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NAVi (Nonprofit Aid Visualizer) Methodology
Vanguard Charitable’s Nonprofit Aid Visualizer (NAVi) is comprised of data sets sourced from three data providers: Candid’s information on COVID-19 grants and nonprofit organizations, The Surgo Foundation, and the Johns Hopkins Coronavirus Resource Center. These data sets were used to populate the database, which underlies the NAVi tool. Below we have detailed the methodology used to create this tool. This methodology applies to the tool itself and not the underlying data sets created by Vanguard Charitable’s data providers. Vanguard Charitable does not control or endorse such data sets and makes no representations as to the accuracy or completeness of such data sets.
Nonprofit profiles in Vanguard Charitable’s NAVi
Nonprofits found within NAVi resource are drawn from Candid’s extensive database of U.S.-based 501(c) nonprofits. Candid’s database is the most complete source of information about U.S. charities and other nonprofit organizations in existence and includes information on more than 1.8 million IRS-recognized organizations. In addition to listings of all 501(c) nonprofits registered with the IRS, Candid’s platform maintains an active database of self-reported nonprofit information that provides the basis for their proprietary GuideStar Profile Standard Seal of Transparency system. Nonprofits apply to be recognized with the GuideStar Bronze, Silver, Gold or Platinum Seals of Transparency by adhering to the standards and reporting protocols detailed in this guide on GuideStar’s website.
Selection of nonprofits
Not all U.S. IRS-registered 501(c) organizations are included in NAVi. Vanguard Charitable, in its sole discretion, selected approximately 302,000 nonprofits (the “Listed Nonprofits”) whose corresponding National Taxonomy of Exempt Entities (NTEE) code registrations are considered, in Vanguard Charitable’s determination, to be highly relevant to COVID-19 related response and recovery efforts.
The IRS uses the NTEE system to classify nonprofit organizations into 10 major groupings according to the nonprofit’s primary form of activity or programming. These categories include:
Major NTEE Groups | Group Code |
---|---|
Arts, Culture & Humanities | A |
Education Institutions & Related Activities | B |
Environmental Quality Protection & Beautification | C |
Animal-Related | D |
Health General & Rehabilitative | E |
Mental Health Crisis Intervention | F |
Disease Disorders, Medical Disciplines | G |
Medical Research | H |
Crime, Legal Related | I |
Employment, Job Related | J |
Food, Agriculture and Nutrition | K |
Housing Shelter | L |
Public Safety, Disaster Preparedness & Relief | M |
Recreation, Sports & Leisure Athletics | N |
Youth Development | O |
Human Services, Multipurpose & Other | P |
International Foreign Affairs & National Security | Q |
Civil Rights, Social Action Advocacy | R |
Community Improvement, Capacity Building | S |
Philanthropy, Voluntarism and Grant-Making Foundations | T |
Science and Technology Research Institutes Services | U |
Social Science Research Institutes | V |
Public Society Benefit, Multipurpose | W |
Religion Related, Spiritual Development | X |
Mutual, Membership Benefit Organizations, Other | Y |
Internal Use | Z |
Source: Internal Revenue Service
Intended Uses
Vanguard Charitable’s NAVi is intended for informational purposes and is a nonpartisan, nondiscriminatory platform designed to help donors easily identify registered nonprofits operating in the U.S. Inclusion of a Listed Nonprofit on the NAVi tool in no way indicates Vanguard Charitable’s endorsement of the organization nor implies any affiliation whatsoever between Vanguard Charitable and the Listed Nonprofit. As a cause-neutral organization, Vanguard Charitable does not promote the Listed Nonprofits in any way, nor does it receive any compensation or other consideration for the inclusion of the Listed Nonprofits in this tool. In addition, Vanguard Charitable cannot guarantee that the Listed Nonprofits are operating a COVID-19-specific program. Users of the NAVi tool are responsible for confirming the intended use of their grant and/or establishing any grant restrictions associated with a subsequent donation with the Listed Nonprofit directly.
Decile Codes
Decile Codes follow Major Group Codes and further distinguish the activities and programming of the individual nonprofit within its NTEE Major Group.
Of these, Vanguard Charitable elected to include the following NTEE Major Group and Decile Codes in the database underlying NAVi:
Selected NTEE Major Group and Decile Codes utilized in NAVi
- E,F,H,J,K,L,M,P,S,T excluding T20, T21, T22, T23, T90, T99
- Foundation codes: 2,3,10,11,12,13,14,15,16,17,18,21,22,23
These selected NTEE Major Group and Decile Codes are additionally eligible to receive funds from donor advised fund accounts in accordance with IRS regulations. The seed data file of Listed Nonprofits that comprise the NAVi tool is updated approximately every quarter by Candid. Vanguard Charitable does not guarantee that the data will be updated immediately upon the end of a quarter.
Listed Nonprofits
Individual Listed Nonprofits featured on NAVi are displayed alongside their corresponding information available through Candid’s information on COVID-19 grants and nonprofit organizations data set acquired for the purposes of this use case. Information related to the organizations’ federal Employer Identification numbers EIN, NTEE code registrations, logos, mission statements, physical address information, website address, and financial information, such as total expenses, assets, and revenues, are drawn from Candid's seed data file.
