Understanding social disparities through the practice of public transportation in post Covid-19 period, lessons from Brussels, Belgium

Abstract

The COVID-19 pandemic has seriously affected mobility in cities around the world. From the first moment, the effects of this change in various parts of the world have been investigated and analyzed. Since the rapid decline trend of mobility during the pandemic has had a significant impact on almost every person, institution and sector in cities, the studies carried out are far from reaching the saturation point and are very diverse. In this process, to make observations faster and act more effectively, global companies such as Apple and Google have made their mobility data available to the public. Many scientists generally consider these data trustworthy and have already been part of many studies. In addition to providing activity reports from Apple and Google, Google has launched Google Popular Times. Popular times is a system in which people using public transportation can transfer the occupancy information of a vehicle or a stop to the user through a survey after their mobility is over. The system turns the data into graphs and informs the users at what times the current stop or bus line is busy or not busy. Acquiring Google popular times data, this study investigates the location of the activities during the pandemic when governments called for stay at home in Brussels. To do this, first, the mobility map of the city was created by processing Google popular times data into the GIS environment. The density data acquired from Google for each public transportation stop transferred in a day during the post COVID-19 period. Overlaying this map with socio-economic data that can be obtained from public institutions could help understand the impact of the pandemic on different social groups living in the same city. Income status data of the city of Brussels based on neighborhoods and the data of minority groups who later immigrated to Belgium were focused on in this study. This study assumes that the city's migrant concentrated neighborhoods are made up of lower-income groups who are more exposed to inequalities and argues that the urban poor were not lucky enough to comply with stay-at-home calls during the COVID-19 pandemic. It is estimated that the actual mobility is relatively less in the neighborhoods where people with no immigration background are concentrated in the past.