Regional COVID Response Dashboard – Methodology

Published on August 4, 2020, these data visualizations represent data shared with the CHIP team from 13 different COVID-19 response funds. Each shared fund was asked to share grants data in two rounds of data collection, with the latter according to a data standard, which consisted of minimum data fields, definitions, and standard formats.

The CHIP team developed the data standard iteratively. First, we identified key data fields that were needed to answer project questions. (How much money was awarded? What needs was that money intended to address? Who were the intended beneficiaries? Where did the money go?). For the first round of data collection, we conducted initial consultative calls with each shared fund to request both grants award and application data based on this initial list of data fields. The diversity of availability, quality, and format was assessed across shared funds to narrow the minimum key data fields, including restricting the data to only awarded grants. Each data field was defined, and a standard format for each data field was developed. The data across shared funds was cleaned accordingly and merged into the first round master data set.

Two data fields of particular interest were “community need addressed” and “special population served.” The data field for “community need addressed” was developed based on cause areas known to be important for donors, based on the Center’s work in knowledge and education for funders over the past 13 years; review of the National Taxonomy of Exempt Entities (NTEE); surveys implemented by response funds to collect additional grantee information, and a selection of external databases and dashboards that track community needs, including CUSP, Candid’s Foundation Maps and COVID Response Tracker, and Devex COVID Response Tracker. Community needs were classified into 11 broad categories including “Other,” and 39 sub-categories. When the need addressed was only assigned at the high level, the corresponding subcategory assigned was labeled “General” high level need category.

The data field for “subpopulations served” was composed of 14 subpopulations including an “Other” category, based on the categories of the first and largest response fund, PHL-COVID. Examples of subpopulations in ‘Other” include low-income families, a specific geographic area, those with mental illness, and those of a specific demographic group. “Medically Frail” subpopulations refers to those with or at risk of one or more diseases, such as cancer and COVID-19. The result was the initial data standard. Other subpopulations are self-explanatory.

We conducted a second round of consultative calls with each of the shared funds to request data, based on the data standard. In cases where funds did not submit a second round of data consistent with the initial data standard, the CHIP team manually entered or re-coded data based on collected data in Round 1 and/or publicly available information. In this process, analysts identified gaps in the data field for “community need addressed” and added additional need categories. This reflected the final data standard for this phase of the COVID Response Dashboard. To ensure uniformity across data provided by all shared funds, the CHIP team recoded all grant awards data as needed according to the revised data standard.

This process resulted in an aggregated dataset consisting of 4,892 grants from 13 funds. That data was then used to create the charts and graphs depicted on this page. Map-based visualizations were created by Urban Spatial by overlaying CHIP’s data on the CDC’s social vulnerability index and other indicators of need.

Participating Funds and Organizations

Community Needs and Subcategories

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