In some cases, information about the Listed Nonprofit from the seed data file did not include latitude and longitude coordinates, or lacked a county assignment. In these cases, the technical provider for the platform used a geocoder to generate locations for those charities based on the provided addresses. Vanguard Charitable is not responsible for the accuracy of the location data about the Listed Nonprofits provided or the geocoded results based on said provided data.
Nonprofit locations are displayed on the map based on organizations’ physical addresses as reported to the IRS and Candid by the Listed Nonprofits. Vanguard Charitable cannot guarantee that an organization’s displayed physical location corresponds to the service area which it serves. Users of NAVi should conduct their own thorough, independent research to confirm details of the nonprofit’s physical location, its standing, its service areas, and the existence of COVID-19 related programming, if any.
Staff and affiliates of the Listed Nonprofits that believe information about a listed organization is shown in error are asked to contact Candid to request a correction. Corrected files will be displayed on the map at the conclusion of the next regularly scheduled seed data file refresh, but Vanguard Charitable cannot guarantee that Candid will make the specific correction requested by the organization. We regret that we cannot make changes, corrections or amendments to individual nonprofit listings on an ad hoc basis at this time.
Unlisted Nonprofits
Unlisted nonprofits specifically excluded from the seed data file underlying the NAVi tool are asked to contact Candid directly with information about their COVID-19 programming and/or updated NTEE code eligibility.
Search Results
Results of user searches based on selected filters are displayed in the selected sort order. Sort order options include total revenue, GuideStar ratings, and alphabetical listings.
Using the “Help Me Find Charities” Charity finding wizard and filters
NAVi offers a wizard functionality that guides users through the various available filters on the site; alternatively, users may select filters from the main page. When searching by location, Listed Nonprofits are limited to within the area visible in the map viewer.
When viewing results, users may dynamically view both updated information on COVID-19 incidence in the corresponding region as well as its COVID-19 Community Vulnerability Index Scores, as described in the “Visual Map Data Layers” section below; and information about publicly announced or reported COVID-19 grants originated by grant-making foundations through August 2020. On the map interface, these visual map data layers are represented at the county-level at the most detailed view. Incidence data is available for most U.S. counties. CCVI Community Vulnerability Index scores are available for most counties; notably all U.S. territories are not included.
Filter Types
NAVi includes four primary filter menus:
- Location
The location filter can be used to search by state, zip code, county, or address. - Cause Areas
The provided cause areas were selected at Vanguard Charitable’s sole discretion. These cause areas correspond to the selected NTEE codes, as defined above. - COVID-19 Filters
These filters allow users to search for charities based on selected thresholds of interest for both COVID-19 disease incidence rates and COVID-19 CCVI scores, as defined below. - Charity Filters
These sets of filters rely primarily on self-reported information taken from the Candid database. Users may search for nonprofits based on their GuideStar Seals of Transparency (Platinum, Gold, Silver, Bronze or Unreported) level; the nonprofit’s affiliation type (Parent, Subordinate, Independent or Headquarters); the availability of diversity, equity and inclusion statistics about the organization; and the size of the nonprofit.
About the GuideStar Standard Seal of Transparency
Information about a Listed Nonprofit’s GuideStar by Candid’s Seal of Transparency level is included as a filter option in NAVi. The GuideStar Seal of Transparency is a free, voluntary program that allows qualified U.S.-based nonprofit organizations to earn Seals of Transparency when they submit information about their organization to the GuideStar platform. Seals are awarded based on the following disclosure requirements: 2020 GuideStar Profile Standards.
The purpose of the Seal of Transparency program is to recognize a nonprofit’s commitment to transparent communication about its function, purpose, staff and programming. However, the absence of a GuideStar Seal of Transparency in a Listed Nonprofit’s profile card in no way implies that a Listed Nonprofit is not in good standing.
Affiliation Type
As tracked and defined by Candid, ‘Affiliation Types’ refer to the relationship of one organization to others. Parent organizations are designated by the IRS as the governing body for a number of subordinate organizations within a group exemption.
Diversity, Equity & Inclusion Statistics
Applying this filter will limit results to only those Listed Nonprofits that have provided data on diversity, equity and inclusion.
Financials/Nonprofit Size
Listed Nonprofits may also be filtered by the size of the nonprofit as determined by the Listed Nonprofit’s filing status with the IRS. These size classifications (small, medium, large) reflect the IRS’ filing requirements for nonprofits based on a nonprofit’s reported gross receipts and/or total assets, as noted in the table below. For the purposes of the NAVi tool, all Listed Nonprofits that do not file a 990 or 990EZ form with the IRS are classified as ‘Small’. Listed Nonprofits that have a 990EZ form for the previous year on file with the IRS are classified as ‘Medium’. Listed Nonprofits that have a 990 form on file for the previous year are classified as ‘Large’.
Status | Form to File |
---|---|
Gross receipts normally ≤$50,000 | 990-N |
Gross receipts ≤$200,000 and total assets <$500,000 | 990-EZ or 990 |
Gross receipts ≥$200,000 or total assets ≥$500,000 | 990 |
Source: Form 990 series which forms do exempt organizations file.
