## 4 Discussion
Figure 10 shows for the months of February, April, and June the number of people or passengers using the BRT Transmilenio urban transport system in the city of Bogota for the years 2017 to 2020, which, in this city, is the urban transport system of reference consisting of exclusive transit buses. The figure shows that the number of people using the system fell below 20,000,000 per day in April 2020, which is down 18%, compared to the same month in previous years. Additionally, there was a slight recovery in the number of passengers for the month of June 2020, but they did not exceed 25% of the same month in previous years [48]. According to \"it can be argued that these findings do not support the effectiveness of suspending mass urban transport systems as a pandemic countermeasure aimed at reducing or slowing population spread because, whatever the relevance of public transport is to individual-level risk, household exposure most likely poses a greater threat\" [48]. Interestingly, the point of greatest decline in the use of private vehicles was greater than that of public transport. However, in each city, the speed of recovery of the mobility of particular vehicles was greater than that of public transport. This can be due to two factors: public transport follows the guidelines dictated by the regional or national government; it is also possible that due to fear of infection, people use private vehicles instead of public transport. Likewise, the rebound in use was earlier for private vehicles than for public transport. \begin{table}
\begin{tabular}{l c c c c} \hline \hline \multirow{2}{*}{**City**} & \multicolumn{2}{c}{**Traffic Congestion**} & \multicolumn{2}{c}{**Public Urban Transport**} \\ \cline{2-5}  & **Maximum Decay (\%)** & **Mobility Recovery Rate (\%)** & **Maximum Decay (\%)** & **Mobility Recovery Rate (\%)** \\ \hline Bogota & \(-97.00\) & \(27.9\) & \(-89.00\) & \(7.31\) \\ Buenos Aires & \(-94.08\) & \(14.4\) & \(-86.00\) & \(9.79\) \\ México City & \(-92.05\) & \(41.8\) & \(-84.00\) & \(12.2\) \\ Santiago & \(-92.52\) & \(44.2\) & \(-88.00\) & \(17.3\) \\ Lima & \(-97.24\) & \(45.2\) & \(-94.00\) & \(11.9\) \\ Brasilia & \(-95.04\) & \(35.9\) & \(-69.00\) & \(14.9\) \\ São Paulo & \(-92.74\) & \(50.4\) & \(-73.00\) & \(17.4\) \\ Rio de Janeiro & \(-94.22\) & \(45.1\) & \(-75.00\) & \(25.6\) \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Percentages of maximum decline and mobility recovery rate applied to traffic congestion and urban public transport in the Latin American cities under study. An indicator of the change in the behavior model associated with mobility restrictions due to the pandemic is the increase in internet data traffic [49], affecting some cities, such as Bogot\(\grave{a}\), up to 40%. Another indicator is the behavior of people, as shown in Table 4, depending on the destination of their movements during the months of the COVID-19 pandemic. In this study, it is observed that trips to second homes only increased in the five countries considered in the study. In turn, there was a significant reduction in visits to parks, this being the main destination affected by the reduction in mobility in Argentina, Brazil and Chile, while in Peru and Colombia, respectively, the destination to shops and leisure, and to transport stations were reduced. The greatest average decrease in trips, regardless of destination, occurred in Chile, with an average decrease of \(-59\%\), followed by Peru and Argentina, both with decreases of over \(-50\%\). On the contrary, the lowest average decrease in trips was observed in Brazil, with a value of \(-28\%\), highlighting in this country the destinations of supermarkets and pharmacies, which practically reached the same values as those before the start of the pandemic. Table 4 shows in bold the maximum drop in the mobility percentage according to the destination for each country.