7 Data from Google community mobility trend shows traffic was:
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To tackle the Coronavirus pandemic, countries across the world have implemented a range of stringent policies, including stay-at-home ‘lockdowns‘; school and workplace closures; cancellation of events and public gatherings; and restrictions on public transport.
These measures were implemented to slow the spread of the virus by enforcing physical distance between people.
How effective have these policies been in reducing human movement? What impact has it had on how people across the world work; live; and where they visit?
We can get some insights on this from the data that Google presents in its COVID-19 Community Mobility Reports. Using anonymized data provided by apps such as Google Maps, the company has produced a regularly updated dataset that shows how peoples’ movements have changed throughout the pandemic.1
This new dataset from Google measures visitor numbers to specific categories of location (e.g. grocery stores; parks; train stations) every day and compares this change relative to baseline day before the pandemic outbreak. Baseline days represent a normal value for that day of the week, given as median value over the five‑week period from January 3rd to February 6th 2020. Measuring it relative to a normal value for that day of the week is helpful because people obviously often have different routines on weekends versus weekdays.
On Google’s website the data is only visualized in pdfs – one for each country. We present Google’s data in interactive charts below to make it easier to see changes over time in a given country; and how specific policies may have affected (or not) behavior across communities. Google note that we should avoid comparing places across regions or countries; this is because there may be local differences in categories which could be misleading.
We should also emphasise that change in visitors is measured relative to the baseline period between January and February 2020. This means changes in movement do not take account of seasonal variation – for example, we might expect visitors to parks or outdoor spaces to be higher during the summer. The data may therefore reflect some changes in seasonal movements, rather than being fully explained by changes due to the pandemic.
The amount of day-to-day variability in the raw data can make it difficult to understand how overall movements are changing over time. To make this easier to understand we have converted the raw data into the rolling seven-day average. This is what is shown in the data in the following charts.
Google plan to continue adding more countries updating this data throughout the pandemic. As you see in the charts, the latest data is some days old. We will continue updating our charts regularly to reflect the latest update.