Delineo: Data-Drive Simulation of COVID-19 Spread for Community-Level Decisions and Resilience

Team: CS Research Project (1)

Program: Computer Science

Current models of disease spread provide a limited understanding of the dynamics of contagion and typically don’t take into account the local variables of the geographic regions being studied, instead employing a generic, inflexible approach. The goal of our project is to create a highly scalable system that can be run across computing platforms to create a virtual simulation in which the spread of a disease can be observed and measured, along with studying the impact of various intervention and different types of events on the spread of the disease. The model envisions populations in terms of extremely localized and specific “modules” comprised of people, their dwellings, and shared community spaces.

Dr. Anton Dahbura

Team Members

  • Serena Chan
  • Mathias Insley

Project Links