The CrowdMeter Project

by Human Computation Institute
Team Lead: Pietro Michelucci

During a viral outbreak, it may be possible to substantially reduce transmission with minimal societal disruption by giving individuals behavioral alternatives with less associated risk. For example, if a person intends to shop for groceries, they might be motivated to drive the extra mile to a location with a lower likelihood of exposure. CrowdMeter is a navigation app that displays sets of similar destinations and the estimated transmission risk associated with each option. The team conducted epidemiological and behavioral simulations to inform the algorithms that power CrowdMeter’s deployment for the current COVID-19 outbreak.

Check out the CrowdMeter App
View the Project Results Two-Pager
View the Simulation Demo