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global-health-data

Retrieve and analyze global public health metrics via WHO GHO and IHME GBD datasets.

33|6|Updated Mar 17, 2026
Search Tags:#data analysis#epidemiology#choropleth mapping#global health#age-standardization#health inequality#WHO GHO API
One-click install
npx skills add https://github.com/xjtulyc/awesome-rosetta-skills --skill global-health-data
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: global-health-data
Source: https://github.com/xjtulyc/awesome-rosetta-skills/tree/main/skills/17-public-health/global-health-data
Command: npx skills add https://github.com/xjtulyc/awesome-rosetta-skills --skill global-health-data

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes assets (resource) components.

What problem does it solve?

This Skill streamlines the access, processing, and analysis of global public health datasets so you can compute burden-of-disease metrics, compare countries over time, and quantify health inequality.

Core Features & Use Cases

  • WHO GHO API ingestion: Query WHO Global Health Observatory indicators by indicator code, countries, years, and dimensions, returning a clean pandas DataFrame.
  • IHME GBD data retrieval (with fallback): Download Global Burden of Disease results via HealthData API when authenticated, or use a local CSV fallback when not.
  • Burden, standardization, and inequality analytics: Compute DALYs (DALYs = YLLs + YLDs), perform direct age-standardization with WHO standard weights, and estimate health inequality via concentration index calculations.
  • Global choropleth mapping: Generate publication-ready choropleth maps for country-level health indicators using geopandas.

Quick Start

Use the global-health-data skill to fetch a WHO indicator for selected countries and years, then compute and visualize a global choropleth for a chosen year.

Frequently Asked Questions about global-health-data

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I calculate DALYs from YLLs and YLDs for global health data?▼

Yes, you can generate publication-ready choropleth maps for country-level health indicators using geopandas. This Skill processes WHO GHO API and IHME datasets to create global choropleth visualizations across selected countries and years.

How do I perform direct age-standardization using WHO standard weights in Python?▼

Direct age-standardization in Python is performed by applying WHO standard weights to your health data. This Skill uses pandas and numpy to execute age-standardization workflows, normalizing health metrics across different populations for accurate cross-country comparisons over time.

Do I need an API key to fetch WHO GHO indicators and IHME GBD results?▼

Fetching WHO GHO indicators uses the WHO_API_KEY environment variable, while IHME GBD results require an IHME_API_TOKEN. If unauthenticated, this Skill provides a local CSV fallback to ensure you can still download and analyze Global Burden of Disease data.

What is the best way to measure health inequality using a concentration index?▼

Measuring health inequality with a concentration index involves quantifying the distribution of health metrics across ranked groups. This Skill streamlines this process by retrieving global public health datasets and estimating health inequality via concentration index calculations.

Can I query WHO Global Health Observatory indicators by country and year into a pandas DataFrame?▼

Querying WHO Global Health Observatory indicators by code, countries, and years returns a clean pandas DataFrame. This Skill ingests WHO GHO API data directly, allowing you to filter dimensions and retrieve structured data for immediate epidemiological analysis.

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