COVID-19 Outcomes Among the Hispanic Population of 27 Large US Cities, 2020–2021

Abstract

Objectives. To examine racial/ethnic disparities in COVID-19 outcomes between Hispanics and Whites across 27 US jurisdictions whose health departments are members of the Big Cities Health Coalition (BCHC).

Methods. Using surveillance data from the BCHC COVID-19 dashboard as of mid-June 2021, we computed crude incidence, age-adjusted hospitalization and mortality, and full vaccination coverage rates for Hispanics and Whites by city. We estimated relative and absolute disparities cumulatively and for 2020 and 2021 and explored associations between city-level social vulnerability and the magnitude of disparities.

Results. In most of the cities with available COVID-19 incidence data, rates among Hispanics were 2.2 to 6.7 times higher than those among Whites. In all cities, Hispanics had higher age-adjusted hospitalization (1.5–8.6 times as high) and mortality (1.4–6.2 times as high) rates. Hispanics had lower vaccination coverage in all but 1 city. Disparities in incidence and hospitalizations narrowed in 2021, whereas disparities in mortality remained similar. Disparities in incidence, hospitalization, mortality, and vaccination rates were wider in cities with lower social vulnerability.

Conclusions. A deeper exploration of racial/ethnic disparities in COVID-19 outcomes is essential to understand and prevent disparities among marginalized communities. (Am J Public Health. 2022;112(7): 1034–1044. https://doi.org/10.2105/AJPH.2022.306809)

The United States has been one of the countries most affected by the COVID-19 pandemic.¹ Hispanics and other minoritized racial/ethnic groups have been disproportionately affected throughout the country.² This has led to life expectancy reductions among Hispanics that are 3 to 4 times larger than the reductions observed among non-Hispanic Whites (hereafter referred to as Whites).³ Despite disproportionate COVID-19 infection, hospitalization, and mortality rates among Hispanics, evidence emerging from different regions of the country shows that this population lags in vaccination rates relative to Whites.⁴

Although COVID-19 inequities have received substantial attention in the academic literature, this research has primarily focused on disparities measured at the state or county level^5–7 or within zip codes in a small number of cities.^8,9 For example, Xu et al. found disproportionate effects due to COVID-19 among Hispanics and non-Hispanic Blacks (hereafter referred to as Blacks) relative to Whites across 45 states and the District of Columbia,⁶ Gross et al. reported a similar burden among Hispanics and Blacks with respect to COVID-19 mortality across 28 states and New York City,⁵ Moore et al. found wider racial/ethnic COVID-19 disparities in “hotspot” counties,⁷ and Benitez et al., using zip code–level data across 6 cities, found a positive association between the percentage of Hispanic and Black residents and COVID-19 incidence.¹⁰ Some studies have also assessed the association between county-level social vulnerability and COVID-19 outcomes^11–13 and even explored changes over time in this association.¹¹

However, to our knowledge, no study has investigated racial/ethnic inequities in different COVID-19 outcomes with a focus on the largest US cities, where a majority of Hispanics live,¹⁴ or assessed the ways in which disparities have evolved over time^11,15 or according to social vulnerability. Cities are heterogeneous in terms of both composition and context, which may influence health inequities. Therefore, examining how factors that vary across cities (e.g., social vulnerability) relate to the magnitude of disparities within cities can help identify intervention points as state and local governments and community-led initiatives work to design, implement, and coordinate responses to the pandemic.

Using surveillance data on COVID-19 cases, hospitalizations, mortality, and vaccinations, we examined disparities in COVID-19 outcomes between Hispanic and White populations across large US cities (from 13 to 20 cities depending on the outcome) and explored associations between the magnitudes of disparities and city-level social vulnerability. Documenting racial/ethnic inequities across cities is critical in not only revealing differential exposures and vulnerabilities among Hispanic communities but also informing resource allocation and the development of more targeted interventions to mitigate inequities.

