Supplementary material from "Simulating contact networks for livestock disease epidemiology: a systematic review"

Models simulating realistic contact networks therefore have important applications for generating insights relevant to livestock diseases. This systematic review identifies and compares such models, their applications, data sources, and how their validity was assessed.

From 52 publications, 37 models were identified comprising seven model frameworks. These included mathematical models (n = 8; including generalized random graphs, scale-free, Watts–Strogatz and spatial models), agent-based models (n = 8), radiation models (n = 1) (collectively, considered ‘mechanistic’), gravity models (n = 4), exponential random graph models (n = 9), other forms of statistical model (n = 6) (statistical) and random forests (n = 1) (machine learning).