Replica produces large-scale models that accurately represent mobility, economic activity, people, and land use in detail throughout the United States.
Replica customers have access to a number of datasets, which are described below. Click to see detailed descriptions and schema.
Replica Trends is a nationwide dataset updated weekly covering mobility, consumer spending, and COVID-19 cases. Customers use Trends to understand the current state of the world and monitor how it is changing in near-real time. Trends data is accessible through Replica’s web-based platform.
Each week, the Trends dataset is generated from a full activity-based model, run for the entire country for a typical weekday and typical weekend day. Mobility and spend data are available for each week from the beginning of 2019 to the most recent complete week. COVID-19 data, sourced from the Centers for Disease Control and Prevention’s Covid Data Tracker, is available from the beginning of 2020 to the most recent week.
The geographies available in Trends match the U.S. Census definitions for States, Combined Statistical Areas, Metropolitan Statistical Areas, Micropolitan Statistical Areas, Cities, Counties, and Census Tracts. Customers can also aggregate this data into their own custom geographies.
Trends estimates are based on a composite of data sources, including but not limited to mobile location and financial transaction data. For spending data, advanced modeling and statistical weighting methods are applied to generate a representative weekly total estimate of consumer spending activity.
Together, these provide vital indicators for tracking, understanding, and comparing patterns of mobility and economic recovery across geographic regions in a high level of detail.
The Trends mobility table contains the aggregate trips and associated attributes in selected geographies. Users can choose to download mobility data for typical weekdays or typical weekend days, aggregated at the weekly or monthly level. Replica provides Trends mobility data from January 2019 onwards.
The GEOID of the corresponding row's. geography, as defined by the US Census Bureau. [origin/destination] depends on whether the user selects to view trips starting in a given geography, or ending in a given geography.
The name corresponding to the row’s geography, as defined by the US Census Bureau or specified by the user. [origin/destination] depends on whether the user selects to view trips starting in a given geography, or ending in a given geography.
The total number of people in the corresponding row’s geography, from our modeled population based on the 2019 ACS. [origin/destination] depends on whether the user selects to view trips starting in a given geography, or ending in a given geography.
The first day of the week (Saturday) or month of the corresponding row’s data, depending on whether monthly or weekly data was selected.
The hour of the day in 24h format, local to the corresponding row’s geography.
The total number of trips starting or ending (depending on the selection made in the download menu) in the corresponding row’s geography on a typical weekday or weekend day. When trip start time is selected as a metric, the trip count reflects the number of trips taken during the corresponding start_hour. When trip start time has not been selected as a metric, the trip count reflects the total number of trips taken during the day.
The number of trips taken by [mode] on a typical weekday or weekend day].
There is a single primary mode assigned to each trip. For example, a trip that involved a short walk and long bus ride would be classified as a single “Transit” trip. A trip that involved two separate bus segments with a brief transfer in between would also be counted as a single “Transit” trip. The summation of all modes’ trips will equal the total trip volume for the selected geography.
Each mode option is defined below:
While rideshare, delivery, and long-haul freight are included in total trip volumes, we do not track them individually and do not recommend using Trends data to analyze them at this time.
The total number of vehicle miles traveled by residents of the corresponding row’s geography, regardless of where the vehicle trips occurred, on an average weekday or weekend day depending on the user’s selection.
The average number of vehicle miles traveled per resident of the corresponding row’s geography, regardless of where the vehicle trips occurred, on an average weekday or weekend day depending on the user’s selection. Equal to vmt/ [origin/destination_population].
The Trends consumer spending table shows the estimated consumer spending that occurred in the selected geography in a given week. Consumer spending includes all transactions — including credit card, debit card, and cash transactions — that take place at a point of sale, such as at retail stores, supermarkets, restaurants, taxis, and bars. It also includes e-commerce transactions in these same categories.
For each geography, Replica produces two data tables. The first includes all spending that takes place at brick and mortar locations in a given census tract, regardless of where the purchaser lives. The second table includes all money spent by residents of each geography, regardless of where the transaction takes place. This latter table also includes breakdowns of online and offline spending.
The data does not include all household expenditures; for example, rent, car payments, and healthcare spending is not included. This most closely aligns Replica’s consumer spending metric to the Census Bureau’s Monthly Retail Trade Estimates. Transactions are categorized by the merchant’s NAICS code.
The GEOID of the corresponding row’s geography, as defined by the US Census Bureau.
The name corresponding to the row’s geography, as defined by the US Census Bureau or specified by the user.
The first day of the week (Saturday) or month of the corresponding row’s data, depending on whether monthly or weekly data was selected.
The total population in the geography selected.
The total consumer spend in [category] in a given week across the following categories:
• Airline/hospitality/car rental
• Entertainment/recreation
• Gas stations/parking/taxis/tolls
• Grocery stores
• Restaurants/bars
• Retail
Note: spend by home location includes both online and in-person spend estimates. Spend by merchant estimates only include in-person spending.
Replica provides two tables describing consumer spending flows at the county level. The first includes all spending by residents of the selected counties, expressed as county-to-county origin-destination flows. The second includes all spending at merchants in the selected counties, expressed as county-to-county origin-destination flows.
FIPS county code of the home location county.
Name of the home location county.
FIPS county code of the merchant location county.
Name of the merchant location county.
The first day of the week (Saturday) or month of the corresponding row’s data, depending on whether monthly or weekly data was selected.
The total estimated consumer spend in [category] in a given week by residents of the [home_name] county at merchants in the [merchant_name] county. Categories include:
The estimated mean spend per transaction in [category] in a given week by residents of the [home_name] county at merchants in the [merchant_name] county. Categories include:
3610 W. 95th Street
Leawood, KS. 66206