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EoN (Epidemics on Networks): a fast, flexible Python package for simulation, analytic approximation, and analysis of epidemics on networks

Joel C. Miller; Tony Ting

EoN is a python package designed for simulating contagion spread in static networks.  It was originally created as a supplement to the book "Mathematics of Epidemics on Networks" by Kiss, Miller, & Simon

It primarily focuses on stochastic SIS and SIR spread (both Markovian and non-Markovian), but it can also It also simulate many other contagious processes (if they are Markovian), including many complex contagions.  If the flag `return_full_data` is `False`, then the simulations return the time series counts of each status.  If it is `True`, then the simulations return the full data required to reconstruct the epidemic, including who infected whom.

In addition to the stochastic simulations, EoN provides about 20 ODE models which can be used to approximate SIS and SIR spread in networks.

The documentation is available at https://epidemicsonnetworks.readthedocs.io/en/latest/ (including instructions for installing the latest version).  A citable publication describing the software is (or will soon be) at https://doi.org/10.21105/joss.01731

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  • 10.1007/978-3-319-50806-1. Mathematics of Epidemics on Networks

  • http://conference.scipy.org/proceedings/SciPy2008/paper_2/. Networkx

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