From mobility to crime: Collective patterns of human mobility and gun violence in Baltimore City

Purpose: In this research, I investigated the link between collective mobility patterns—specifically inward population flow and residential mobility—and changes in reported gun violence incidents in Baltimore City. I also examined whether this relationship differs among various types of gun violence. Furthermore, I explored the potential moderating influence of collective mobility patterns on the relationship between neighborhood hotspot coverage and occurrences of gun violence.

Methods: The data were sourced from a blend of mobile device location data, Part 1 crime data from the Baltimore Police Department, the American Community Survey, and the zoning map of Baltimore. I used Poisson regression with Moran Eigenvector Spatial Filtering (MESF) for the analysis.

Results: Inward population flow consistently exhibited a positive relationship with gun violence regardless of its subtype, whereas residential mobility demonstrated significant influence primarily on firearm-related robbery incidents. Moderation analysis indicated that depending on the type of gun violence being assessed, either inward population flow or residential mobility could attenuate its association with neighborhoods' crime hotspot coverage.

Conclusions: Understanding collective mobility patterns is crucial for comprehending the spread of gun violence. Such insights can assist law enforcement agencies in refining hotspot policing strategies and adapting police tactics accordingly.