Typical patterns of time use and travel behavior have been transformed by the COVID-19 pandemic. The drastic change has been documented in several studies to date, especially in the realm of transport, which have asked respondents about how their behavior has changed compared with their prepandemic routines. This work complements those efforts, offering a valuable evaluation of the decision-making process behind choosing which activities to engage in and for how long. A mixed multiple discrete-continuous extreme value (MMDCEV) model was applied to panel GPS data collected between September 2019 and October 2020. The estimation results uncovered how different demographic and mobility tool ownership characteristics affected the choice of activities and their duration. Additional interaction effects of different time periods exogenously introduced into the model allowed for the assessment of the differential effects of these components. Our findings revealed that the choice to participate in out-of-home activities strongly differed with respect to prepandemic conditions. Not only were individuals choosing to spend more time at home during the pandemic, but when they did engage in out-of-home activities, it was also for a shorter duration. Notably, age, gender, education level, and income all affected the propensity to engage in out-of-home activities during the pandemic. These results and their implications for policy as we try to plan for the “new normal” daily life are discussed.

This paper analyzes the impact of the COVID-19 pandemic on activity time use and timing behavior in Switzerland. The evaluation is based on mobility tracking data collected in Switzerland during the COVID-19 pandemic. The pandemic has affected how people spend their time and schedule their activities throughout the day, subsequently creating new activity patterns. Because of the rare occurrences of pandemics in the recent past, little is known about their implications on the behavioral choices of affected people. This paper analyzes these implications by applying a multiple discrete-continuous choice model on mobility tracking data from Switzerland. The applied model is consistent with the results of the descriptive analysis and shows that the different stages of the pandemic drove changes in the activity patterns. During the lockdown, an increase in home activities comes along with decreases in the other activity types. With progressive relaxation of the measures in the following phases, the trends slowly return to the initial state before the pandemic. In addition, it can be seen that the impact of main drivers such as age, gender, household size, income and weather on time use and activity scheduling varies between phases, activity types, and time of day.