GEMFsim: A Stochastic Simulator for the Generalized Epidemic Modeling Framework

TL;DR

GEMFsim is a versatile stochastic simulation tool for the generalized epidemic modeling framework, enabling precise modeling of complex network spreading processes and evaluation of approximation methods.

Contribution

This paper introduces GEMFsim, an exact continuous-time simulation algorithm for GEMF-based processes, implemented across multiple programming platforms.

Findings

GEMFsim accurately simulates stochastic epidemic processes.

The tool helps assess the validity of mean-field approximations.

It supports diverse spreading models within the GEMF framework.

Abstract

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.