METHODS

In this ecological study, we examined the Hispanic and White populations of 27 of the 30 jurisdictions whose health departments are members of the Big Cities Health Coalition (BCHC). To be eligible for BCHC membership, cities must be in the top 30 of the country’s most populous urbanized areas (as defined by the US Census Bureau), have a population of 400 000 or more, and have a locally controlled health department or, if they are not among the top 30 most populous urban areas, they must have a population of 800 000 or more and a locally controlled health department.¹⁶

We obtained data from the BCHC COVID-19 Inequities in Cities Dashboard project,¹⁷ which compiles data from city, county, or state health department repositories or from the Centers for Disease Control and Prevention (CDC) COVID-19 Case Surveillance Restricted Access Detailed Data (June 21, 2021, version). To ensure the greatest possible number of outcomes per city, the dashboard employs a combination of city-level data and county-level data to proxy cities (Table A, available as a supplement to the online version of this article at http://www.ajph.org).

We also used the CDC’s 2018 Social Vulnerability Index (SVI) at the city or county level,¹⁸ depending on the level of data availability for each city or outcome. The SVI quantifies the degree to which a community is vulnerable to external stressors, including disease outbreaks. The index summary score includes 15 variables representing 4 domains (socioeconomic status, household composition and disability, minority status and language, housing type and transportation). The SVI is calculated by ranking cities (nationally) according to the values of the 15 variables in each domain, and percentile ranks are then computed for each city according to domain and summary score. SVI scores range from 0 to 1, with higher scores indicating higher vulnerability.

Outcomes

We examined 4 COVID-19 outcomes: incidence rates per 100 000, hospitalization rates per 100 000, mortality rates per 100 000, and vaccination coverage (percentage of individuals fully vaccinated across the entire population, irrespective of age). We used cumulative data as of mid-June 2021 and cumulative data for all of 2020, as well as data from January to mid-June 2021 separately, to compute these outcomes. To make the 2020 and 2021 rates comparable, we multiplied 2021 rates by 365/168, where 168 is the number of days covered by the 2021 data, so that both 2020 and 2021 rates involved a 1-year cumulative rate interpretation. Data on total and race/ethnicity-specific city populations were obtained from the 2015 to 2019 American Community Survey. All rates were calculated for Hispanics and Whites separately.

Although the terms “Hispanic” and “Latinx” may refer to the same groups of individuals (i.e., Hispanic refers to those of Spanish-speaking origin and Latinx refers to those of Latin American descent), we use Hispanic to encapsulate individuals of either Hispanic or Latinx descent. We included only cities that reported race and ethnicity jointly (e.g., Hispanic, non-Hispanic White).

Age has a critical role in determining disease severity. Therefore, we used age-adjusted rates for hospitalizations and mortality, with the 2000 US standard population as the reference population. Because the number of cities providing data on incidence or vaccination by both race/ethnicity and age was limited, we decided to use crude incidence and vaccination coverage to maximize data availability. Moreover, although we examined 27 member cities of the BCHC, not all 27 cities reported all 4 of our outcomes by race/ethnicity. We decided to maximize the number of cities included in our study by not limiting the sample to the 7 cities that reported all outcomes. We used data on crude incidence for 20 cities (representing 29.7 million inhabitants), data on age-adjusted hospitalizations for 19 cities (28.5 million inhabitants), data on age-adjusted mortality for 20 cities (29 million inhabitants), and data on crude full vaccination coverage for 13 cities (27.4 million inhabitants; for a description of the included cities, see Table B, available as a supplement to the online version of this article at http://www.ajph.org).