Visual data map layers
COVID-19 Charitable Donations
Information about prior charitable granting activity is compiled and provided by the Foundation Center and accessible at the following link. Per Candid, “COVID-19 funding commitments and grants paid are identified from publicly available sources, including press releases, websites, membership reports and surveys, and local reporting. Information on grants paid is also provided by a growing number of funders sharing data directly with Candid through eReporting. All cash grants and commitments and in-kind gifts with a dollar value are included.” Grants included in this data set represent both committed and paid amounts, and are displayed according to the corresponding grant recipient’s address at the county level, as reported by Candid. In most cases, grants included in this data layer originated from grant-making organizations and foundations throughout the U.S., and not individual donors.
Where data is available, counties are determined to have been awarded charitable grants from grant-making foundations in response to COVID-19 at a rate varying from “Very Low” to “Very High”. These ranking are determined based on the following scale:
Charitable Donation Rank | Reported Total Dollars Granted through August 2020 (as compiled by Foundation Center) |
---|---|
Very Low | <$100,000 |
Low | $100,000-1 million |
Moderate | $1-25 million |
High | $25-100 million |
Very High | $100 million+ |
Grant activity data presented in NAVi is current as of August 2020 and will be updated periodically. Grants that can be associated with an organization at a county level are included in this data layer; those that were not associated with a known recipient in a U.S. county were excluded from this visual map data layer. Vanguard Charitable cannot guarantee the accuracy or completeness of this data.
COVID-19 Incidence Rate
Terms of Use:
- This data set is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) by the Johns Hopkins University on behalf of its Center for Systems Science in Engineering. Copyright Johns Hopkins University 2020.
- Attribute the data as the "COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University" or "JHU CSSE COVID-19 Data" for short, and the url: https://github.com/CSSEGISandData/COVID-19.
- For publications that use the data, please cite the following publication: "Dong E, Du H, Gardner L. An interactive web-based dashboard to track COVID-19 in real time. Lancet Inf Dis. 20(5):533-534. doi: 10.1016/S1473-3099(20)30120-1"
Additional methodological notes available here.
COVID-19 Incidence Rate data is displayed at the county level and is updated as the underlying data sets are refreshed. Where available, COVID-19 incidence rates at the individual county level are classified as Low, Medium, High or Very High. The NAVi tool utilizes a natural jenks clustering methodology for these classifications. The natural jenks classification method groups data at natural breaking points within the data set and is meant to diminish levels of variance within classes while simultaneously maximizing the variance between classes.
COVID-19 Community Vulnerability Index (CCVI) Scores
Overview to the Methodology
The Surgo Foundation constructed a COVID-19 Community Vulnerability Index (CCVI) to assess which U.S. communities may be less resilient to the impacts of the COVID-19 pandemic. Mapped nationally at state, county, and census tract levels, the CCVI can aid in COVID-19 planning and mitigation at a granular level. The CCVI builds on the Centers for Disease Control and Prevention’s (CDC) Social Vulnerability Index (SVI), a validated metric intended to help policy makers and public health officials respond to emergencies. The current COVID-19 outbreak poses new challenges contingent on a host of health and structural factors, not all of which are captured in the SVI. To understand vulnerability within the context of the coronavirus pandemic, COVID-specific epidemiological risk factors and public health system capacity variables were combined with SVI sociodemographic variables. The 34 variables cover six core themes: all four SVI variable themes (unchanged, as is) and new COVID-specific themes 5 and 6 to account for additional factors that make a community or individual susceptible to the COVID-19 pandemic (Table 1 below). The composite CCVI metric ranks each geography (state, county, or census tract) relative to one another across quintiles: very low, low, moderate, high, and very high vulnerability. Data was sourced from the CDC, Centers for Medicare, & Medicaid Services (CMS), the Harvard Global Health Institute, PolicyMap, the U.S Bureau of Labor Statistics (BLS), the U.S. Census Bureau (USCB), and the Association of Public Health Laboratories.
Please note that CCVI data is not available for U.S. territories and only partially available for a county in New Mexico.
COVID-19 Variable Selection
The CDC SVI links socioeconomic status, household composition and disability, minority status and language, and housing type and transportation as a composite metric representative of populations disproportionately affected by and less resilient to disasters. Social issues can be impacted across the disaster cycle, such as economic and infrastructure loss, and demographic characteristics, such as age, race, and economic status, can underlie the differential impacts of hazardous events.1 Though the SVI applies to a variety of emergencies, including natural events (e.g. hurricanes) and disease outbreaks, COVID-19 has brought unprecedented challenges globally.2 To adequately account for COVID-19 vulnerability, The Surgo Foundation added CCVI Themes 5 (Epidemiological Factors) and 6 (Health Care System Factors) to address epidemiological and healthcare systems factors important to the COVID pandemic.
