Vulnerability, Inequity, and COVID-19: A Portrait of the Pandemic in Allegheny County

Tracking evolving disparities in testing, cases, hospitalizations, and deaths

Vulnerability, Inequity, and COVID-19: A Portrait of the Pandemic in Allegheny County

Tracking Evolving Disparities in Testing, Cases, Hospitalizations, Deaths, and the Ability to Practice Physical Distancing

Published on May 24, 2021.

Overview

This tool is for

  • policymakers in Allegheny County and across the country
  • COVID-19 testing providers
  • institutional leaders in Allegheny County
  • members of the public who are interested in the state of the COVID-19 pandemic for communities experiencing vulnerability in Allegheny County.

No community in the United States has been spared from the effects of coronavirus disease 2019 (COVID-19), but certain populations have been affected more than others. However, community data systems often fail to capture inequities at a more granular level. Underserved communities in the city of Pittsburgh and in Allegheny County have experienced inequities in cases, hospitalizations, deaths, and the ability to practice physical distancing (also known as social distancing), much like other disadvantaged populations throughout the nation.

By late May 2020, it had become clear that Black residents were disproportionately affected by COVID-19. In response, efforts were launched to mitigate racial inequities in the county by the Black Equity Coalition (BEC), a group that is predominately made up of Black health care providers, public health experts, social scientists, community funders, and public officials working to address the effects of COVID-19 on historically marginalized people and communities (BEC, undated-a; BEC, undated-b). The RAND Corporation, the BEC, and Surgo Ventures partnered to explore the state of COVID-19 testing, cases, and deaths in Allegheny County in order to investigate disparities in COVID-19 response and the pandemic’s effects at the community level (BEC, undated-b; Surgo Ventures, undated-a).

To investigate these disparities, we visualized existing data on COVID-19 cases and testing rates and compared them with defined levels of vulnerability to COVID-19 within the different municipalities and neighborhoods in Allegheny County. We also explored testing access, testing rates, cases, and such health outcomes as hospitalizations and deaths by race to explore the existence of disparities. Finally, we examined physical distancing over time by vulnerability and demographic and socioeconomic factors. We also examined the association of physical distancing with COVID-19 testing and deaths.

The results of these analyses create a portrait of communities that are most vulnerable to COVID-19 and that experience racial inequities. We hope that these analyses inform individual and policymaker efforts to mitigate the spread of COVID-19 as the pandemic continues and provide a model for future tracking of inequities in future pandemic response.

Visualizations 1 and 2 present some high-level information about vulnerability, demographic and socioeconomic characteristics, and COVID-19 testing and cases in Allegheny County for context. The sections that follow offer a deeper dive into vulnerability and inequity in COVID-19 testing and outcomes.

Visualization 1. Vulnerability and Socioeconomic Characteristics, by Municipality or Pittsburgh Neighborhood

This map shows how vulnerability is distributed across Allegheny County. It also shows a set of socioeconomic and demographic characteristics for each county municipality and City of Pittsburgh neighborhood. We used Surgo’s COVID-19 Community Vulnerability Index (CCVI)—a resource that identifies communities that are most in need of support during the pandemic—to define vulnerability (Surgo Ventures, undated-b). Surgo defined vulnerability to COVID-19 as a limited ability to mitigate, treat, and delay transmission of the virus and to weather its secondary effects on health, economic, and social outcomes.

Select whether the maps show all of Allegheny County (with neighborhood and municipal boundaries) or the city of Pittsburgh (with neighborhood boundaries).

The CCVI ranks each geographic area (e.g., census tract) relative to one another on a 0–1 scale (where 0 is least vulnerable and 1 is most vulnerable). Vulnerability was classified into CCVI terciles illustrating low (bottom third of census tracts), medium (middle third of census tracts), and high (top third of census tracts).

Use the dropdown menu to toggle between maps to explore demographic and socioeconomic information by municipality in Allegheny County and city of Pittsburgh neighborhood.