Statistical Analyses

Because small relative differences can mask large absolute differences, we calculated both rate ratios (RRs) and rate differences (RDs). Rate ratios were used to assess relative disparities by dividing the rate among Hispanics versus the rate among Whites, whereas rate differences were used to assess absolute disparities by subtracting the rate among Whites from the rate among Hispanics. The appendix (available as a supplement to the online version of this article at http://www.ajph.org) contains details on the calculation of confidence intervals (CIs) for both measures. To examine whether disparities changed in 2021, we also graphically compared rates and disparities in incidence, hospitalizations, and mortality in 2020 and 2021. As a means of assessing the association between the magnitude of disparities and social vulnerability, we used scatterplots and Spearman correlation coefficients to explore correlations of city-level SVI values (and their 4 domains) with COVID-19 outcome rates among Hispanics and Whites and with relative disparities in COVID-19 outcomes.

We used R version 4.0.1 (R Foundation, Vienna, Austria) to conduct all of the statistical analyses. BCHC data are available for download at the BCHC COVID-19 Inequities in Cities Dashboard project Web site (http://www.covid-inequities.info).

RESULTS

Our analysis incorporated up to 27 cities with a total of 37.1 million residents (median city size = 874 401; interquartile ratio [IQR] = 640 032–1 458 828), including 11.9 million Hispanic residents and 13.2 million White residents (see Table B for further details on city characteristics). Table 1 shows racial/ethnic disparities in COVID-19 crude incidence, age-adjusted hospitalization, and age-adjusted mortality rates between Hispanics and Whites. Incidence, hospitalization, and mortality disparities were statistically significant for all cities with available data, as confidence intervals did not include 1 (for relative disparities) or 0 (for absolute disparities) for any of these cities.

TABLE 1—

COVID-19 Crude Incidence Rates, Age-Adjusted Hospitalization Rates, and Age-Adjusted Mortality Rates Among Hispanics and Non-Hispanic Whites in 23 Large US Cities, 2020 and 2021

