More than 1.3 million (12%) COVID-19 cases have been reported in children in the United States as of late November 2020.1 Several case series have described the clinical characteristics of COVID-19 in pediatric patients 2–8 and suggest milder illness severity in children compared with adults.4,5,7–11 However, children can present with a wide spectrum of disease ranging from asymptomatic infection to severe respiratory disease and diverse inflammatory complications.12–14
Severe or life-threatening disease occurs in about 10%–20% of adults with COVID-19.15,16 Increasing age, male sex, and certain comorbid conditions are risk factors for severe COVID-19 in adults.17–20 Medically complex children may be more likely to require critical care, but most early pediatric studies have not evaluated specific risk factors in further detail.4,5,7,8,11,21 Much remains to be learned regarding the epidemiologic, demographic, and clinical risk factors for severe COVID-19 illness in children.
Colorado has reported over 36,000 pediatric cases of SARS-CoV-2 as of early December 2020, representing 14% of all cases in the state.22 Children’s Hospital Colorado (CHCO) has established one of the largest single-institution cohorts of pediatric patients with COVID-19 disease in the United States. In this study, we evaluated risk factors for severe disease among children with SARS-CoV-2 infection. Our findings can help pediatric providers and public health stakeholders to tailor clinical management and enhance pandemic planning and resource allocation.
MATERIALS AND METHODS
Study Design and Setting
In this retrospective cohort study, we captured clinical and epidemiologic data from every pediatric patient with SARS-CoV-2 infection at CHCO between March 15 and July 8, 2020. CHCO is the largest pediatric referral center for children in a 7-state region and includes a 434-bed acute care hospital in Aurora, Colorado, a 111-bed acute care hospital in Colorado Springs, Colorado, and 13 additional network locations offering outpatient, specialty, and urgent care. All sites use a common electronic health record (EHR; Epic systems, Verona, WI).
SARS-CoV-2 Testing
SARS-CoV-2 molecular testing was performed on nasopharyngeal swabs, nasopharyngeal washes/aspirates, tracheal aspirates, and bronchoalveolar lavage specimens using 1 of 4 qualitative real-time reverse transcription PCR assays for molecular detection of SARS-CoV-2, all of which have been granted Emergency Use Authorization (EUA) from the Food and Drug Administration (FDA): CDC 2019-nCoV Real-Time RT-PCR Diagnostic Panel (CDC, Atlanta, GA), Simplexa COVID-19 Direct assay (DiaSorin Molecular LLC, Cypress, CA), Abbott RealTime SARS-CoV-2 assay (Abbott Molecular Inc., Des Plaines, IL), and Xpert Xpress SARS-CoV-2 test (Cepheid, Sunnyvale, CA). These 4 assays had 100% positive and negative agreement in preclinical studies, demonstrated no cross-reactivity to other human coronaviruses nor to a diverse panel of other common respiratory pathogens.
Study Population
All patients <21 years of age with a positive SARS-CoV-2 molecular test performed at CHCO were included. Patients ≥21 years were included only if they were followed by CHCO for a chronic medical condition. SARS-CoV-2 molecular testing first became available on March 16, 2020, with the first positive patient identified on March 19. During the first 4 weeks, testing was limited to admitted patients with fever and respiratory symptoms who tested negative for other respiratory viruses on a multiplex panel and symptomatic immunocompromised outpatients. On April 10, 2020, CHCO began testing all patients for SARS-CoV-2 on admission. On April 18, a drive-through test site opened for preprocedural and ambulatory patients. We excluded patients tested outside of the state of Colorado, parents/caregivers of pediatric patients, pregnant women, and health care workers.
Data Collection and Management
We received a daily report from the EHR for every patient with a positive SARS-CoV-2 PCR result in the CHCO system. Demographic and clinical data were abstracted from the EHR in real time and entered into standardized data collection forms developed in REDCap, hosted by the University of Colorado, Denver. EHR data included all available emergency department/urgent care encounters, primary care or specialty provider encounters, in-patient notes and diagnostic test results as available. Race and ethnicity were recorded as documented in the EHR. Body mass index (BMI) was calculated from the most recent height and weight documented in the EHR (measured within the last month for infants <12 months of age, within the last 6 months for those 1–5 years, and within the last year for children >5 years). Those with BMI in the 85th percentile to <95th percentile for age were considered overweight, those ≥the 95th percentile were considered obese, and those ≥120% of the 95th percentile for age were considered severely obese.23,24 Active comorbid conditions were recorded as documented in the EHR and categorized according to body system. Exposure history, social history, and other risk factors for SARS-CoV-2 acquisition were recorded if documented in the EHR. Results of diagnostic testing were recorded for all inpatients during the period of admission or through symptom resolution, for outpatients from symptom onset through symptom resolution, and for asymptomatic patients if any laboratory testing or imaging was performed on the same day as SARS-CoV-2 PCR testing. Chest radiographs were considered abnormal if the impression included airspace opacity, consolidation, or peribronchial thickening.25,26 We categorized patients as requiring critical care if they either (1) were admitted to the pediatric intensive care unit (ICU) for symptomatic COVID-19, or (2) were admitted to the neonatal ICU for symptomatic COVID-19 and required a higher level of respiratory support than low-flow nasal cannula. This study was approved by the Colorado Multiple Institutional Review Board with a waiver of informed consent.