Hover over each neighborhood or municipality for more information on its vulnerability score, demographic breakdown, and socioeconomic characteristics.

Data sources: Surgo Ventures, “The U.S. COVID Community Vulnerability Index (CCVI),” webpage, undated-b; U.S. Census Bureau, “Table B02001, Race & Ethnicity, 5-Year Estimates,” American Community Survey table, 2019a; U.S. Census Bureau, “Table S0101, Age and Sex—United States, 5-Year Estimates,” American Community Survey table, 2019e; U.S. Census Bureau, “Table S1903: Median Income in the Past 12 Months (in 2019 Inflation-Adjusted Dollars)—Allegheny County, Pennsylvania,” American Community Survey table, 2019g; U.S. Census Bureau, “Table S1903: Median Income in the Past 12 Months (in 2019 Inflation-Adjusted Dollars)—Pittsburgh City, Pennsylvania,” American Community Survey table, 2019h.

Visualization 2. Monthly COVID-19 Cases and Tests, by Municipality or Pittsburgh Neighborhood

This map shows new monthly COVID-19 cases and tests per 100,000 people in each Allegheny County municipality or city of Pittsburgh neighborhood over time to illustrate how the distribution of cases has changed over the course of the pandemic.

Select whether the map shows all of Allegheny County (with neighborhood and municipal boundaries) or the city of Pittsburgh (with neighborhood boundaries).

This map shows estimates of new monthly COVID-19 cases and tests per 100,000 people in each Allegheny County municipality or Pittsburgh neighborhood. Bubbles over each neighborhood or municipality are sized to indicate the number of new monthly tests and are shaded from blue to yellow to represent the percentage of those tests that were positive. Geographic areas are colored along a gray scale, representing the total number of cases per 100,000 people.

By moving along the time slider, it is possible to explore where new cases were concentrated during any month since September 2020.

Hovering over each bubble or geographic area provides information about monthly and cumulative tests and cases within that area, as well as the populations and population-adjusted values used to color the bubbles and map.

Data notes: Monthly tests are capped at 500, meaning that new test counts above 500 are all sized the same. Positivity rates are capped at 50 percent, so positivity rates above 50 percent are all shaded yellow. Cumulative cases are capped at 15,000 per 100,000, so case counts above 15,000 per 100,000 appear in the darkest shade of gray. Over time, data corrections have led to large changes in cumulative test and case counts, which are evident in specific neighborhoods and municipalities as you move the time slider.

Data sources: Surgo Ventures, “The U.S. COVID Community Vulnerability Index (CCVI),” webpage, undated-b; U.S. Census Bureau, “U.S. Census Bureau Releases 2015–2019 ACS 5-Year Estimates,” webpage, December 10, 2020; Western Pennsylvania Regional Data Center, “0f214885-ff3e-44e1-9963-e9e9062 [Allegheny County COVID-19 counts, by municipality and Pittsburgh neighborhood],” Excel data file, undated-b.

Research Highlights

  • Black residents in Allegheny County test positive and are hospitalized from COVID-19 at higher rates than White residents.
  • COVID-19 positivity rates in Allegheny County as a whole have exceeded World Health Organization (WHO) recommended thresholds, with an average test positivity rate of 13 percent—much higher than the 5 percent benchmark rate.
  • More tests per capita have been conducted for Black residents than for White residents in Allegheny County, unlike at the national level.
  • Available testing sites are located near communities experiencing the highest vulnerability to COVID-19, reflecting the community’s advocacy to provide access in these communities.
  • Physical-distancing initiatives are associated with lower death rates, especially among the communities that are most vulnerable to COVID-19. However, residents in these communities are also less likely to be able to spend more time at home.

