electricsheepafrica/africa-south-sudan-attacks-on-health-care-data-2cc994d9

Attacks On Health Care Data | Africa (Insecurity Insight)

1,603 rows - 1 Africa country/area - 2020-2023 - 19 indicators - Engineered by Electric Sheep Africa

TL;DR

This dataset contains 1,603 rows from Insecurity Insight, covering Attacks On Health Care Data. It is published as ML-ready Parquet with consistent Hugging Face metadata, source provenance, and analysis-friendly loading examples.

What This Dataset Measures

Health datasets help analysts monitor disease burden, service delivery, population health outcomes, and public-health program performance.

Source-provided context: Dataset covering 01 January 2020 to 31 December 2023 on incidents in which vital medicine and equipment were looted, stolen or seized in Burkina Faso, Mali and Niger based on agency- and open source events. Categorised by country.

How To Read This Dataset

• One row means: one indicator observation for one geography, time period, and optional source dimensions.
• Primary geography column: country_iso3.
• Best time column: year.
• Time coverage basis: year.
• Recommended join keys: country_iso3, year, indicator_id.

Coverage

Dimension	Value
Rows	1,603
Countries/areas	1
First period	2020
Last period	2023
Indicators	19
Columns	35
Source format	XLSX

Geographic Coverage

Top areas shown below, sorted by row count when available:

Area	Rows	First year	Last year	Name
SSD	1,603	2020	2023	South Sudan

Indicators, Variables, Or Resource Contents

• attacks-on-health-care-data-latitude-63d8779e - Attacks on Health Care Data - latitude(source_units_unspecified)
• attacks-on-health-care-data-longitude-39e0c687 - Attacks on Health Care Data - longitude(source_units_unspecified)
• attacks-on-health-care-data-number-of-attacks-on-health-facilities-repor-dc077d83 - Attacks on Health Care Data - number of attacks on health facilities reporting destruc(source_units_unspecified)
• attacks-on-health-care-data-number-of-attacks-on-health-facilities-repor-73a301de - Attacks on Health Care Data - number of attacks on health facilities reporting damaged(source_units_unspecified)
• attacks-on-health-care-data-forceful-entry-into-health-facility-b17f075d - Attacks on Health Care Data - forceful entry into health facility(source_units_unspecified)
• attacks-on-health-care-data-occupation-of-health-facility-5054425f - Attacks on Health Care Data - occupation of health facility(source_units_unspecified)
• attacks-on-health-care-data-vicinity-of-health-facility-affected-555626a8 - Attacks on Health Care Data - vicinity of health facility affected(source_units_unspecified)
• attacks-on-health-care-data-health-transportation-destroyed-65b81695 - Attacks on Health Care Data - health transportation destroyed(source_units_unspecified)
• attacks-on-health-care-data-health-transportation-damaged-9726b0d9 - Attacks on Health Care Data - health transportation damaged(source_units_unspecified)
• attacks-on-health-care-data-health-transportation-stolen-hijacked-64dc2d9f - Attacks on Health Care Data - health transportation stolen hijacked(source_units_unspecified)
• attacks-on-health-care-data-looting-theft-robbery-burglary-of-health-sup-42ba2b28 - Attacks on Health Care Data - looting theft robbery burglary of health supplies(source_units_unspecified)
• attacks-on-health-care-data-health-workers-killed-eeceb68a - Attacks on Health Care Data - health workers killed(source_units_unspecified)
• attacks-on-health-care-data-health-workers-injured-320b7e0d - Attacks on Health Care Data - health workers injured(source_units_unspecified)
• attacks-on-health-care-data-health-workers-kidnapped-a15a8c88 - Attacks on Health Care Data - health workers kidnapped(source_units_unspecified)
• attacks-on-health-care-data-health-workers-arrested-94fd5bff - Attacks on Health Care Data - health workers arrested(source_units_unspecified)
• attacks-on-health-care-data-health-workers-threatened-230ced0d - Attacks on Health Care Data - health workers threatened(source_units_unspecified)
• attacks-on-health-care-data-health-workers-assaulted-b3f0e74d - Attacks on Health Care Data - health workers assaulted(source_units_unspecified)
• attacks-on-health-care-data-health-workers-sexually-assaulted-97506c05 - Attacks on Health Care Data - health workers sexually assaulted(source_units_unspecified)
• attacks-on-health-care-data-sind-event-id-b89f151b - Attacks on Health Care Data - sind event id(source_units_unspecified)