Statistical Analysis
We described demographic characteristics using summary statistics. Descriptive data include all eligible patients with positive SARS-CoV-2 testing and are presented as means and standard deviations; medians and interquartile ranges; or counts and proportions. Among all patients with symptomatic SARS-CoV-2 infection, we analyzed the odds of severe outcomes, defined as either (1) hospital admission; (2) need for critical care; or (3) need for respiratory support. Asymptomatic inpatients who were incidentally identified with SARS-CoV-2 were excluded from these analyses. Simple logistic regression was performed for admission, respiratory support, and critical care. Multivariable regression grouped variables to identify demographic predictors, comorbidity predictors, and symptom predictors of the outcomes. Each variable within a group was tested using the following criteria: P < 0.10 for entry and P < 0.05 to remain. Those variables with >20% of missing data were excluded from the multivariable analyses; these included BMI, laboratory values, baseline oxygen use, and exposure history; all other variables had zero missing values, so no imputation was required. All analyses were 2-tailed and P values <0.05 were considered significant. Multivariable analysis was not done for the outcome of critical care due to small numbers in this category. All analyses were performed in SAS 9.4 (SAS Institute, Inc., Cary, NC).
RESULTS
Study Population
A total of 454 children and youth median age 11 years (upper limit 23 years), 42.1% female were identified with SARS-CoV-2 infection during the study period (Fig. 1 and Table 1). The vast majority (N = 427, 94%) were identified during expanded testing access in which asymptomatic and symptomatic children could be tested. The number of cases per week during the study period steadily rose and peaked in the second week of July (Fig. 2A). Patients identifying as Latino or Hispanic contributed 54.6% of cases followed by White non-Hispanic (22.9%), and Black non-Hispanic (5.1%) (Table 1). The proportion of patients with SARS-CoV-2 infection with Hispanic ethnicity was significantly higher than the patient population seen at CHCO in 2019 (29%, P < 0.0001) (Fig. 2B,C).
TABLE 1. -
Characteristics of Children and Youth Positive for
SARS-CoV-2 by Admission Status
|
Critical Care |
Hospital Admission |
|
| Symptomatic Only |
Symptomatic Only |
Total |
| Yes |
No |
Yes |
No |
All |
| (n = 11) |
(n = 55) |
(n = 66)* |
(n = 369) |
(n = 454)† |
| n (%) |
n (%) |
n (%) |
n (%) |
n (%) |
| Child’s age (yrs), median (IQR) |
16.0 (12–17) |
9.0 (0.2–16) |
12 (1.7–17) |
10 (3–16) |
11 (3–11) |
| Age category |
|
|
|
|
|
| 0–3 mo |
1 (9.1) |
14 (25.4) |
15 (22.7) |
14 (3.8) |
30 (6.6) |
| 4–12 mo |
0 (0) |
0 (0) |
0 (0) |
21 (5.7) |
22 (4.8) |
| 1–5 yrs |
0 (0) |
10 (18.2) |
10 (15.1) |
93 (25.2) |
107 (23.6) |
| 6–10 yrs |
1 (9.1) |
6 (10.9) |
7 (10.6) |
57 (15.4) |
65 (14.3) |
| 11–15 yrs |
1 (9.1) |
10 (18.2) |
11 (16.7) |
84 (22.8) |
101 (22.2) |
| 16–20 yrs |
6 (54.5) |
13 (23.6) |
19 (28.8) |
94 (25.5) |
119 (26.2) |
| >20 yrs |
2 (18.2) |
2 (3.6) |
4 (6.1) |
6 (1.6) |
10 (2.2) |
| Gender |
|
|
|
|
|
| Male |
6 (54.5) |
32 (59.3) |
39 (59.1) |
211 (57.2) |
262 (57.7) |
| Female |
5 (45.5) |
22 (40.7) |
27 (40.9) |
157 (42.5) |
191 (42.1) |
| Other |
0 (0) |
0 (0) |
0 (0) |
1 (0.3) |
1 (0.2) |
| Race/ethnicity |
|
|
|
|
|
| White—not Hispanic/Latino |
1 (9.1) |
12 (21.8) |
13 (19.7) |
87 (23.6) |
104 (22.9) |
| Black/African American—not Hispanic/Latino |
1 (9.1) |
2 (3.6) |
3 (4.5) |
18 (4.9) |
23 (5.1) |
| Hispanic/Latino |
8 (72.7) |
32 (58.2) |
40 (60.6) |
196 (53.1) |
248 (54.6) |
| Other |
1 (9.1) |
9 (16.4) |
10 (15.1) |
68 (18.4) |
79 (17.4) |
| Body mass index‡
|
|
|
|
|
|
| Normal weight |
3 (37.5) |
15 (46.9) |
19 (46.3) |
90 (58.1) |
116 (55.0) |
| Overweight |
5 (62.5) |
17 (53.1) |
22 (53.7) |
65 (41.9) |
95 (45.0) |
| Obese |
4 (50.0) |
15 (46.9) |
19 (46.3) |
40 (25.8) |
63 (30.1) |
| Severely Obese |
0 (0) |
11 (34.4) |
11 (26.8) |
11 (7.1) |
24 (11.4) |
| Symptomatic COVID-19 |
|
|
|
|
|
| Yes |
11 (100.0) |
55 (100.0) |
66 (100.0) |
249 (67.5) |