Theme 5 epidemiological factors were selected according to CDC guidelines, which identify high risk populations as elderly adults and individuals with underlying conditions including respiratory conditions, heart conditions, obesity, diabetes, and conditions related to immunodeficiency.3 Influenza and pneumonia death rates and population density were also included in Theme 5 given evidence of COVID-19 human transmission4 and high transmissibility (i.e. greater spread) in comparison to previous outbreaks.5
Theme 6 (Health Care System Factors) variables were selected as a measure of the capacity, strength, and preparedness to COVID-19. Hospital beds are needed to accommodate the influx of coronavirus patients, who stay an average of 11-12 days in care.6,7 Density of epidemiologists was included as a proxy measure for state capability of COVID-19 surveillance and contact tracing, an effective method to detect cases and slow COVID-19 spread.8,9,10 Health system strength, as measured by total health expenditure and quality of care, can reflect potential effectiveness of an outbreak response. The Agency for Healthcare Research and Quality’s (AHRQ) prevention quality indicator (PQI) composite was selected as a metric of poor outpatient care.11 Additional factors on health system preparedness considered state readiness to address disease outbreaks, including funding available from the CDC12 and density of emergency services for rapid response. Public health laboratory density was also included as a proxy of readiness to test, which is essential to slowing the COVID-19 pandemic.13
Creating the CCVI Composite
Variables per CCVI theme were represented by percentiles, a statistical measure ranking each data point in relation to the full dataset (e.g. the 20th percentile represents the value below which 20% of the data falls). To create a composite CCVI measure, percentiles of each variable were aggregated per CCVI theme. For Theme 5 and 6 variables that included sub-metrics (e.g. several indicators encompassing one variable such as health system capacity), percentiles for each indicator were aggregated into sub-categories per theme. Each variable percentile was then aggregated per CCVI theme and subsequently across all 6 themes to create one metric. All themes were weighted equally. This method of aggregation was based on the CDC construction of the SVI. Vulnerability was classified into CCVI quintiles illustrating very low (<20%), low (20-40%), moderate (40-60%), high (60-80%), and very high vulnerability (>80%).
Validating the CCVI
True validation of the metric can only occur deep into the outbreak, when accurate numbers regarding case fatality and economic impact are available. At this stage, The Surgo Foundation attempted to assess the value of the metric in several ways. Firstly, Theme 5 and 6 only weakly correlate with the CDC’s SVI, showing the COVID-specific elements of the CCVI are not simply reflecting the same variation between geographies as the SVI. Secondly, The Surgo Foundation did a preliminary check based on whether the county-level CCVI correlates with county-level case fatality rates (CFR) (# of deaths / # of cases per county)14 in New York and Washington15 for counties with more than 50 confirmed cases. CFR is not a reliable indicator of the risk of dying upon infection16 but the infection fatality rate is not yet available. The analysis revealed the addition of the COVID-specific Themes improved the correlation between index and CFR. However, this only included 28 counties and upon further examination, turned out to be sensitive to the cut-off of the minimum number of cases per county. Future validation will explore varied weighting of the added COVID Themes 5 and 6 (equal, 1.5 times, 2 times) on health and economic outcomes.
Mapping the CCVI
The CCVI was calculated nationally per census tract. For theme variables that were not at a census tract level (i.e. coarser geography), the metric was used for each respective unit within a larger geography (i.e. state-only metrics were reflected within the CCVI as the same value being attributed to every census tract within) to create the CCVI composite measure. Once calculated at the census tract level, CCVI data was aggregated to county and state levels by taking the average across the respective geographic unit and weighting the calculation by the population of each unit, and calculating the percentiles across geographic units again. ArcGIS and Tableau were used for geographic preprocessing and visualization to map the CCVI nationally per census tract, county, and state. Census tracts with missing SVI data were not included - shown as grayed map areas (n = 95, 2% of census tracts) and ignored to compute county- and state-level CCVI. The average for each variable was imputed for the small proportion of census tracts with available SVI data, but missing Theme 5 and 6 data.
1 Flanagan, Barry & Gregory, Edward & Hallisey, Elaine & Heitgerd, Janet & Lewis, Brian. (2011). A Social Vulnerability Index for Disaster Management. Journal of Homeland Security and Emergency Management. 8. 10.2202/1547-7355.1792.
2 World Health Organization. “WHO Director-General's opening remarks at the media briefing on COVID-19 - 11 March 2020.” 11 Mar. 2020.
3 Centers for Disease Control and Prevention. People who are at higher risk for severe illness. Accessed March 31, 2020.
4 C. Huang et al., "Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China,"The Lancet, vol. 395, no. 10223, pp. 497-506, 2020/02/15
5 Y. Liu, A. A. Gayle, A. Wilder-Smith, and J. Rocklöv, "The reproductive number of COVID-19 is higher compared to SARS coronavirus,"Journal of Travel Medicine, vol. 27, no. 2, 2020.
6 W.-j. Guan et al., "Clinical Characteristics of Coronavirus Disease 2019 in China," The New England Journal of Medicine, 2020.
7 F. Zhou et al., "Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study," The Lancet, vol. 395, no. 10229, pp. 1054-1062, 2020.
8 Ng Y, Li Z, Chua YX, et al. Evaluation of the Effectiveness of Surveillance and Containment Measures for the First 100 Patients with COVID-19 in Singapore — January 2–February 29, 2020. MMWR Morb Mortal Wkly Rep 2020;69:307-311
9 Q. Bi et al., "Epidemiology and Transmission of COVID-19 in Shenzhen China: Analysis of 391 cases and 1,286 of their close contacts,"medRxiv, p. 2020.03.03.20028423, 2020
10 J. Hellewell et al., "Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts,"The Lancet Global Health, vol. 8, no. 4, pp. e488-e496, 2020.
11 Agency for Healthcare Research and Quality (2019). Quality Indicator User Guide: Prevention Quality Indicators (PQI) Composite Measures.
