How many people are staying at home during the COVID-19 pandemic? How far are people traveling when they don’t stay home? Which states and counties have more people taking trips? Start exploring our Daily Travel data to answer those questions.
In which States and Counties are people staying at home? Which ones show the most activity?
Dive into the map below to see what percentage of the population is staying at home in your state or county. You can also use the Select A Metric drop-down to see state or county-level measures for the average number of daily trips people are taking and more.
How much are people traveling as the pandemic continues?
Use the line graph below to see how the the number of trips has changed over time. Then, use the Select A Metric drop-down to view changes in other measures during the COVID-19 pandemic.
When they leave the home, how far are people traveling?
Are people going farther on each trip, or are they sticking close to home? Use the date selector to learn how patterns have changed.
Explore the Trips By Distance Data on Your Own
Click on the image below to see the metadata for the Daily Travel data in our Data Inventory. There, you can download the data or use the inventory platform to create your own visualizations and share them with others.
The Daily Travel data and number of people staying home and not staying home are estimated for the Bureau of Transportation Statistics by the Maryland Transportation Institute and Center for Advanced Transportation Technology Laboratory at the University of Maryland.
The daily travel estimates are from a mobile device data panel from merged multiple data sources that address the geographic and temporal sample variation issues often observed in a single data source. The merged data panel only includes mobile devices whose anonymized location data meet a set of data quality standards, which further ensures the overall data quality and consistency. The data quality standards consider both temporal frequency and spatial accuracy of anonymized location point observations, temporal coverage and representativeness at the device level, spatial representativeness at the sample and county level, etc. A multi-level weighting method that employs both device and trip-level weights expands the sample to the underlying population at the county and state levels, before travel statistics are computed.
Data in the charts and graphs above is updated weekly on Mondays. The data lags one week behind the current date.
Data analysis is conducted at the aggregate national, state, and county levels. To assure confidentiality and support data quality, no data are reported for a county if it has fewer than 50 devices in the sample on any given day.
Trips are defined as movements that include a stay of longer than 10 minutes at an anonymized location away from home. A movement with multiple stays of longer than 10 minutes before returning home is counted as multiple trips.