Release Notes
Release notes for the epydemix WebAPI per version. Mirrors the GitHub Releases page.
v0.7.2 (2026-05-20)
- Faster simulations (~2.7x) with identical output, via an engine upgrade and population caching
- Upgraded epydemix to v1.2.1
- Built-in population data is now cached across requests
- Deployment: Python 3.13 image, configurable
PORT, Cloud Run guide
v0.7.1 (2026-05-19)
- New interactive
/playgroundpage with a request editor and response viewer with plots - V-SEIHR now ships a default initial condition
- Bug fixes in V-SEIHR response metadata
- Documentation improvements: initial conditions page, parameterization options, UI refinements
- Expanded test coverage: SIR dynamics, parameter transforms, initial conditions
v0.7.0 (2026-05-18)
- New
V-SEIHRmodel preset with a vaccinated branch andVE_S/VE_Hefficacy parameters - New top-level
vaccinationblock: campaigns, age targeting, dose-sink flows, multi-target rollouts - Per-preset registry: each preset owns its parameter conversions and defaults
v0.6.0 (2026-05-13)
- Calculated parameters: arithmetic expressions in
model.parameters - Reserved name
CONTACT_MATRIX_EIGENVALUE_ALLfor calibration - Population metadata regenerated to match upstream subnational naming
v0.5.1 (2026-05-04)
- Detailed documentation on populations, including overview, presets, and customizations
- Dependency updates
v0.5.0 (2026-05-04)
- Support custom populations in simulation endpoint
v0.4.1 (2026-05-01)
- Improve AI integration: MCP server,
llms.txt/llms-full.txt, markdown content negotiation, per-page Copy / Open in chat widget max_valuein seasonality is now optional (default1.0)
v0.3.0 (2026-05-01)
- Add parameter transformations: seasonality (
balcan),scale,override. (Breaking:parameter_overridesmoved intoparameter_transforms) - Support age-varying parameters
- Return effective parameter values in results
- Responses are now compressed in gzip
- Improve agent discoverability
v0.2.2 (2026-04-24)
- Substantial API reshape from v0.1.1; includes breaking changes
- Simulation metadata is now nested into
model/population/simulationsections that mirror the request shape results.summaryis returned by default and nested by age group with aquantilesdict- Population endpoints:
total_populationreturned for every location,age_groupsis now a flat{label: count}dict, newage_distributionfield with raw single-year counts