GEMFsim: A stochastic simulator for the generalized epidemic modeling framework

• DOI: 10.1016/j.jocs.2017.08.014
• Publication Date: 2017-08-23T07:46:26Z
• Authors: Faryad Darabi Sahneh; Aram Vajdi; Heman Shakeri; Futing Fan; Caterina Scoglio
• Keywords: Social and Information Networks (cs.SI); FOS: Computer and information sciences; Physics - Physics and Society; 0103 physical sciences; FOS: Mathematics; FOS: Physical sciences; Computer Science - Social and Information Networks; Physics and Society (physics.soc-ph); Dynamical Systems (math.DS); Mathematics - Dynamical Systems; 01 natural sciences

The recently proposed generalized epidemic modeling framework (GEMF) \cite{sahneh2013generalized} lays the groundwork for systematically constructing a broad spectrum of stochastic spreading processes over complex networks. This article builds an algorithm for exact, continuous-time numerical simulation of GEMF-based processes. Moreover the implementation of this algorithm, GEMFsim, is available in popular scientific programming platforms such as MATLAB, R, Python, and C; GEMFsim facilitates simulating stochastic spreading models that fit in GEMF framework. Using these simulations one can examine the accuracy of mean-field-type approximations that are commonly used for analytical study of spreading processes on complex networks.