A Project of IVT, ETH Zurich and WWZ, University of Basel
This work is licensed under Creative Commons.
Contact: Joseph Molloy (joseph.molloy@ivt.baug.ethz.ch)
Previous and future reports can be found at: https://ivtmobis.ethz.ch/mobis/covid19/en
25 January:
14 December:
Previous news (click to expand)
18 November:
2 November:
6 October:
28 September:
24 August:
11 August:
6 August:
13 July:
29 June:
15 June:
25 May:
18 May:
11 May:
4 May:
27 April:
20 April:
13 April:
On March 16, 2020, 3700 participants who completed the MOBIS study between September 2019 and January 2020 were invited to reinstall the GPS Logger and Travel Diary App ‘Catch-My-Day’, developed by MotionTag. This voluntary recording of their mobility behaviour allowed us to track the impact of the various special measures during the unfolding pandemic. The pandemic is still going on one year later and many participants are still tracking.
Participation decreased from about 1’300 participants to around 500 by the start of the second COVID19 wave in autumn/fall 2020 for any number of good reasons, such as a new smartphone, operating system updates, etc.. About 250 rejoined the panel after a second invitation in October 2020. We are very grateful for their engagement. Still, we happily agreed, when LINK offered to recruit more participants to the panel. This further increase of our sample allows us to complement the existing core. By mid-January a total of 393 additional participants had joined via LINK.
This week’s report is the first based on the new sample.
The results are shown in comparison to those of the first 4 weeks of mobility data from the original MOBIS Study which were recorded between 1st September and 15th November 2019, and thus serve as a baseline well before the pandemic hit Switzerland. The four weeks are spread over a period of time as the sample was built up successively in waves. Only trips inside Switzerland are currently considered, although data on cross border travel is available. For the MOBIS study, participants were only eligible if they used a car at least 3 days a week - which skews the sample away from the Swiss general population. We did not impose a similar condition on the LINK-recruited participants as we are now aiming towards a more representative sample of the population.
The number of tracking participants each day used to calculate the average daily values, includes all participants who recorded tracks before or after that date. This allows the consideration of those who stay at home while still allowing for survey dropouts.
The GPS Travel diary used, Catch-My-Day (for iOS and Android) can have a 2-3 day delay before the tracks are available for analysis. The scaling by active participants accommodates for this, but the results of previous reports may change when the report is updated. The scales are calculated against the representative sample we obtained as part of the MOBIS recruitment process.
[1] “Download chart data”
[1] “Download chart data”
[1] “Download chart data”
[1] “Download chart data”
[1] “Download chart data”
The following graph shows the effect of the COVID-19 crisis on median car travel speeds during the week, i.e. excluding weekends and holidays. During the lockdown period from March 16th to May 11th, an increase in the peak-hour speeds was observed, indicating a decrease in overall congestion. Since the relaxation of the measures, peak-hour speeds have returned to pre-COVID-19 values, a sign that congestion is back to usual levels.
[1] “Download chart data”
A ternary plot is the graphical representation of triplets of numerical data. It is suitable for representing a constant sum, which is broken down into three summands. The following figure shows an example of such a plot with a single point. The triplet corresponding to this point can be read by following the green lines: A=0.5, B=0.3 and C=0.2. The sum of the three values is equal to 1.
The following ternary plots show the change in mode shares over the course of the COVID-19 crisis, for different types of public transport subscriptions (GA, Halbtax and other). The modes are grouped into the following categories:
During the lockdown, a higher share of kilometers and trips were performed using motorized individual and unmotorized modes as compared to the reference period. After the lockdown, the share of public transport has increased and the share unmotorized modes has decreased, both slightly. The share of motorized individual modes it still greater than during the reference period.
Participants in MOBIS-Covid19 were asked to report their working status on 24/4/2020. The following charts use these results, with the working status imputed using sociodemographic indicators for those who didn’t respond. Specifically, we asked for the number of days working both at home and out of home, and these were then grouped into the categories used below:
[1] “Download chart data”
[1] “Download chart data”
[1] “Download chart data”
A commonly used definition of the activity space is the 95% confidence ellipse of the activity locations, in this case weighted by duration. In the following analysis, the activities at the home location are included, for those that had the app activated on that day. This is an important metric which gives an idea of the area in which travel is being performed. The daily travel radius is also presented.
[1] “Download chart data”
The number of trips started per hour. The y axis is normalized by the maximum hourly value in the graph.