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.
- Event-based simulation
- Numerical solvers for ODE models
- pair approximation models
- effective degree models
- edge-based compartmental models