Ecosystem¶

To support scalable epidemic modeling and research, the ecosystem is built on four independent repositories that can evolve independently:

Component	Role
epydemix	Epidemic modeling engine in Python with support for model calibration using Approximate Bayesian Computation
epymodelingsuite	YAML-configured modeling suite for routine epidemic forecasting with support for interventions like school closures and vaccines. Uses epydemix as engine.
epymodelingsuite-cloud	Cloud infrastructure and `epycloud` CLI for running parallel workloads on Google Cloud with local development support
Experiment data repository	YAML experiment configurations, shared surveillance data, and custom functions. Typically one per project (e.g. flu, COVID-19, RSV).

For detailed descriptions of each component, see Ecosystem Components.

Next Steps¶