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electricsheepasia/asia-who-number-of-malaria-positive-cases-by-microscopy

Africa — WHO GHO: Number of malaria positive cases by microscopy Indicator code: MALARIA_MICR_POS HuggingFace slug: electricsheepafrica/asia-who-number-of-malaria-positive-cases-by-microscopy Source: WHO Global Health Observatory License: CC BY 4.0 — WHO Open Data Dataset Description This dataset contains country-level observations for the WHO GHO indicator "Number of malaria positive cases by microscopy" (MALARIA_MICR_POS) across Asian nations, spanning… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepasia/asia-who-number-of-malaria-positive-cases-by-microscopy.

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Dataset Card

Africa — WHO GHO: Number of malaria positive cases by microscopy

Indicator code: MALARIA_MICR_POS HuggingFace slug: electricsheepafrica/asia-who-number-of-malaria-positive-cases-by-microscopy Source: WHO Global Health Observatory License: CC BY 4.0 — WHO Open Data

Dataset Description

This dataset contains country-level observations for the WHO GHO indicator "Number of malaria positive cases by microscopy" (MALARIA_MICR_POS) across Asian nations, spanning 2015–2024. It is part of the Electric Sheep Asia collection — a unified, ML-ready repository of African data.

Data is sourced directly from the WHO Global Health Observatory OData API and repackaged as Parquet files with a consistent schema. All values are drawn from NumericValue (the float-precision field), not the display string. Confidence interval bounds (value_low, value_high) are included where available.

Coverage

Countries31 Asian nations
Years2015 – 2024
Total rows263
Region filterWHO Asia regions (SEAR + WPR + EMR), filtered to Asian ISO3 codes

Countries included: AFG, ARM, AZE, BGD, BTN, CHN, GEO, IDN, IND, IRN, KAZ, KGZ, KHM, KOR, LAO, LKA, MMR, MYS, NPL, PAK … and 11 more

Sub-dimensions

No sub-dimensions (single value per country/year)

When an indicator is stratified (e.g., by sex or age group), each unique combination of country × year × dimension produces a separate row. Filter on dim1 / dim2 for the stratum you need, or aggregate across strata.

Schema

ColumnTypeDescription
indicator_codestringGHO indicator code (e.g., MALARIA_MICR_POS)
country_iso3stringISO 3166-1 alpha-3 country code
who_regionstringWHO region code (always AFR here)
yearintObservation year
value_numericfloatPoint estimate (primary ML target)
value_lowfloatLower confidence bound (if available)
value_highfloatUpper confidence bound (if available)
value_displaystringFormatted display string, e.g. "58.3 [57.7–59.0]"
dim1_typestringDimension 1 type, e.g. SEX, RESIDENCEAREATYPE
dim1stringDimension 1 value, e.g. SEX_BTSX, RURAL
dim2_typestringDimension 2 type (if present)
dim2stringDimension 2 value (if present)
last_updatedstringWHO data last-updated timestamp

Usage

python
from datasets import load_dataset

ds = load_dataset("electricsheepafrica/asia-who-number-of-malaria-positive-cases-by-microscopy")
df = ds["train"].to_pandas()

# Both-sexes, national level only
national = df[df.get("dim1", "").str.endswith("_BTSX") | df.get("dim1", pd.Series()).isna()]

# Time series for one country
kenya = df[df["country_iso3"] == "KEN"].sort_values("year")

Citation

bibtex
@misc{who_gho_malaria_micr_pos,
  title     = {WHO Global Health Observatory: Number of malaria positive cases by microscopy},
  author    = {World Health Organization},
  year      = {2024},
  url       = {https://www.who.int/data/gho/data/indicators/indicator-details/GHO/MALARIA_MICR_POS},
  note      = {Repackaged by Electric Sheep Asia}
}

Repackaged by [Electric Sheep Asia](https://huggingface.co/electricsheepasia) from WHO GHO open data. Original data © World Health Organization, licensed CC BY 4.0.