12 CDC, Center for Preparedness and Response (2020). Emergency Preparedness Funding.
13 M. Fisher and C. Sang-Hun, "How South Korea Flattened the Curve," in The New York Times, ed, 23 March 2020.
14 As of March 30th, 2020. Downloaded from https://github.com/CSSEGISandData/COVID-19
15 States were selected based on established COVID-19 prevalence over a longer duration.
16 H. Ritchie and M. Roser. (25 March 2020). What do we know about the risk of dying from COVID-19?
Table of contents
Nonprofit profiles in Vanguard Charitable’s NAVi
Nonprofits found within NAVi resource are drawn from Candid’s extensive database of U.S.-based 501(c) nonprofits. Candid’s database is the most complete source of information about U.S. charities and other nonprofit organizations in existence and includes information on more than 1.8 million IRS-recognized organizations. In addition to listings of all 501(c) nonprofits registered with the IRS, Candid’s platform maintains an active database of self-reported nonprofit information that provides the basis for their proprietary GuideStar Profile Standard Seal of Transparency system. Nonprofits apply to be recognized with the GuideStar Bronze, Silver, Gold or Platinum Seals of Transparency by adhering to the standards and reporting protocols detailed in this guide on GuideStar’s website.
Selection of nonprofits
Not all U.S. IRS-registered 501(c) organizations are included in NAVi. Vanguard Charitable, in its sole discretion, selected approximately 302,000 nonprofits (the “Listed Nonprofits”) whose corresponding National Taxonomy of Exempt Entities (NTEE) code registrations are considered, in Vanguard Charitable’s determination, to be highly relevant to COVID-19 related response and recovery efforts.
The IRS uses the NTEE system to classify nonprofit organizations into 10 major groupings according to the nonprofit’s primary form of activity or programming. These categories include:
Major NTEE Groups | Group Code |
---|---|
Arts, Culture & Humanities | A |
Education Institutions & Related Activities | B |
Environmental Quality Protection & Beautification | C |
Animal-Related | D |
Health General & Rehabilitative | E |
Mental Health Crisis Intervention | F |
Disease Disorders, Medical Disciplines | G |
Medical Research | H |
Crime, Legal Related | I |
Employment, Job Related | J |
Food, Agriculture and Nutrition | K |
Housing Shelter | L |
Public Safety, Disaster Preparedness & Relief | M |
Recreation, Sports & Leisure Athletics | N |
Youth Development | O |
Human Services, Multipurpose & Other | P |
International Foreign Affairs & National Security | Q |
Civil Rights, Social Action Advocacy | R |
Community Improvement, Capacity Building | S |
Philanthropy, Voluntarism and Grant-Making Foundations | T |
Science and Technology Research Institutes Services | U |
Social Science Research Institutes | V |
Public Society Benefit, Multipurpose | W |
Religion Related, Spiritual Development | X |
Mutual, Membership Benefit Organizations, Other | Y |
Internal Use | Z |
Source: Internal Revenue Service
Intended Uses
Vanguard Charitable’s NAVi is intended for informational purposes and is a nonpartisan, nondiscriminatory platform designed to help donors easily identify registered nonprofits operating in the U.S. Inclusion of a Listed Nonprofit on the NAVi tool in no way indicates Vanguard Charitable’s endorsement of the organization nor implies any affiliation whatsoever between Vanguard Charitable and the Listed Nonprofit. As a cause-neutral organization, Vanguard Charitable does not promote the Listed Nonprofits in any way, nor does it receive any compensation or other consideration for the inclusion of the Listed Nonprofits in this tool. In addition, Vanguard Charitable cannot guarantee that the Listed Nonprofits are operating a COVID-19-specific program. Users of the NAVi tool are responsible for confirming the intended use of their grant and/or establishing any grant restrictions associated with a subsequent donation with the Listed Nonprofit directly.
Decile Codes
Decile Codes follow Major Group Codes and further distinguish the activities and programming of the individual nonprofit within its NTEE Major Group.
Of these, Vanguard Charitable elected to include the following NTEE Major Group and Decile Codes in the database underlying NAVi:
Selected NTEE Major Group and Decile Codes utilized in NAVi
- E,F,H,J,K,L,M,P,S,T excluding T20, T21, T22, T23, T90, T99
- Foundation codes: 2,3,10,11,12,13,14,15,16,17,18,21,22,23
These selected NTEE Major Group and Decile Codes are additionally eligible to receive funds from donor advised fund accounts in accordance with IRS regulations. The seed data file of Listed Nonprofits that comprise the NAVi tool is updated approximately every quarter by Candid. Vanguard Charitable does not guarantee that the data will be updated immediately upon the end of a quarter.
Listed Nonprofits
Individual Listed Nonprofits featured on NAVi are displayed alongside their corresponding information available through Candid’s information on COVID-19 grants and nonprofit organizations data set acquired for the purposes of this use case. Information related to the organizations’ federal Employer Identification numbers EIN, NTEE code registrations, logos, mission statements, physical address information, website address, and financial information, such as total expenses, assets, and revenues, are drawn from Candid's seed data file.
In some cases, information about the Listed Nonprofit from the seed data file did not include latitude and longitude coordinates, or lacked a county assignment. In these cases, the technical provider for the platform used a geocoder to generate locations for those charities based on the provided addresses. Vanguard Charitable is not responsible for the accuracy of the location data about the Listed Nonprofits provided or the geocoded results based on said provided data.
