Map shows historical redlining, as demonstrated by lending risk assessment grades assigned to different neighborhoods by the Home Owners' Loan Corporation (1935-1940) | Source: University of Richmond, University of Maryland, Virginia Tech, and Johns Hopkins University
Mapping inequality is difficult, and even more so without the right data.
That’s why PolicyMap has compiled these resources and solutions to help you get started on mapping and analyzing disparities. How might you use our data to examine inequality in your community?
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Achievement Gap
Another way to look into racial and ethnic disparities is through access to internet. Now, more than ever internet access is becoming a vital part of everyday life, some even argue that it should be treated as a public utility or a human right. We’ve seen the proliferation of telecommuting and distance learning during the COVID-19 pandemic, and those without internet access are being left out.
BLOG POST
Racial Inequities in Education Exacerbated by COVID-19
Identifying which students are at higher risk of falling behind and needing support is key to addressing inequality exacerbated by the pandemic.
CASE STUDY VIDEO
University of Delaware sociology professor Dr. Victor Perez uses PolicyMap to educate students about the geography of environmental injustice.
What if we were to ask, what patterns do we see in internet access in New Orleans? The two maps in this section show the relationship between households without any type of computer and predominant race in New Orleans.
In the first map we see the estimated percent of households with no internet access with the darkest purple areas having nearly a quarter of households without internet access.
We are then able to compare that map to a map of predominant race. In this map, the green represents areas with > 50% Black residents, while the blue represents areas with >50% White residents. We are able to see that the areas with the least internet access are often times the areas with the highest percentage of Black residents.
Environmental Justice
Environmental justice issues are one of the many ways to look at racial and ethnic disparities. If we were to ask the question, which communities in Philadelphia are the most likely to live near polluted areas, how would you go about finding an answer to that?
The following map provides an example of one way to go about finding this answer. The data available on PolicyMap allows one to look further into disparities by layering Census data (like race, income, education, etc.) with other datasets.
Case Study Video
University of Delaware sociology professor Dr. Victor Perez uses PolicyMap to educate students about the geography of environmental injustice.
In this instance, we see predominant racial or ethnic group Census data layered with EPA brownfield sites in Philadelphia. According to the EPA, Brownfield sites are locations that may be deemed hazardous due to either contamination and/or pollution. These sites then undergo testing to determine the severity of the contamination and how to move forward with cleanup if necessary.
Taking a look at the map, it is clear that the vast majority of these sites are located in neighborhoods that are either predominantly Black or predominantly Hispanic (darker green or orange on the map). This is only one of the many types of spatial analyses that are possible with PolicyMap.
Disproportionate Impact of COVID-19
The COVID-19 pandemic has made it clear that Racial and Ethnic disparities in health care and access to medicine are still prevalent today. We know that these disparities exist, but what if we were to ask a specific question like what populations are at highest risk for COVID-19 and also more likely to be uninsured.
BLOG POSTS
New Study Can Help Target COVID-19 Vaccines
A new study shows two tools that help people understand their risk of dying from COVID-19 based on where they live, along with their socioeconomic information and certain health conditions.
The Risk of COVID-19 Spread in Intergenerational Households
The spread of COVID-19 has put intergenerational households at high risk, making it critical for health officials to be able to identify them.
For this question, we will be looking at the city of Columbia, SC. The two maps in this section attempt to answer that question, while also providing a view of the Racial and Ethnic populations in the area.
In the first map we see the intersection of populations that are at severe risk of developing COVID-19 symptoms mapped in conjunction with areas where the greater than 10% of the population is uninsured. The residents in these areas are at a higher risk of developing COVID-19 symptoms while also being less likely to have insurance to cover the costs of medical bills associated with the treatment of their symptoms.

We are then able to compare that map to a map of predominant race. In this map, the green represents areas with > 50% Black residents, while the blue represents areas with >50% White residents.
Real World Solutions
Data on Racial and Ethnic Disparity
These datasets can help jump start your analysis on racial and ethnic disparities.
Access to Credit
It has been shown that homeownership is one of the main ways to build wealth in the United States today, though the lasting impacts of redlining and discrimination make the possibility homeownership very difficult for Black and Latino Americans.*
The following series of maps shows the percentage of home loan denials, predominant racial or ethnic group as well as Bank Branch locations.
Blog post
Addressing Racial Inequality by Investigating Mortgage Denials
New mortgage denial data shows how certain racial groups face greater challenges getting home loans, denying them a crucial tool in generating wealth.
The first map displays areas where over 25% of home loan applications have been denied (dark purple areas). You can look at these areas in comparison to areas that have higher percentages of minority populations in Orlando and see that they generally track together.

Adding Bank Branch Locations to the map of predominant race allows another layer of analysis. These locations don’t appear to be only related to the racial/ethnic composition of an area, but more related to the population density of an area (ie. there are more banks where there are more people). If we were to look at access to credit as a function of there not being enough banks in certain areas, this quick analysis would be able to provide some insight into some of the factors that play into the gap in access to credit between different races and/or ethnicities.
Blog Posts on Racial and Ethnic Disparities
Using PolicyMap Data to Find Equity at the Intersection of Housing and Opportunity in the US
PolicyMap is a one-stop shop for visualizing nationally available data that can facilitate the open conversations needed to guide the implementation of fair housing practices in neighborhoods across the United States.
Using Historical Data to Inform Future Fair Housing Policy
While federal fair housing protections have been recently reintroduced, fair housing advocates suggest more is needed to ameliorate the numerous effects of historic unfair lending practices on today’s Americans.
Digging Deeper into Racial Disparities
Mapping race, income, incarceration, lending practices, and more can help shed light on some of the underpinnings of racial inequities.
Racial Disparities Magnified by COVID-19 Cases and Deaths
Mapping data on race alongside health and occupation data shows which neighborhoods may be hardest hit by the COVID-19 outbreak.
Addressing Racial Inequality by Investigating Mortgage Denials
New mortgage denial data shows how certain racial groups face greater challenges getting home loans, denying them a crucial tool in generating wealth.
Internet Access Disparities Highlighted in All-New Maps from PolicyMap
According to recent Census data, some city neighborhoods are severely lacking in internet access. See how the digital divide affects your city.
Data on the Racial Wealth Gap
Explore factors driving the racial wealth gap, such as disparities in homeownership, educational attainment and income, using PolicyMap.
Customer Stories
See firsthand examples of how PolicyMap subscribers have used data to study disparities in their communities.

Childcare Map Philadelphia
To identify gaps in child care access in Philadelphia, the William Penn Foundation supported an analysis of existing child care services and childcare demand using locally available data. The results of the analysis were put on a PolicyMap Integrated Mapping Tool, along with other helpful indicators showing the number of young children and existing childcare resources, like certified and uncertified child care centers, and Head Start centers.
The tool also uses other data to show potential locations for new or expanded child care facilities, like previously certified centers and for-sale school district buildings. This gave providers a tool for siting new child care centers, gave investors and policy makers a tool for targeting resources to increase high-quality child care access, and gave parents a tool for finding high-quality child care centers near where they live and work.