The CONNECT Program was an integral part of our Institute for nearly 10 years. In November 2024, the program took an exciting step and transitioned into its own university center. The new Center for Computational and Social Sciences in Health (COMPASS) is led by Michelle Birkett, PhD, director, and Patrick Janulis, PhD, associate director. COMPASS is housed within the Institute for Artificial Intelligence in Medicine (I.AIM) at Feinberg School of Medicine.
About CONNECT
Directed by Michelle Birkett, PhD, the CONNECT Complex Systems and Health Disparities Research Program focused around elucidating the complex mechanisms driving the health disparities of stigmatized populations, in particular gender and sexual minorities. CONNECT built research capacity in this area by strategically growing an interdisciplinary cadre of scholars addressing issues health disparities from a systems perspective. Patrick Janulis, PhD, served as the program's associate director.
Why Complex Systems and Health Disparities?
Understanding the drivers of health disparities within populations is extremely complex – particularly within stigmatized populations, such as sexual and gender minorities. Health disparities have been suggested to occur because of intersecting individual, relational, and environmental processes caused by stigma, but little is known about the exact pathways. A complicating factor is that these pathways are often difficult to measure due to nonlinear relationships as well as time-delayed effects. Therefore it has been suggested that a systems science perspective must be used.
The term “systems science” refers here to a perspective in which the problem space is conceptualized as a system of interrelated component parts (i.e., the “big picture”). A systems science approach to health disparities is a major paradigm shift from focusing on one specific pathway toward focusing on how the entire system fits together to produce health disparities in a particular population.
This work requires a shift away from traditional statistical association analyses toward complex modeling approaches that can account for this complexity. These approaches include simulation modeling, machine learning, and network analysis. However, new analytic techniques alone are unlikely to yield high impact findings. This innovative approach requires transdisciplinary collaborations between health researchers, with in-depth knowledge of the population and systems under investigation, and investigators at the forefront of innovative data collection and analytic techniques. For example, health disparities often manifest via multiple negative health outcomes such as the syndemic health burden of HIV, drug use, violence, and mental health problems faced by young men who have sex with men (YMSM). Accordingly, system-level approaches are required to accurately model, understand, and alter these interconnected health disparities.
While operating as a research program at the Institute, CONNECT's projects included Network Canvas, the Bias in Big Data initiative, PLoT ME, and ChiSTIG.