| Autor: |
Kim, Kyusik, Lee, Jiyoung, Ahn, Yoonjung, Sim, Sunhui, Jung, Jihoon |
| Zdroj: |
Applied Spatial Analysis & Policy; Mar2024, Vol. 17 Issue 1, p139-156, 18p |
| Abstrakt: |
The COVID-19 pandemic provided an unprecedented environment for studying the impact of lockdowns and mobility restrictions on crime. Focusing on crimes, this study first detected emerging clusters of four types of crime (larceny, auto theft, burglary, and robbery) in Atlanta using space-time permutation scan statistics. We then investigated how the spatiotemporal patterns of these clusters changed during the pandemic (2020) compared to the pre-pandemic period (2019). Finally, we classified the detected clusters based on their duration and radius. Our results show that burglary clusters became shorter and smaller during the pandemic. The average duration and radius of statistically significant burglary clusters were 10.75 days and 0.79 km for 2019, but 6.86 days and 0.45 km for 2020, respectively. In contrast, we observed more larceny clusters that were temporally longer and spatially larger during the pandemic than in the pre-pandemic period. The duration and radius of statistically significant larceny clusters were 17.67 days and 0.46 km for 2019 and 23.22 days and 0.75 km for 2020, respectively. Furthermore, we noted a shift in the clusters from residential areas to commercial areas. We however detected a very limited number of auto theft and robbery clusters. Our findings have the potential to help prioritize future police force deployment and resource allocation in similar lockdown environments, such as pandemics or natural disasters. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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