Entry Date:
November 3, 2015

Underworlds: A Vast Reservoir of Information on Human Health and Behavior Lives in Our Sewage

Principal Investigator Eric Alm

Co-investigator Carlo Ratti


We imagine a future in which sewage is mined for real-time information that can inform policy makers, health practitioners, designers, and researchers alike.

Such is the idea behind Underworlds: a cross-disciplinary, open-data platform for monitoring urban health patterns, shaping more inclusive public health strategies, and pushing the boundaries of urban epidemiology. Pioneered by the Senseable City Lab and the Alm Lab, and sponsored by the MIT-Kuwait Center for Natural Resources and the Environment, a prototype smart sewage platform is being developed at MIT consisting of physical infrastructure, biochemical measurement technologies, and the down­stream computational tools and analytics necessary to interpret and act on our findings.

The Underworlds project is the first of its kind, and a proof of concept that cities can make use of their waste water system to do near real-time urban epidemiology and understand human health and behavior with a fine spatio-temporal resolution. Probably the most obvious first application of smart sewage technology is infectious disease surveillance, and the prediction of outbreaks.

Early warnings in relation to the presence of new flu strains in urban centers could significantly reduce a community’s medical costs and even help mitigate outbreaks. In addition, smart sewage could impact the way non-communicable diseases are studied, because biomarkers for diseases such as obesity and diabetes can be measured at unprecedented scale and temporal resolution.

The implications of this platform extend beyond just disease surveillance to the development of a new type of human population census. Analyzed in tandem with demographic data, this platform can study the aggregate health of a city to the particular health of a neighborhood.

Underworlds will study the urban geography, network topology, and demographic distribution in conjunction with wastewater loads over time, to propose and validate a model that informs wastewater sampling and correlates to target population samples. Together with the Depart­ment of Public Works, this work has already started in a pilot study in Cambridge.