Disaster, Social Disorganization, and Crime in the Largest Cities in Texas

Abstract

This study uses multiple regressions and moderation analysis to examine the relationship between disaster and crime in the 10 largest cities in Texas. The regressions revealed that yearly days with disaster significantly predicted Robbery, Murder, Rape, Burglary, and Auto Theft. Additionally, social disorganization and population density were often found to predict crime. Moderation analysis revealed that social disorganization increases the effect of yearly days with disaster on Burglary rates, which serve as a proxy for looting. These findings indicate that, on average, disaster responders, public safety, and security personnel in large cities can expect increases to crime as days with major weather events and disasters increase, particularly when those increases are paired with high levels of social disorganization in a city. Future security and disaster research should incorporate disaster phase timing, as well as compliance with disaster warnings to better understand the relationship between disaster, crime, and security.