Researchers from the University of Cambridge and Imperial College London have developed a mathematical model to help predict the risk of disease transmission in a train carriage.
They found that the risk is the same along the entire length of the carriage.
The easiest to apply and most effective measure is enforced mask wearing, particularly if class FFP2 or higher masks are used.
The model, developed from controlled experiments in a real train carriage, also shows that masks are more effective than social distancing at reducing transmission, especially in trains that are not well ventilated with high rates of fresh air intake.
The results, reported in the journal Indoor Air, demonstrate how important it is for train operators to improve their ventilation systems in order to help keep passengers safe.
Co-author Dr. Huw Woodward, from the Centre for Environmental Policy at Imperial, said: “What we found was that physical distancing can reduce the risk of airborne infection, but the carriage needs to be less than half full.
“Increasing the rate of fresh air supplied to the carriage will also reduce the risk of airborne infection; however, this is not cheap or easy to do on these carriages as they are designed for energy efficiency.
“The easiest to apply and most effective measure is enforced mask wearing, particularly if class FFP2 or higher masks are used.”
Assessing risk on public transport
The work was done as part of the TRACK project, with the goal of understanding the risk of COVID-19 infection on public transport. They looked at inter-city trains specifically, as they suspected these may be particularly high risk.
Since COVID-19 is airborne, ventilation is vital in reducing transmission. Although COVID-19 restrictions have been lifted in the UK, the government continues to highlight the importance of good ventilation in reducing the risk of transmission of COVID-19, as well as other respiratory infections such as influenza.
The ventilation systems on inter-city trains however are optimized for energy efficiency and passenger comfort, rather than indoor air quality: most commuter trains recirculate the majority of air instead of pulling fresh air in from outside, since fresh air has to be either heated or cooled, which is more expensive.
The team carried out several experiments on a train carriage, measuring CO2 concentrations while in service, and measuring salt aerosol droplets released within the carriage to understand how droplets were being dispersed by the airflow driven by the ventilation.
Based on these experiments, they developed a model that allowed them to understand the spatial variation of risk of infection via the airborne route within the carriage. They found that air movement is slowest in the middle part of a train carriage.
However, this doesn’t necessarily determine infection risk. First author Rick de Kreij, who completed the research while based at Cambridge’s Department of Applied Mathematics and Theoretical Physics, said: “If an infectious person is in the middle of the carriage, then they’re more likely to infect people than if they were standing at the end of the carriage. However, in a real scenario, people don’t know where an infectious person is, so infection risk is constant no matter where you are in the carriage.”
Dr Woodward added: “For this work we have only determined relative risk – how different factors affect your risk of infection within a train carriage, but not absolute risk – how likely you are to get COVID-19 by travelling on trains in general. It is likely that single train journeys are low risk, while regular commuters may have a higher risk.”
The model the researchers developed is ‘one-dimensional’ (1D), which considers the essential physics for transporting airborne contaminants while using relatively little computing power, especially compared to 3D models. The model is based on a single train carriage with closing doors at either end, although it can be adapted to fit different types of trains, or different types of transport, such as planes or buses.