fccoelho

fccoelho / epidemiological-datasets

Public

A curated collection of openly accessible epidemiological datasets from around the world with Python access scripts

12
2
100% credibility
Found Mar 19, 2026 at 12 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

Curated collection of global epidemiological datasets with user-friendly Python tools for accessing and exploring public health statistics.

How It Works

1
🔍 Discover health data collection

You stumble upon a friendly guide to free health and disease data from countries worldwide, organized by region like Americas or Europe.

2
📋 Browse datasets

Pick interesting topics like outbreaks, vaccinations, or mortality stats from sources like WHO or Brazil's health system.

3
💡 Grab your first dataset

Follow a simple example to pull real data on something like dengue cases or life expectancy – it feels effortless and exciting.

4
📊 Explore and analyze

See ready-made notebooks that turn numbers into charts, comparing countries or tracking trends over years.

5
💾 Save your findings

Export clean tables ready for reports, studies, or sharing with your team.

🎉 Insights unlocked

Now you have reliable health data at your fingertips, powering your research, stories, or decisions.

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Star Growth

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AI-Generated Review

What is epidemiological-datasets?

This Python repo delivers a curated collection of openly accessible epidemiological datasets from around the world, bundled with scripts for seamless data access. It pulls from sources like WHO, PAHO, Eurostat, OWID, Africa CDC, and national systems (Brazil DATASUS, Colombia INS), outputting clean pandas DataFrames for analysis. Developers get a github curated list that skips manual API wrangling or scraping, focusing on reproducible epi research.

Why is it gaining traction?

Unlike scattered data portals, it standardizes heterogeneous feeds into one accessible collection, with ready-to-run examples for multi-source comparisons like COVID trends or vaccination rates. The MIT license, example notebooks, and CI/CD setup make it a low-friction entry for global health pulls. Niche hooks like region-specific access (Africa, Europe, Americas) draw users tired of siloed github curated lists.

Who should use this?

Public health analysts tracking outbreaks across continents, infectious disease modelers needing quick WHO/PAHO pulls, or data scientists comparing regional mortality via Eurostat/OWID. Ideal for researchers prototyping epi dashboards or validating models with real-time accessible datasets from underrepresented areas like Africa CDC or South America.

Verdict

Grab it for targeted epi data access if you're in public health—docs and examples shine despite 12 stars and 1.0% credibility score signaling early maturity. Contribute access scripts to boost it; solid foundation for a true github curated list.

(198 words)

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