Urban Health Risk Mapping – Measuring the impact of neighborhood environments on personal health

This project developed an AI system that can measure the health effects of neighborhood environments in ten major US cities using citizen crowd-sourced data. The research team mapped the computed health risk scores at the census tract-level for all selected municipalities and also built an interactive website that allows users to understand how changes to their neighborhoods can affect their health. For example, if a user changes neighborhood sidewalk density, the website will show the expected changes in health behavior and outcomes, such as decreased physical activity level and increased diabetes risk. The research team will make the health risk map database available to the general public.

Speaker: Junfeng Jiao
Founding Director, Urban Information Laboratory