Effect of concurrency on stochastic epidemic dydnamics in SIS and SIR models on networks

We provide here code to accompany the following paper:

R. Liu, M. Ogura, E. Fonseca dos Reis, N. Masuda. Effects of concurrency on epidemic spreading in Markovian temporal networks. Preprint on arXiv: arXiv:2201.00754

Jupyter notebook to create figures

figure_X.ipynb

contains the code to produce fig X in the manuscript, where $X = 2, 3, 4, 5, 6, 7$, and $8$. The folder notebooks/data/ contains the numerical results based on which Figures 5-8 are produced.

Python code for running stochastic SIS and SIR dynamics

The following Python codes are also included:

• SIS_Model_1prime.py -- to simulate the SIS model on networks with partnership model 1'.
• SIS_Model_2.py -- to simulate the SIS model on networks with partnership model 2.
• SIS_Model_1dprime.py -- to simulate the SIS model on networks with partnership model 1''.
• SIS_Model_3.py -- to simulate the SIS model on networks with partnership model 3.
• SIR_Model_1prime.py -- to simulate the SIR model on networks with partnership model 1'.
• SIR_Model_2.py -- to simulate the SIR model on networks with partnership model 2.
• SIR_Model_1dprime.py -- to simulate the SIR model on networks with partnership model 1''.
• SIR_Model_3.py -- to simulate the SIR model on networks with partnership model 3.