Research to Improve Health

To understand the drivers of population health, the systems around populations must be understood — as it is not individuals themselves, but the social and structural inequities individuals encounter in their everyday lives that shape their health.

This is a major paradigm shift from focusing on a single specific pathway toward considering how the entire system fits together to produce health inequities for a particular population. This work requires a shift toward complex modeling and computational approaches. It also requires new tools and methods for the capture, integration and analysis of rich social data necessary to understand systemic influences on individual health.

Through numerous studies, our team has been at the forefront of understanding of the social and structural drivers of population health via measurement tools, modeling and analysis, and the transdisciplinary integration of scientists and community members. Some of our current projects include:

• SILOS: Structural Inequities across Layers Of Social-Context as Drivers of HIV and Substance Use (R01DA061247)
• ChiSTIG: Simulation Modeling to Understand and Address HIV Disparities in Racial, Ethnic, and Sexual Minority Populations (R01MD014703)
• Caregiver: Measuring Caregiver Networks of Older Adults with Alzheimer's Disease (R01AG083034)
• Network Canvas (R01DA042711; ODSS Supplement to R34DA052216; and R01DA057973)
• PUG2: Leveraging Data Synthesis to Identify Optimal and Robust Strategies for HIV Elimination Among Substance-using MSM (R01DA055502)
• MCDC: Metropolitan Chicago Data-Science Corps (NSF Award Abstract # 2123447)