🌍 WHO GHO Health Indicators Scraper

🚀 Export the World Health Organization Global Health Observatory dataset in seconds. Browse 3,000+ health indicators or pull country, year, sex, and age-stratified facts for any indicator code. No API key, no manual SQL.

The WHO GHO Health Indicators Scraper exports the WHO Global Health Observatory, the reference dataset behind WHO's flagship reports on mortality, immunisation, non-communicable diseases, air pollution, mental health, maternal and child health, tuberculosis, malaria, HIV, and dozens more programmatic areas. Each fact record returns the indicator code, country, parent region, year, sex, age group, raw and numeric values, confidence-interval bounds, and methodological comments. Catalog records return the indicator code, name, and language only.

The catalog covers 3,058 indicators across 194 WHO member states and territories, with deep historical depth going back decades. Two run modes are supported: catalog mode lists every indicator code and name, indicator mode pulls every country-year-stratification fact for one indicator code so you can build dashboards, time series, and cross-country comparisons.

🎯 Target Audience	💡 Primary Use Cases
Epidemiologists, public-health researchers, global-health NGOs, health-policy analysts, data journalists, BI teams, ML researchers	Disease-burden modelling, health-policy analysis, comparative country studies, mortality trend tracking, SDG monitoring, ML training datasets

📋 What the WHO GHO Scraper does

Two run modes plus precise filters:

• 📚 Catalog mode. Returns every indicator (code + name) in the GHO, so you can discover what data exists before pulling it.
• 📊 Indicator mode. Returns every country-year-sex-age fact for a single indicator code, with confidence-interval bounds when published.
• 🌎 Country filter. Restrict to one or more ISO 3-letter country codes from the full WHO membership.
• 📅 Year range. Constrain to a yearFrom/yearTo window (e.g. last decade only).
• 🧮 Stratifications preserved. Sex (SEX_MLE, SEX_FMLE, SEX_BTSX), age groups (AGEGROUP_*), and parent regions all come through intact.

Each record includes the indicator code and name, the spatial dimension (country, region, world), the ISO-3 country code, the WHO parent region, the year, the sex and age stratification, the raw value (with confidence interval text), the numeric value, the low and high CI bounds, methodological comments, and the language of the record.

💡 Why it matters: the WHO GHO is the canonical reference for global health statistics, but the underlying data service is uneven across indicators and stratifications. Pulling indicator data manually means writing custom code for each topic. This Actor returns clean rows for any indicator in one call.

📊 Data fields

Each record includes: ageGroup, comments, countryCode, high, indicatorCode, indicatorName, language, low, numericValue, parentLocation, scrapedAt, sex, spatialDimType, value, year. These field names come straight from the actor's dataset schema, so what you see here is what lands in your dataset.

🚀 How to use

1. 📝 Sign up. Create a free account with $5 credit (takes 2 minutes).
2. 🌐 Open the Actor. Go to the WHO GHO Health Indicators Scraper page on the Apify Store.
3. 🎯 Set input. Start in catalog mode to discover indicators, then switch to indicator mode with a code.
4. 🚀 Run it. Click Start and let the Actor collect your data.
5. 📥 Download. Grab your results in the Dataset tab as CSV, Excel, JSON, or XML.

⏱️ Total time from signup to downloaded dataset: 3-5 minutes. No coding required.

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💡 Pro Tip: browse the complete ParseForge collection for more global-data scrapers.

⚠️ Disclaimer: this Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by the World Health Organization. All trademarks mentioned are the property of their respective owners. Only publicly available WHO GHO data is collected.

🆘 Need Help?

If you hit a bug, have questions about setup, or need a scraper we haven't built yet, open our contact form or write to parseforge@protonmail.com. We also take on paid custom data projects.

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