Longevity Simulator

A browser-based tool showing how curing diseases or slowing aging could change lifespan and healthspan for a U.S. resident. It's a static site with no backend: everything runs in the browser.

Data sources:

• CDC/NCHS United States Life Tables (2010–2019): mortality rates by age
• CDC Multiple Cause of Death database (2024): cause-of-death fractions by age
• IHME Global Burden of Disease (2023): chronic-condition prevalence by age

Run locally

cd web && python3 -m http.server 5180
# open http://127.0.0.1:5180

Any static file server works. Opening index.html directly from disk won't, because the page fetches data.json.

Deploy

Deploy web/ as a static site (on Vercel, set the project's Root Directory to web, with no framework and no build command).

Project structure

web/                  # The app (deployed as-is)
  index.html          # Layout and copy
  app.js              # UI wiring, charts (Plotly.js), CSV export
  model.js            # The simulation: cause removal, aging slowdown, survival, healthspan, Gompertz fit
  model.check.mjs     # Regression check for model.js: node web/model.check.mjs
  data.json           # Bundled runtime data, generated from data/
data/                 # Processed CSVs (committed)
preprocessing/        # Python scripts: raw_data/ -> data/ -> web/data.json
raw_data/             # Large raw source files (gitignored)

Updating the data

pip install -r requirements.txt
cd preprocessing && python process_life_table.py && python process_mmcd.py && cd ..
python preprocessing/export_web_data.py    # rebuilds web/data.json
node web/model.check.mjs                   # reference values may need updating if the data changed

See preprocessing/README.md for details on the raw data.

License

MIT License, see LICENSE.

Author

Alexander Epstein, Cao Lab, Rockefeller University