Abstract

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.

中文翻译：

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2018-2020 年佛罗里达州迈阿密戴德县 COVID-19 封锁期间暴力​​犯罪的地理差异

摘要

目标

本研究使用两种集群检测技术来识别迈阿密戴德县 2020 年 COVID-19 封锁期间的 3 个月期间与 2018 年和 2019 年同期相比的暴力犯罪集群。

方法

分析了来自迈阿密戴德中央记录局的暴力犯罪数据。Local Indicators of Spatial Association 统计数据和时空排列统计数据用于识别暴力犯罪和异常值的集群，而 Global Moran's I 工具用于评估暴力犯罪的空间模式。邻里劣势数据是从与逮捕地点相关的美国社区调查 5 年估计中获得的。

结果

暴力犯罪逮捕在 2020 年下降了 7.1%。逮捕主要集中在北部的黑人弱势社区，并且在所有研究年中，这两种具有正全局 Moran's I 的聚类技术对核心聚类产生了类似的结果。虽然只占县人口的 17%，但近一半的暴力犯罪逮捕是针对黑人或非裔美国人的。男性构成了大多数暴力犯罪逮捕。

结论

犯罪预防和干预工作应重点关注高风险场所和犯罪者。