City	Incidence				Hospitalization				Mortality
Hispanic, Rate	Non-Hispanic White, Rate	RR (95% CI)	RD (95% CI)	Hispanic, Rate	White, Rate	RR (95% CI)	RD (95% CI)	Hispanic, Rate	White, Rate	RR (95% CI)	RD (95% CI)
Boston, MA	14 167	7 126	1.99 (1.95, 2.02)	7 041 (6 834, 7 248)	50	204	3.18 (2.90, 3.49)	445 (406, 485)	256	176	1.45 (1.29, 1.64)	80 (53, 107)
Charlotte, NC	9 802	4 342	2.26 (2.21, 2.30)	5 460 (5 296, 5 625)	588	98	5.97 (5.35, 6.68)	489 (449, 530)	266	62	4.27 (3.68, 4.96)	204 (176, 232)
Chicago, IL	12 027	6 171	1.95 (1.93, 1.97)	5 856 (5 769, 5 944)	771	300	2.57 (2.49, 2.65)	470 (454, 487)	323	139	2.33 (2.22, 2.44)	185 (174, 195)
Cleveland, OH	8 036	6 216	1.29 (1.26, 1.33)	1 820 (1 616, 2 023)	506	255	1.98 (1.78, 2.22)	251 (199, 303)	176	132	1.34 (1.11, 1.60)	44 (13, 76)
Columbus, OH	10 868	5 730	1.90 (1.85, 1.95)	5 139 (4 869, 5 409)	676	179	3.77 (3.40, 4.18)	496 (436, 557)	252	123	2.05 (1.75, 2.40)	129 (91, 167)
Dallas, TX	7 822	8 372	0.93 (0.93, 0.94)	−550 (−631, −469)	NA	NA	NA	NA	NA	NA	NA	NA
Denver, CO	11 486	5 223	2.20 (2.16, 2.24)	6 264 (6 110, 6 417)	1 050	258	4.08 (3.78, 4.39)	792 (746, 839)	230	102	2.26 (1.97, 2.58)	128 (105, 151)
Kansas City, MO	NA	NA	NA	NA	1 300	873	1.49 (1.37, 1.62)	427 (324, 531)	204	77	2.65 (2.09, 3.35)	127 (87, 167)
Las Vegas, NV (metro)	11 941	6 565	1.82 (1.80, 1.84)	5 377 (5 285, 5 469)	978	409	2.39 (2.30, 2.49)	568 (542, 595)	303	139	2.18 (2.03, 2.33)	164 (149, 179)
Long Beach, CA	9 859	4 031	2.45 (2.37, 2.52)	5 828 (5 659, 5 997)	NA	NA	NA	NA	NA	NA	NA	NA
Los Angeles, CA	26 348	8 310	3.17 (3.16, 3.18)	18 038 (17 987, 18 089)	2 354	755	3.12 (3.07, 3.16)	1 599 (1 582, 1 616)	694	258	2.69 (2.62, 2.76)	436 (426, 445)
Miami, FL	NA	NA	NA	NA	296	172	1.72 (1.58, 1.87)	124 (108, 139)	206	134	1.54 (1.40, 1.70)	73 (59, 86)
Minneapolis, MN	16 301	6 160	2.65 (2.60, 2.69)	10 141 (9 889, 10 393)	NA	NA	NA	NA	219	117	1.87 (1.60, 2.18)	102 (70, 134)
New York, NY	8 855	6 449	1.37 (1.36, 1.38)	2 405 (2 359, 2 452)	1 419	720	1.97 (1.94, 2.01)	700 (682, 718)	367	199	1.85 (1.79, 1.91)	169 (159, 178)
Oakland, CA	9 480	1 807	5.24 (5.13, 5.36)	7 673 (7 572, 7 774)	463	80	5.78 (5.19, 6.43)	383 (359, 406)	116	41	2.83 (2.40, 3.34)	75 (63, 88)
Philadelphia, PA	7 206	8 253	0.87 (0.86, 0.89)	−1 047 (−1 175, −919)	1 674	583	2.87 (2.74, 3.01)	1 091 (1 035, 1 147)	336	175	1.92 (1.75, 2.11)	161 (135, 187)
Phoenix, AZ	11 056	7 676	1.44 (1.43, 1.45)	3 380 (3 317, 3 443)	1 517	690	2.20 (2.15, 2.24)	826 (803, 850)	381	131	2.91 (2.79, 3.04)	251 (239, 262)
Portland, OR	9 056	2 310	3.92 (3.82, 4.02)	6 745 (6 557, 6 934)	NA	NA	NA	NA	NA	NA	NA	NA
San Diego, CA	11 465	3 857	2.97 (2.94, 3.00)	7 608 (7 542, 7 675)	843	191	4.42 (4.24, 4.61)	652 (634, 671)	224	55	4.09 (3.78, 4.42)	169 (159, 178)
San Francisco, CA	10 761	1 589	6.77 (6.57, 6.98)	9 171 (9 000, 9 343)	530	61	8.64 (7.43, 10.06)	469 (429, 509)	99	31	3.20 (2.48, 4.12)	68 (50, 86)
San Jose, CA	12 217	2 666	4.58 (4.51, 4.66)	9 551 (9 451, 9 652)	710	96	7.41 (6.78, 8.08)	614 (589, 639)	185	48	3.85 (3.37, 4.39)	137 (124, 150)
Seattle, WA	NA	NA	NA	NA	856	176	4.86 (4.57, 5.17)	680 (640, 720)	139	57	2.43 (2.12, 2.78)	82 (65, 98)
Washington, DC	9 712	2 756	3.52 (3.41, 3.64)	6 956 (6 736, 7 175)	1 454	195	7.45 (6.70, 8.28)	1259 (1172, 1345)	270	43	6.23 (4.94, 7.85)	227 (189, 265)

Note. CI = confidence interval; NA = not available; RD = rate difference; RR = rate ratio. Data are cumulative as of mid-June 2021. Incidence, hospitalization, and mortality rates are per 100 000. Non-Hispanic Whites are the referent populations in rate ratios and rate differences.

