Algorithms for epidemic contact tracing on networks


Description of the problem

Managing a global epidemic is a difficult task. This is especially true in COVID-19, where not every individual develops severe symptoms and it is difficult to track the spread of the epidemic. Besides costly population-wide lockdowns, the main tool to mitigate the epidemic spread is (centralized or decentralized) contact tracing. The effectiveness of contact tracing varies a lot from country to country. This is probably because different countries allocate different amounts of resources and implement different strategies to track the spread of the disease. In the INDY lab, we have developed a toy model that aims to capture many of the challenges of (centralized) contact tracing. An interactive version of the model is available online at the website: The goal of the project is to develop heuristics to play this “game” and find out which heuristics work best under which problem parameters. Since this is a toy model, the project has more educational than scientific value. As an optional extension, the toy model can also be connected with the scientific literature, in which case the project could result in a publication.

Due to COVID-19, the project will be supervised online.

Learning outcomes

The project is already well-defined and does not require too many resources or domain-specific knowledge. This way, the student can play with the model and contribute creative ideas starting from the first week. Over the course of the semester, the student will become familiar with standard methods to model and control epidemics.


  • Strong programming skills (python)
  • An interest in developing new algorithms