Nonprofit locations are displayed on the map based on organizations’ physical addresses as reported to the IRS and Candid by the Listed Nonprofits. Vanguard Charitable cannot guarantee that an organization’s displayed physical location corresponds to the service area which it serves. Users of NAVi should conduct their own thorough, independent research to confirm details of the nonprofit’s physical location, its standing, its service areas, and the existence of COVID-19 related programming, if any.
Staff and affiliates of the Listed Nonprofits that believe information about a listed organization is shown in error are asked to contact Candid to request a correction. Corrected files will be displayed on the map at the conclusion of the next regularly scheduled seed data file refresh, but Vanguard Charitable cannot guarantee that Candid will make the specific correction requested by the organization. We regret that we cannot make changes, corrections or amendments to individual nonprofit listings on an ad hoc basis at this time.
Unlisted Nonprofits
Unlisted nonprofits specifically excluded from the seed data file underlying the NAVi tool are asked to contact Candid directly with information about their COVID-19 programming and/or updated NTEE code eligibility.
Search Results
Results of user searches based on selected filters are displayed in the selected sort order. Sort order options include total revenue, GuideStar ratings, and alphabetical listings.
Using the “Help Me Find Charities” Charity finding wizard and filters
NAVi offers a wizard functionality that guides users through the various available filters on the site; alternatively, users may select filters from the main page. When searching by location, Listed Nonprofits are limited to within the area visible in the map viewer.
When viewing results, users may dynamically view both updated information on COVID-19 incidence in the corresponding region as well as its COVID-19 Community Vulnerability Index Scores, as described in the “Visual Map Data Layers” section below; and information about publicly announced or reported COVID-19 grants originated by grant-making foundations through August 2020. On the map interface, these visual map data layers are represented at the county-level at the most detailed view. Incidence data is available for most U.S. counties. CCVI Community Vulnerability Index scores are available for most counties; notably all U.S. territories are not included.
Filter Types
NAVi includes four primary filter menus:
- Location
The location filter can be used to search by state, zip code, county, or address. - Cause Areas
The provided cause areas were selected at Vanguard Charitable’s sole discretion. These cause areas correspond to the selected NTEE codes, as defined above. - COVID-19 Filters
These filters allow users to search for charities based on selected thresholds of interest for both COVID-19 disease incidence rates and COVID-19 CCVI scores, as defined below. - Charity Filters
These sets of filters rely primarily on self-reported information taken from the Candid database. Users may search for nonprofits based on their GuideStar Seals of Transparency (Platinum, Gold, Silver, Bronze or Unreported) level; the nonprofit’s affiliation type (Parent, Subordinate, Independent or Headquarters); the availability of diversity, equity and inclusion statistics about the organization; and the size of the nonprofit.
About the GuideStar Standard Seal of Transparency
Information about a Listed Nonprofit’s GuideStar by Candid’s Seal of Transparency level is included as a filter option in NAVi. The GuideStar Seal of Transparency is a free, voluntary program that allows qualified U.S.-based nonprofit organizations to earn Seals of Transparency when they submit information about their organization to the GuideStar platform. Seals are awarded based on the following disclosure requirements: 2020 GuideStar Profile Standards.
The purpose of the Seal of Transparency program is to recognize a nonprofit’s commitment to transparent communication about its function, purpose, staff and programming. However, the absence of a GuideStar Seal of Transparency in a Listed Nonprofit’s profile card in no way implies that a Listed Nonprofit is not in good standing.
Affiliation Type
As tracked and defined by Candid, ‘Affiliation Types’ refer to the relationship of one organization to others. Parent organizations are designated by the IRS as the governing body for a number of subordinate organizations within a group exemption.
Diversity, Equity & Inclusion Statistics
Applying this filter will limit results to only those Listed Nonprofits that have provided data on diversity, equity and inclusion.
Financials/Nonprofit Size
Listed Nonprofits may also be filtered by the size of the nonprofit as determined by the Listed Nonprofit’s filing status with the IRS. These size classifications (small, medium, large) reflect the IRS’ filing requirements for nonprofits based on a nonprofit’s reported gross receipts and/or total assets, as noted in the table below. For the purposes of the NAVi tool, all Listed Nonprofits that do not file a 990 or 990EZ form with the IRS are classified as ‘Small’. Listed Nonprofits that have a 990EZ form for the previous year on file with the IRS are classified as ‘Medium’. Listed Nonprofits that have a 990 form on file for the previous year are classified as ‘Large’.
Status | Form to File |
---|---|
Gross receipts normally ≤$50,000 | 990-N |
Gross receipts ≤$200,000 and total assets <$500,000 | 990-EZ or 990 |
Gross receipts ≥$200,000 or total assets ≥$500,000 | 990 |
Source: Form 990 series which forms do exempt organizations file.
Visual data map layers
COVID-19 Charitable Donations
Information about prior charitable granting activity is compiled and provided by the Foundation Center and accessible at the following link. Per Candid, “COVID-19 funding commitments and grants paid are identified from publicly available sources, including press releases, websites, membership reports and surveys, and local reporting. Information on grants paid is also provided by a growing number of funders sharing data directly with Candid through eReporting. All cash grants and commitments and in-kind gifts with a dollar value are included.” Grants included in this data set represent both committed and paid amounts, and are displayed according to the corresponding grant recipient’s address at the county level, as reported by Candid. In most cases, grants included in this data layer originated from grant-making organizations and foundations throughout the U.S., and not individual donors.