Recommendations for Policymakers

  • Routinely access and monitor disaggregated data related to racial inequity and geography; the impacts of the pandemic across different populations and communities change over time.
  • Provide greater assistance to help those who are most vulnerable to COVID-19 to practice physical distancing and use mobile testing so that they can receive the testing they need while reducing community transmission.
  • Consider appointing an equity-focused executive governance panel to provide continuous expert advice and feedback on critical issues and interventions moving forward.
  • Document and adapt best practices from testing access to inform the equitable distribution of and access to vaccines once availability is widespread.

Vulnerability and Inequity in Allegheny County

Vulnerability

We compared Allegheny County Health Department (ACHD) data that describe how testing, cases, and deaths have been distributed across neighborhoods and populations with data from Surgo’s CCVI, as shown earlier in Visualizations 1 and 2 (Surgo Ventures, undated-b). CCVI vulnerability scores are calculated by U.S. census tract for six themes—socioeconomic status, household composition or disability, minority status or language, housing type and transportation, epidemiological factors, and health care system factors—which are rolled up into a community score between 0 and 1.

Vulnerability in Allegheny County is driven primarily by socioeconomic status and household composition or disability, although vulnerability varies across the county. Table 1 below shows the communities with the highest and lowest CCVI scores in the county. (Neighborhoods in the city of Pittsburgh are indicated in parentheses.)

The combination of factors that constitute the CCVI definition of vulnerability can influence various health, economic, and social outcomes that are related to COVID-19, including severe COVID-19 spread, growth in unemployment, loss of income, decreased food security, and increased eviction and foreclosure.

Table 1. Communities with the Highest and lowest CCVI scores in Allegheny County

Highest CCVI Scores Lowest CCVI Scores
Municipality or Neighborhood CCVI Score Municipality CCVI Score
Crawford-Roberts (Pittsburgh) 0.94 Thornburg 0.01
Homestead 0.92 Rosslyn Farms 0.01
Homewood West (Pittsburgh) 0.89 Pine 0.01
Bedford Dwellings (Pittsburgh) 0.88 Bell 0.01
Northview Heights (Pittsburgh) 0.87 Reserve 0.01

Racial Inequity and Geography-Specific Trends

Since the beginning of the pandemic, the data working group of the BEC has been active in advocating for data transparency and the accuracy of COVID-19 outcomes data disaggregated by race and geography. In real time, the BEC takes a data-to-action approach, highlighting the impact of COVID-19 on historically marginalized populations for the community via original data dashboards and applied research.

When ACHD began releasing weekly updates about cumulative, neighborhood, and municipality-level COVID-19 cases and tests, the BEC began examining the weekly changes in cases and tests, and created a publicly available visualization of weekly case distribution, similar to that in Visualization 2 (Jared Kohler and the BEC Data Working Group, 2020). By mapping these numbers within constrained time windows, it became easier to identify geography-specific trends and hot spots.

Our analyses of these data track how COVID-19 has affected residents representing different races and geographies over time and have lent additional specificity to what we learned from applying the CCVI.

Cases, Hospitalizations, and Deaths

Key Findings

  • Black and Asian residents test positive for COVID-19 at higher rates than White residents.
  • Geographically, case incidences varied throughout the pandemic, reflecting varied patterns of community transmission, social behaviors, and containment efforts.
  • Black residents had higher death rates from COVID-19 than White populations for much of the pandemic, although the gap has narrowed.

Cases

Cases by Race

Disparities in COVID-19 cases by race in the county largely mirror national patterns, with rates among Black and Asian residents trending higher than rates among White residents since the beginning of the pandemic (Visualization 3).

As of January 17, 2021, there were 3,395 total cases (cumulative) per 100,000 people among the county’s White population, while there were 5,176 and 4,908 cases per 100,000 people among the county’s Black and Asian populations, respectively.

Visualization 3. Average New COVID-19 Cases, by Race, and Weekly Cumulative Cases, by Race

View average new confirmed and probable cases by race and cumulative confirmed and probable cases by race, per 100,000 people.

