A multidisciplinary team that includes several Institute for Translational Medicine (ITM) leaders is receiving up to $250,000 for its collaborative research studying how social factors impact people’s health and diseases.
The award is from the new Discovery Challenge program from the University of Chicago’s Center for Data and Computing (CDAC) along with support from UChicago’s Office of Research and National Laboratories Joint Task Force Initiative. Funding is given to projects that will build partnerships, open-source software, and tools to fight challenging real-world problems.
Read an excerpt about the award given to the collaboration with ITM leaders below, and enjoy the full story about all the Discovery Challenge recipients here.
Source: CDAC
ADVancing the SOCiome For SociAl and HealTh Equity (ADVOCATE)
The Challenge: Social factors influence health and disease. How can we use them in data-driven medicine?
Samuel Volchenboum, Ellen Cohen, Stacy Lindau, David Meltzer, Doriane Miller, Lainie Ross, Julian Solway, and Dana Suskind, Medicine, all ITM leaders or investigators.
Luc Anselin, Center for Spatial Data Science
Kathleen Cagney, Sociology
Sanjay Krishnan, Pedro Lopes, and Anoop Mayampurath, Computer Science
Jonathan Ozik, Argonne
External Partnerships: Chicago Department of Public Health
Beyond the biological mechanisms of disease, social, environmental, behavioral, and psychological factors play a critical role in human health. These factors – that we collectively call the “sociome” – interact with human biology to cause or exacerbate disease and injuries and may disrupt wellness. But in contrast to genomic and clinical data, sociome factors have not been comprehensively collected, codified and quantified for the large-scale data mining and analysis techniques transforming modern healthcare.
This collaboration will build the scalable and extensible infrastructure and architecture that will ultimately assemble, quantify, and organize the entirety of social context experienced by every individual. Once catalogued, researchers can link this information to biologic and clinical data at individual and population scale to understand, predict, and treat health and health-related outcomes. A paradigm project will use this approach to build predictive models for children with asthma on the South Side of Chicago, hopefully leading to better immediate and long-term interventions to minimize disease severity.