- Chart data
- Total extreme poverty living in extreme poverty by world reg
Total extreme poverty living in extreme poverty by world region, 1990 to 2040
The numbers behind a chart Our World in Data published, redrawn natively. Check the original, study the data, then make your own.
Simplified redraw
Drawn by us from the numbers below. Hover, tap or use the arrow keys.A simplified redraw: it shows the numbers in our own look, not the look of the original. One accent marks what the chart is about. Values marked with ~ in the table are estimates.
The numbers
First 10 of 77 points are free| Group | Series | Value (billion) | Source | Conf. |
|---|---|---|---|---|
| 1990 | South Asia (WB) | ~1.3 | Estimate | 0.30 |
| 1990 | East Asia and Pacific (WB) | ~0.4 | Estimate | 0.30 |
| 1990 | Sub-Saharan Africa and Pakistan (WB) | ~0.2 | Estimate | 0.30 |
| 1990 | MENA, Afghanistan and Pakistan (WB) | ~0.1 | Estimate | 0.30 |
| 1990 | Latin America and Caribbean (WB) | ~0.05 | Estimate | 0.80 |
| 1990 | Europe and Central Asia (WB) | ~0.02 | Estimate | 0.80 |
| 1990 | North America (WB) | ~0.01 | Estimate | 0.80 |
| 1995 | South Asia (WB) | ~1.2 | Estimate | 0.30 |
| 1995 | East Asia and Pacific (WB) | ~0.4 | Estimate | 0.30 |
| 1995 | Sub-Saharan Africa and Pakistan (WB) | ~0.2 | Estimate | 0.30 |
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| 1995 | MENA, Afghanistan and Pakistan (WB) | ~0.1 | Estimate | 0.30 |
|---|---|---|---|---|
| 1995 | Latin America and Caribbean (WB) | ~0.05 | Estimate | 0.80 |
| 1995 | Europe and Central Asia (WB) | ~0.02 | Estimate | 0.80 |
| 1995 | North America (WB) | ~0.01 | Estimate | 0.80 |
| 2000 | South Asia (WB) | ~1.1 | Estimate | 0.30 |
| 2000 | East Asia and Pacific (WB) | ~0.3 | Estimate | 0.30 |
| 2000 | Sub-Saharan Africa and Pakistan (WB) | ~0.2 | Estimate | 0.30 |
| 2000 | MENA, Afghanistan and Pakistan (WB) | ~0.1 | Estimate | 0.30 |
| 2000 | Latin America and Caribbean (WB) | ~0.05 | Estimate | 0.80 |
| 2000 | Europe and Central Asia (WB) | ~0.02 | Estimate | 0.80 |
| 2000 | North America (WB) | ~0.01 | Estimate | 0.80 |
| 2005 | South Asia (WB) | ~0.9 | Estimate | 0.30 |
| 2005 | East Asia and Pacific (WB) | ~0.2 | Estimate | 0.30 |
| 2005 | Sub-Saharan Africa and Pakistan (WB) | ~0.2 | Estimate | 0.30 |
| 2005 | MENA, Afghanistan and Pakistan (WB) | ~0.1 | Estimate | 0.30 |
| 2005 | Latin America and Caribbean (WB) | ~0.05 | Estimate | 0.80 |
| 2005 | Europe and Central Asia (WB) | ~0.02 | Estimate | 0.80 |
| 2005 | North America (WB) | ~0.01 | Estimate | 0.80 |
| 2010 | South Asia (WB) | ~0.7 | Estimate | 0.30 |
| 2010 | East Asia and Pacific (WB) | ~0.2 | Estimate | 0.30 |
| 2010 | Sub-Saharan Africa and Pakistan (WB) | ~0.2 | Estimate | 0.30 |
| 2010 | MENA, Afghanistan and Pakistan (WB) | ~0.1 | Estimate | 0.30 |
| 2010 | Latin America and Caribbean (WB) | ~0.05 | Estimate | 0.80 |
| 2010 | Europe and Central Asia (WB) | ~0.02 | Estimate | 0.80 |
| 2010 | North America (WB) | ~0.01 | Estimate | 0.80 |
| 2015 | South Asia (WB) | ~0.5 | Estimate | 0.30 |
| 2015 | East Asia and Pacific (WB) | ~0.1 | Estimate | 0.30 |
| 2015 | Sub-Saharan Africa and Pakistan (WB) | ~0.2 | Estimate | 0.30 |
| 2015 | MENA, Afghanistan and Pakistan (WB) | ~0.1 | Estimate | 0.30 |
| 2015 | Latin America and Caribbean (WB) | ~0.05 | Estimate | 0.80 |
| 2015 | Europe and Central Asia (WB) | ~0.02 | Estimate | 0.80 |
| 2015 | North America (WB) | ~0.01 | Estimate | 0.80 |
| 2020 | South Asia (WB) | ~0.4 | Estimate | 0.30 |
| 2020 | East Asia and Pacific (WB) | ~0.1 | Estimate | 0.80 |
| 2020 | Sub-Saharan Africa and Pakistan (WB) | ~0.2 | Estimate | 0.30 |
| 2020 | MENA, Afghanistan and Pakistan (WB) | ~0.1 | Estimate | 0.30 |
| 2020 | Latin America and Caribbean (WB) | ~0.05 | Estimate | 0.80 |
| 2020 | Europe and Central Asia (WB) | ~0.02 | Estimate | 0.80 |