In more than half (11) of the 20 cities with crude incidence data available, rates among Hispanics were twice as high as those among Whites. Relative incidence disparities were greatest in San Francisco (RR = 6.77; 95% CI = 6.57, 6.98) and Oakland (RR = 5.24; 95% CI = 5.13, 5.36), California, whereas absolute disparities were greatest in Los Angeles, California (RD = 18 038 per 100 000; 95% CI = 17 986, 18 089), and Minneapolis, Minnesota (RD = 10 140 per 100 000; 95% CI = 9889, 10 392). Dallas, Texas, and Philadelphia, Pennsylvania, were the only 2 cities in which incidence rates were lower among Hispanics than among Whites. The incidence rate was 7% lower among Hispanics than Whites in Dallas (RR = 0.93; 95% CI = 0.93, 0.94; RD = −550 per 100 000; 95% CI = −631, −469) and 13% lower among Hispanics than Whites in Philadelphia (RR = 0.87; 95% CI = 0.86, 0.89; RD = −1047 per 100 000; 95% CI = −1175, −919).

In 15 of the 19 cities with age-adjusted hospitalization data available, hospitalization rates were 2 to almost 9 times as high among Hispanics as among Whites (with rate ratios ranging from 2.19 to 8.64). San Francisco (RR = 8.64; 95% CI = 7.43, 10.06) and Washington, DC (RR = 7.45; 95% CI = 6.70, 8.28), had the widest relative disparities, and Los Angeles (RD = 1599 per 100 000; 95% CI = 1582, 1616) and Washington, DC (RD = 1259 per 100 000; 95% CI = 1172, 1345), had the widest absolute disparities.

Age-adjusted mortality rates were higher among Hispanics in all 20 cities with age-adjusted mortality data available; however, relative disparities differed widely (with rate ratios ranging from 1.33 to 6.23). The widest relative disparities were observed in Washington, DC (RR = 6.23; 95% CI = 4.94, 7.85); Charlotte, North Carolina (RR = 4.27; 95% CI = 3.68, 4.96); San Diego, California (RR = 4.09; 95% CI = 3.78, 4.42); and San Jose, California (RR = 3.85; 95% CI = 3.37, 4.39). The widest absolute disparities were observed in Los Angeles (RD = 436 per 100 000; 95% CI = 426, 445) and Phoenix, Arizona (RD = 250 per 100 000; 95% CI = 239, 262).

Finally, Table C (available as a supplement to the online version of this article at http://www.ajph.org) shows racial/ethnic disparities in crude vaccination coverage among Hispanics versus Whites. Vaccination coverage (percentage of individuals fully vaccinated) was 12% to 44% lower among Hispanics than Whites in all but 1 of the 13 cities (San Francisco) with vaccination coverage data available (with Hispanic to White ratios ranging from 0.46 to 0.88). Fort Worth, Texas (RR = 0.56; 95% CI = 0.55, 0.56), had the widest relative disparity, with Hispanics 44% less likely than Whites to have been vaccinated. Austin, Texas, had the widest absolute disparity (−20.2%; 95% CI = −20.4, −20.1).

Figure 1 provides a comparison of relative disparities between Hispanics and Whites in COVID-19 incidence, hospitalization, and mortality rates in 2020 versus 2021 (up to mid-June). Of the 15 cities with incidence and hospitalization data for both periods, 13 had narrower disparities during 2021 than 2020; approximately half of the study cities had wider disparities in mortality during 2021. Figure A (available as a supplement to the online version of this article at http://www.ajph.org) shows changes in absolute disparities, which narrowed in most cities (10 of 15 cities for incidence, 14 of 15 cities for hospitalizations, 14 of 17 cities for mortality). Figure B (available as a supplement to the online version of this article at http://www.ajph.org) shows that incidence rates were similar in 2020 and 2021 among Hispanics but increased in all cities among Whites, hospitalization rates declined among Hispanics in 2021 and remained similar among Whites, and mortality rates decreased in most cities in both groups.

