[SARS-CoV-2 Infections during Travel by Train and Bus: A Systematic Review of Epidemiological Studies].

AIM

The aim of this review is to identify epidemiological studies on the risk of infection with SARS-CoV-2 during travel by train and bus and to critically evaluate them also with regard to extrapolating the findings to the German situation.

METHODS

Systematic review based on searching two electronic databases (PubMed, Web of Science) according to the principle of Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) for epidemiological studies on SARS-CoV-2 or COVID-19 and travel by train or bus.

RESULTS

Searches of the two electronic databases yielded 746 publications. Of these, 55 met the selection criteria and were included in the full-text search. Finally, 5 original publications were used to answer the question about SARS-CoV-2 infections related to long-distance travel by train and 4 related to bus travel. The studies were very heterogeneous and referred almost exclusively to long-distance travel in China. They consistently showed a risk of infection when infected persons travelled in the same train, car or bus without mouth-to-nose (MNB) coverage. The risk was not limited to those sitting in close proximity to an infected fellow traveler. Despite all the differences between travel by train and bus in China and Germany, there is no fundamental doubt that the reported results from China can also be extrapolated to Germany in qualitative terms. However, it must be taken into account that the results of the three key publications predominantly included the period before the lockdown in China without the strict use of MNB. Thus, the question remains whether the results would be similar under current conditions with MNB and more virulent viral mutations. No single study was found related to infection when using public transportation.

CONCLUSIONS

There are several lines of evidence that travel by train is associated with a significantly lower risk of infection compared with the risk of infection in the home environment. Due to a lack of observational data, one will need to model the risk of infection for long-distance travel by bus and use of local public transport based on air exchange in the passenger compartment, travel duration, distance from other passengers, and ultimately passenger density.