epiworldRcalibrate

epiworldRcalibrate: Fast and Effortless Calibration of Agent-Based Models using Machine Learning

From the DESCRIPTION:

The 'epiworldRcalibrate' package provides tools and pre-trained Machine Learning [ML] models for calibration of Agent-Based Models [ABMs] built with the R package 'epiworldR'. It implements methods described in Najafzadehkhoei, Vega Yon, Modenesi, and Meyer (2025) doi:10.48550/arXiv.2509.07013. Using 'epiworldRcalibrate', users can automatically calibrate ABMs in seconds with its pre-trained ML models, effectively focusing on simulation rather than calibration. This tool bridges a gap by allowing public health practitioners to run their own ABMs without the advanced technical expertise often required by calibration.

epiworldRcalibrate provides fast, data-driven calibration of SIR epidemic parameters using a pretrained Bidirectional LSTM (BiLSTM) model. Given a single incidence time series, the package estimates:

• Transmission rate (ptran)
• Contact rate (crate)
• Basic reproduction number (R0)

The package is fully integrated with epiworldR and requires no external Python setup.