	negative	no	positive	false	yes	no	2,023
OCC-C7431689	artisanal	zimbabwe	40	male	1.1	true	digger	positive	negative	no	negative	false	yes	yes	2,019
OCC-409E868E	artisanal	south_africa	47	male	12.5	true	digger	positive	negative	yes	negative	false	no	no	2,023
OCC-2FB73A24	artisanal	ghana	18	male	1.1	true	digger	negative	positive	yes	positive	true	yes	no	2,018
OCC-01396CA1	formal_platinum	south_africa	42	female	20.7	false	winch_operator	negative	negative	no	negative	false	no	no	2,022
OCC-5A5C7D7E	formal_gold	south_africa	46	female	12.5	true	other	negative	negative	no	negative	false	yes	no	2,020
OCC-E9C4E640	formal_coal	zimbabwe	33	male	15	true	maintenance	negative	negative	no	negative	false	no	no	2,019
OCC-0544AB3F	formal_gold	zimbabwe	50	female	14.3	true	other	negative	negative	yes	positive	false	yes	yes	2,024
OCC-A488ADE3	artisanal	ghana	34	male	12.2	true	digger	negative	negative	no	negative	false	no	no	2,023
OCC-1956B6EC	artisanal	zimbabwe	58	female	3.3	true	processor	negative	negative	no	negative	false	yes	no	2,022
OCC-D245B613	artisanal	drc	44	male	9.9	true	digger	positive	negative	no	negative	false	yes	no	2,022
OCC-F79DA141	formal_platinum	tanzania	28	male	5.2	true	winch_operator	positive	negative	yes	positive	false	yes	no	2,019
OCC-9B1E9640	artisanal	tanzania	18	male	2	true	transporter	negative	negative	no	negative	false	yes	no	2,021
OCC-B25E6ABD	artisanal	ghana	45	male	5.8	true	transporter	negative	negative	no	positive	false	yes	no	2,020
OCC-C56967CC	artisanal	ghana	28	male	8.3	true	processor	negative	negative	no	negative	false	no	no	2,024
OCC-8313C386	formal_gold	ghana	26	male	8	false	loader_operator	negative	negative	no	negative	false	no	no	2,022
OCC-532F8BF3	formal_coal	zimbabwe	43	male	24.4	false	blaster	negative	negative	no	negative	false	no	no	2,024
OCC-1CD38E40	formal_gold	south_africa	42	male	24	true	blaster	negative	negative	no	negative	false	no	no	2,019
OCC-F2BF477A	formal_gold	zimbabwe	47	male	28.7	true	driller	negative	negative	no	negative	false	yes	yes	2,020
OCC-12AFFFC0	artisanal	south_africa	46	male	2.4	true	processor	negative	negative	no	negative	false	no	yes	2,022
OCC-55E4F294	artisanal	south_africa	28	male	0.5	true	digger	negative	negative	no	negative	false	no	no	2,024
OCC-4DC806C0	artisanal	tanzania	36	male	6.3	true	transporter	negative	negative	no	positive	false	yes	no	2,018
OCC-6B41B346	formal_platinum	south_africa	38	male	8.7	true	winch_operator	negative	negative	no	negative	false	yes	no	2,018
OCC-E000B1C3	formal_platinum	zimbabwe	63	male	22	false	other	positive	negative	yes	negative	false	yes	no	2,023
OCC-98E03574	formal_coal	ghana	46	male	18.5	true	supervisor	negative	negative	no	negative	false	no	yes	2,018
OCC-3EA6C282	formal_gold	south_africa	46	male	21.5	true	driller	positive	positive	yes	positive	true	yes	no	2,020
OCC-D4E10962	formal_gold	tanzania	46	male	23.3	true	driller	negative	positive	no	negative	false	yes	no	2,022
OCC-C2AD1614	formal_coal	south_africa	54	male	11.4	true	driller	negative	positive	no	negative	false	yes	no	2,020
OCC-5EC7C531	formal_gold	tanzania	50	male	20.9	false	maintenance	positive	negative	yes	negative	false	yes	no	2,023
OCC-6DE70F5F	artisanal	tanzania	30	male	2.8	true	processor	negative	negative	no	negative	false	no	no	2,018
