The CrowdMeter Project

by Human Computation Institute
Team Lead: Pietro Michelucci


During a viral outbreak, it may be possible to substantially reduce virus transmission with minimal societal disruption by informing individuals about behavioral alternatives and their associated risk profiles. For example, if a person intends to shop for groceries and is provided with alternative destinations that have lower exposure risks, they might be sufficiently motivated to drive an extra mile so they can shop at a location where they are less likely to become infected. One way of achieving this goal is through a navigation app, CrowdMeter, that displays the estimated transmission risks associated with a set of similar destinations.

This project investigates the potential impacts of this approach by conducting epidemiological and behavioral simulations to assess the range of conditions under which such an intervention would be effective. Simulation findings will be incorporated into the algorithms that power CrowdMeter in a near-term deployment to address the current COVID-19 outbreak.

Stay tuned for more information on this exciting project.


Check out the CrowdMeter App