Research shows that people with low incomes and racial/ethnic minority populations experience greater levels of stress than their more affluent, white counterparts. This can lead to significant disparities in both mental and physical health that ultimately affect life expectancy and shows correlation with a reduction in household SES as paired with mental and physical health barriers. To learn more about stress responses and their direct implications in diverse communities, a microscale model was built to stimulate the simultaneous operations and interactions of multiple agents to re-create the predict the appearance of this complex phenomena. This model analyzed and visualized the complex dynamic systems of stress to understand how individual environment interactions influence decisions with the mesa documentation in python. The adaptive behavior of the model and its complex systems allows for non-linear causality: an environmental variation prompts the agents’ behavioral responses, which then feed back into additional environmental variations, and so on.

This project anticipated to be part of a step in a larger research agenda enabling local Chicago families to make healthier decisions, and enforcing public health departments across the country to give communities the resources to make positive changes.