Data for: Calibration of individual-based models to epidemiological data: a systematic review

Calibrating or fitting an individual-based model (IBM) to data is a crucial step in model development. We performed a systematic review to provide an overview of calibration methods used in IBMs modelling infectious disease spread. We included articles if models stored individual-specific information and calibration involved running the model and comparing model output to population-level targets expressed as summary statistics. The dataset contains information for each of the included articles on model calibration methods, including; the parameter-search strategy, the goodness-of-fit measure, acceptance criteria, and stopping rules. Also, the dataset contains information on contextual variables for model calibration such as target statistics and parameters.