Data Visualization of Agent-Based Modeling of Virus Spread

We present a novel data visualization that displays the contact trace of the spread of an infection. This visualization presents the spread as a radial organizational chart, where each node is an infected person, and the distance from the root to a node is proportional to time. We use real registration information for a population of students at a small college to generate a social network that is fed to an agentbased simulator. The simulation implements the SIR model to control how the infection moves from individual to another. Contrarily to other models that generate expected quantities, our tool displays scenarios of a typical outbreak, where individual involved in the spread are identified, along with the trace of their infection. The usefulness of our tool is in illustrating at the micro level phenomena such as the appearance of super-spreaders, or the influence of interventions such as quarantine or vaccination. We present several visualizations corresponding to different SIR parameters, and also illustrating the effect of vaccination.