FIGURE 1—

Relative Disparities Between Hispanics and Whites for COVID-19 (a) Crude Incidence Rates, (b) Age-Adjusted Hospitalization Rates, and (c) Age-Adjusted Mortality Rates: 19 Large US Cities, 2020 and 2021

Note. NH = non-Hispanic; RR = rate ratio. The RR for 2020 refers to the ratio of crude incidence rates, age-adjusted hospitalization rates, or age-adjusted mortality rates between Hispanics and NH Whites up to December 31, 2020. The RR for 2021 refers to the ratio of crude incidence rates, age-adjusted hospitalization rates, or age-adjusted mortality rates between Hispanics and NH Whites from January 1 to mid-June 2021. The diagonal line represents a y = x line. A point on that line represents a city where disparities in 2020 were similar to those in 2021, a point above the line represents a city where disparities were wider in 2021, and a point below the line represents a city where disparities were wider in 2020.

Figure 2 shows the relationship between city-level summary SVI values and COVID-19 rates among Hispanics and Whites, and Figure 3 shows the relationship between SVI values and relative disparities for each outcome. Relative disparities in incidence, hospitalization, and mortality rates were narrower in cities with higher social vulnerability, reflecting higher rates among Whites in these cities; rates among Hispanics varied less by city-level SVI (and, in the case of incidence, were even slightly lower in cities with higher SVI values). These correlations were driven by the socioeconomic status and household composition and disability domains, with the minority status and language and housing and transportation domains having weaker correlations (Table D, available as a supplement to the online version of this article at http://www.ajph.org).

FIGURE 2—

Associations Between Social Vulnerability and COVID-19 (a) Incidence, (b) Hospitalization, and (c) Mortality Rates Among Hispanics and Non-Hispanic Whites: 23 Large US Cities, 2020 and 2021

Note. CI = confidence interval. Data represent cumulative rates as of mid-June 2021. Solid black lines represent the linear fit between the Social Vulnerability Index and log(rates) for Hispanics, and dashed lines represent the linear fit between the Social Vulnerability Index and log(rates) for Non-Hispanic Whites. Βeta coefficients for slopes and associated P values are displayed separately for Hispanics and non-Hispanic Whites.

FIGURE 3—

Associations Between Social Vulnerability and COVID-19 (a) Incidence, (b) Hospitalization, and (c) Mortality Disparities Among Hispanics and Non-Hispanic Whites: 23 Large US Cities, 2020 and 2021

Note. CI = confidence interval. Data represent cumulative disparities as of mid-June 2021. Rate Ratio was computed by dividing rates among Hispanics over rates among non-Hispanic Whites. The solid line represents the linear fit between the log(rate ratio) of each outcome and the Social Vulnerability Index. Βeta coefficients for slopes and associated P values are displayed. The dashed horizontal line represents the reference rate ratio of 1, which indicates no disparities.

We found narrower disparities in vaccination coverage in cities with higher social vulnerability (Figure C, available as a supplement to the online version of this article at http://www.ajph.org); correlations were stronger for the socioeconomic status and housing and transportation domains than for the household composition and disability domain (Table D). The contribution of the socioeconomic status and household composition and disability domains was mainly driven by lower vaccination coverage among Whites in cities with higher vulnerability in those 2 domains.

DISCUSSION

In this study, we investigated the heterogenous nature of COVID-19 inequities between Hispanics and Whites across several of the most populous cities in the United States. Hispanics had rates more than double those of Whites in more than half of the cities with respect to incidence, in most cities with respect to hospitalizations, and in all cities with respect to mortality. Disparities in incidence and hospitalizations narrowed in 2021, but disparities in mortality did not change substantially. Moreover, in all but 1 of the 13 cities with available vaccination data, Hispanics had lower vaccination rates than Whites. In addition, we found that disparities in incidence, hospitalization, mortality, and vaccination rates were widest in low social vulnerability cities, mostly because Whites had lower rates as social vulnerability declined, whereas rates among Hispanics had a weak association with SVI values.