Hover over the bars and lines for a period of interest to show the specific value of new cases or cumulative cases.

Data notes: All counts of new cases include confirmed and probable cases of COVID-19. The “other” category includes biracial and multiracial and other race categories from source data. Per capita data for the “unknown” race category are not included because of the inability to calculate rates per 100,000 people when the total population size is unknown.

Data sources: U.S. Census Bureau, “Table B02001, Race & Ethnicity, 5-Year Estimates,” American Community Survey table, 2019a; Western Pennsylvania Regional Data Center, “4051a85a-bf92-45fc-adc6-b31eb8e [Allegheny County COVID-19 tests and cases],” Excel data file, undated-c.

Cases by Geography

As shown in Visualization 2, instead of following a consistent pattern of case distribution, case incidence shifted around the county from month to month, reflecting varied patterns of community transmission, social behaviors, and containment efforts.

For example, although early fall 2020 showed outbreaks in municipalities in the South Hills region of the county, such as Baldwin and Whitehall (where outbreaks were known to be concentrated in small immigrant communities), holiday periods showed widespread suburban incidence of infection, including in many of the more affluent and majority White portions of the county.

Hospitalizations and Deaths

Disparities in COVID-19 cases also have translated to differences in hospitalizations and deaths (see Visualization 4).

Since the start of the pandemic and as of January 17, 2021:

  • Black residents of Allegheny County were 2.1 times as likely as White residents to be hospitalized with COVID-19.
  • Black residents of Allegheny County were 2.4 times as likely as White residents to be admitted to the Intensive Care Unit (ICU) with COVID-19.
  • Black residents of Allegheny County were 2.3 times as likely as White residents to be placed on a ventilator after contracting COVID-19.

In the early months of the pandemic, Black residents were significantly more likely to die from COVID-19 than White residents, although the gap has narrowed. The cumulative death rate among Black residents has reached 100 per 100,000; the death rate among White residents is 103 per 100,000.

Visualization 4. Total Hospitalizations, ICU Admissions, Ventilator Use, and Deaths Because of COIVD-19, by Race, per 100,000 People

View cumulative hospitalizations, ICU admissions, ventilator use, and deaths per 100,000 people, by race.

Hover over the lines for a time period of interest to show the specific value.

Data notes: Over time, data corrections have led to large changes in cumulative test and case counts.

Data sources: U.S. Census Bureau, “Table B02001, Race & Ethnicity, 5-Year Estimates,” American Community Survey table, 2019a; Western Pennsylvania Regional Data Center, “4051a85a-bf92-45fc-adc6-b31eb8e [Allegheny County COVID-19 tests and cases],” Excel data file, undated-c; Western Pennsylvania Regional Data Center, “7507526c-1e28-49be-8b62-808fdd0 [Allegheny County COVID-19 deaths, by demographic group],” Excel data file, undated-d.

Access to Testing

Key Findings

  • Communities experiencing the highest vulnerability are the closest to available testing sites, which is consistent with local efforts to expand access in these communities.
  • Unlike at the national level, more tests per capita have been conducted for Black residents than for White residents.
  • Testing remains inadequate across the country, with positivity rates averaging higher than the World Health Organization benchmark rate.

Available Testing Options

Beginning in late May 2020, the BEC approached ACHD to consider a comprehensive, data-driven approach that centered the federally qualified Health centers (FQHCs) to provide more-convenient access to testing and other wrap-around services for priority communities. This resulted in the FQHCs offering free COVID-19 testing to their patients, and, in fall 2020, embedding culturally competent contact tracers in the centers with close coordination with ACHD. FQHCs typically serve low-income, largely racial and ethnic minority populations, and the Coronavirus Aid, Relief, and Economic Security Act (CARES) Act funding allowed ACHD to test anyone who needed it for free.

Several private testing providers also exist, including local health systems and national pharmacy and urgent care chains, the majority of which bill insurance for COVID-19 tests.

