OBJECTIVES:

To evaluate racial and/or ethnic and socioeconomic differences in rates of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection among children.

METHODS:

We performed a cross-sectional study of children tested for SARS-CoV-2 at an exclusively pediatric drive-through and walk-up SARS-CoV-2 testing site from March 21, 2020, to April 28, 2020. We performed bivariable and multivariable logistic regression to measure the association of patient race and/or ethnicity and estimated median family income (based on census block group estimates) with (1) SARS-CoV-2 infection and (2) reported exposure to SARS-CoV-2.

RESULTS:

Of 1000 children tested for SARS-CoV-2 infection, 20.7% tested positive for SARS-CoV-2. In comparison with non-Hispanic white children (7.3%), minority children had higher rates of infection (non-Hispanic Black: 30.0%, adjusted odds ratio [aOR] 2.3 [95% confidence interval (CI) 1.2–4.4]; Hispanic: 46.4%, aOR 6.3 [95% CI 3.3–11.9]). In comparison with children in the highest median family income quartile (8.7%), infection rates were higher among children in quartile 3 (23.7%; aOR 2.6 [95% CI 1.4–4.9]), quartile 2 (27.1%; aOR 2.3 [95% CI 1.2–4.3]), and quartile 1 (37.7%; aOR 2.4 [95% CI 1.3–4.6]). Rates of reported exposure to SARS-CoV-2 also differed by race and/or ethnicity and socioeconomic status.

CONCLUSIONS:

In this large cohort of children tested for SARS-CoV-2 through a community-based testing site, racial and/or ethnic minorities and socioeconomically disadvantaged children carry the highest burden of infection. Understanding and addressing the causes of these differences are needed to mitigate disparities and limit the spread of infection.

What’s Known on This Subject:

Racial and/or ethnic and socioeconomic disparities in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection have been reported among adults but are understudied in relation to infection risk in children.

What This Study Adds:

In this cross-sectional study of a large cohort of children tested in the United States for SARS-CoV-2 through an exclusively pediatric drive-through and walk-up testing site, rates of SARS-CoV-2 infection were disproportionately higher among minority and socioeconomically disadvantaged youth.

Racial and/or ethnic and socioeconomic disparities in health outcomes have been reported for years, across multiple clinical conditions.1  The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has served to shine a spotlight on and amplify such disparities because reports indicate that racial and/or ethnic minorities and socioeconomically disadvantaged populations are the most severely impacted.

More than 1.5 million cases of SARS-CoV-2 infection have been diagnosed in the United States, and children are estimated to comprise ∼50 000 of those cases.2  Recent data highlight the disproportionate burden of SARS-CoV-2–related illness and death on racial and/or ethnic minorities among adults.35  Additional data further suggest that low socioeconomic status may further exacerbate health outcomes for racial and ethnic minorities.4 

Data regarding disparities in SARS-CoV-2 infection and outcomes have been, thus far, mostly limited to adults. It is unknown whether such disparities extend to children as well. Our primary objective for this study was to investigate the presence of racial and/or ethnic and socioeconomic disparities in rates of SARS-CoV-2 infection in a large sample of non–acutely ill children who were tested at an exclusively pediatric drive-through and walk-up SARS-CoV-2 testing site.

This study was a planned cross-sectional analysis of a registry of children tested for SARS-CoV-2 at an exclusively pediatric drive-through and walk-up urban SARS-CoV-2 testing site from March 21, 2020, to April 28, 2020. This SARS-CoV-2 specimen collection site is affiliated with a tertiary care urban children’s hospital. This service was funded through philanthropic support; therefore, patients seeking this service did not incur any out of pocket charges. To broaden access to those without motor vehicles, the testing site also allowed for walk-up testing. Targeted outreach to non–English-speaking communities was also conducted to advertise this service to all communities. Furthermore, interpreters proficient in Spanish and Amharic were present at the testing site daily to assist non–English-speaking families, and translated information material was made available to all. The institutional review board approved this study and provided a waiver of informed consent because this was a post hoc analysis of previously collected data.

