Blog Global Health Center

Modeling our future to build healthy, sustainable cities

Written by Maya Patel, BA candidate (2023) in anthropology: global health and environment at Washington University in St. Louis, and participant in the 2022 Institute for Public Health Research Program

As a student in the Summer Research Program’s Public and Global Health Track, I had the opportunity to attend a thought-provoking seminar with Deborah Salvo, PhD, assistant professor at the Brown School and co-director of the People, Health and Place Unit at the Prevention Research Center. Salvo’s work centers around understanding relationships between the built environment and physical activity, which we quickly learned works synergistically with the United Nation’s 11th Sustainable Development Goal (SDG): Make cities and human settlements inclusive, safe, resilient and sustainable.

For context on the utility of her research for achieving SDG 11, Salvo points to evidence indicating that the built and food environments of cities not only influence obesity-related behaviors but are also critical for sustainable development. Research on this subject informs policymakers on effective interventions that directly improve health outcomes and simultaneously promote sustainable development. These promising possibilities are best illustrated by Salvo’s research, of which she spoke to two recent projects.

The first study we discussed examined the impact of large-scale modifications to the built environment of cities on both physical activities and sustainable development outcomes. The researchers observed this through agent-based modeling, a simulation-based technique that uses computer science to essentially simulate a physical environment based on real-world data. Once this simulated environment is built, researchers can enact several scenarios and determine which is most effective in achieving the desired outcome.

Professor Salvo’s project modeled three types of cities: those of high, middle, and low-income countries. They ran several scenarios through the program, finding that a combination of physical activity strategies (i.e. reducing public transportation inequalities, adding public recreational spaces, encouraging cycling/walking) is most effective in combating the physical inactivity pandemic and working towards SDGs in low-and-middle-income city types. The study not only links physical activity and sustainable development but also underscores the need for the implementation of simultaneous interventions rather than one at a time.

Depiction of the three city types simulated in Salvo’s model.

Professor Salvo later walked us through another of her projects, which also utilizes an agent-based simulation— in this case to model the city of Austin’s food environment and spatial distribution of income. This project ran scenarios to identify the most effective strategy for increasing vegetable intake among low-income minority groups. The model found slight improvement with the general addition of more farm stands and mobile markets, but the most substantial increase in vegetable intake is observed when the number of farm stands is quadrupled and vegetables are discounted by 50 percent. A highly underutilized resource, these modeling systems are powerful, evidence-based tools that can provide policymakers with options for interventions. Relying on agent-based models significantly reduces the cost and risk associated with implementing urban large-scale policy changes, helping push us in the direction of lasting public health and sustainable development action.

Professor Salvo’s seminar unfolded the vast possibilities that model-based research holds. Healthy, sustainable cities are within reach— simulation research can be key to building the settlements we envision.