Additionally, a small number of providers (typically FQHCs) offer mobile testing services, the locations of which vary from week to week (Allegheny County Health Department, undated). As of March 2021, there were typically two to three mobile testing sites open per day around the county for at least three to four hours per day, and they would tweet their locations daily.

One faith-based initiative has expanded access to testing in partnership with churches, both via fixed sites at church facilities and via mobile testing vans in church parking lots.

Proximity to Testing

We compared the distance to testing sites by vulnerability to determine the average distance and travel time to the nearest test site by vulnerability. We specifically looked at vulnerability within the housing type and transportation theme of the CCVI (Visualization 5).

Consistent with the local push to offer testing at FQHCs, the average distance (in miles and travel time) is inversely related to vulnerability, with the census tracts that experience higher vulnerability located closer to test sites, on average.

Visualization 5. Test Sites, by Neighborhood or Municipality Vulnerability, and Census Tracts with Test Site Access Challenges

Select whether the map shows all of Allegheny County (with neighborhood and municipal boundaries) or the city of Pittsburgh (with neighborhood boundaries).

Toggle among maps that show test site locations and the vulnerability (per the CCVI, including the specific CCVI theme related to housing type and transportation) of each neighborhood or municipality, longer-than-median travel times to the nearest test site, or larger-than-median proportions of residents without access to a vehicle.

Data sources: GISCorps, “Locate COVID-19 Testing Sites,” data set, undated-b; Google Maps, “Web Services: Distance Matrix API,” webpage, updated April 20, 2021.

According to the CCVI, only a small proportion (about 8 percent) of all census tracts experience high vulnerability. However, a subset of these tracts have a longer-than-median commute to the nearest test site (more than 22 minutes) and higher-than-median proportion of the population without a vehicle (more than 15.7 percent) (Table 2).

Overall, COVID-19 testing in Allegheny County remains inadequate, with positivity rates averaging 13 percent and ranging between 1 percent and 29 percent, which is much higher than the 5 percent benchmark recommended by the WHO. Increased testing, in addition to compliance with physical-distancing, mask-wearing, and other interventions to reduce community transmission, might help to lower positivity rates and reduce cases in the county.

Table 2. Median Distance (Miles) and Median Travel Time (Minutes) to the Nearest Testing Site, by Vulnerability

  High Vulnerability Medium Vulnerability Low Vulnerability
Median distance (miles) 2.0 2.8 3.7
Median travel time (minutes) 15.7 21.4 38.9

At the national level, studies have indicated disparities in access to testing among racial and ethnic minorities. This coincides with extensive historical evidence describing the disparate access to health care services experienced by racial and ethnic minorities.

However, in Allegheny County, more tests per capita have been conducted for Black residents (13.6 percent of the county’s population) than White residents (78.3 percent of the county’s population), reflecting the extensive efforts of local stakeholders to expand equitable access to testing. Despite increased testing for Black residents, positivity rates generally have been higher for Black residents than for White residents over the course of the pandemic. At times, positivity rates for Asian residents have been especially high, although they have been falling since December 2020.

Cases among the Black population spiked in July 2020 to high per-capita levels, and this pattern appeared to reemerge in the winter pandemic wave. Testing rates among other racial and ethnic minorities (e.g., Asian residents, comprising 3.5 percent of the county’s population) have varied significantly over the course of the pandemic, with rates among Asian residents surpassing other racial and ethnic groups in early fall 2020 (Visualization 6).

Visualization 6. Positivity Rates and Number of Tests Conducted per 100,000 People, by Race and by Week

View average positivity rates by race (number of positive tests divided by the total number of tests) (top), average daily tests and cases overall (middle), and average daily tests by race (per 100,000 people) (bottom). The average positivity rate is displayed alongside the benchmark positivity rate of 5 percent set by the WHO, which is shown as a blue line in the top graph.

Hover over the bars or lines for a period of interest to show specific values of positivity rates, test counts, and case counts.