315 (69.4) |
| No |
0 (0) |
0 (0) |
0 (0) |
62 (16.8) |
80 (17.6) |
| Unknown |
0 (0) |
0 (0) |
0 (0) |
58 (15.7) |
59 (13.0) |
| Specific symptoms |
|
|
|
|
|
| Fever (>100.4 F) |
9 (81.2) |
34 (61.8) |
43 (65.1) |
81 (21.9) |
124 (27.3) |
| Chills |
1 (9.1) |
5 (9.1) |
6 (9.1) |
11 (3.0) |
17 (3.7) |
| Cough (new or above baseline) |
7 (63.6) |
23 (41.8) |
30 (45.5) |
72 (19.5) |
102 (22.5) |
| Congestion/runny nose |
1 (9.1) |
16 (29.1) |
17 (25.8) |
65 (17.6) |
82 (18.1) |
| Shortness of breath |
7 (63.6) |
12 (21.8) |
19 (28.8) |
18 (14.9) |
37 (8.1) |
| Chest pain/tightness |
2 (18.2) |
7 (12.7) |
9 (13.6) |
12 (3.2) |
21 (4.6) |
| Loss of taste/smell |
0 (0) |
5 (9.1) |
5 (7.6) |
18 (4.9) |
23 (5.1) |
| Headache |
0 (0) |
12 (21.8) |
12 (18.2) |
38 (10.3) |
50 (11.0) |
| Myalgia |
3 (27.3) |
7 (12.7) |
10 (15.1) |
32 (8.7) |
42 (9.2) |
| Joint pain |
0 (0) |
2 (3.6) |
2 (3.0) |
1 (0.3) |
3 (0.7) |
| Sore throat |
2 (18.2) |
6 (10.9) |
8 (12.0) |
37 (10.0) |
45 (9.9) |
| Wheezing |
0 (0) |
4 (7.3) |
4 (6.1) |
1 (0.3) |
5 (1.1) |
| Hypoxia |
4 (36.4) |
10 (18.2) |
14 (21.2) |
0 (0) |
14 (3.1) |
| Diarrhea |
0 (0) |
7 (12.7) |
7 (10.6) |
13 (3.5) |
20 (4.4) |
| Abdominal pain |
1 (9.1) |
12 (21.8) |
13 (19.7) |
10 (2.7) |
23 (5.1) |
| Vomiting |
3 (27.3) |
12 (21.8) |
15 (22.7) |
12 (3.2) |
27 (5.9) |
| Seizure |
0 (0) |
2 (3.6) |
2 (3.0) |
2 (0.5) |
4 (0.9) |
| Rash |
1 (9.1) |
1 (1.8) |
2 (3.0) |
9 (2.4) |
11 (2.4) |
| Conjunctivitis |
0 (0) |
1 (1.8) |
1 (1.5) |
2 (0.5) |
3 (0.7) |
| Altered mental status |
0 (0) |
2 (3.6) |
2 (3.0) |
0 (0) |
2 (0.4) |
| Fatigue |
2 (18.2) |
15 (27.3) |
17 (25.8) |
24 (6.5) |
41 (9.0) |
| Other |
7 (63.6) |
27 (47.3) |
33 (50.0) |
33 (8.9) |
66 (14.5) |
| Respiratory support |
|
|
|
|
|
| Yes |
10 (90.9) |
26 (47.3) |
36 (54.5) |
0 (0) |
43 (9.5) |
| No |
1 (9.1) |
29 (52.7) |
30 (45.5) |
350 (94.8) |
392 (86.3) |
| Unknown |
– |
– |
– |
19 (5.2) |
19 (5.2) |
*Includes only symptomatic children, including critical care admissions.
†Includes 19 admitted patients who were asymptomatic.
‡Categories may overlap, for example, overweight (BMI >85th %ile) includes obese (>95th %ile) and severely obese (>120% of 95th %ile).
;)
FIGURE 1.: Summary of patients with SARS-CoV-2 at Children’s Hospital Colorado (March 19–July 8, 2020). *Patients with respiratory support and critical care may overlap; percentages are of symptomatic admitted patients.
FIGURE 2.: A, Number of SARS-CoV-2 positive children and youth by week. Red line indicates number admitted. B, Comparison of ethnicity of patients with COVID-19 versus usual patient visits at Children’s Hospital Colorado in 2019. C, Comparison of ethnicity of patients admitted with COVID-19 versus patients admitted to Children’s Hospital Colorado in 2019.
Clinical Presentation
Among all SARS-CoV-2 PCR positive patients, 315 (69%) were symptomatic and 80 (18%) were asymptomatic (Fig. 1). The most common symptom at time of positive SARS-CoV-2 PCR result was fever (>100.4 F) (27%), followed by cough (23%), and congestion or rhinorrhea (18%) (Table 1).
The most frequently documented risk factor for COVID-19 exposure was a family member testing positive for SARS-CoV-2 (N = 114, 25%) followed by social gatherings of more than 10 people (N = 85, 19%). Symptomatic cases more commonly reported these risk factors with 98 (31%) reporting a family member with COVID-19 versus 16 (12%) of asymptomatic cases, and 79 (25%) of symptomatic cases reporting a social gathering compared with 6 (4%) of asymptomatic cases. Over a third of symptomatic cases (N = 115, 37%) had no exposure documented, while over two-thirds (N = 98, 71%) of asymptomatic cases had no documented risk factor.
Nearly half (45%) of children with SARS-CoV-2 had at least 1 comorbid condition. The most common types of comorbid conditions identified were pulmonary (16.7%), gastrointestinal (10.8%), and neurologic disease (10.6%) (specific diagnoses in Table, Supplemental Digital Content 1, https://links.lww.com/INF/E299). Of the 211 children with BMI data available, nearly half (45%) were overweight. Of these, 30% were categorized as obese and 11% were considered severely obese.
