Estimated malaria incidence (per 1000 population at risk)

Name: Estimated malaria incidence (per 1000 population at risk)
Creator: WHO Global Health Observatory
License: https://www.who.int/about/policies/terms-of-use
Keywords: malaria, incidence, who

Estimated malaria incidence (per 1000 population at risk) Source: WHO Global Health Observatory (indicator MALARIA_EST_INCIDENCE). Rows are country x year; sex-disaggregated rows carry a sex label.

Source: WHO Global Health Observatory2,680 lignesMis à jour: 21/09/2026

malariaincidencewho

Qualité

Attribution

World Health Organization (WHO)

Schéma

Colonne	Type	Description
country_code	string	Country code (WHO GHO API field SpatialDim, country-level rows only).
country_name	string	Country name from the WHO GHO COUNTRY dimension labels.
year	integer	Year of observation (WHO GHO API field TimeDim).
value	float	Estimate value for the country, year (and sex where present), as defined by the WHO GHO indicator (see the dataset description; WHO GHO API field NumericValue).
low	float	Lower bound of the published uncertainty interval (WHO GHO API field Low). Only present when the indicator publishes uncertainty intervals.
high	float	Upper bound of the published uncertainty interval (WHO GHO API field High). Only present when the indicator publishes uncertainty intervals.

Exemple de lignes

country_code	country_name	year	value	low	high
AFG	AFG	2000	84.47579881	54.25512883	130.1220417
AFG	AFG	2001	83.83453346	54.22209176	128.1355109
AFG	AFG	2002	83.78813399	55.50926617	127.6064756
AFG	AFG	2003	70.81400733	46.16021887	109.1417015
AFG	AFG	2004	39.41327514	26.39863434	58.92526626

Utiliser avec un LLM

Dirigez n’importe quel LLM vers le point d’accès des métadonnées — la documentation ci-dessus est aussi lisible par machine (JSON-LD + Croissant).

cURL

curl "https://datazimuts.com/v1/datasets/who_gho/malaria_incidence" | jq '{title, rows, columns_count, license}'

Python

import requests

ds = requests.get("https://datazimuts.com/v1/datasets/who_gho/malaria_incidence").json()
print(ds["title"], ds["rows"], "rows")

# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
    print(row)

Point d’accès API: https://datazimuts.com/v1/datasets/who_gho/malaria_incidence

Astuce : récupérez /llms.txt pour le catalogue complet lisible par machine.