Agent-Based Simulation for Contact Tracing using Human Activity Data

The spread of the COVID-19 has added an unprecedented burden on the healthcare systems, daily lives, and economies around the world. A model from W.H.O indicates that the peak can come as late as July and other studies warn that COVID-19 could become a recurring disease, posting long-term uncertainties on our entire human society. Social contact has proven a contributor to the fast spread of COVID-19. As a result, social distancing and self-quarantine have been recommended or required in many states. This research project builds a large-scale, agent-based model (ABM) to simulate smartphone-assisted, privacy-preserving COVID-19 contact tracing. The goal of the project is to simulate how human contacts and voluntary contact tracing can impact the spread of COVID-19. The objectives of the project are: (1) building ABM platform to simulate social contacting in the U.S.; (2) processing and analyzing large-scale human mobility data into the ABM model; and (3) exploring voluntarily contact tracing and its impact on the spread of COVID-19. We especially focus on identifying the needed numbers of the population to adopt voluntarily tracing to reduce the spread of the coronavirus.