Where data is available, counties are determined to have been awarded charitable grants from grant-making foundations in response to COVID-19 at a rate varying from “Very Low” to “Very High”. These ranking are determined based on the following scale:
Charitable Donation Rank | Reported Total Dollars Granted through August 2020 (as compiled by Foundation Center) |
---|---|
Very Low | <$100,000 |
Low | $100,000-1 million |
Moderate | $1-25 million |
High | $25-100 million |
Very High | $100 million+ |
Grant activity data presented in NAVi is current as of August 2020 and will be updated periodically. Grants that can be associated with an organization at a county level are included in this data layer; those that were not associated with a known recipient in a U.S. county were excluded from this visual map data layer. Vanguard Charitable cannot guarantee the accuracy or completeness of this data.
COVID-19 Incidence Rate
Terms of Use:
- This data set is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) by the Johns Hopkins University on behalf of its Center for Systems Science in Engineering. Copyright Johns Hopkins University 2020.
- Attribute the data as the "COVID-19 Data Repository by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University" or "JHU CSSE COVID-19 Data" for short, and the url: https://github.com/CSSEGISandData/COVID-19.
- For publications that use the data, please cite the following publication: "Dong E, Du H, Gardner L. An interactive web-based dashboard to track COVID-19 in real time. Lancet Inf Dis. 20(5):533-534. doi: 10.1016/S1473-3099(20)30120-1"
Additional methodological notes available here.
COVID-19 Incidence Rate data is displayed at the county level and is updated as the underlying data sets are refreshed. Where available, COVID-19 incidence rates at the individual county level are classified as Low, Medium, High or Very High. The NAVi tool utilizes a natural jenks clustering methodology for these classifications. The natural jenks classification method groups data at natural breaking points within the data set and is meant to diminish levels of variance within classes while simultaneously maximizing the variance between classes.
COVID-19 Community Vulnerability Index (CCVI) Scores
Overview to the Methodology
The Surgo Foundation constructed a COVID-19 Community Vulnerability Index (CCVI) to assess which U.S. communities may be less resilient to the impacts of the COVID-19 pandemic. Mapped nationally at state, county, and census tract levels, the CCVI can aid in COVID-19 planning and mitigation at a granular level. The CCVI builds on the Centers for Disease Control and Prevention’s (CDC) Social Vulnerability Index (SVI), a validated metric intended to help policy makers and public health officials respond to emergencies. The current COVID-19 outbreak poses new challenges contingent on a host of health and structural factors, not all of which are captured in the SVI. To understand vulnerability within the context of the coronavirus pandemic, COVID-specific epidemiological risk factors and public health system capacity variables were combined with SVI sociodemographic variables. The 34 variables cover six core themes: all four SVI variable themes (unchanged, as is) and new COVID-specific themes 5 and 6 to account for additional factors that make a community or individual susceptible to the COVID-19 pandemic (Table 1 below). The composite CCVI metric ranks each geography (state, county, or census tract) relative to one another across quintiles: very low, low, moderate, high, and very high vulnerability. Data was sourced from the CDC, Centers for Medicare, & Medicaid Services (CMS), the Harvard Global Health Institute, PolicyMap, the U.S Bureau of Labor Statistics (BLS), the U.S. Census Bureau (USCB), and the Association of Public Health Laboratories.
Please note that CCVI data is not available for U.S. territories and only partially available for a county in New Mexico.
COVID-19 Variable Selection
The CDC SVI links socioeconomic status, household composition and disability, minority status and language, and housing type and transportation as a composite metric representative of populations disproportionately affected by and less resilient to disasters. Social issues can be impacted across the disaster cycle, such as economic and infrastructure loss, and demographic characteristics, such as age, race, and economic status, can underlie the differential impacts of hazardous events.1 Though the SVI applies to a variety of emergencies, including natural events (e.g. hurricanes) and disease outbreaks, COVID-19 has brought unprecedented challenges globally.2 To adequately account for COVID-19 vulnerability, The Surgo Foundation added CCVI Themes 5 (Epidemiological Factors) and 6 (Health Care System Factors) to address epidemiological and healthcare systems factors important to the COVID pandemic.
Theme 5 epidemiological factors were selected according to CDC guidelines, which identify high risk populations as elderly adults and individuals with underlying conditions including respiratory conditions, heart conditions, obesity, diabetes, and conditions related to immunodeficiency.3 Influenza and pneumonia death rates and population density were also included in Theme 5 given evidence of COVID-19 human transmission4 and high transmissibility (i.e. greater spread) in comparison to previous outbreaks.5
Theme 6 (Health Care System Factors) variables were selected as a measure of the capacity, strength, and preparedness to COVID-19. Hospital beds are needed to accommodate the influx of coronavirus patients, who stay an average of 11-12 days in care.6,7 Density of epidemiologists was included as a proxy measure for state capability of COVID-19 surveillance and contact tracing, an effective method to detect cases and slow COVID-19 spread.8,9,10 Health system strength, as measured by total health expenditure and quality of care, can reflect potential effectiveness of an outbreak response. The Agency for Healthcare Research and Quality’s (AHRQ) prevention quality indicator (PQI) composite was selected as a metric of poor outpatient care.11 Additional factors on health system preparedness considered state readiness to address disease outbreaks, including funding available from the CDC12 and density of emergency services for rapid response. Public health laboratory density was also included as a proxy of readiness to test, which is essential to slowing the COVID-19 pandemic.13
Creating the CCVI Composite
Variables per CCVI theme were represented by percentiles, a statistical measure ranking each data point in relation to the full dataset (e.g. the 20th percentile represents the value below which 20% of the data falls). To create a composite CCVI measure, percentiles of each variable were aggregated per CCVI theme. For Theme 5 and 6 variables that included sub-metrics (e.g. several indicators encompassing one variable such as health system capacity), percentiles for each indicator were aggregated into sub-categories per theme. Each variable percentile was then aggregated per CCVI theme and subsequently across all 6 themes to create one metric. All themes were weighted equally. This method of aggregation was based on the CDC construction of the SVI. Vulnerability was classified into CCVI quintiles illustrating very low (<20%), low (20-40%), moderate (40-60%), high (60-80%), and very high vulnerability (>80%).