We found that incidence rates were higher among Hispanics than Whites in all but 2 of our cities, a result aligned with previous research at the neighborhood,¹⁰ county,^11,19,20 and state¹⁹ levels. In addition, we found that age-adjusted hospitalization and mortality rates were higher among Hispanics in all cities, also consistent with previous studies.^2,11,20,21

Although we cannot point to specific causative factors that led to the observed COVID-19 disparities between Hispanics and Whites, these findings most likely reflect both increased exposure to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and increased vulnerability to severe COVID-19.²² Hispanics are more likely than Whites to work in service-related occupations and other job sectors that are deemed essential but do not include paid medical leave.^23,24 Also, they have the lowest health insurance coverage rates across all major racial/ethnic groups, and thus they are more likely to forgo seeking medical services.²⁵ Finally, they are more likely to live in household conditions that impede proper social distancing measures, such as overcrowded housing²⁶ and multigenerational households.^7,27

In addition, factors related to migration and citizenship status²⁸ have recently been documented as strong predictors in explaining higher COVID-19 incidence rates among Hispanic populations than among other racial/ethnic minority groups.²⁹ For example, the public charge rule implemented in 2019 limited access to public benefit programs among immigrants and penalized them for accessing services such as Medicaid and health care.³⁰

Hispanics, especially those who are undocumented and do not speak English, face further disparities in access to high-quality, culturally and linguistically appropriate medical care.³¹ These challenges in accessing health care and the higher prevalence of comorbidities among Hispanics may also drive increased hospitalizations and mortality rates in this population.³² Structural barriers that prevent access to timely and quality health services for populations of color, such as insufficient insurance coverage, limited availability of quality health services in high-poverty neighborhoods, understaffed and overcrowded hospitals, limited access to advanced COVID-19 treatments or high-quality care, systemic racism and discrimination against these groups, and a history of medical mistrust due to past injustices, all help explain these pervasive disparities in COVID-19 outcomes.^33,34

Hispanics and Blacks represent a large share of the COVID-19 vaccination priority groups for health care, frontline, and other essential workers.³⁵ Despite this, we found that in all but 1 of the 13 cities with available vaccination coverage data, the percentage of Hispanics fully vaccinated was 12% to 44% lower than that among Whites, consistent with other studies.³⁶ Relative to their White counterparts, greater percentages of Hispanics, especially those who are undocumented,^35,37 have expressed concerns about access to vaccination;³⁷ specifically, more than half of unvaccinated and undocumented Hispanics have expressed immigration-related concerns with respect to getting vaccinated.³⁷

Disproportionate COVID-19 outcomes among Hispanics and current trends in vaccination coverage suggest that Hispanics may have a higher likelihood of facing adverse health outcomes in the ensuing months of the vaccination rollout unless local city efforts help dismantle barriers that have created need and access gaps (e.g., by providing worker protections and paid medical leave) and help fortify COVID-19 recovery efforts (e.g., by improving communication in outreach programs in terms of language-concordant care and offering conveniently located pop-up testing and vaccination clinics). Of note, we found similar vaccination rates among Hispanics and Whites in San Francisco. Although California has an extensive equity plan,^38,39 we still observed wide disparities in other cities of the state. San Francisco specifically has placed special emphasis on equity in its vaccination plan,⁴⁰ including expanding the network of vaccination sites to cover more deprived areas.⁴¹

We also found generally narrower disparities during 2021 than 2020; at the relative scale, incidence and hospitalization disparities were especially narrower, and at the absolute scale all disparities were narrower. Narrowing of disparities, especially when differences are observed at the relative and absolute scales, can indicate an improvement in rates in the disadvantaged group or a worsening of rates in the advantaged group. We found that incidence rates increased among Whites during 2021 and that hospitalizations declined among Hispanics only. The similarity in incidence rates among Hispanics with declining hospitalizations and mortality may be the result of improvements in testing or declines in severity, potentially as a result of improved vaccination coverage during 2021.

