When designating a disproportionately impacted class, how can the class be structured and what data is needed to justify this designation?

The U.S. Department of the Treasury’s (“Treasury”) Final Rule on the Coronavirus State and Local Fiscal Recovery Funds (“CSLFRF”) states that CSLFRF assistance can be used to provide assistance such as:

A program, service, capital expenditure, or other assistance that is provided to a disproportionately impacted household, population, or community, including:

1. Services to address health disparities of the disproportionately impacted household, population, or community;
2. Housing vouchers and relocation assistance;
3. Investments in communities to promote improved health outcomes and public safety such as parks, recreation facilities, and programs that increase access to healthy foods;
4. Capital expenditures and other services to address vacant or abandoned properties;
5. Services to address educational disparities; and
6. Facilities and equipment related to the provision of these services to the disproportionately impacted household, population, or community.[1] 

In addition to this provision of the Final Rule, Treasury’s Supplementary Information discussion that accompanies the Final Rule elaborates generally on disproportionate impact analyses, stating in pertinent part:

With regard to public health impacts, recipients may presume that the general public experienced public health impacts from the pandemic for the purposes of providing services for COVID-19 mitigation and behavioral health. In other words, recipients may provide a wide range of enumerated eligible uses in these categories to the general public without further analysis.[2]

This indicates that recipients can provide CSLFRF assistance to address the public health impacts of the pandemic with the provision of services for COVID-19 mitigation and behavioral health without additional disproportionate impact analyses. 

Treasury also notes in its discussion of the Final Rule:

Many different geographic, income-based, or poverty-based presumptions could be used to designate disproportionately impacted populations. The combination of permitting recipients to use QCTs, low-income households, and services provided by Tribal or territorial governments as presumptions balances these varying methods… However, Treasury recognizes that QCTs do not capture all underserved populations….By allowing recipients to also presume that low-income households were disproportionately impacted, the final rule provides greater flexibility to serve underserved households or communities. Data on household incomes is also readily available at varying levels of geographic granularity (e.g., Census Tracts, counties), again permitting flexibility to adapt to local circumstances and needs. Finally, Treasury notes that, as discussed further below, recipients may also identify other households, populations, and communities disproportionately impacted by the pandemic, in addition to those presumed to be disproportionately impacted.[3]

The Supplementary Information narrative also notes:

Under the interim final rule, presuming eligibility for services in QCTs, for populations living in QCTs, and for Tribal governments was intended to ease administrative burden, providing a simple path for recipients to offer services in underserved communities, and is not an exhaustive list of disproportionately impacted communities. To further clarify, the final rule codifies the interpretive framework discussed above, including presumptions of groups disproportionately impacted, as well as the ability to identify other disproportionately impacted populations, households, or geographies (referred to here as disproportionately impacted classes).[4]

Finally, Treasury’s narrative states:

The interim final rule allowed, and the final rule maintains, the ability for recipients to demonstrate a public health or negative economic impact on a class and to provide assistance to beneficiaries that fall within that class. Consistent with the scope of beneficiaries included in sections 602(c)(1)(A) and 603(c)(1)(A) of the Social Security Act, Treasury is clarifying that a recipient may identify such impacts for a class of households, small businesses, or nonprofits. In such cases, the recipient need only demonstrate that the household, small business, or nonprofit is within the relevant class. For example, a recipient could determine that restaurants in the downtown area had generally experienced a negative economic impact and provide assistance to those small businesses to respond. When providing this assistance, the recipient would only need to demonstrate that the small businesses receiving assistance were restaurants in the downtown area. The recipient would not need to demonstrate that each restaurant served experienced its own negative economic impact….[5]

These Treasury statements demonstrate that recipients can presume that funding for services provided in Qualified Census Tracts (“QCTs”) and for Tribal governments is eligible for CSLFRF assistance and that recipients also have substantial discretion to identify other disproportionately affected populations that are eligible for such funding.

In addition to Treasury’s statements above, Treasury has also identified a number of other federal authorities for which pre-pandemic eligibility dictates categorical eligibility for CSLFRF assistance. Treasury states in this regard:

Treasury agrees that allowing recipients to identify impacted and disproportionately impacted beneficiaries based on their eligibility for other programs with similar income tests would ease administrative burden. To the extent that the other program’s eligibility criteria align with a population or class that experienced a negative economic impact of the pandemic, this approach is also consistent with the process allowed under the final rule for recipients to determine that a class has experienced a negative economic impact, and then document that an individual receiving services is a member of the class.[6]

Treasury recognizes categorical eligibility for several specific programs and populations in the Final Rule.[7]

With respect to the need for recipients to document their disproportionate impact determinations, Treasury notes:

…in identifying other disproportionately impacted classes, recipients should be able to support their determination that the pandemic resulted in disproportionate public health or economic outcomes to the specific populations, households, or geographic areas to be served….The interim final rule then identified QCTs, a common, readily accessible, and geographically granular method of identifying communities with a large proportion of low-income residents, as presumed to be disproportionately impacted by the pandemic. In other words, the interim final rule identified disproportionately impacted populations by assessing the impacts of the pandemic and finding that some populations experienced meaningfully more severe impacts than the general public. Similarly, to identify disproportionately impacted classes, recipients should compare the impacts experienced by that class to the typical or average impacts of the pandemic in their local area, state, or nationally.[8]

Treasury’s narrative also states:

In designing a program or service that responds to a disproportionately impacted class, a recipient must first identify the impact and then identify an appropriate response. To assess disproportionate impact, recipients should rely on data or research that measures the public health or negative economic impact. An assessment of the effects of a response (e.g., survey data on levels of resident support for various potential responses) is not a substitute for an assessment of the impact experienced by a particular class. Data about the appropriateness or desirability of a response may be used to assess the reasonableness of a response, once an impact or disproportionate impact has been identified but should not be the basis for assessing impact.[9]

Recipients may identify classes of households, communities, small businesses, nonprofits, or populations that have experienced a disproportionate impact based on academic research or government research publications, through analysis of their own data, or through analysis of other existing data sources. To augment their analysis, or when quantitative data is not readily available, recipients may also consider qualitative research and sources like resident interviews and applicability of analysis to their determination. or feedback from relevant state and local agencies, such as public health departments or social services departments. In both cases, recipients should consider the quality of the research [and] data…[10]