electricsheepafrica/africa-covid-19-vaccine-doses-in-hrp-countries

---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: cc-by-4.0
multilinguality:
- monolingual
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- tabular-classification
task_ids: []
tags:
- africa
- humanitarian
- hdx
- electric-sheep-africa
- covid-19
- epidemics-outbreaks
- health
- hxl
- vaccination-immunization
- afg
- bfa
- cmr
- caf
- tcd
pretty_name: "COVID-19 Vaccine Doses in HRP Countries"
dataset_info:
splits:
- name: train
num_examples: 24
- name: test
num_examples: 6
---

# COVID-19 Vaccine Doses in HRP Countries

**Publisher:** HDX · **Source:** [HDX](https://data.humdata.org/dataset/covid-19-vaccine-doses-in-hrp-countries) · **License:** `cc-by-igo` · **Updated:** 2026-03-30

---

## Abstract

This dataset contains COVID-19 vaccine dose availability forecasts as well as actual deliveries for countries with Humanitarian Response Plans. The data on vaccine availability forecasts was manually extracted from the COVAX Facility Interim Distribution Forecast as announced by COVAX on 3 February 2021. Figures for actual deliveries through channels other than COVAX are compiled by OCHA from press reports. The source(s) press releases, official announcements or articles for each such vaccine delivery are included in the dataset.

Each row in this dataset represents country-level aggregates. Data was last updated on HDX on 2026-03-30. Geographic scope: **AFG, BFA, CMR, CAF, TCD, COL, COD, ETH, and 18 others**.

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

---

## Dataset Characteristics

| | |
|---|---|
| **Domain** | Public health |
| **Unit of observation** | Country-level aggregates |
| **Rows (total)** | 31 |
| **Columns** | 16 (0 numeric, 16 categorical, 0 datetime) |
| **Train split** | 24 rows |
| **Test split** | 6 rows |
| **Geographic scope** | AFG, BFA, CMR, CAF, TCD, COL, COD, ETH, and 18 others |
| **Publisher** | HDX |
| **HDX last updated** | 2026-03-30 |

---

## Variables

**Geographic** — `country` (#country+name, Mali, Yemen), `iso3` (#country+code, MLI, YEM), `population_undesa` (#population+total, 20,250,834, 29,825,968), `covax_forecast_total` (0, #capacity+covax+total, 1,332,000), `covax_astrazeneca_sii` (0, #capacity+covax+azsii+doses, 3,600,000) and 5 others.

**Outcome / Measurement** — `total_delivered`.

**Identifier / Metadata** — `deprecataed_other_delivered_source_urls`, `esa_source`, `esa_processed`.

**Other** — `sfp_amc` (AMC, SFP, #meta+participant_status), `other_delivered` (#capacity+others+delivered+doses, 1,900,000, 80,000).

---

## Quick Start

```python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-covid-19-vaccine-doses-in-hrp-countries")
train = ds["train"].to_pandas()
test = ds["test"].to_pandas()

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

---

## Schema

| Column | Type | Null % | Range / Sample Values |
|---|---|---|---|
| `country` | object | 0.0% | #country+name, Mali, Yemen |
| `iso3` | object | 0.0% | #country+code, MLI, YEM |
| `sfp_amc` | object | 3.2% | AMC, SFP, #meta+participant_status |
| `population_undesa` | object | 0.0% | #population+total, 20,250,834, 29,825,968 |
| `covax_forecast_total` | object | 0.0% | 0, #capacity+covax+total, 1,332,000 |
| `covax_astrazeneca_sii` | object | 3.2% | 0, #capacity+covax+azsii+doses, 3,600,000 |
| `covax_astrazeneca_skbio` | object | 0.0% | 0, #capacity+covax+azskbio+doses, 2,066,400 |
| `covax_pfizer_biontech` | object | 0.0% | 0, 117,000, #capacity+covax+pfizerbiontech+doses |
| `covax_delivered` | object | 0.0% | #capacity+covax+delivered+doses, 4,319,050, 2,516,000 |
| `other_delivered` | object | 0.0% | #capacity+others+delivered+doses, 1,900,000, 80,000 |
| `total_delivered` | object | 0.0% | |
| `population_covered_two_dose` | object | 0.0% | |
| `deprecataed_other_delivered_source_country` | object | 64.5% | |
| `deprecataed_other_delivered_source_urls` | object | 71.0% | |
| `esa_source` | object | 0.0% | |
| `esa_processed` | object | 0.0% | |

---

## 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 HDX and has not been independently validated by ESA.
- Automated cleaning cannot correct for misreported values, definitional inconsistencies, or sampling bias in the original collection.
- The following columns have >20% missing values and should be treated with caution in modelling: `deprecataed_other_delivered_source_country`, `deprecataed_other_delivered_source_urls`.
- This dataset spans 26 countries; geographic and methodological inconsistencies across national boundaries may affect cross-country comparability.
- Refer to the [original HDX dataset page](https://data.humdata.org/dataset/covid-19-vaccine-doses-in-hrp-countries) for the publisher's own methodology notes and caveats.

---

## Citation

```bibtex
@dataset{hdx_africa_covid_19_vaccine_doses_in_hrp_countries,
title = {COVID-19 Vaccine Doses in HRP Countries},
author = {HDX},
year = {2026},
url = {https://data.humdata.org/dataset/covid-19-vaccine-doses-in-hrp-countries},
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.*