Children between the ages of 0 and 22 years with mild symptoms not requiring acute medical care were eligible to be tested at this site with a physician referral. Age criteria for access to the testing site were consistent with the policies of the affiliated children’s hospital and primary care practices. Physicians could refer patients through the use of an electronic portal available on the hospital Web site if they met age criteria, reported mild symptoms, and had at least one of the following: known exposure, high-risk status, family member with high-risk status, and/or required testing for work. The online referral form included patient demographics (name, age, sex, race and/or ethnicity, and address), reported symptoms, and reason for referral.

The testing site, located within 1 mile of the hospital at an outdoor enclosed parking lot of a local university, offered testing 2 to 3 times per week, including weekends, between the hours of 10 am and 2 pm. Because the testing site was not equipped to provide any medical management, patients who appeared ill were immediately rerouted to the hospital before receipt of SARS-CoV-2 testing.

The primary outcome was rate of SARS-CoV-2 positivity. Trained staff collected nasopharyngeal or throat swabs, which were refrigerated and sent to an off-site commercial laboratory (Quest Diagnostics, Inc, Secaucus, NJ) for polymerase chain reaction testing. Quest Diagnostics publishes that they use 4 different molecular tests granted emergency use authorization by the US Food and Drug Administration, including a laboratory-developed test, the cobas Roche Diagnostics test, the Hologic Panther Fusion test, and the Hologic Panther Covid-19 molecular assay. The published limits of detection of these tests are as follows: Quest laboratory-developed test, 136 copies per mL; Roche, 0.009 50% median tissue culture infectious dose per mL; and both Hologic tests, 0.01 50% median tissue culture infectious dose per mL. The secondary outcome included patient- and/or family-reported SARS-CoV-2 exposure status based on data from the standardized online referral form.

Exposure variables were race and/or ethnicity and socioeconomic status. Consistent with other studies, race and/or ethnicity was categorized as non-Hispanic (NH) Black, NH white, Hispanic, and other.68  We used median family income (MFI) by census block group from the American Community Survey (2014–2018) as a proxy for socioeconomic status. The American Community Survey uses 5-year estimates derived from home addresses to estimate MFI.9  MFI was then categorized into quartiles. Potential confounding variables included age and sex.

We used means and frequency analyses to describe the study population and calculate unadjusted SARS-CoV-2 positivity rates. Home addresses were geocoded by using ArcGIS Pro (version 2.5.1; Esri, Redlands, CA) to create a point layer for all patients. The point layer was spatially joined with a census block group polygon layer and then merged with American Community Survey population-level data by census block group to derive MFI.

Bivariable and multivariable logistic regression analyses were developed to estimate unadjusted odds ratios (ORs) and adjusted odds ratios (aORs) to assess the strength of association of race and/or ethnicity and socioeconomic status with the outcome measures. We tested for an interaction between race and/or ethnicity and socioeconomic status but only retained interactions that were statistically significant, and thus the interaction was excluded from the final models. Linear regression analysis was used to assess trends in rates of SARS-CoV-2 infection over the study period among each racial and/or ethnic group. Estimates derived from the multivariable models included aORs with 95% confidence intervals (CIs) and adjusted probabilities. All analyses were conducted by using Stata 16.0 (Stata Corp, College Station, TX).

During the study period, 1000 children were tested for SARS-CoV-2 at the drive-through and walk-up specimen collection site. The median age was 8.0 (interquartile range 2.0–14.0) years, and 52.3% of children were male.

Of the children tested, approximately one-third were NH Black and one-quarter were Hispanic. MFI ranged from $11 667 to >$250 000. Approximately one-third (29.1%) had an MFI below the national MFI of $78 500 (Table 1, Fig 1A). MFI differed by race and/or ethnicity, with a significantly lower MFI for minority youth (NH white: $161 250; NH Black: $92 188 [P < .001]; Hispanic: $75 114 [P < .001]; other: $139 568 [P = .001]).

