Simulation of an Infectious Process on Graphs

Contact: Paula Murmann


Take a simple undirected graph where nodes represent individuals and edges represent the contacts between them. On this graph we consider a SI (susceptible-infected) epidemic process. I.e., each node can be in a susceptible or infected state and nodes transition from the susceptible into the infected state if they get infected by a neighbour.

The goal of this project is to create a simulator of this process depending on the underlying structure and compare the infection model to more realistic real-world simulators (e.g.

Suggested steps:

  • Implement a simulator for the spreading process on a synthetic graph model

  • Test implementation on real world graph

  • Adapt published Covid simulator to problem parameters

  • Compare published simulator to theoretical simulator


  • Familiarity with random graph models, probability, sampling techniques

  • Strong programming skills & good code organisation/documentation/maintainability

  • Language: python or take this project as a chance to learn a new language

  • For published simulators, you will need to familiarise yourself with R