A total of 85 children (19%) were admitted of whom 66 (78%) were symptomatic. The remaining 19 patients (22%) were admitted for other reasons and were never symptomatic with COVID-19. Among the 66 symptomatic admitted children, 55% required respiratory support and 17% required critical care (Fig. 1). A total of 40 admitted patients had chest radiographs performed on admission, of which 25 (63%) had abnormal findings. Five of 39 (13%) admitted patients tested with a respiratory pathogen panel had coinfection with an additional respiratory tract virus.
Treatment and Outcomes
Of the patients admitted for symptomatic COVID-19, median length of stay was 3.0 days (IQR, 1–6). Among the 36 children requiring respiratory support, 26 (72%) received low-flow oxygen via nasal cannula, 2 (6%) high-flow oxygen via nasal cannula, 5 (14%) noninvasive positive pressure ventilation, 2 (6%) intubation/ventilation, and 1 (3%) ECMO. Eight patients (12%) received COVID-directed antiviral therapy and 10 (15%) received COVID-19-directed immunomodulatory therapy (Table, Supplemental Digital Content 2, https://links.lww.com/INF/E299). Five patients required readmission for COVID-19–related disease, 1 of whom was readmitted twice. Three patients (4.5%) had complications of venous thromboembolism. One medically complex patient with multiple preexisting comorbidities died due to complications of ECMO.27 All other patients were discharged from the hospital.
Risk Factors for Severe COVID-19
Risk factors associated with symptomatic hospital admission were evaluated (Table 2). There were no sex or race/ethnicity differences associated with need for admission. As compared with children age 11–15 years, infants 0–3 months [odds ratio (OR), 7.86; P < 0.001] and young adults >20 years (OR, 5.09; P = 0.03) were more likely to require admission. Comorbid conditions emerged as significant predictors of admission. The presence of any comorbid condition increased the odds of admission (OR, 2.73; P = 0.0003), and the odds increased with each additional comorbidity (OR, 1.36; P < 0.0001). Several categories of comorbidities increased the risk of admission including pulmonary, gastrointestinal, endocrine, neurologic, and psychiatric disease; immunocompromising conditions; and history of preterm birth (Table 2). Specific diagnoses including asthma, obstructive sleep apnea, baseline oxygen requirement, and diabetes or prediabetes were all significantly associated with admission. Obesity resulted in more than twice the odds of admission and severe obesity almost 5 times the odds. Symptoms of respiratory infection (including fever, cough, shortness of breath) were predictive of admission as were diarrhea, abdominal pain, and fatigue.
TABLE 2. -
Univariable and Multivariable Predictors of Admission and Respiratory Support in Children With COVID-19
|
Admitted |
Respiratory Support |
|
|
|
Univariable |
Multivariable |
|
|
Univariable |
Multivariable |
| Demographic Predictors |
Yes |
No |
OR (95% CI) Yes vs. No |
P
|
OR‡ (95% CI) |
P
|
Yes |
No |
OR (95% CI) Yes vs. No |
P
|
OR‡ (95% CI) |
P
|
| n = 66(%) |
n = 369(%) |
n = 36(%) |
n = 399(%) |
| Age |
|
|
|
|
|
|
|
|
|
|
|
|
| 0–3 mo |
15 (23) |
14 (4) |
7.86 (3.0–20.4) |
<.0001 |
7.86 (3.0–20.4) |
<.0001 |
7 (19) |
22 (6) |
4.59 (1.4–14.6) |
0.01 |
4.59 (1.4–14.6) |
0.01 |
| 4–12 mo |
0 (0) |
21 (6) |
0.17 (0.01–3.2) |
0.24 |
|
|
0 (0) |
21 (5) |
0.32 (0.02–6.3) |
0.45 |
|
|
| 1–5 yrs |
10 (15) |
93 (25) |
0.83 (0.3–2.0) |
0.67 |
|
|
4 (11) |
99 (25) |
0.62 (0.2–2.2) |
0.45 |
|
|
