Risk Analysis of Stampede in New Delhi Railway Station and Social Policy

India has experienced many fatal stampedes during major religious gatherings, with railway stations often becoming critical points of vulnerability due to overcrowding, delays, and insufficient crowd control infrastructure. Another stampede occurred on June 4, 2025, outside a cricket stadium in Karnataka during celebrations of the Indian team’s victory in the Indian Premier League (IPL). Despite the recurring nature of these tragedies, risk modelling frameworks specifically designed for high-density transit environments are limited. This study addresses this gap by conducting a comprehensive risk analysis of stampede events at New Delhi Railway Station, a key transit hub during the MahaKumbh and similar mass gatherings. The research employs a hybrid methodology combining Catastrophe Theory and Bayesian Networks within a Bow-Tie framework, enabling dynamic modelling of nonlinear crowd behaviour and probabilistic inference under uncertainty. The model includes 92 interconnected variables covering behavioural, infrastructural, operational, and emergency response factors. Due to the lack of detailed empirical data, the Delphi method was used to derive conditional probabilities based on expert judgment, ensuring relevance and methodological robustness. The findings indicate a base-case likelihood of 62.9% for stampede occurrence, with panic behaviour, train delays, communication failures, and group agitation identified as key risk factors. Public safety policies should incorporate these insights to improve urban safety and emergency response strategies, facilitating proactive decision-making, real-time hazard monitoring, and system-level interventions to prevent crowd disasters and enhance public safety.