Schema

Column	Type	Description	Example
indicator_id	string	Stable source or Electric Sheep Africa indicator identifier.	attacks-on-health-care-data-latitude-63d8779e
indicator_name	string	Human-readable indicator name.	Attacks on Health Care Data - latitude
country_iso3	string	ISO3 country or area code.	SSD
source_sheet	string	Source column from the original resource.	Sheet1
country_name	string	Country or area name.	South Sudan
year	int64	Observation year.	2023
value	double	Numeric observation value.	13.7840368
unit	string	Measurement unit, when supplied by the source.	source_units_unspecified
dimension_event_description	string	Source dimension retained during long-form normalization.	November 2023: A pharmaceutical warehouse was ransacked and medical s...
dimension_country	string	Source dimension retained during long-form normalization.	Burkina Faso
dimension_country_iso	string	Source dimension retained during long-form normalization.	BFA
dimension_admin_1	string	Source dimension retained during long-form normalization.	Sahel
dimension_geo_precision	string	Source dimension retained during long-form normalization.	(2) 25 km Precision
dimension_reported_perpetrator	string	Source dimension retained during long-form normalization.	NSA
dimension_reported_perpetrator_name	string	Source dimension retained during long-form normalization.	Islamic State of the Greater Sahara
dimension_weapon_carried_used	string	Source dimension retained during long-form normalization.	Firearms
dimension_location_of_incident	string	Source dimension retained during long-form normalization.	Health Building
dimension_access_denied_or_obstructed	string	Source dimension retained during long-form normalization.	False
dimension_known_kidnapping_or_arrest_outcome	string	Source dimension retained during long-form normalization.	``
dimension_conflict_related_violence	string	Source dimension retained during long-form normalization.	ConflictEvent
dimension_political_related_violence	string	Source dimension retained during long-form normalization.	NotApplicable
dimension_covid_19_related_violence	string	Source dimension retained during long-form normalization.	NotApplicable
dimension_ebola_related_violence	string	Source dimension retained during long-form normalization.	NotApplicable
dimension_vaccination_related_violence	string	Source dimension retained during long-form normalization.	NotApplicable
source_period_start_year	int64	Start year inferred from source metadata.	2020
source_period_end_year	int64	End year inferred from source metadata.	2023
source_period_label	dictionary<values=string, indices=int8, ordered=0>	Source column from the original resource.	2020-2023
source_provider	dictionary<values=string, indices=int8, ordered=0>	Publishing organization.	Insecurity Insight
source_dataset	dictionary<values=string, indices=int8, ordered=0>	Source dataset or package title.	Attacks on Health Care Data
source_resource	dictionary<values=string, indices=int8, ordered=0>	Source resource title, table name, or file name.	2020-2023 Looting of Health Supplies Across the Sahel Incident Data.xlsx
source_package_id	dictionary<values=string, indices=int8, ordered=0>	Source package identifier.	3777392b-8dc6-4615-ab1d-8ea136075d93
source_resource_id	dictionary<values=string, indices=int8, ordered=0>	Source resource identifier.	be27556e-791c-4371-bdd6-febf0e2f360d
source_url	dictionary<values=string, indices=int8, ordered=0>	Original source URL or download URL.	https://data.humdata.org/dataset/3777392b-8dc6-4615-ab1d-8ea136075d93...
license_id	dictionary<values=string, indices=int8, ordered=0>	Source license identifier.	cc-by-sa
retrieved_at	dictionary<values=string, indices=int8, ordered=0>	UTC source retrieval timestamp from the Electric Sheep Africa pipeline.	2026-08-10T18:18:23Z

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-south-sudan-attacks-on-health-care-data-2cc994d9")
df = ds["train"].to_pandas()
print(df.head())

Inspect Columns

print(df.info())
print(df.head())

Filter By Geography

if "country_iso3" in df.columns:
    sample = df[df["country_iso3"] == "SSD"]

Time-Series Pattern

if "value" in df.columns and "year" in df.columns:
    trend = df.sort_values("year")

Pivot For Analysis

if {"indicator_id", "year", "value"}.issubset(df.columns):
    matrix = df.pivot_table(index="year", columns="indicator_id", values="value")
    print(matrix.tail())

Data Quality Notes

• Canonical time field: year.
• Missing values are preserved rather than silently imputed.
• Column names are standardized for machine use; source meanings are preserved where known.
• Always confirm source methodology, units, and collection definitions before policy, production, or redistribution-sensitive use.

Source And Provenance

• Source: Insecurity Insight
• Publisher: Insecurity Insight
• Portal: https://data.humdata.org
• Resource: 2020-2023 Looting of Health Supplies Across the Sahel Incident Data.xlsx
• License: CC BY-SA 4.0
• Retrieved/generated: 2026-08-10T18:19:40Z
• Hugging Face repo: electricsheepafrica/africa-south-sudan-attacks-on-health-care-data-2cc994d9

Transformations Applied

• Converted the source table to Parquet for efficient analytics and ML workflows.
• Added or preserved source provenance columns where available.
• Standardized README metadata, dataset loading configuration, schema documentation, and citation format.
• Preserved source-reported values without analytical imputation.

Suggested Analyses

• Compare health outcomes across geographies
• Track changes over time
• Join with population or facility data
• Build time-series views and period-over-period comparisons
• Pivot to geography x period or indicator x period matrices
• Check missingness before modeling
• Use country_iso3 as the safest geography join key when present

Citation

@misc{electric_sheep_africa_africa_south_sudan_attacks_on_health_care_data_2cc994d9_2023,
  title        = {Attacks On Health Care Data | Africa (Insecurity Insight)},
  author       = {Insecurity Insight},
  year         = {2023},
  url          = {https://data.humdata.org/dataset/sind-safeguarding-healthcare-monthly-news-briefs-dataset},
  publisher    = {Hugging Face Datasets, engineered by Electric Sheep Africa},
  howpublished = {\url{https://huggingface.co/datasets/electricsheepafrica/africa-south-sudan-attacks-on-health-care-data-2cc994d9}}
}

License

Released under CC BY-SA 4.0.

Original data is published by Insecurity Insight. Electric Sheep Africa engineering standardizes the data for discovery, loading, and analysis on Hugging Face. Cite both the original source and this ML-ready dataset when used.

About Electric Sheep Africa

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

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Provenance: README standardized 2026-08-12 by the Electric Sheep Africa README system. Source URL: https://data.humdata.org/dataset/sind-safeguarding-healthcare-monthly-news-briefs-dataset