| 6–10 yrs |
7 (11) |
57 (15) |
0.96 (0.4–2.6) |
0.93 |
|
|
3 (8) |
61 (15) |
0.78 (0.2–3.0) |
0.72 |
|
|
| 16–20 yrs |
19 (29) |
94 (25) |
1.52 (0.7–3.3) |
0.30 |
|
|
13 (36) |
100 (25) |
1.85 (0.7–4.9) |
0.22 |
|
|
| > 20 yrs |
4 (6) |
6 (2) |
5.1 (1.2–20.7) |
0.03 |
5.1 (1.2–20.7) |
0.03 |
3 (8) |
7 (2) |
6.43 (1.4–30.4) |
0.02 |
6.43 (1.4–30.4) |
0.02 |
| 11–15 yrs |
11 (16) |
84 (23) |
Reference |
|
Reference |
|
6 (17) |
89 (22) |
Reference |
|
Reference |
|
| Age (continuous) |
– |
– |
1.00 (1.0–1.0) |
0.99 |
|
|
– |
– |
1.03 (0.9–1.1) |
0.26 |
|
|
| Gender |
|
|
|
|
|
|
|
|
|
|
|
|
| Male vs. female |
39 (59) |
211 (57) |
1.07 (0.6–1.8) |
0.83 |
|
|
19 (8) |
231 (92) |
0.81 (0.4–1.6) |
0.99 |
|
|
| Race/ethnicity |
|
|
|
|
|
|
|
|
|
|
|
|
| African Am./Black |
3 (4) |
19 (5) |
1.12 (0.3–4.3) |
0.87 |
|
|
1 (5) |
20 (95) |
2.45 (0.2–28.3) |
0.47 |
|
|
| Hispanic |
40 (61) |
196 (53) |
1.37 (0.7–2.7) |
0.37 |
|
|
28 (12) |
208 (88) |
6.60 (1.5–28.2) |
0.01 |
|
|
| Other |
10 (15) |
68 (18) |
0.98 (0.4–2.4) |
0.97 |
|
|
5 (6) |
73 (94) |
3.36 (0.6–17.8) |
0.15 |
|
|
| White (non-Hispanic) |
13 (20) |
87 (24) |
Reference |
– |
|
|
2 (2) |
98 (98) |
Reference |
– |
|
|
| Household size (continuous) |
– |
– |
1.12 (0.9–1.3) |
0.22 |
|
|
– |
– |
1.23 (0.9–1.5) |
0.06 |
|
|
| Baseline Oxygen* |
|
|
|
|
|
|
|
|
|
|
|
|
| Yes vs. No |
9 (14) |
3 (1) |
13.03 (3.3–50.9) |
0.0002 |
|
|
– |
– |
– |
– |
|
|
| Body mass index*†
|
|
|
|
|
|
|
|
|
|
|
|
|
| BMI (continuous) |
– |
– |
1.02 (1.01–1.04) |
0.0016 |
|
|
– |
– |
1.02 (1.0–1.03) |
0.03 |
|
|
| Overweight |
22 (25) |
65 (75) |
1.60 (0.8–3.2) |
0.18 |
|
|
13 (15) |
74 (85) |
1.57 (0.7–3.7) |
0.31 |
|
|
| Obese |
19 (32) |
44 (68) |
2.48 (1.2–5.1) |
0.01 |
|
|
12 (20) |
47 (80) |
2.66 (1.1–6.3) |
0.03 |
| Severely obese |
11 (50) |
11 (50) |
4.8 (1.9–12.1) |
0.0009 |
|
|
6 (22) |
16 (78) |
3.25 (1.1–9.4) |
0.03 |
| Any comorbidities |
23 (35) |
219 (59) |
2.73 (1.6–4.7) |
0.0033 |
|
|
12 (33) |
169 (42) |
2.72 (1.3–5.6) |
0.01 |
|
|
| Type Comorbidities |
|
|
|
|
|
|
|
|
|
|
|
|
| Pulmonary disease |
21 (32) |
52 (14) |
2.85 (1.6–5.2) |
0.0006 |
|
|
14 (39) |
59 (15) |
3.67 (1.8–7.6) |
0.0004 |
|
|
| Asthma |
16 (24) |
37 (10) |
2.87 (1.5–5.5) |
0.0017 |
2.17 (1.1–4.5) |
0.04 |
11 (31) |
42 (11) |
3.74 (1.7–8.1) |
0.0009 |
3.1 (1.4–6.9) |
0.007 |
| Sleep Apnea |
10 (15) |
19 (5) |
3.29 (1.5–7.4) |
0.0042 |
|
|
5 (14) |
24 (6) |
2.52 (0.9–7.1) |
0.08 |
|
|
| Gastrointestinal disease |
17 (26) |
28 (8) |
4.22 (2.2–8.3) |
<0.0001 |
2.71 (1.3–5.7) |
0.0087 |
11 (31) |
34 (9) |
4.72 (2.1–10.4) |
0.0001 |
3.96 (1.7–9.0) |
0.001 |
| Endocrine disease |
13 (20) |
10 (3) |
8.81 (3.7–21.1) |
<0.0001 |
|
|
7 (19) |
16 (4) |
5.78 (2.2–15.2) |
0.0004 |
|
|
| Diabetes/prediabetes |
5 (8) |
2 (.5) |
15.03 (2.9–79.2) |
0.0014 |
6.6 (1.1–39.8) |
0.04 |
2 (6) |
5 (1) |
4.6 (0.9–24.8) |
0.07 |
| Cardiac disease |
3 (5) |
12 (3) |
1.42 (0.4–4.2) |
0.60 |
|
|
2 (6) |
13 (3) |
1.75 (0.4–8.1) |
0.47 |
| Neurologic disease |
11 (17) |
31 (8) |
2.18 (1.0–4.6) |
0.04 |
|
0.004 |
7 (19) |
35 (9) |
2.51 (1.0–6.1) |
0.04 |
| Immunocompromising |
13 (20) |
18 (5) |
4.78 (2.2–10.3) |
<0.0001 |
3.47 (1.5–8.1) |
|
4 (11) |
27 (7) |
1.72 (0.6–5.2) |
0.34 |
| Psychiatric disease |
7 (11) |
15 (4) |
2.80 (1.1–7.2) |
0.03 |
|
|
4 (11) |
18 (5) |
2.65 (0.8–8.3) |
0.09 |
| Develop/Behavioral |
9 (14) |
29 (8) |
1.85 (0.8–4.1) |
0.13 |
|
|
6 (17) |
32 (8) |
2.29 (0.9–5.9) |
0.09 |
| Otolaryngolic disease |
2 (3) |
25 (7) |
0.43 (0.1–1.9) |
0.26 |
|
|
1 (3) |
26 (7) |
0.41 (0.05–3.1) |
