Geospatial Analysis for Sustainable Urban Planning: Mapping Crime Dynamics in Mexico City During the COVID-19 Pandemic
Ensuring a high quality of life for citizens is a fundamental objective for every city, with public safety representing one of the most critical challenges to social sustainability and equitable urban development. This study analyzes the spatiotemporal dynamics of violent crime in Mexico City across pre-pandemic, pandemic, and post-pandemic periods (2019–2023) to evaluate how COVID-19 mobility restrictions were associated with changes in crime patterns. Using publicly available crime reports, we applied Seasonal-Trend decomposition using Loess (STL) and Moran’s I to examine four violent crimes: homicide, robbery, kidnapping, and rape. The results reveal crime-specific pandemic-related patterns. While robbery showed a sustained decline, its spatial clustering intensified significantly, with Moran’s I increasing from 0.22 to 0.59, indicating highly localized risk zones. Conversely, rape exhibited a steady increase that appeared unaffected by lockdown measures, while maintaining significant spatial autocorrelation. Likewise, Cuauhtémoc borough persisted as the main urban hotspot across all phases. Overall, crime did not decline uniformly during the pandemic; instead, mobility restrictions reshaped the geographic distribution and concentration of specific offenses. This research contributes to the understanding of crime dynamics during and after a public health emergency.