Differences across cities of the built environment and the underlying transport sector policy framework can explain diverging patterns of mobility behaviors, including in times of unanticipated change. As urban residents and transport planners around the world enter into a new – post-pandemic – phase, it is useful to take stock of the more lasting impacts of the pandemic in urban areas with different underlying contexts. While some of the behavioral changes were temporary responses to public policy measures such as lockdowns, closure of borders, limits to public transport capacity, or pop-up cycling lanes, others have turned out to persist, reflecting new preferences or accelerating incipient trends that were already shaping up for several years prior to March 2020.
Detailed indicators that track mobility – of people and goods – using innovative data sources can help propose solutions in real time, while building long-term evidence to inform transport planning at a more strategic level. Even in large metropolitan areas like Bogota and Buenos Aires, where public authorities invest significant efforts into continuous monitoring of key mobility indicators, the existing data and tools were not adequate to understand – and respond to – the “new normal” of the post-pandemic context.
Through a World Bank Latin America and the Caribbean (LAC) regional initiative led by the Transport Global Practice, several analytical work streams were developed to help the transport planners in Bogota and Buenos Aires – and eventually other LAC cities – leverage innovative data and tools to better understand the rapidly unfolding mobility patterns. Taking advantage of the high mobile phone penetration rates in both metropolitan areas (70-80 percent) and, thus, availability of call detail records (CDR) as an invaluable source of data for constructing a range of policy relevant mobility indicators, the World Bank team set out to analyze, first,
The analysis conducted in response to the first question found that even two years after the start of the pandemic, the return to pre-pandemic public transport ridership was still partial in both urban areas, especially so in Buenos Aires. While in Bogotá the pandemic appeared to have induced a lasting shift to nonmotorized modes, in the Buenos Aires Metropolitan Area any initial gains in non-motorized mobility had dissipated by late 2021. These differences are partly explained by the underlying policy and regulatory context in the two urban areas, such as the presence of a strong transport demand management policy in Bogota (including measures such as Pico y Placa that restricts private vehicle circulation) that does not exist in Buenos Aires, despite the highly developed mass transit and cycling infrastructure in both of the central cities.
Figure 1: Modal shares in the two metropolitan areas in 2019 vs. 2020 vs. 2021 (%)
Other mobility indicators that had changed more permanently (among others) include lower average distances traveled and lower overall trip generation rates and, specifically, peak-hour travel, mainly due to teleworking.
The study that looked at the second question found that during the pandemic the demand for e-commerce grew in both cities. In Bogota, the share of residents using the Internet to purchase products rose from 18.9 percent to 22.1 percent between 2019 and 2021. In Buenos Aires, the pandemic accelerated the growth in the number of online consumers which had shown signs of stagnation in the pre-pandemic years; 20 percent of Internet users bought online for the first time during the quarantine.
Yet, the future potential of e-commerce substituting personal mobility trips estimated by the analysis is considerable: it could replace up to 9.1 percent of the trips made on weekdays in Bogota and between 7 percent and 12 percent of trips on weekdays in Buenos Aires.
The findings of the two analytical studies are relevant for designing transport policy in the post-pandemic context, specifically, pointing to the need to implement demand management policies combined with investment in non-motorized transport; improving the quality of the public transport system to be able to attract back the higher-income ridership segment; adjusting service frequencies to the less distinct ridership spikes during the historical morning and evening peak hours; managing e-commerce as a mobility-generating challenge in the short-to-medium term; and focusing on the optimization of distribution routes and the electrification of urban freight distribution fleets.