electricsheepafrica/africa-burkinafaso-covid19-subnational

---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- tabular-classification
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- affected-population
- covid-19
- disease
- epidemics-outbreaks
- fatalities
- gender
- health
- bfa
pretty_name: "Burkina Faso: Coronavirus (Covid-19) Subnational"
dataset_info:
splits:
- name: train
num_examples: 7512
- name: test
num_examples: 1878
---

# Burkina Faso: Coronavirus (Covid-19) Subnational

**Publisher:** HERA - Humanitarian Emergency Response Africa · **Source:** [HDX](https://data.humdata.org/dataset/burkinafaso_covid19_subnational) · **License:** `cc-by` · **Updated:** 2025-05-05

---

## Abstract

Subnational data about Covid19 in Burkina Faso - Infected (new cases, gender), Deceased, Recovered.
NEW (!) : VACCINATION DATA PER REGION (1st & 2nd dose)
Type of vaccine : AstraZeneca ; Johnson&Johnson

Each row in this dataset represents first-level administrative unit observations. Data was last updated on HDX on 2025-05-05. Geographic scope: **BFA**.

*Curated into ML-ready Parquet format by [Electric Sheep Africa](https://huggingface.co/electricsheepafrica).*

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Public health |
| **Unit of observation** | First-level administrative unit observations |
| **Rows (total)** | 9,391 |
| **Columns** | 3 (0 numeric, 3 categorical, 0 datetime) |
| **Train split** | 7,512 rows |
| **Test split** | 1,878 rows |
| **Geographic scope** | BFA |
| **Publisher** | HERA - Humanitarian Emergency Response Africa |
| **HDX last updated** | 2025-05-05 |

---

## Variables

**Geographic** — `id_date_iso_3_pays_id_pays_region_id_region_contamines_deces_gueris_contamines_femme_contamines_homme_contamines_genre_non_specifie_nouveaux_individus_vaccines_1dose_total_individus_vaccines_1dose_nouveaux_agents_sante_vaccines_1dose_total_agents_sante_vaccines_1dose_nouveaux_individus_vaccines_2doses_total_individus_vaccines_2doses_nouveaux_agents_sante_vaccines_2doses_total_agents_sante_vaccines_2doses_source` (1;09/03/2020;BFA;Burkina Faso;16;Boucle du Mouhoun;208;0;0;0;0;0;0;0;0;0;0;0;0;0;0;Ministère de la Santé - Burkina Faso, 6273;03/06/2021;BFA;Burkina Faso;16;Centre-Est;211;0;0;;0;0;0;0;0;0;0;0;0;0;0;Ministère de la Santé - Burkina Faso, 6257;02/06/2021;BFA;Burkina Faso;16;Cascades;209;0;0;0;0;0;0;0;0;0;0;0;0;0;0;Ministère de la Santé - Burkina Faso).

**Identifier / Metadata** — `esa_source` (HDX), `esa_processed` (2026-04-04).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-burkinafaso-covid19-subnational")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

print(train.shape)
train.head()
```

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `id_date_iso_3_pays_id_pays_region_id_region_contamines_deces_gueris_contamines_femme_contamines_homme_contamines_genre_non_specifie_nouveaux_individus_vaccines_1dose_total_individus_vaccines_1dose_nouveaux_agents_sante_vaccines_1dose_total_agents_sante_vaccines_1dose_nouveaux_individus_vaccines_2doses_total_individus_vaccines_2doses_nouveaux_agents_sante_vaccines_2doses_total_agents_sante_vaccines_2doses_source` | object | 0.0% | 1;09/03/2020;BFA;Burkina Faso;16;Boucle du Mouhoun;208;0;0;0;0;0;0;0;0;0;0;0;0;0;0;Ministère de la Santé - Burkina Faso, 6273;03/06/2021;BFA;Burkina Faso;16;Centre-Est;211;0;0;;0;0;0;0;0;0;0;0;0;0;0;Ministère de la Santé - Burkina Faso, 6257;02/06/2021;BFA;Burkina Faso;16;Cascades;209;0;0;0;0;0;0;0;0;0;0;0;0;0;0;Ministère de la Santé - Burkina Faso |
| `esa_source` | object | 0.0% | HDX |
| `esa_processed` | object | 0.0% | 2026-04-04 |

---

## Numeric Summary

| Column | Min | Max | Mean | Median |
|---|---|---|---|---|
_No numeric columns._

---

## Curation

Raw data was downloaded from HDX via the CKAN API and converted to Parquet. Column names were lowercased and standardised to snake_case. Common missing-value markers (`N/A`, `null`, `none`, `-`, `unknown`, `no data`, `#N/A`) were unified to `NaN`. The dataset was split 80/20 into train and test partitions using a fixed random seed (42) and saved as Snappy-compressed Parquet.

---

## Limitations

- Data originates from HERA - Humanitarian Emergency Response Africa and has not been independently validated by ESA.
- Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/burkinafaso_covid19_subnational) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_burkinafaso_covid19_subnational,
title = {Burkina Faso: Coronavirus (Covid-19) Subnational},
author = {HERA - Humanitarian Emergency Response Africa},
year = {2025},
url = {https://data.humdata.org/dataset/burkinafaso_covid19_subnational},
note = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}
```

---

*[Electric Sheep Africa](https://huggingface.co/electricsheepafrica) — Africa's ML dataset infrastructure. Lagos, Nigeria.*