Epydemix: An open-source Python package for epidemic modeling with integrated approximate Bayesian calibration.

ABSTRACT: We present Epydemix, an open-source Python package for the development and calibration of stochastic compartmental epidemic models. The framework supports flexible model structures that incorporate demographic information, age-stratified contact matrices, and dynamic public health interventions. A key feature of Epydemix is its integration of Approximate Bayesian Computation (ABC) techniques to perform parameter inference and model calibration through comparison between observed and simulated data. The package offers a range of ABC methods such as simple rejection sampling, simulation-budget-constrained rejection, and Sequential Monte Carlo (ABC-SMC). Epydemix is modular, and supports ABC-based calibration both for models defined within the package and for those developed externally. To de

SUBMITTER: Gozzi N 

PROVIDER: S-EPMC12654906 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature