Opportunities for violence prevention in the night-time economy using agent-based modeling

The NHS estimates that more than 10 million people in England drink above the safe recommended limits. Not only does this have severe health implications, but an association between alcohol consumption and violent behaviour has been routinely identified. To ameliorate alcohol-related violence there is a need to better understand how pubs and clubs influence drinking behaviour and the associated violent crime that often occurs in city centres at night. However, the relationships between the alcohol and violence are complex. Many biological, psychological and social factors shape drinking practices. From a social perspective, drinking patterns are necessarily context dependent, shaped by characteristics of the drinking location and the company with whom drinking takes place. attempts to leverage quantitative methods to better understand the complex drinking phenomenon have been hampered by difficulties in accounting for heterogeneity across the population of individuals, the effects of group dynamics, and the impacts of variations in practices across licensed premises. To resolve these issues, this project will apply agent-based modelling to explore drinking practices in the night-time economy in order to better understand their association with violent behavioural outcomes. Agent-based models attempt to represent the individuals, rather than merely considering the behaviour patterns of larger groups and demographics. ABMs represent a more natural description of a system and can act as a bridge between verbal theories and mathematical models. This research will aim at better understanding the cause of alcohol-related violence in the night time economy of Leeds city centre specifically, but eh models and academic insights will be more broadly applicable.

This research will enable an assessment of known strategies for preventing alcohol-related harm such as modifications to alcohol pricing and taxation, pub trading hours and clustering of licensed premises. In terms of policy impact, I envisage this research and its resultant findings being of interest to policing and community safety partners. The project also has broader relevance to the College of Policing and the local Council's planning and licensing departments.