Grounded in social disorganization theory and its extensions (Johnson and Roman, 2022), I am interested in revealing the complex social pathways that offer ecological explanations for concentrated structural disparities in major public health challenges such as gun violence and air pollution. Across these projects, I draw on GIS and remote sensing tools together with geospatial modeling and spatial analysis to characterize the built and social environment and to test how it relates to health outcomes.
My earlier study of Syracuse gun violence found that annual gunshot counts summed across the city’s 133 census block groups exhibit a spatially clustered pattern, one that persisted throughout the 2009–2023 period, spanning both pre- and post-COVID-19 years. This persistence suggests that gun violence in Syracuse is rooted in entrenched social and economic disparities. Building on this finding, I used GIS-based spatial data integration alongside a variety of (geo)statistical and spatial modeling techniques to examine the relationship between social structural determinants, the urban built environment, and gun violence. The results identify two reliable predictors of Syracuse gunshot activity: sociodemographic disadvantage and time-lagged childhood lead poisoning rate. I am now investigating, through mediation modeling, the social and environmental processes that may explain these two predictors.
In a separate project, I am collaborating with a group of engineering scientists to predict the spatial distribution of air pollution across Syracuse resulting from highway construction, using a meso-scale CFD model. This work will provide a foundation for exploring the social processes that drive disproportionate air pollution exposure in socially deprived Syracuse neighborhoods.
I am also interested in how the urban built environment shapes urban microclimate, particularly through the urban heat island effect. This research relies on remote sensing imagery and GIS-based spatial analysis to derive parameters characterizing the three-dimensional properties of buildings within each census block group. Using Python algorithms I developed to automate these calculations, we examine the spatial patterns of these parameters in Syracuse—both present-day and historical—as well as in many other U.S. cities. We then establish associations between these built-form parameters and land surface temperature (derived from satellite remote sensing) as a function of city microclimate, a relationship we term the form-functional relationship.
Johnson, N. J., & Roman, C. G. (2022). Community correlates of change: A mixed-effects assessment of shooting dynamics during COVID-19. Plos One, 17(2), e0263777. https://doi.org/10.1371/journal.pone.0263777