TABLE 1

Demographics of Study Population

Demographic CharacteristicTested for SARS-CoV-2 Infection (N = 1000), n (%)
Age, y  
 <1 89 (8.9) 
 1–4 282 (28.2) 
 5–11 279 (27.9) 
 12–17 222 (22.2) 
 ≥18 128 (12.8) 
Sex  
 Male 523 (52.3) 
 Female 477 (47.7) 
Race and/or ethnicity  
 NH white 203 (20.3) 
 NH Black 304 (30.4) 
 Hispanic 229 (22.9) 
 Other 171 (17.1) 
 Unknown 93 (9.3) 
MFI (quartiles)  
 Quartile 4: $157 679–>$250 000 236 (23.6) 
 Quartile 3: $107 321–$157 308 237 (23.7) 
 Quartile 2: $70 341–$107 292 236 (23.6) 
 Quartile 1: $11 667–$70 300 237 (23.7) 
 Unknown 54 (5.4) 
Demographic CharacteristicTested for SARS-CoV-2 Infection (N = 1000), n (%)
Age, y  
 <1 89 (8.9) 
 1–4 282 (28.2) 
 5–11 279 (27.9) 
 12–17 222 (22.2) 
 ≥18 128 (12.8) 
Sex  
 Male 523 (52.3) 
 Female 477 (47.7) 
Race and/or ethnicity  
 NH white 203 (20.3) 
 NH Black 304 (30.4) 
 Hispanic 229 (22.9) 
 Other 171 (17.1) 
 Unknown 93 (9.3) 
MFI (quartiles)  
 Quartile 4: $157 679–>$250 000 236 (23.6) 
 Quartile 3: $107 321–$157 308 237 (23.7) 
 Quartile 2: $70 341–$107 292 236 (23.6) 
 Quartile 1: $11 667–$70 300 237 (23.7) 
 Unknown 54 (5.4) 
FIGURE 1

SARS-CoV-2 testing and positivity by MFI. A, Geospatial distribution of patients tested for SARS-CoV-2 and MFI quartiles. B, Geospatial distribution of patients positive for SARS-CoV-2 and MFI quartiles. DC, Washington, District of Columbia; Q1, quartile 1; Q2, quartile 2; Q3, quartile 3; Q4, quartile 4.

FIGURE 1

SARS-CoV-2 testing and positivity by MFI. A, Geospatial distribution of patients tested for SARS-CoV-2 and MFI quartiles. B, Geospatial distribution of patients positive for SARS-CoV-2 and MFI quartiles. DC, Washington, District of Columbia; Q1, quartile 1; Q2, quartile 2; Q3, quartile 3; Q4, quartile 4.

Of the 1000 children tested, 207 (20.7%) tested positive for SARS-CoV-2. The median age of those testing positive for SARS-CoV-2 was 11.0 (interquartile range 5.0–16.0) years, and 47.8% were male.

Positivity rates for SARS-CoV-2 differed by race and/or ethnicity. In comparison with NH white children (7.3%), NH Black (30.0%; OR 3.3 [95% CI 1.8–5.9]) and Hispanic (46.4%; OR 9.1 [95% CI 5.1–16.4]) children had higher rates of SARS-CoV-2 infection (Fig 2, Table 2). After adjustment for age, sex, and MFI, minority children had a greater likelihood of SARS-CoV-2 infection compared with NH white children (NH Black: aOR 2.3 [95% CI 1.2–4.4]; Hispanic: aOR 6.3 [95% CI 3.3–11.9]; Table 2). Furthermore, positivity rates increased over time among Hispanic children (P for trend = .002) but not among other racial and/or ethnic groups (Fig 3).

FIGURE 2

Rates of SARS-CoV-2 infection by race and/or ethnicity and socioeconomic status. Q1, quartile 1; Q2, quartile 2; Q3, quartile 3; Q4, quartile 4.

FIGURE 2

Rates of SARS-CoV-2 infection by race and/or ethnicity and socioeconomic status. Q1, quartile 1; Q2, quartile 2; Q3, quartile 3; Q4, quartile 4.