Data notes: Positivity rates have been suppressed when the number of average daily tests is less than 25. The “other” category includes biracial and multiracial and other race categories from source data.

Data sources: Johns Hopkins University of Medicine Coronavirus Resource Center, “Which U.S. States Meet WHO Recommended Testing Criteria?” webpage, updated May 3, 2021; U.S. Census Bureau, “Table B02001, Race & Ethnicity, 5-Year Estimates,” American Community Survey table, 2019a; Western Pennsylvania Regional Data Center, “4051a85a-bf92-45fc-adc6-b31eb8e [Allegheny County COVID-19 tests and cases],” Excel data file, undated-c.

Other Barriers in Access to Testing

Despite local efforts, disparities in access to COVID-19 testing remain. In addition to distance to testing sites, the following barriers prevent some individuals from receiving testing:

  • necessary referrals or appointments: At the time this tool was produced, three out of four COVID-19 testing sites required an appointment before testing. Although this is a necessary step for safely coordinating testing, it still adds extra steps to the care-seeking process.
  • testing eligibility requirements: Only 45 precent of the 94 test sites suggested by the results of a December 12, 2020, Google search for "COVID test Allegheny Pennsylvania" offered testing for all patients. The rest advertised "Testing limited to certain patients."
  • constrained capacity: The average hours of operation for test sites in Allegheny County is 4.5 hours, which is little more than half of the normal eight-hour workday. Interviews with testing providers identified human resources issues (including staff shortages and fatigue) and access to appropriate facilities (including those with sufficient outdoor or indoor space to allow for testing and conducting normal operations with physical-distancing requirements in place) as major constraints.

Physical Distancing

Key Findings

  • Physical-distancing initiatives are associated with fewer deaths, especially among communities expericiencing the highest vulnerability.
  • When communities increase their time spent at home at the same rate, the likelihood of being tested declines most among communities experiencing the highest vulnerability.

By reducing face-to-face contact and interpersonal transmission, physical-distancing policies (also referred to as social distancing) help “flatten the curve” of infections to minimize the burden on the health care system.

One way to measure adherence to the policy of physical distancing is to look at the percentage of time individuals spend at home. Analyses based on cell phone tracking data from Allegheny County show a dramatic change in the percentage of time spent at home leading up to and following a stay-at-home order issued by Governor Tom Wolf (Office of the Governor, Commonwealth of Pennsylvania, 2020a). Between early and late March 2020, the percentage of time spent at home increased from approximately 70 percent to nearly 95 percent.

However, there is an equity concern with the policy of physical distancing. Those who work in essential services, work in jobs that cannot be performed remotely, or face financial pressures to continue working throughout the pandemic often are less able to practice physical distancing and thereby face greater risks of infection.

Differences in adherence to physical-distancing policies were associated with vulnerability (per the CCVI, both overall and specific to the housing type and transportation theme), and with demographic and socioeconomic measures. Communities in Allegheny County that were experiencing the highest COVID-19 vulnerability were also the communities that were spending the lowest percentage of time at home, particularly in the early days of the pandemic in spring 2020 and in November and December 2020 (Visualization 7).

Visualization 7. Changes in Time Spent at Home in Allegheny County, by Week

Toggle between graphs to explore the percentage of time spent at home overall, by vulnerability (per the CCVI), and by demographic and socioeconomic information. Data last updated on April 16, 2021.

Govenor Wolf’s plan to reopen Pennsylvania was divided into red, yellow, and green phases, which transitioned from most to least restrictive (Office of the Governor, Commonwealth of Pennsylvania, 2020b). Hover over the lines to a time period of interest to view the precise percentage of time spent at home.