Finally, we found that racial/ethnic inequities in incidence, hospitalization, mortality, and vaccination rates were widest in cities with the lowest social vulnerability. Although additional research is needed to understand the mechanisms behind this pattern, this finding suggests that the potential benefits of low social vulnerability are not shared equally across racial/ethnic groups. According to the fundamental causes theory,⁴² populations with greater access to resources (in this case, Whites) may be more able to leverage those resources to overcome barriers to avoiding occupational or household exposures to SARS-CoV-2 and accessing health care, testing, and vaccination, whereas populations with fewer resources (in this case, Hispanics) cannot opt out of these exposure risks. However, because city-level SVI represents the vulnerability of cities as a whole rather than vulnerability ascribed to Hispanic and White populations, SVI values can potentially mask significant differences in vulnerability faced by those populations.

We found that these patterns were mostly driven by the socioeconomic status and household composition and disability domains (along with the housing and transportation domain in the case of vaccination). This apparent effect modification of disparities by city-level social vulnerability or the constructs it proxies requires further investigation to gain insights into the processes linking contextual characteristics of cities and the emergence of health disparities.

Strengths and Limitations

This study has several strengths, including the use of comprehensive COVID-19 data on incidence, hospitalization, mortality, and vaccination rates in up to 27 of the most populous and largest cities in the United States. We were also able to explore age-adjusted hospitalization and mortality rates, a critical approach when comparing populations with different age distributions. In addition, we explored relative and absolute disparities, both cumulatively and during 2 periods, allowing for a more comprehensive description of disparities.

However, we acknowledge some limitations. First, we relied on surveillance data. In the early phases of the pandemic, testing was extremely limited, especially in low socioeconomic status and minority populations,⁴³ although testing access improved over time. Testing data may help in overcoming this limitation, but lack of availability and quality (e.g., missing data on race/ethnicity) makes using race/ethnicity-specific testing and positivity data challenging. Relatedly, the outcomes we used involved issues with completeness, specifically missing race/ethnicity data.⁴⁴ Although we restricted our analysis to cities with less than 30% (for cases) or 15% (for deaths or hospitalizations) missing data on race/ethnicity, there is still the possibility for bias in the assignment of race/ethnicity.⁴⁵ Second, we were not able to examine disparities between different Hispanic subgroups (e.g., Cubans, Mexicans, Puerto Ricans, Central Americans), obscuring potential heterogeneities within this population.

Third, our vaccination coverage data may also have specific issues, as data for some cities did not include individuals vaccinated outside of their cities but in their respective states or captured suburban White populations who traveled into the city to get vaccinated, which could have led to an overestimation of rates among Whites. Fourth, we elected to use crude incidence and vaccination data to maximize the number of included cities. This may have failed to capture differences in the age distribution between Hispanic and White populations, especially in the case of vaccination, as initial strategies included prioritization by age. However, at the time our data were collected, all adults had been eligible to be vaccinated for at least 2 months.

Fifth, we used a mixture of city and county data to maximize data availability, but county-level metrics may not fully represent city-level metrics.⁴⁶ As a result, our results may potentially mask the heterogeneity of city–county differences. Moreover, because we used city-level SVI data, we were unable to explore within-city heterogeneity in social vulnerability by race/ethnicity. Finally, our analysis of the association between social vulnerability and COVID-19 outcomes was descriptive in nature, and controlling for confounders was beyond the scope of our study. Therefore, our assessment of why racial/ethnic disparities are wider in lower SVI cities merits additional research at a granular level to account for potential city-level confounders.

Conclusions

We found large but heterogeneous COVID-19 inequities between Hispanics and Whites across 27 large cities in the United States. Overall, Hispanics had higher COVID-19 incidence, hospitalization, and mortality rates and lower vaccination coverage than Whites in a majority (or, in some cases, all) of the cities in our sample, although disparities in COVID-19 outcomes narrowed in 2021. Disparities were wider in cities with lower social vulnerability, highlighting potential areas of structural and social heterogeneity that merit the attention of local and state health departments and other policymakers.