Viral Infection Simulation in a Crowded Train

Abstract

In conjunction with the spread of COVID-19, crowded trains have been cited as locations in which there are concerns regarding infection of the disease. Prior to this article, the author visualized the behavior of an invisible virus by using computational fluid dynamics to carry out a simulation of infection on a crowded train. Since February 2020, when COVID-19 began to spread, the results of this simulation have been covered in various forms of media, such as television, newspapers, and magazines, but due to insufficient explanations resulting from limitations in, e.g., broadcast time and/or articles, such coverage led to significant audience misunderstanding. This article offers accurate information regarding the simulation which has been featured in media to this point, and describes the risk of infection on a crowded train as considered by the author. The author concludes that on trains in Japan, where the majority of passengers wear masks, the likelihood of clusters occurring will continue to be low, similar to the situation up to this point.