| 2020 | North America (WB) | ~0.01 | Estimate | 0.80 |
| 2025 | South Asia (WB) | ~0.3 | Estimate | 0.80 |
| 2025 | East Asia and Pacific (WB) | ~0.1 | Estimate | 0.80 |
| 2025 | Sub-Saharan Africa and Pakistan (WB) | ~0.2 | Estimate | 0.30 |
| 2025 | MENA, Afghanistan and Pakistan (WB) | ~0.1 | Estimate | 0.30 |
| 2025 | Latin America and Caribbean (WB) | ~0.05 | Estimate | 0.80 |
| 2025 | Europe and Central Asia (WB) | ~0.02 | Estimate | 0.80 |
| 2025 | North America (WB) | ~0.01 | Estimate | 0.80 |
| 2030 | South Asia (WB) | ~0.2 | Estimate | 0.30 |
| 2030 | East Asia and Pacific (WB) | ~0.1 | Estimate | 0.80 |
| 2030 | Sub-Saharan Africa and Pakistan (WB) | ~0.2 | Estimate | 0.30 |
| 2030 | MENA, Afghanistan and Pakistan (WB) | ~0.1 | Estimate | 0.30 |
| 2030 | Latin America and Caribbean (WB) | ~0.05 | Estimate | 0.80 |
| 2030 | Europe and Central Asia (WB) | ~0.02 | Estimate | 0.80 |
| 2030 | North America (WB) | ~0.01 | Estimate | 0.80 |
| 2035 | South Asia (WB) | ~0.2 | Estimate | 0.30 |
| 2035 | East Asia and Pacific (WB) | ~0.1 | Estimate | 0.80 |
| 2035 | Sub-Saharan Africa and Pakistan (WB) | ~0.2 | Estimate | 0.30 |
| 2035 | MENA, Afghanistan and Pakistan (WB) | ~0.1 | Estimate | 0.30 |
| 2035 | Latin America and Caribbean (WB) | ~0.05 | Estimate | 0.80 |
| 2035 | Europe and Central Asia (WB) | ~0.02 | Estimate | 0.80 |
| 2035 | North America (WB) | ~0.01 | Estimate | 0.80 |
| 2040 | South Asia (WB) | ~0.2 | Estimate | 0.30 |
| 2040 | East Asia and Pacific (WB) | ~0.1 | Estimate | 0.80 |
| 2040 | Sub-Saharan Africa and Pakistan (WB) | ~0.2 | Estimate | 0.30 |
| 2040 | MENA, Afghanistan and Pakistan (WB) | ~0.1 | Estimate | 0.30 |
| 2040 | Latin America and Caribbean (WB) | ~0.05 | Estimate | 0.80 |
| 2040 | Europe and Central Asia (WB) | ~0.02 | Estimate | 0.80 |
| 2040 | North America (WB) | ~0.01 | Estimate | 0.80 |
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On the Max plan you can pull this chart's numbers with the provenance of each one, as JSON or CSV, with its redraw spec, or call it from an agent over MCP. Chart id 62782d46a3a9.
| Path | Returns | Plan | |
|---|---|---|---|
| GET | /api/v1/charts/62782d46a3a9 | Title, publisher, date, form, point count; with a Max key, the data link | Open |
| GET | /api/v1/charts/62782d46a3a9/data | Every point with its provenance and confidence, plus the redraw spec. Add ?format=csv for CSV | Max |
| GET | /api/v1/charts/62782d46a3a9/render?view=1 | The draw-only view this page uses | Open |
| POST | /mcp | Tool get_chart_data with this id, for Claude, Cursor and other agents | Max |
curl -s https://viral-chart.com/api/v1/charts/62782d46a3a9/data \
-H "Authorization: Bearer $VIRALCHART_KEY"claude mcp add --transport http viralchart https://viral-chart.com/mcp \
--header "Authorization: Bearer $VIRALCHART_KEY"60 requests a minute per key; over that you get 429 with Retry-After. Up to 5 keys per account, made on your account page and shown once. Without Max, the data route answers 402 with a link to the plans. The numbers describe a chart its publisher owns, and every file carries a license note.
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How accurate are these numbers?
They are estimated from the image by two independent passes, with confidence 0.55 on a 0 to 1 scale. Printed numbers read well; values read off an axis can be a few percent off.
Can I reuse this data?
The numbers describe a chart that Our World in Data published. The image, layout and styling belong to them. Use the numbers with a credit to the publisher, and make your picture from your own data.
How do I get the file?
The JSON, CSV and agent skill file are under the email gate on this page. In this prototype they are static files at /api/charts/62782d46a3a9.json and /api/charts/62782d46a3a9.skill.md.