CUSP Public (Alpha release)

We are excited to announce the alpha release of CUSP Public, 3Si’s first publicly available interactive data and visualization solution to explore, analyze, and download child population and demographic data for all states and counties in the United States. Built in partnership with the Gates Foundation and with guidance and input from the U.S. Department of Health and Human Services’ Administration for Children and Families (ACF), several state agencies, researchers, demographers, and other subject matter experts across the country, CUSP Public makes a portion of 3Si’s industry-leading population data asset available free of cost to everyone as a single, comprehensive child population data resource.


  • Advanced dashboards that allow users to dynamically explore and visualize child population estimates by age, household income, and household employment status for every state and county in the United
    States—cross-sectionally and over time.
  • Compelling, easy-to-use, and easy-to-navigate user interface with infographic and tooltip features that allow users to interpret and understand data.
  • CUSP Public’s collection of cohesive and coherently structured dashboards enables users to view, explore, and analyze population data and data on children eligible for major subsidized child care programs such as CCDF, Head Start, and Early Head Start, segmented by state and county, and by key demographic characteristics.
  • Dynamic, flexible, and innovative scenario analysis tool empowers users to examine the impact of different eligibility requirements for subsidized programs on the estimated number of children eligible for them. This capability enables users to flexibly analyze how variations in program requirements affect the size of eligible child populations in every county in every state, allowing a more nuanced and comprehensive view of the variable impact of program eligibility changes on different communities in a state.
  •  First-of-its-kind analysis of how the racial/ethnic composition of different communities in a state intersects with the impact on those communities of changes in the eligibility requirements of  subsidized early childhood programs.
  •  Creative combinations of maps, charts, graphs, and other visualization techniques ensures that users can engage and interact easily and flexibly with comprehensive and complex data.
  • Cross-sectional and longitudinal data views allow comparisons across geographies and over time, with segmentation along a range of dimensions based on child demographics and funding programs.
  • Free data download capability allows users to easily access national and state population datasets with estimates available by county, age, income bracket, and household employment status.
  • Informative and user-friendly documentation on CUSP Public’s data sources and 3Si’s stepwise estimation methodology for analyzing and synthesizing ACS data.


  • Reliable, rigorous, and innovative data product that combines Census data with 3Si’s advanced and proven data science and analytical methodology to democratize integrated population data for everyone to access, use, and analyze.
  • CUSP Public’s compelling, user-friendly, and well-structured dashboards address foundational questions related to population and eligibility analyses for every state and county in the country.
  • Pioneering source of data on populations eligible for subsidized child care services by major funding programs that reach the most children across the United States.
  • CUSP Public’s unique scenario analysis capability empowers users to view and analyze in a nuanced, fine-grained way—and with just a few clicks—the variable impact of adjustments in eligibility requirements on communities and the children who live in them.
  • Free data download capability makes detailed population data—for the whole country and for individual states—readily available in the form of zip files for users to access, use, and analyze anytime.
  • Our step-by-step documentation increases methodological transparency and learning and allows users to approach the data and their analysis of it in an informed way.