Abstract

The COVID-19 pandemic, as well as the government measures to curb its spread, have significantly affected mobility. Various studies have investigated behavioral changes across different transport modes accounting for sociodemographic variables, yet the focus has predominantly been on public transportation. This article addresses this gap by quantifying the impact of mobility restrictions on an urban highway in Santiago, Chile. To do so, we develop several econometric models based on panel data, which enable us to assess control measures' effects while accounting for their spatial heterogeneity. Our computational experiments demonstrate that traffic reductions were more significant among higher-income drivers (1% reduction per each 100,000 pesos increase). Conversely, municipalities with a higher proportion of elderly residents saw less drastic decreases in traffic. Regarding the effectiveness of control measures, we confirm that the lockdown is affected by fatigue and social interaction. The fatigue implies that users do not fulfill the lockdown as time passes, reducing the effect of quarantines by about 50% during October, 2020. The social interaction effect suggests the lockdown is less effective when not all city's municipalities are restricted to travel, which might be an argument against dynamic or partial lockdowns.