As the COVID-19 pandemic and stay-at-home orders continue, the US could lose half of its licensed child care capacity, according to a new geospatial analysis. The analysis finds child care closures will likely disproportionally affect rural and low- and middle-income communities that have also faced high unemployment levels and hardship during the pandemic.
This geospatial analysis builds on administrative data (PDF)—information governments and organizations collect about the people they serve. These data help policymakers identify and direct resources toward areas that most need early care and education programs and services.
The Urban Institute updated a resource on working with administrative data, hosted on Research Connections, that provides policymakers and state child care administrators with tools for analyzing, linking, managing, and securing state-level early care and education data. It includes several reports analyzing geographic data (PDF) that suggest where you live may determine your access to child care.
Identifying child care deserts can help policymakers target resources to those communities
For example, an innovative analysis used location data on licensed child care providers to identify child care deserts, or areas with insufficient child care supply. The researchers defined child care deserts as counties with a ratio of more than three children younger than 5 for every licensed child care slot. They found rural families faced the greatest challenges in finding licensed child care, with three in five rural communities lacking sufficient child care supply. The lowest-income urban areas may also face outsize challenges, as these communities have roughly the same rate of child care deserts as the average rural area. By providing key information on which communities have the highest child care needs, these findings can help policymakers target resources to build capacity in these areas.
Another geospatial analysis of statewide data from Massachusetts linked administrative data on child care subsidies with community-level data to evaluate how service rates differed across cities and towns. The authors identified “extreme child care deserts” as neighborhoods with a high level of unmet need for child care and constrained supply and which were surrounded by neighborhoods with similar conditions. The study found that nearly one in five subsidy-eligible children lived in an extreme child care desert. Linking geospatial and administrative data enabled researchers to identify areas where families may struggle to find child care.
Geospatial analyses of administrative data could help improve child care access during the pandemic
These analyses have been valuable tools in evaluating the landscape of child care access. During the COVID-19 pandemic, policymakers have used such analyses to propose legislation that would stabilize the Child Care and Development Block Grant, which provides funds to states and tribes to help families with low incomes access child care.
Analyses such as these provide valuable information on local access to child care that is not available in state or national-level analyses. These analyses are critical at a time when researchers warn that the pandemic is deepening structural inequities in child care, and have called for a $50 billion federal investment (PDF) to tackle them. Identifying communities who face barriers to child care during the pandemic and targeting funds and policies designed to ameliorate these barriers could mean the difference between families accessing vital child care or having to make do on their own.