Objectives: This study uses two cluster detection techniques to identify clusters of violent crime during the 3 months of the 2020 COVID-19 lockdown in Miami-Dade County compared to that during an equivalent period in 2018 and 2019.
Methods: Violent crime data from the Miami-Dade Central Records Bureau were analyzed. The Local Indicators of Spatial Association statistics and a space-time permutation statistic were used to identify clusters of violent crimes and outliers, and Global Moran's I tool was used to assess spatial patterning in violent crime. Neighborhood disadvantage data were obtained from the American Community Survey 5-year estimates linked with arrest locations.
Results: Violent crime arrests fell by 7.1% in 2020. Arrests were concentrated in predominantly Black disadvantaged neighborhoods in the northern part, and similar results were produced for core clusters by the two cluster techniques with positive global Moran's I for all study years. Although accounting for only 17% of the county population, nearly half of violent crime arrests were for Black or African American. Males comprised most violent crime arrests.
Conclusions: Crime prevention and intervention efforts should be focused on both high-risk places and offenders.
Keywords: COVID-19; GIS; Geographic analysis; Miami-Dade County; Neighborhood Health; United States; Violence; Violent crime.
© The Author(s), under exclusive licence to Springer Nature B.V. 2021.