Study on the spatiotemporal evolution and influencing factors of theft crimes: A comparative analysis before and during COVID-19

Abstract

Focusing on JZ Province, China, the present study employs spatial analysis methods, including kernel density estimation, spatial autocorrelation, and Geodetector to explore the changes in the spatial and temporal patterns of theft crimes before and during COVID-19, as well as the spatial relationships between theft crimes and various factors concerning urban economic conditions and population dynamics. The results show that: (1) The pandemic significantly impacts theft rates, with an overall decrease of 27%. (2) Both before and during the pandemic, city centers and coastal regions experience the highest incidence of theft crimes. Theft crimes are mostly observed in economically prosperous and dynamic urban areas. The COVID-19 restrictions have a strong inhibitory effect on theft occurrences. (3) In both periods, government finances and regional economic conditions demonstrate strong explanatory power for theft crimes. A vibrant urban setting with more elderly and young people is positively correlated with theft activities.