OCC-2A082FF4	formal_platinum	south_africa	48	male	29	true	winch_operator	positive	positive	no	negative	false	yes	no	2,022
OCC-B2637407	artisanal	south_africa	37	male	5.1	true	general	negative	negative	no	negative	false	yes	no	2,022
OCC-4E56D7B3	artisanal	south_africa	30	male	7	true	processor	negative	negative	no	negative	false	no	no	2,019
OCC-0F126E01	formal_platinum	zimbabwe	51	female	31.6	true	supervisor	negative	negative	yes	negative	false	no	no	2,022
OCC-C4852958	artisanal	south_africa	34	male	1.5	true	transporter	positive	positive	yes	positive	true	no	no	2,021
OCC-6DD857E2	artisanal	drc	22	male	3.2	true	digger	negative	negative	no	negative	false	yes	no	2,024
OCC-D41550C0	formal_platinum	south_africa	26	male	8	true	driller	negative	negative	no	negative	false	no	no	2,023
OCC-158A80CF	formal_platinum	tanzania	26	male	8	true	maintenance	negative	negative	no	negative	false	yes	no	2,023
OCC-18494D24	artisanal	south_africa	43	male	2.5	true	digger	negative	negative	yes	negative	false	no	no	2,021
OCC-5B72201D	formal_gold	drc	43	male	16.9	true	other	positive	positive	yes	negative	false	no	no	2,022
OCC-2B89035D	formal_gold	south_africa	42	male	24	true	driller	negative	positive	no	negative	false	yes	yes	2,018
OCC-CD7C498E	formal_gold	zimbabwe	50	male	8.7	true	other	negative	negative	no	negative	false	no	no	2,020
OCC-781F2611	artisanal	zimbabwe	39	female	0.5	true	processor	negative	negative	no	negative	false	yes	no	2,020
OCC-A1329967	artisanal	south_africa	18	male	2	true	processor	negative	negative	yes	negative	false	yes	no	2,018
OCC-D94D207E	artisanal	tanzania	50	male	6.9	true	processor	negative	negative	no	negative	false	no	no	2,023
OCC-B6D9ED36	artisanal	south_africa	35	male	0.5	false	general	positive	negative	no	negative	false	yes	no	2,022
OCC-547EF76F	formal_coal	zimbabwe	44	male	14.7	true	other	negative	negative	no	negative	false	no	no	2,020
OCC-6DE4B350	formal_coal	zimbabwe	50	male	8.3	true	loader_operator	negative	negative	no	negative	false	no	no	2,018
OCC-0195D979	formal_gold	ghana	32	male	14	true	winch_operator	positive	positive	yes	positive	true	yes	no	2,024
OCC-51DBA21C	formal_gold	south_africa	44	male	25.4	true	loader_operator	positive	positive	yes	positive	true	yes	yes	2,022
OCC-A7D49FDC	artisanal	south_africa	39	male	3.1	true	digger	negative	negative	yes	negative	false	yes	no	2,023
OCC-DB714F66	formal_coal	south_africa	31	male	13	true	winch_operator	negative	positive	yes	negative	false	yes	yes	2,018
OCC-04A39D53	formal_coal	south_africa	48	male	13.7	false	other	positive	negative	yes	negative	false	no	no	2,024
OCC-08CD857F	artisanal	south_africa	47	male	2.5	true	general	negative	negative	no	negative	false	no	no	2,018
OCC-F6042D1C	artisanal	drc	41	female	5.2	true	general	negative	negative	no	negative	false	no	no	2,024
OCC-A80F5415	formal_coal	zimbabwe	25	male	7	true	loader_operator	negative	negative	no	positive	false	yes	no	2,021
OCC-9DAAB81A	formal_coal	ghana	47	male	14.7	false	supervisor	negative	negative	no	negative	false	no	yes	2,024
OCC-35413659	formal_platinum	zimbabwe	29	male	9.3	true	maintenance	negative	negative	no	negative	false	no	no	2,024
OCC-8CB90F51	formal_gold	south_africa	40	male	22	true	winch_operator	negative	negative	no	negative	false	no	no	2,024
OCC-AAEAEA5A	formal_platinum	zimbabwe	53	male	35	false	loader_operator	negative	negative	no	negative	false	no	no	2,023
