Spatio-Temporal Stratified Associations between Urban Human Activities and Crime Patterns: A Case Study in San Francisco Around the Covid-19 Stay-at-Home Mandate

17 Pages Posted: 11 Jan 2022

See all articles by Tongxin Chen

Tongxin Chen

University College London

Kate Bowers

University College London

Di Zhu

affiliation not provided to SSRN

Xiaowei Gao

University College London

Tao Cheng

University College London

Abstract

Crime changes have been reported as a result of human routine activity shifting due to containment policies, such as stay-at-home (SAH) mandates during the COVID-19 pandemic. However, the way in which the manifestation of crime in both space and time is affected by dynamic human activities in urban areas has not been explored in depth in empirical studies hitherto. Here, we aim to quantitatively measure the spatio-temporal associations between crime patterns and human activities in the context of an unstable period of the ever-changing socio-demographic backcloth. We propose an analytical framework to detect the dynamic stratified associations between the spatial distributions of human activities and crimes. The results of a case study in San Francisco, United States reveal that the spatial patterns of most crime types are statistically significantly associated with that of human activities zones. Property crime exhibits higher stratified association than violent crime across all temporal scales. Further, the strongest association is obtained with the eight-week time span centered around the SAH order. These findings not only enhance our understanding of the relationships between urban crime and human activities, but also offer insights that tailored crime intervention strategies need to consider human activity variables.

Keywords: Spatial stratified heterogeneity, Crime pattern analysis, Human activity, Social sensing, COVID-19

Suggested Citation

Chen, Tongxin and Bowers, Kate and Zhu, Di and Gao, Xiaowei and Cheng, Tao, Spatio-Temporal Stratified Associations between Urban Human Activities and Crime Patterns: A Case Study in San Francisco Around the Covid-19 Stay-at-Home Mandate. Available at SSRN: https://ssrn.com/abstract=4004696 or http://dx.doi.org/10.2139/ssrn.4004696

Tongxin Chen

University College London ( email )

Gower Street
London, WC1E 6BT
United Kingdom

Kate Bowers

University College London ( email )

Gower Street
London, WC1E 6BT
United Kingdom

Di Zhu (Contact Author)

affiliation not provided to SSRN ( email )

No Address Available

Xiaowei Gao

University College London ( email )

Gower Street
London, WC1E 6BT
United Kingdom

Tao Cheng

University College London ( email )

Gower Street
London, WC1E 6BT
United Kingdom

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