Evaluating the impact of crowd flow control on disease spread - Ma, Wenyue (Nanyang Technological University, 2024)
The global response to infectious diseases, particularly during the COVID-19 pandemic, has highlighted the need for consistent, evidence-based crowd flow control measures. Despite the general recognition of disease transmission risks at large gatherings, such as religious events, a clear evidence-based approach for analysing these scenarios remains lacking. Understanding how disease spreads is essential in large-scale events where human interactions are frequent and dense. Analysing data such as contact patterns and movement flow in these events can identify vulnerable points in crowd dynamics, where transmission risk is the highest. This report presents simulations of a Co-Curricular Activities Fair within a school setting, using the open-source software VADERE to explore various crowd flow control measures. The simulation model incorporates locomotion, behavioural, and interest models to simulate pedestrian interactions and preferences. The generated output is used to construct temporal contact networks, which enables analysis of exposure risk to disease through risk assessment frameworks. Results indicate that the implemented measures effectively reduce disease transmission risk, with social distancing emerging as the most significant factor. Overall, combining all crowd control measures yields the greatest reduction in contact frequency and exposure time.