OCC-4BF4F688	formal_gold	south_africa	46	male	28	true	other	positive	negative	no	negative	false	yes	no	2,018
OCC-FE4F4268	formal_platinum	south_africa	28	male	10	true	blaster	positive	negative	no	negative	false	no	no	2,022
OCC-2D120479	artisanal	zimbabwe	52	male	0.9	true	digger	negative	negative	no	negative	false	no	no	2,021
OCC-42C6EC7F	formal_gold	zimbabwe	37	male	17.9	true	winch_operator	positive	positive	no	negative	false	yes	no	2,023
OCC-7C625F49	formal_gold	drc	29	male	10.4	true	other	positive	negative	yes	positive	false	yes	no	2,024
OCC-E9A1C569	formal_platinum	south_africa	27	female	9	true	winch_operator	negative	negative	no	negative	false	yes	no	2,021
OCC-F5B9D140	formal_platinum	zimbabwe	45	male	21.9	true	other	negative	negative	no	negative	false	yes	no	2,019
OCC-2C298DC6	artisanal	south_africa	33	male	1.5	true	digger	negative	positive	yes	negative	false	no	no	2,023
OCC-0FC6D160	formal_coal	south_africa	50	male	16.9	false	driller	positive	negative	yes	negative	false	no	no	2,019
OCC-D49927CA	artisanal	ghana	50	male	6.6	true	processor	negative	negative	no	negative	false	no	no	2,021
OCC-28F17A32	artisanal	south_africa	39	male	3.4	true	digger	negative	negative	no	negative	false	yes	no	2,022
OCC-DDEB5EFD	formal_platinum	zimbabwe	48	male	17.5	true	supervisor	negative	positive	yes	positive	true	yes	no	2,024
OCC-03DE4B74	artisanal	zimbabwe	43	male	4.4	true	digger	negative	negative	no	negative	false	no	no	2,023
OCC-E7CEEF93	formal_gold	south_africa	50	male	15.9	true	maintenance	negative	negative	no	negative	false	no	no	2,022
OCC-B4DE613C	formal_gold	drc	44	male	12.6	false	driller	positive	negative	no	negative	false	no	no	2,021
OCC-17D2815A	formal_gold	zimbabwe	41	male	23	true	driller	positive	negative	no	negative	false	yes	no	2,020
OCC-7C7255E2	artisanal	tanzania	42	male	5.7	true	processor	negative	negative	no	negative	false	yes	no	2,023
OCC-76F5917F	formal_coal	zimbabwe	33	male	15	false	winch_operator	negative	negative	no	negative	false	no	no	2,020
OCC-0A40898B	formal_gold	drc	40	male	6.9	true	maintenance	negative	negative	no	positive	false	yes	no	2,019
OCC-5398A0A1	formal_coal	south_africa	31	male	13	false	blaster	negative	negative	no	negative	false	no	no	2,022
OCC-49BE5756	formal_gold	zimbabwe	36	male	18	true	winch_operator	negative	negative	no	negative	false	no	no	2,024
OCC-729EC46B	artisanal	tanzania	53	male	0.6	true	processor	negative	negative	no	negative	false	no	no	2,021
OCC-16970B31	formal_platinum	south_africa	45	male	14.8	true	loader_operator	negative	negative	no	negative	false	yes	no	2,020
OCC-3FAE0288	formal_platinum	zimbabwe	43	male	25	false	other	negative	negative	no	negative	false	yes	no	2,019
OCC-EC9F19E7	formal_platinum	drc	65	male	10.6	true	driller	positive	negative	no	negative	false	no	no	2,023
OCC-01F6C1CC	artisanal	zimbabwe	46	male	6.1	true	digger	positive	positive	yes	positive	true	yes	no	2,022
OCC-21316DCB	formal_platinum	ghana	31	male	13	true	maintenance	positive	positive	yes	negative	false	yes	no	2,019
OCC-86F039E1	formal_gold	ghana	43	male	25	true	other	negative	negative	no	negative	false	no	no	2,022
OCC-917D0BCD	formal_gold	tanzania	30	male	12	false	loader_operator	negative	negative	no	negative	false	yes	no	2,020
OCC-35E6E401	artisanal	tanzania	31	female	6.9	true	general	negative	negative	no	negative	false	yes	no	2,018

