Abstract
Public transportation plays a critical role in meeting transportation demands, particularly in densely populated areas. The COVID-19 pandemic has highlighted the importance of public health measures, including the need to prevent the spread of the virus through public transport. The spreading of the virus on a passenger ship is studied using the Computational Fluid Dynamic (CFD) model and Monte Carlo simulation. A particular focus was the context of Bangladesh, a populous maritime nation in South Asia, where a significant proportion of the population utilizes passenger ships to meet transportation demands. In this regard, a turbulence model is used, which simulates the airflow pattern and determines the contamination zone. Parameters under investigation are voyage duration, number of passengers on board, social distance, the effect of surgical masks, and others. This study shows that the transmission rate of SARS-CoV-2 infection on public transport, such as passenger ships, is not necessarily directly proportional to voyage duration or the number of passengers onboard. This model has the potential to be applied in various other modes of transportation, including public buses and airplanes. Implementing this model may help to monitor and address potential health risks effectively in the public transport networks.