Application of crowd simulation for modelling infectious disease spreading

• Main Author: Xing, Wanting
• Other Authors: Cai Wentong
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2021
• Subjects: Engineering::Computer science and engineering
• Online Access: https://hdl.handle.net/10356/148111
• Institution: Nanyang Technological University

Crowd simulation has been a widely applied to study the movement and/or behaviour of a large number of crowds. In recent years, it has been widely applied to various fields of research, such as entertainment, traffic engineering and city planning. Under the current situation of COVID-19 pandemic, crowd simulation is an effective approach for studying the spread of infectious disease among populations. In this report, a crowd simulation model for Singapore General Hospital Emergency Department is developed using an open-source software VADERE. The simulation model combines pedestrian dynamics, a queuing model, and a disease transmission model to generate and study pedestrian trajectories. Various parameters such as effective contact radius and infection probability are carefully controlled to achieve realistic simulation results. to analyse effectiveness of several crowd control measures, including restricted seating arrangements and social distancing measures. From the simulation results, it can be concluded that social distancing can effectively reduce transmission of infectious diseases such as COVID-19. By adopting an appropriate social distancing, number of contacts between pedestrians can be effectively reduced, leading to lower numbers of new infections. If the infectious disease studied has a larger effective contact radius, either a larger social distance or other crowd control measures need to be adopted in order to effectively mitigate the spread of the disease. Furthermore, the idea of multiscale model applied in this project is effective and reliable in analysing spread of infectious disease among individuals, and parameters controlled in the crowd simulation and analysis can be easily modified. Therefore, this project has the potential to be extended to studying the spread of many infectious diseases in other crowded facilities for more complex scenarios.