TABLE 2

Racial and/or Ethnic and Socioeconomic Factors Associated With SARS-CoV-2 Positivity

Demographic CharacteristicOR (95% CI)aOR (95% CI)a
Race and/or ethnicity   
 NH white Reference Reference 
 NH Black 3.3 (1.8–5.9) 2.3 (1.2–4.4) 
 Hispanic 9.1 (5.1–16.4) 6.3 (3.3–11.9) 
 Other 1.9 (0.9–3.8) 1.8 (0.9–3.7) 
MFI (quartiles)   
 Quartile 4: $157 679–>$250 000 Reference Reference 
 Quartile 3: $107 321–$157 308 3.2 (1.8–5.6) 2.6 (1.4–4.9) 
 Quartile 2: $70 341–$107 292 3.8 (2.1–6.6) 2.3 (1.2–4.3) 
 Quartile 1: $11 667–$70 300 5.9 (3.4–10.3) 2.4 (1.3–4.6) 
Demographic CharacteristicOR (95% CI)aOR (95% CI)a
Race and/or ethnicity   
 NH white Reference Reference 
 NH Black 3.3 (1.8–5.9) 2.3 (1.2–4.4) 
 Hispanic 9.1 (5.1–16.4) 6.3 (3.3–11.9) 
 Other 1.9 (0.9–3.8) 1.8 (0.9–3.7) 
MFI (quartiles)   
 Quartile 4: $157 679–>$250 000 Reference Reference 
 Quartile 3: $107 321–$157 308 3.2 (1.8–5.6) 2.6 (1.4–4.9) 
 Quartile 2: $70 341–$107 292 3.8 (2.1–6.6) 2.3 (1.2–4.3) 
 Quartile 1: $11 667–$70 300 5.9 (3.4–10.3) 2.4 (1.3–4.6) 
a

Adjusted for age, sex, race and/or ethnicity, and MFI.

FIGURE 3

Trends in rates of SARS-CoV-2 positivity over the study period by race and/or ethnicity.

FIGURE 3

Trends in rates of SARS-CoV-2 positivity over the study period by race and/or ethnicity.

Positivity rates for SARS-CoV-2 infection also differed by MFI (Fig 1B). Children residing in households of lower MFI had higher rates of positivity compared with those residing in households with the highest MFI. In comparison with children in the highest MFI quartile (8.7%), SARS-CoV-2 infection rates were higher among children in quartile 3 (23.7%; OR 3.2 [95% CI 1.8–5.6]), quartile 2 (27.1%; OR 3.8 [95% CI 2.1–6.6]), and quartile 1 (37.7%; OR 5.9 [95% CI 3.4–10.3]) (Fig 2, Table 2). In the fully adjusted model, rates of SARS-CoV-2 positivity were higher among children within the lowest MFI quartiles compared with those in quartile 4 (quartile 3: aOR 2.6 [95% CI 1.4–4.9]; quartile 2: aOR 2.3 [95% CI 1.2–4.3]; quartile 1: aOR 2.4 [95% CI 1.3–4.6]) (Table 2).

Of the 1000 children tested, 106 (10.6%) reported exposure to SARS-CoV-2. Reports of exposure to people infected with SARS-CoV-2 differed by race and/or ethnicity. In comparison with NH white children (11.3%), NH Black children (34.9%; aOR 2.3 [95% CI 1.0–5.1]) and children of other racial and/or ethnic groups (19.8%; aOR 2.5 [95% CI 1.1–5.8]) reported higher rates of a known exposure. Furthermore, patient- and/or family-reported exposure also differed by MFI, with higher rates of exposure in less socioeconomically advantaged households (quartile 4: 12.3%; quartile 2: 29.3% [aOR 2.4; 95% CI 1.1–5.2]) (Table 3).