0.39 |
| Preterm birth |
5 (8) |
8 (2) |
3.70 (1.2–11.7) |
0.03 |
3.48 (1.1–11.4) |
0.04 |
2 (6) |
11 (3) |
2.10 (0.4–9.7) |
0.36 |
| Symptom Predictors |
|
|
|
|
|
|
|
|
|
|
|
|
| Fever (>100.4F) |
43 (65) |
81 (22) |
6.65 (3.8–11.7) |
<.0001 |
3.82 (2.0–7.4) |
<.0001 |
25 (69) |
99 (25) |
6.89 (3.3–14.5) |
<.0001 |
5.26 (2.2–12.5) |
0.0002 |
| Chills |
6 (9) |
11 (3) |
3.26 (1.2–9.1) |
0.02 |
|
|
5 (14) |
12 (3) |
5.20 (1.7–15.7) |
0.0035 |
|
|
| Cough |
30 (45) |
72 (20) |
3.44 (2.0–6.0) |
<.0001 |
|
|
21 (58) |
81 (20) |
5.50 (2.7–11.1) |
<.0001 |
|
|
| Congestion/runny nose |
17 (26) |
65 (18) |
1.62 (0.9–3.0) |
0.12 |
|
|
11 (31) |
71 (18) |
2.03 (0.9–4.3) |
0.07 |
|
|
| Shortness of breath |
19 (29) |
18 (5) |
7.88 (3.9–16.1) |
<.0001 |
6.32 (2.8–14.3) |
<.0001 |
17 (47) |
20 (5) |
16.96 (7.7–37.5) |
<.0001 |
15.71 (6.4–38.5) |
<.0001 |
| Chest pain/tightness |
9 (14) |
12 (3) |
4.70 (1.9–11.7) |
0.0008 |
|
|
9 (25) |
12 (3) |
10.75 (4.2–27.7) |
<.0001 |
|
|
| Loss of taste/smell |
5 (8) |
18 (5) |
1.60 (0.6–4.5) |
0.37 |
|
|
3 (8) |
20 (5) |
1.72 (0.5–6.1) |
0.40 |
|
|
| Headache |
12 (18) |
38 (10) |
1.94 (1.0–3.9) |
0.07 |
|
|
7 (19) |
43 (11) |
2.00 (0.8–4.8) |
0.12 |
|
|
| Myalgia |
10 (15) |
32 (9) |
1.88 (0.9–4.0) |
0.11 |
|
|
7 (19) |
35 (9) |
2.51 (1.0–6.1) |
0.04 |
|
|
| Sore throat |
8 (12) |
37 (10) |
1.24 (0.5–2.8) |
0.61 |
|
|
5 (14) |
40 (10) |
1.45 (0.5–3.9) |
0.47 |
|
|
| Diarrhea |
7 (11) |
13 (4) |
3.25 (1.2–8.5) |
0.02 |
|
|
3 (8) |
17 (4) |
2.04 (0.6–7.3) |
0.27 |
|
|
| Abdominal pain |
13 (20) |
10 (2) |
8.81 (3.7–21.1) |
<.0001 |
3.01 (1.1–8.5) |
0.04 |
7 (19) |
16 (4) |
5.78 (2.2–15.2) |
0.0004 |
3.88 (1.4–11.1) |
0.01 |
| Vomiting |
15 (23) |
12 (3) |
8.75 (3.9–19.7) |
<.0001 |
3.89 (1.5–10.2) |
0.0059 |
9 (25) |
18 (5) |
7.06 (2.9–17.2) |
<.0001 |
|
|
| Fatigue |
17 (26) |
24 (5) |
4.99 (2.5–9.9) |
<.0001 |
|
|
11 (31) |
30 (8) |
3.78 (1.04–13.7) |
0.04 |
|
|
| Other |
33 (50) |
33 (9) |
10.18 (5.6–18.6) |
<.0001 |
5.17 (2.6–10.2) |
<.0001 |
16 (44) |
50 (13) |
5.58 (2.7–11.5) |
<.0001 |
2.63 (1.1–6.1) |
0.02 |
*Variable excluded from multivariate analysis due to missing data.
†Body mass index categorized as overweight (>85%ile), obese (>95%ile), and severely obese (120% of the 95%ile). Categories may overlap (e.g., overweight includes obese and severely obese).
‡For variables with more than 2 categories only significant Wald statistics are shown in multivariate analysis.
Many of the same risk factors were associated with need for respiratory support and critical care (Tables 2 and 3). Demographic risk factors associated with the need for respiratory support included Hispanic ethnicity, age 0–3 months or >20 years. Comorbid conditions including obesity and asthma were associated with the need for respiratory support, as were several symptoms of respiratory infection at the time of SARS-CoV-2 testing. The need for critical care was associated with comorbid obstructive sleep apnea (OR, 4.7; P = 0.04) as well as elevated C-reactive protein (CRP) at time of admission (Table 3). Median CRP among patients requiring critical care was 17.7 mg/dL (IQR, 5.3–22.9) compared with those not requiring critical care (1.95 mg/dL; IQR, 0.7–5.5). For every 1-unit increase in CRP at admission, the odds of requiring critical care increased by 1.2 (P = 0.02). Other laboratory values at admission were not associated with the need for critical care, including white blood cell count, absolute neutrophil count, platelet count, procalcitonin, ferritin, D-dimer, and lactate.
