epydemic: Epidemic simulations on networks in Python

epydemic is a library for performing simulations for a range of epidemic spreeading (and other) processes, simulated over networks represented using networkx.

Epidemic processes are very important in both network science and its applications. The most common application is to study the was in which diseases progress in different network conditions, depending on their infectiousness and other properties. Typically such processes are modelled as a compartmented model of disease with conditional probabilities for moving between compartments (familiar to computer scientists as stochastic finite state machines).

epydemic provides the basic simulation machinery for performing epidemic simulations under two different simulation regimes: synchronous discrete time simulation in which time proceeds in discrete time intervals, and stochastic or Gillespie continuous time simulations which are better for handling a wider range of event probabilities (but which are slightly harder to specify).