TABLE 3

Racial and/or Ethnic and Socioeconomic Factors Associated With Reported SARS-CoV-2 Exposure

Demographic CharacteristicOR (95% CI)aOR (95% CI)a
Race and/or ethnicity   
 NH white Reference Reference 
 NH Black 2.2 (1.1–4.4) 2.3 (1.0–5.1) 
 Hispanic 2.2 (1.1–4.5) 1.9 (0.8–4.4) 
 Other 2.0 (1.0–4.5) 2.5 (1.1–5.8) 
MFI (quartiles)   
 Quartile 4: $157 679–>$250 000 Reference Reference 
 Quartile 3: $107 321–$157 308 2.0 (1.0–4.1) 1.9 (0.9–4.1) 
 Quartile 2: $70 341–$107 292 2.6 (1.3–5.1) 2.4 (1.1–5.2) 
 Quartile 1: $11 667–$70 300 2.5 (1.3–4.9) 2.1 (0.9–4.6) 
Demographic CharacteristicOR (95% CI)aOR (95% CI)a
Race and/or ethnicity   
 NH white Reference Reference 
 NH Black 2.2 (1.1–4.4) 2.3 (1.0–5.1) 
 Hispanic 2.2 (1.1–4.5) 1.9 (0.8–4.4) 
 Other 2.0 (1.0–4.5) 2.5 (1.1–5.8) 
MFI (quartiles)   
 Quartile 4: $157 679–>$250 000 Reference Reference 
 Quartile 3: $107 321–$157 308 2.0 (1.0–4.1) 1.9 (0.9–4.1) 
 Quartile 2: $70 341–$107 292 2.6 (1.3–5.1) 2.4 (1.1–5.2) 
 Quartile 1: $11 667–$70 300 2.5 (1.3–4.9) 2.1 (0.9–4.6) 
a

Models were adjusted for age, sex, race and/or ethnicity, and MFI.

In this large cohort of children tested for SARS-CoV-2 through community-based testing, we found evidence of both racial and/or ethnic and socioeconomic disparities in SARS-CoV-2 infection. Specifically, minority and socioeconomically disadvantaged children had a higher likelihood of SARS-CoV-2 infection. Furthermore, these observed racial and/or ethnic disparities in infection rates only slightly attenuated after adjustment for socioeconomic status.

Our findings of disproportionately higher rates of SARS-CoV-2 infection among minority youth mirror those found in recent adult literature. For instance, Millet et al3  found that US counties with higher populations of Black residents had disproportionately higher rates of SARS-CoV-2–related infection and deaths, beyond adjustment for sociodemographic characteristics, comorbidities, and socioeconomic determinants. Similarly, through an analysis using health system data in California, Azar et al5  found higher rates of SARS-CoV-2 infection among Black adults compared with white patients after adjustment for median household income.

Although it was beyond the scope of this study to understand the causes for these differential rates of infection, the causes may be multifactorial, including, but not limited to, structural factors, poorer access to health care, limited resources, and bias and discrimination. For instance, structural factors may prevent minorities from practicing social distancing and, thus, limiting exposure. Minorities are disproportionately overrepresented in essential service industries that require travel and face-to-face interactions.10,11  When working in the food service industry, health care, and transportation, teleworking and sheltering in place may not be feasible. Additionally, minorities have higher reliance on public transportation and are more likely to live in crowded settings, such as public housing, compared with NH white individuals.12,13  Furthermore, minorities have higher rates of living in multigenerational households, thus, increasing opportunities for exposure to older adults who may be more vulnerable to infection.14  In fact, our data indicate that minority youth had a higher likelihood of reporting exposure to SARS-CoV-2 compared with NH white youth. Another explanation for the disproportionately higher rates of SARS-CoV-2 infection among minority youth may be due to previous experiences of bias and discrimination, which can lead to distrust of the health care system and delays in seeking care15  and, thus, the spread of infection to household members.

Rates of SARS-CoV-2 infection were higher among Hispanic children than NH Black or NH white children. This finding is similar to that recently reported by Martinez et al16 . A study on differences in measures of exposure to H1N1 by race and/or ethnicity revealed that when compared with NH white and NH Black individuals, Hispanic individuals had the highest rates of living in metropolitan areas, in apartment buildings, and with a larger household size. Hispanic individuals also reported the highest rates of difficulty in avoiding public transportation, the lowest rates in ability to telework, and the highest rates of difficulty obtaining child care that was not with a group of children.17  Along with the aforementioned reasons for these disparities, Hispanic children may have experienced the most pronounced burden of infection because of compounding additional factors, such as immigration status and language barriers. Furthermore, symptomatic adults may avoid testing because of fears of deportation.17,18  Future work to ensure equitable allocation of testing and culturally appropriate prevention education may help improve early identification, quarantine, and distribution of resources to reduce community spread of disease.