TABLE 3. -
Association of Demographic, Clinical, and Laboratory Predictors With Symptomatic Critical Care Compared With Noncritical Care Admissions in Children With COVID-19
|
Yes |
No |
Odds ratio |
P
|
| N = 11 |
N = 55 |
(95% confidence interval) |
| N (%) |
N (%) |
| Age |
|
|
|
|
| 0–3 mo |
1 (9) |
14 (25) |
0.7 (0.06–8.7) |
0.80 |
| 4–12 mo |
0 (0) |
0 (0) |
– |
– |
| 1–5 yrs |
0 (0) |
10 (18) |
0.3 (0.01–10.7) |
0.53 |
| 6–10 yrs |
1 (9) |
6 (11) |
1.6 (0.1–21.9) |
0.72 |
| 16–20 yrs |
6 (55) |
13 (24) |
3.4 (0.4–25.6) |
0.24 |
| >20 yrs |
2 (18) |
2 (4) |
7.0 (0.5–99.3) |
0.15 |
| 11–15 yrs |
1 (9) |
10 (18) |
reference |
| Age (continuous) |
|
|
1.12 (1.01–1.25) |
0.03 |
| Gender |
|
|
|
|
| Male vs. female |
6 (55) |
32 (58) |
0.83 (0.2–3.0) |
0.77 |
| Race/Ethnicity |
|
|
|
|
| Black non-Hispanic |
1 (9) |
2 (4) |
6.0 (0.3–140.0) |
0.26 |
| Hispanic |
8 (73) |
32 (58) |
3.0 (0.3–26.6) |
0.32 |
| Other |
1 (9) |
9 (16) |
1.3 (0.07–24.3) |
0.85 |
| White non-Hispanic |
1 (9) |
12 (22) |
reference |
| Household size |
|
|
1.2 (1.0–1.3) |
0.03 |
| Comorbidities |
|
|
|
|
| Pulmonary |
6 (29) |
15 (71) |
3.2 (0.8–12.1) |
0.09 |
| Asthma |
4 (25) |
12 (75) |
2.0 (0.5–8.2) |
0.31 |
| Sleep Apnea |
4 (40) |
6 (60) |
4.7 (1.0–20.8) |
0.04 |
| GI |
4 (24) |
13 (76) |
1.8 (0.5–7.3) |
0.38 |
| Endocrine |
4 (31) |
9 (69) |
2.9 (0.7–12.1) |
0.14 |
| Diabetes or prediabetes |
1 (20) |
4 (80) |
1.3 (.1–12.6) |
0.84 |
| Neurology |
3 (28) |
8 (73) |
2.2 (0.5–10.1) |
0.31 |
| Immunocompromising |
1 (8) |
12 (92) |
0.4 (0.04–3.1) |
0.35 |
| Prematurity |
1 (20) |
4 (80) |
1.3 (0.1–12.6) |
0.84 |
| Number of comorbidities |
|
|
1.19 (0.9–1.6) |
0.21 |
| Symptoms |
|
|
|
|
| Fever (>100.4 F) |
9 (81.2) |
34 (61.8) |
2.78 (0.5–14.1) |
0.22 |
| Cough |
7 (63.6) |
23 (41.8) |
2.44 (0.6–9.3) |
0.19 |
| Congestion/runny nose |
1 (9.1) |
16 (29.1) |
0.24 (0.3–2.1) |
0.20 |
| Shortness of breath |
7 (63.6) |
12 (21.8) |
6.27 (1.6–25.0) |
0.01 |
| Chest pain/tightness |
2 (18.2) |
7 (12.7) |
1.52 (0.3–8.5) |
0.63 |
| Diarrhea |
0 (0) |
7 (12.7) |
––––––– |
–––––– |
| Abdominal pain |
1 (9.1) |
12 (21.8) |
0.36 (0.04–3.1) |
0.35 |
| Vomiting |
3 (27.3) |
12 (21.8) |
1.34 (0.31–5.9) |
0.69 |
| Fatigue |
2 (18) |
15 (27) |
0.60 (0.1–3.1) |
0.53 |
| Baseline oxygen use |
2 (18) |
7 (13) |
11.24 (0.2–7.5) |
0.82 |
| Body mass index* |
|
|
|
|
| Overweight |
5 (45) |
17 (31) |
1.57 (0.3–7.7) |
0.58 |
| Obese |
4 (36) |
15 (27) |
1.20 (0.3–5.6) |
0.82 |
| Severely obese |
0 (0) |
11 (20) |
––––––– |
–––––– |
| Laboratory values |
Median (IQR) |
Median (IQR) |
|
|
| C-reactive protein |
17.7 (5.3–22.9) |
1.95 (0.7–5.5) |
1.22 (1.03–1.43) |
0.02 |
| White blood cell |
6.1 (4.0–8.1) |
7.3 (5.5–12.8) |
0.91 (0.78–1.06) |
0.23 |
| Absolute neutrophil count |
4.1 (2.7–6.3) |
3.4 (2.4–6.1) |
0.98 (0.79–1.21) |
0.83 |
| Platelet count |
169.5 (102–265) |
232 (216–325) |
0.99 (0.99–1.00) |
0.09 |
| Procalcitonin |
0.3 (0.2–3.1) |
0.1 (0.1–0.5) |
1.15 (0.55–2.37) |
0.71 |
| Ferritin |
315 (309–453) |
86 (58–673) |
1.00 (1.00–1.00) |
0.98 |
| D-dimer |
2.85 (1.5–6.8) |
0.8 (0.5–1.0) |
7.17 (0.69–74.89) |
0.1 |
| Lactate |
4.8 (1.8–6.1) |
1.25 (1.1–2.2) |
1.06 (0.85–1.33) |
0.61 |
*Body mass index categorized as overweight (>85%ile), obese (>95%ile), and severely obese (120% of the 95%ile). Categories may overlap (e.g., overweight includes obese and severely obese).
