Evaluating the impact of crowd flow control on disease spread

Abstract

The coronavirus pandemic begun in 2020 and has since detrimentally affected the daily lives of billions of people. It is hence important to understand how the disease spread among population and how it is possible to reduce this spread. Many studies have been conducted to do so. However, many of these past studies were conducted with data collected from non-pandemic conditions, which does not reflect how people will behave during the pandemic. As such, a crowd simulation can be used to model pedestrian behavior during the height of the pandemic. This data can then be used to determine the effectiveness of the crowd control measures. In this report, a crowd simulation model is created using an open-source software VADERE. This crowd simulation model is applied on to a scenario based on the Tampines IKEA food court. There are a total of four scenario, each to model a different set of crowd control measures used. The simulation model utilises a combination of a pedestrian locomotion model, a queuing model and a seat allocation model to generate and study the pedestrian contacts. The generated results is compared based on its general statistics and the exposed time. The simulation results show that crowd control measures can effectively reduce trans- mission of infectious respiratory disease. Different crowd control measures results in different impacts to contacts located in the two major areas in the food court. Overall, the combination of all crowd control measures produces the greatest reduction in the number of contacts and the exposed time.