The findings of this study should be considered in the context of several potential limitations. Race and ethnicity data were provided by the clinician at the time of referral rather than self-reported and, thus, may be subject to misclassification bias. We used MFI from the American Community Survey as a proxy for socioeconomic status, which may be another source of misclassification bias. However, to provide greater precision, estimates on MFI were based on census block group rather than zip code. Recent adult data reveal higher rates of morbidity and mortality among racial and/or ethnic minorities and socioeconomically disadvantaged groups. Because our study was conducted outside a clinical care setting, we could not assess disparities in morbidity and mortality. Access to the testing site required physician referral. Therefore, our findings of racial and/or ethnic and socioeconomic disparities in positivity rates may be an underestimate because racial and/or ethnic minority and socioeconomically disadvantaged groups have less access to primary care physicians.1921  In addition, referral to the testing site by clinicians may have been differentially provided, and advertisement of the testing site may not have been uniformly distributed among all potential referring clinicians. Furthermore, the testing site was available a few days per week and during the hours of 10 am and 2 pm, which may not have been convenient for all. The testing site was located in a relatively low-income neighborhood with a large proportion of minority residents. However, our data revealed that children of various socioeconomic backgrounds traveled across state lines to access the testing site. In addition, 4 different diagnostic tests were used for SARS-CoV-2 testing, which was a standard laboratory approach to keep up with test demand during this pandemic. It is unlikely that these polymerase chain reaction amplification-based tests were differentially distributed by patient race, ethnicity, and/or MFI. Furthermore, we were unable to adjust for unmeasured confounding variables, including, but not limited to, housing conditions or occupancy. Finally, because this was a single-center study, these results may not be generalizable to other geographic locations with different racial and/or ethnic and socioeconomic compositions of their communities.

We found higher rates of SARS-CoV-2 infection among minority and socioeconomically disadvantaged children. Future research should confirm and extend this work by focusing on the modifiable reasons for these observed disparities as well as their differential impact in terms of SARS-CoV-2–related morbidity and mortality outcomes to mitigate the spread of infection and its health effects.

We thank Abigail Ralph, MS, MBA, and Mark McGuire, MTMS, MBA, for their tireless leadership and support of running the drive-through and walk-up testing site. We also thank Pat McGuire (president) and Ann Pauley (vice president for institutional advancement and media relations) of Trinity Washington University, who provided the location and ground support so that so many children in our region could have access to testing. Lastly, we express gratitude on behalf of the children and families served by our testing site to our philanthropic donors who made the initiative possible.

Dr Goyal conceptualized and designed the study, drafted the initial manuscript, and reviewed and revised the manuscript; Dr Simpson conceptualized and designed the study, designed the data collection instruments, coordinated and supervised data collection, and reviewed and revised the manuscript; Ms Boyle and Ms Badolato collected data, conducted the initial analyses, and reviewed and revised the manuscript; Dr Delaney coordinated and supervised data collection and reviewed and revised the manuscript; Dr McCarter supervised and conducted the analyses and reviewed and revised the manuscript; Dr Cora Bramble conceptualized and designed the study and reviewed and revised the manuscript; and all authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.

FUNDING: No external funding.

     
  • aOR

    adjusted odds ratio

  •  
  • CI

    confidence interval

  •  
  • MFI

    median family income

  •  
  • NH

    non-Hispanic

  •  
  • OR

    odds ratio

  •  
  • SARS-CoV-2

    severe acute respiratory syndrome coronavirus 2

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Competing Interests

POTENTIAL CONFLICT OF INTEREST: Dr Goyal is a member of the Pediatrics editorial board; the other authors have indicated they have no potential conflicts of interest to disclose.

FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.