Data sources: SafeGraph, homepage, undated; Surgo Ventures, “The U.S. COVID Community Vulnerability Index (CCVI),” webpage, undated-b; U.S. Census Bureau, “Table B02001, Race & Ethnicity, 5-Year Estimates,” American Community Survey table, 2019a; U.S. Census Bureau, “Table S0101, Age and Sex—United States, 5-Year Estimates,” American Community Survey table, 2019e; U.S. Census Bureau, “Table S1903: Median Income in the Past 12 Months (in 2019 Inflation-Adjusted Dollars)—Allegheny County, Pennsylvania,” American Community Survey table, 2019g; U.S. Census Bureau, “Table S1903: Median Income in the Past 12 Months (in 2019 Inflation-Adjusted Dollars)—Pittsburgh City, Pennsylvania,” American Community Survey table, 2019h.

When we examine links by vulnerability, increasing time spent at home by 10 percent is associated with 56 fewer tests per 1,000 people within communities experiencing the most vulnerability.

When we look at demographic and socioeconomic measures, this disparity in the association between testing and the percentage of time spent at home is also seen when comparing by communities’ median household income and the CCVI’s housing type and transportation theme. Among communities with the lowest median household income, increasing time spent at home by 10 percent is associated with 93 fewer tests per 1,000 people. Among communities identified as the most vulnerable based on housing type and transportation, increasing time spent at home by 10 percent is associated with 36 fewer tests per 1,000 people.

Furthermore, among those experiencing the highest vulnerability, the implementation of physical-distancing measures is associated with a greater likelihood of testing positive for COVID-19. This pattern is likely attributable to fewer tests overall among those experiencing the highest vulnerability who practice physical distancing, meaning that a higher proportion of their tests are positive (Visualization 8). (For more details on the model and calculations behind these analyses, see the technical appendix.)

Visualization 8. Changes in Tests and Deaths With a 10-Percent Increase in Time Spent at Home

Toggle between graphs to explore changes in tests and deaths by vulnerability (per the CCVI, including the housing type and transportation theme), and by demographic and socioeconomic information.

Data sources: SafeGraph, “Social Distancing Metrics,” webpage, 2021; Surgo Ventures, “The U.S. COVID Community Vulnerability Index (CCVI),” webpage, undated-b; U.S. Census Bureau, “Table B02001, Race & Ethnicity, 5-Year Estimates,” American Community Survey table, 2019a; U.S. Census Bureau, “Table S0101, Age and Sex—United States, 5-Year Estimates,” American Community Survey table, 2019e; U.S. Census Bureau, “Table S1903: Median Income in the Past 12 Months (in 2019 Inflation-Adjusted Dollars)—Allegheny County, Pennsylvania,” American Community Survey table, 2019g; U.S. Census Bureau, “Table S1903: Median Income in the Past 12 Months (in 2019 Inflation-Adjusted Dollars)—Pittsburgh City, Pennsylvania,” American Community Survey table, 2019h.

Examining physical distancing through the lens of the CCVI and the demographic and socioeconomic measures associated with COVID-19 inequities also suggests that there could be a reduction in COVID-19 deaths when the communities experiencing the highest vulnerability are able to both spend more time at home and receive tests.

For instance, 10 percent more time at home among those who have tested positive and live in the communities experiencing the highest vulnerability as defined by the CCVI is associated with a 1.06-percent decrease in deaths. The percentages of death among the moderately and least vulnerable communities who tested positive decrease by 0.83 percent and 0.15 percent, respectively. When examining those experiencing high vulnerability within the housing type and transportation theme of the CCVI, 10 percent more time at home is associated with a 0.92 percent decrease in deaths among those who tested positive. The same pattern holds when examining variation by the communities’ Black, Asian, and elderly populations: Ten percent more time at home among those who have tested positive and who live in communities with large Black populations is associated with a 1.02-percent decrease in deaths. Similarly, 10 percent more time at home among those who have tested positive and who live in communities with large Asian populations or with large populations of those over age 65 is associated with a 1.55-percent and a 1.42-percent decrease in deaths, respectively.

