Skip to content

Predicting the Next Outbreak

Led by: Cordula Robinson (Kostas Research Institute), Dan O'Brien, Nick Beauchamp, and Ryan Wang

The project will use a variety of social media data describing greater Boston—including Twitter posts, Craigslist listings, and Yelp reviews—in conjunction with infection rates to identify “signals” that might indicate the emergence of an outbreak of COVID-19. This will be the basis of an automated real-time warning system that could support public health officials to respond proactively. This will be especially as we move into a new phase of the pandemic in which the expansion of vaccination has diminished the virus’ prevalence but not yet established herd immunity, meaning outbreaks will be sporadic and less predictable.

Related Research Centers

More Stories

High angle view of large group of students running through the school hallway. Blurred motion.

Why don’t high school bullies pick on someone their own size? Actually, they do.

Louisiana Abolitionist Ecologies: Upcoming Talk by Frances Roberts-Gregory highlights Social Justice and Interdisciplinary Methods

In this July 30, 2015 picture, a member of the Baltimore Police Department removes crime scene tape from a corner where a victim of a shooting was discovered in Baltimore.

Fostering community is the key to stopping group violence and fatal shootings

closeup of the hands of a young caucasian man with his hands clasped, in black and white

Labor trafficking impacts vulnerable U.S. citizens who often suffer in silence