Treffer: Studies from Northeastern University Yield New Information about Science (Epydemix: An open-source Python package for epidemic modeling with integrated approximate Bayesian calibration).

The article focuses on the introduction of Epydemix, an open-source Python package designed for the development and calibration of stochastic compartmental epidemic models. Developed by researchers at Northeastern University, the package incorporates demographic data, age-stratified contact matrices, and dynamic public health interventions, utilizing Approximate Bayesian Computation (ABC) techniques for model calibration. Funded by the CDC's Center for Forecasting and Outbreak Analytics and Fondazione CRT, Epydemix aims to make epidemic modeling more accessible to a diverse range of users, including academic researchers and public health professionals. The article also discusses practical applications of the package, including intervention-driven simulations and benchmarking calibration performance. [Extracted from the article]

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