Looking Ahead

Although testing access to date appears to have been successfully aimed at communities experiencing the highest COVID-19 vulnerability, the future is uncertain, and in general, testing rates in the county are still much lower than recommended. Starting in late November 2020, insured individuals who obtained a test through ACHD began to have their insurance billed.

Currently, uninsured individuals are still able to be tested for free, and recent federal legislation likely will support ongoing free testing, but uncertainty around funding for those tests might begin to influence testing capacity.

Recommendations

Our analyses provide the following important lessons for local policymakers in Allegheny County, as well as policymakers throughout the country:

  • Although the CCVI captures the potential risk for COVID-19 and associated negative outcomes at one snapshot in time, it is also important to monitor trends in an ongoing fashion. Deaths for Black populations were disproportionate throughout the pandemic until the rates of deaths among White populations increased toward the end of 2020. Data also show that the neighborhoods with the highest COVID-19 positivity rates have been changing over time as outbreaks happen in certain communities and populations. This suggests the need to routinely access and monitor disaggregated data that are related to racial inequity and linked to geography because the impacts of the pandemic across different populations and communities change over time.
  • Initiatives that encourage people to physically distance have demonstrated associations with a reduced number of tests, as was broadly intended by such policies. However, it is also evident that certain communities are less able to practice physical distancing, specifically those communities experiencing the highest vulnerability. If physical distancing is practiced and the needed testing is received, the associations with fewer deaths are strongest among those experiencing the highest vulnerability, including those with high vulnerability that is specifically related to housing and transportation factors. This indicates both (1) the need for greater assistance to help those experiencing the highest vulnerability to practice physical distancing and (2) the need for mobile testing so that they can receive the testing they need while reducing community transmission.
  • Interventions are needed to address the alarming inequities in COVID-19 impacts among historically marginalized populations in Allegheny County. Solutions must involve community-centered, collaborative partnerships that operate with a shared goal to address racial inequities and injustices. County officials could appoint an equity-focused executive governance panel to provide continuous expert advice and feedback on critical issues and interventions moving forward.
  • As vaccine allocation and distribution ramps up, it is critical to maintain focus on communities experiencing vulnerability and on equitable access to resources. Replicating best practices from test site distribution, such as engagement with the BEC and strengthening FQHC partnerships, could go a long way toward the equitable distribution of vaccine across communities in Allegheny County. A focus on funding sources that support equitable access and resources will be necessary.

About This Tool

This research was jointly conducted by the Community Health and Environmental Policy Program in RAND Social and Economic Well-Being, the Black Equity Coalition, and Surgo Ventures to examine vulnerability to COVID-19 and the pandemic’s impacts within a specific community.

Surgo constructed the CCVI to predict which U.S. communities would be less resilient to the COVID-19 pandemic. Surgo defined vulnerability as a limited ability to mitigate, treat, and delay transmission of the virus and to weather its secondary effects on health, economic and social outcomes.

RAND researchers then compared the CCVI with public Allegheny County Health Department data that describes how testing, cases, and deaths have been distributed across neighborhoods and populations.

The BEC contributed historical context about the evolution and impact of the pandemic for historically marginalized populations in Allegheny County. The BEC also contributed data from its ongoing dashboard related to trends in COVID-19 by municipality or neighborhood over time. It also contributed to the interpretation of data and recommendations in this tool.

Technical documentation offering additional context and information on methods and data sources used for this analysis is available.

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Community Health and Environmental Policy Program

RAND Social and Economic Well-Being is a division of the RAND Corporation that seeks to actively improve the health and social and economic well-being of populations and communities throughout the world. This research was conducted in the Community Health and Environmental Policy Program within RAND Social and Economic Well-Being. The program focuses on such topics as infrastructure, science and technology, community design, community health promotion, migration and population dynamics, transportation, energy, and climate and the environment, as well as other policy concerns that are influenced by the natural and built environment, technology, and community organizations and institutions that affect well-being. For more information, email chep@rand.org.

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