Welcome to Epidemics on Networks’s documentation!¶
EoN (Epidemics on Networks) is a Python module that provides tools to study the spread of SIS and SIR diseases in networks.
- Support EoN:
The best way to support EoN is to cite EoN’s publication
The next best option is to let me know you’re using it.
Both of these will help my case when applying for grants & promotions and help me justify the time I spend on it.
MIT License:
See license.txt for
full details.
Highlights¶
EoN is based on the book
Mathematics of Epidemics on Networks: from Exact to Approximate Models
EoN is built on top of NetworkX. Its repository is on github. EoN’s tools fall into two broad categories:
Stochastic simulation of SIS and SIR disease
Event-based simulation
much faster than traditional Gillespie simulation
allows weighted graphs
allows non-Markovian dynamics
Gillespie algorithms for Markovian dynamics
Through some careful optimization the unweighted SIS/SIR versions are comparable to the event-based simulation.
The weighted version is slower, but still reasonably fast.
There are methods for generic simple contagions and generic complex contagions.
discrete-time (synchronous update) models
tools for visualizing and animating simulated epidemics.
Numerical solvers for ODE models
pair approximation models
effective degree models
edge-based compartmental models