electricsheepafrica/africa-ebola-cases-and-deaths-drc-north-kivu

Ebola Cases and Deaths in the North Kivu Ebola Outbreak in the Democratic Republic of the Congo (DRC)

Publisher: HDX · Source: HDX · License: cc-by-igo · Updated: 2025-09-06

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Abstract

This Ebola epidemic dataset contains figures on the Ebola cases, deaths and cures in the North Kivu Ebola outbreak of August 2018 in the Democratic Republic of the Congo (DRC).

Each row in this dataset represents country-level aggregates. Temporal coverage is indicated by the publication_date, report_date column(s). Geographic scope: COD.

Curated into ML-ready Parquet format by Electric Sheep Africa.

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Dataset Characteristics

Domain	Public health
Unit of observation	Country-level aggregates
Rows (total)	591
Columns	19 (13 numeric, 4 categorical, 2 datetime)
Train split	472 rows
Test split	118 rows
Geographic scope	COD
Publisher	HDX
HDX last updated	2025-09-06

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Variables

Geographic — country (COD, #adm0 +code).

Temporal — publication_date, report_date.

Outcome / Measurement — confirmed_cases (range 13.0–3317.0), probable_cases (range 3.0–146.0), total_cases (range 34.0–3463.0), confirmed_deaths (range 3.0–2134.0), total_deaths (range 14.0–2280.0) and 8 others.

Identifier / Metadata — source (https://www.who.int/emergencies/diseases/ebola/drc-2019/ebola-daily-case-numbers, https://mailchi.mp/sante.gouv.cd/ebola_kivu_17jan19, https://mailchi.mp/1e3193ca85b8/situation-pidmiologique-du-16-janvier-2020?e=66a89c0f39), esa_source (HDX), esa_processed (2026-04-05).

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Quick Start

from datasets import load_dataset

ds    = load_dataset("electricsheepafrica/africa-ebola-cases-and-deaths-drc-north-kivu")
train = ds["train"].to_pandas()
test  = ds["test"].to_pandas()

print(train.shape)
train.head()

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Schema

Column	Type	Null %	Range / Sample Values
publication_date	datetime64[ns]	0.2%
report_date	datetime64[ns]	0.2%
country	object	0.0%	COD, #adm0 +code
confirmed_cases	float64	0.2%	13.0 – 3317.0 (mean 1732.2271)
probable_cases	float64	0.2%	3.0 – 146.0 (mean 79.2288)
total_cases	float64	0.2%	34.0 – 3463.0 (mean 1811.4661)
confirmed_deaths	float64	0.2%	3.0 – 2134.0 (mean 1115.1983)
total_deaths	float64	0.3%	14.0 – 2280.0 (mean 1196.1104)
total_suspected_cases	float64	11.5%	0.0 – 600.0 (mean 253.5698)
new_deaths	float64	78.3%	0.0 – 9.0 (mean 2.1094)
confirmed_cases_change	float64	2.0%	-1.0 – 27.0 (mean 5.5993)
probable_cases_change	float64	2.0%	-1.0 – 22.0 (mean 0.1848)
total_cases_change	float64	2.0%	-1.0 – 45.0 (mean 5.7841)
confirmed_deaths_change	float64	2.0%	-15.0 – 26.0 (mean 3.6079)
total_deaths_change	float64	2.4%	-13.0 – 31.0 (mean 3.7955)
total_suspected_cases_change	float64	13.0%	-539.0 – 357.0 (mean 0.7237)
source	object	0.0%	https://www.who.int/emergencies/diseases/ebola/drc-2019/ebola-daily-case-numbers, https://mailchi.mp/sante.gouv.cd/ebola_kivu_17jan19, https://mailchi.mp/1e3193ca85b8/situation-pidmiologique-du-16-janvier-2020?e=66a89c0f39
esa_source	object	0.0%	HDX
esa_processed	object	0.0%	2026-04-05

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Numeric Summary

Column	Min	Max	Mean	Median
confirmed_cases	13.0	3317.0	1732.2271	1720.5
probable_cases	3.0	146.0	79.2288	88.0
total_cases	34.0	3463.0	1811.4661	1808.5
confirmed_deaths	3.0	2134.0	1115.1983	1115.5
total_deaths	14.0	2280.0	1196.1104	1209.0
total_suspected_cases	0.0	600.0	253.5698	267.0
new_deaths	0.0	9.0	2.1094	2.0
confirmed_cases_change	-1.0	27.0	5.5993	4.0
probable_cases_change	-1.0	22.0	0.1848	0.0
total_cases_change	-1.0	45.0	5.7841	4.0
confirmed_deaths_change	-15.0	26.0	3.6079	2.0
total_deaths_change	-13.0	31.0	3.7955	3.0
total_suspected_cases_change	-539.0	357.0	0.7237	0.0

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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. 4 column(s) with >80% missing values were removed: new_cured, total_cured, new_suspected_cases, old_suspected_cases. 15 column(s) were cast from string to numeric or datetime based on parse-success rate (>85% threshold). The dataset was split 80/20 into train and test partitions using a fixed random seed (42) and saved as Snappy-compressed Parquet.

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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: new_deaths.
• Refer to the original HDX dataset page for the publisher's own methodology notes and caveats.

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Citation

@dataset{hdx_africa_ebola_cases_and_deaths_drc_north_kivu,
  title     = {Ebola Cases and Deaths in the North Kivu Ebola Outbreak in the Democratic Republic of the Congo (DRC)},
  author    = {HDX},
  year      = {2025},
  url       = {https://data.humdata.org/dataset/ebola-cases-and-deaths-drc-north-kivu},
  note      = {Repackaged for machine learning by Electric Sheep Africa (https://huggingface.co/electricsheepafrica)}
}

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Electric Sheep Africa — Africa's ML dataset infrastructure. Lagos, Nigeria.