End of preview. Expand in Data Studio

African Mining Occupational Health Dataset | Africa (Electric Sheep Africa metadata inventory)

Size category: 1K<n<10K - Formats: parquet - Sector: health - Engineered by Electric Sheep Africa

TL;DR

This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.

What This Dataset Covers

Health datasets help researchers examine disease burden, service delivery, risk factors, outcomes, and public-health program performance.

Dataset context from the existing Hugging Face card: ⚠️ Synthetic dataset — Parameterized from published SSA literature, not real observations. Not suitable for empirical analysis or policy inference. 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… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-synth-mining-occupational-health-all.

Dataset Profile

Field	Value
Hugging Face repo	`electricsheepafrica/africa-synth-mining-occupational-health-all`
Sector	health
Topic tags	mining, occupational-health, tuberculosis, silicosis, hiv, epidemiology, synthetic-data, synthetic
Modalities	`tabular`, `text`
Formats	`parquet`
Size category	`1K<n<10K`
Countries	Africa-wide or source-defined African coverage
ISO3 coverage	`not declared`
Last modified on HF	`2026-04-14 22:39:10+00:00`
Inventory snapshot	`2026-07-16T16:00:34Z`

How To Read This Dataset

Start from the repository files and the dataset viewer when available.
Treat the README context as a fast orientation layer; confirm variable definitions and units in the data files before modeling.
Use explicit country columns when present. When geography is only implied by the title or source metadata, document that assumption in downstream analysis.
Preserve missing values until you have a defensible imputation rule.

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-synth-mining-occupational-health-all")
print(ds)

split_name = next(iter(ds))
table = ds[split_name]
print(table.features)
print(table[:3])

Convert To Pandas When Tabular

from datasets import Dataset

first_split = ds[next(iter(ds))]
if isinstance(first_split, Dataset):
    df = first_split.to_pandas()
    print(df.head())

Data Quality Notes

This card was standardized from the Electric Sheep Africa Hugging Face metadata inventory.
Exact schema, row counts, and source files should be inspected in the repository data files.
Metadata gaps from the inventory: country, upstream_publisher.
Do not infer policy meaning from labels alone; confirm definitions, units, and methods in the source material.

Source And Provenance

Source context: Electric Sheep Africa metadata inventory
Publisher/source attribution: Public dataset metadata
License: CC BY 4.0
Hugging Face URL: https://huggingface.co/datasets/electricsheepafrica/africa-synth-mining-occupational-health-all
Inventory retrieved at: 2026-07-16T16:00:34Z

Suggested Analyses

Inspect schema and missingness before modeling.
Profile variables by geography, time, and subgroup columns where present.
Join with other Electric Sheep Africa datasets using explicit country, year, and indicator fields when available.
Build reproducible notebooks that cite both the original source context and the Electric Sheep Africa Hugging Face repo.

Citation

@misc{electric_sheep_africa_africa_synth_mining_occupational_health_all_2026,
  title        = {African Mining Occupational Health Dataset | Africa (Electric Sheep Africa metadata inventory)},
  author       = {Public dataset metadata},
  year         = {2026},
  url          = {https://huggingface.co/datasets/electricsheepafrica/africa-synth-mining-occupational-health-all},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-synth-mining-occupational-health-all}}
}

License

Released under CC BY 4.0.

Original source rights remain with the original publisher or data provider. Electric Sheep Africa engineering standardizes discovery metadata, documentation, and usage guidance for analysis on Hugging Face.

About Electric Sheep Africa

Electric Sheep Africa publishes ML-ready African public datasets on Hugging Face.

Provenance: metadata-backed README standardized 2026-08-12 by the Electric Sheep Africa README system. Inventory source: catalog/esa_metadata_inventory/master_metadata.jsonl.

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Collection including electricsheepafrica/africa-synth-mining-occupational-health-all

African Mining Datasets

Collection

Research-grounded synthetic datasets for African mining: safety, health, equipment, ASM, and tailings risk. • 5 items • Updated Nov 28, 2025