Abstract
The COVID-19 pandemic has changed people's mobility patterns, increasing the preference for private modes and reducing the public transportation demand. Most scientific contributions have studied the role of mobility levels in the spread of the virus and the influence of public transport on COVID-19 infections, but ignoring the importance of individual-level variables potentially affecting COVID-19 infection, such as daily habits. This paper analyses the relationship between the probability of being infected by COVID-19 and using public transport through a survey data analysis, taking Madrid (Spain) as the case study. This research uses a survey campaign with more than 15,000 responses, capturing socio-demographic aspects, COVID-19 infections, daily habits, and mobility patterns with high risk of COVID-19 infection. Through a multilevel probit model, this paper explores the extent to which a higher use of public transport is related to a greater likelihood of COVID-19 infection. The results suggest a relationship, although not very strong, between the probability of infection and the conjunction of higher frequency of use of metro services and level of crowding during the trip, whereas the use of bus services and travel time within the vehicle do not appear to affect.
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