Validating the CCVI
True validation of the metric can only occur deep into the outbreak, when accurate numbers regarding case fatality and economic impact are available. At this stage, The Surgo Foundation attempted to assess the value of the metric in several ways. Firstly, Theme 5 and 6 only weakly correlate with the CDC’s SVI, showing the COVID-specific elements of the CCVI are not simply reflecting the same variation between geographies as the SVI. Secondly, The Surgo Foundation did a preliminary check based on whether the county-level CCVI correlates with county-level case fatality rates (CFR) (# of deaths / # of cases per county)14 in New York and Washington15 for counties with more than 50 confirmed cases. CFR is not a reliable indicator of the risk of dying upon infection16 but the infection fatality rate is not yet available. The analysis revealed the addition of the COVID-specific Themes improved the correlation between index and CFR. However, this only included 28 counties and upon further examination, turned out to be sensitive to the cut-off of the minimum number of cases per county. Future validation will explore varied weighting of the added COVID Themes 5 and 6 (equal, 1.5 times, 2 times) on health and economic outcomes.
Mapping the CCVI
The CCVI was calculated nationally per census tract. For theme variables that were not at a census tract level (i.e. coarser geography), the metric was used for each respective unit within a larger geography (i.e. state-only metrics were reflected within the CCVI as the same value being attributed to every census tract within) to create the CCVI composite measure. Once calculated at the census tract level, CCVI data was aggregated to county and state levels by taking the average across the respective geographic unit and weighting the calculation by the population of each unit, and calculating the percentiles across geographic units again. ArcGIS and Tableau were used for geographic preprocessing and visualization to map the CCVI nationally per census tract, county, and state. Census tracts with missing SVI data were not included - shown as grayed map areas (n = 95, 2% of census tracts) and ignored to compute county- and state-level CCVI. The average for each variable was imputed for the small proportion of census tracts with available SVI data, but missing Theme 5 and 6 data.
1 Flanagan, Barry & Gregory, Edward & Hallisey, Elaine & Heitgerd, Janet & Lewis, Brian. (2011). A Social Vulnerability Index for Disaster Management. Journal of Homeland Security and Emergency Management. 8. 10.2202/1547-7355.1792.
2 World Health Organization. “WHO Director-General's opening remarks at the media briefing on COVID-19 - 11 March 2020.” 11 Mar. 2020.
3 Centers for Disease Control and Prevention. People who are at higher risk for severe illness. Accessed March 31, 2020.
4 C. Huang et al., "Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China,"The Lancet, vol. 395, no. 10223, pp. 497-506, 2020/02/15
5 Y. Liu, A. A. Gayle, A. Wilder-Smith, and J. Rocklöv, "The reproductive number of COVID-19 is higher compared to SARS coronavirus,"Journal of Travel Medicine, vol. 27, no. 2, 2020.
6 W.-j. Guan et al., "Clinical Characteristics of Coronavirus Disease 2019 in China," The New England Journal of Medicine, 2020.
7 F. Zhou et al., "Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study," The Lancet, vol. 395, no. 10229, pp. 1054-1062, 2020.
8 Ng Y, Li Z, Chua YX, et al. Evaluation of the Effectiveness of Surveillance and Containment Measures for the First 100 Patients with COVID-19 in Singapore — January 2–February 29, 2020. MMWR Morb Mortal Wkly Rep 2020;69:307-311
9 Q. Bi et al., "Epidemiology and Transmission of COVID-19 in Shenzhen China: Analysis of 391 cases and 1,286 of their close contacts,"medRxiv, p. 2020.03.03.20028423, 2020
10 J. Hellewell et al., "Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts,"The Lancet Global Health, vol. 8, no. 4, pp. e488-e496, 2020.
11 Agency for Healthcare Research and Quality (2019). Quality Indicator User Guide: Prevention Quality Indicators (PQI) Composite Measures.
12 CDC, Center for Preparedness and Response (2020). Emergency Preparedness Funding.
13 M. Fisher and C. Sang-Hun, "How South Korea Flattened the Curve," in The New York Times, ed, 23 March 2020.
14 As of March 30th, 2020. Downloaded from https://github.com/CSSEGISandData/COVID-19
15 States were selected based on established COVID-19 prevalence over a longer duration.
16 H. Ritchie and M. Roser. (25 March 2020). What do we know about the risk of dying from COVID-19?