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Epydemix is an open-source Python package designed for flexible, modular, and data-driven epidemic modeling.

It supports the full modeling pipeline—from constructing stochastic compartmental models to running simulations, integrating real-world data, and calibrating parameters. Users can incorporate age-structured contact patterns, dynamic interventions, and population demographics with ease. Built-in Approximate Bayesian Computation (ABC) methods enable robust parameter estimation and model fitting, supporting forecasting, scenario exploration, and policy-relevant analyses. Epydemix bridges the gap between theoretical modeling and practical application, helping researchers and public health professionals translate models into actionable insights.