In multivariable analyses (Table 2), age 0–3 months or >20 years remained significant demographic predictors of need for admission and respiratory support. Comorbid conditions that remained significantly associated with admission included immunocompromising conditions, gastrointestinal disease, history of preterm birth, asthma, and diabetes/prediabetes, while only gastrointestinal disease and asthma remained significantly associated with respiratory support. Fever, shortness of breath, and vomiting at presentation remained significantly associated with admission and respiratory support.
DISCUSSION
In this large pediatric cohort identified at a tertiary referral hospital network, we identify important factors associated with severe COVID-19 in children. Importantly, we focused on symptomatic children who were admitted, required respiratory support or received critical care to better inform health care providers of the population at risk for severe COVID-19. In our cohort, 1 in 5 symptomatic children with SARS-CoV-2 infection required hospital admission. Clear risk factors for admission or need for respiratory support emerged, including extremes of age, obesity, and other underlying comorbidities. Elevated CRP was predictive of the need for critical care.
Our findings support demographic trends identified in literature from the United States and elsewhere.3–5 Similar to other studies, we found a bimodal age distribution among those requiring admission with young infants and young adults most likely to be admitted.5,11,28 We detected a male predominance among children and youth testing positive, but sex was not predictive of severe COVID-19. Nearly 70% of the children in our cohort with positive SARS-CoV-2 PCR were symptomatic, with 21% requiring hospital admission and 3.5% critical care, similar to other pediatric reports.4,5 Encouragingly, lengths of stay were relatively short and the need for intubation/mechanical ventilation or ECMO remained rare, consistent with the published literature on children with COVID-19.4,29,30
We identified an ethnic disparity with overrepresentation of children identifying as Hispanic as compared with the usual population served by CHCO and the general population of Colorado.11,31 Racial and ethnic disparities have emerged as a key predictor of COVID-19 in adults and children throughout the United States.9,32–37 In Colorado, while Hispanic and Latino populations make up 21.7% of Colorado’s residents, they have represented 36.9% of COVID-19 cases.22 Our study demonstrates an even larger disparity among Hispanic children and youth in Colorado. Additionally, Hispanic ethnicity was associated with higher odds of respiratory support in univariable analysis but not in multivariable analyses, indicating that some other factor among Hispanic children may have been confounding this association. Several factors may be contributing to these ethnic and racial disparities, which deserve further exploration, including increased prevalence of medical comorbidities, high-density housing, stigma, and barriers to accessing medical care.38–41
Our study investigated risk factors for severe COVID-19 defined as need for admission, respiratory support, or critical care. We identified particular comorbid conditions, including asthma, diabetes and obesity, to be predictive of more severe pediatric COVID-19. There is growing evidence that children with comorbidities (in particular medically complex patients) may be at higher risk of hospitalization and critical care.3,5,42 One-third of children in our study who were categorized as having a gastrointestinal comorbidity required a gastrostomy or jejunostomy tube, which supports the association of severe COVID-19 with medical complexity. Among children with endocrine disease, one-third had diabetes mellitus or prediabetes, which are related to COVID-19 outcomes in adult studies.43,44 Obesity has emerged as an independent risk factor for severe COVID-19 in adults, with increasing evidence of the same trend in children.11,17–20,45,46 Several factors may be contributing to this association, including increased prevalence of other medical comorbidities, obesity-related complications, race/ethnicity, and socioeconomic or behavioral factors.46,47 Thirty percent of patients in our cohort with BMI data were obese, which is alarming as the obesity rate reported in children with 10–17 years of age in Colorado is only 10.7%.48 Obesity and severe obesity in our cohort were significantly associated with admission and respiratory support; however, due to missing data, we were not able to include this variable in the multivariable analyses.
Importantly, elevated CRP emerged as a clear risk factor for children requiring critical care, consistent with 2 other US studies in children.3,49,50 A history of sleep apnea also emerged as a risk factor for critical care in our cohort. However, we did not identify any other demographic or clinical factors associated with the need for critical care, possibly due to inadequate power to detect these associations given the small number of symptomatic critical care admissions in our cohort.
This is one of the largest pediatric cohorts reported with over 400 children and youth. We performed a comprehensive analysis of factors associated with more severe COVID-19 in children, including demographics, comorbid conditions, and symptoms at presentation. We focused on symptomatic children to ensure that children admitted for other reasons did not bias findings. Further, we performed a multivariable analysis to address potential confounders. Our data were limited to those available in the EHR; while sufficient data were available for most participants, limited information was available for some outpatient cases. Changing recommendations on whom to test may also have impacted our findings; the early focus on testing only symptomatic admitted children may have skewed our cohort toward the inclusion of more ill children, but only 6.9% of our cohort were diagnosed while testing was restricted, so we do not anticipate this created significant bias.
In conclusion, we found that age, comorbid conditions, and elevated CRP are risk factors for severe COVID-19 in children. Findings from this study can inform pediatric providers and public health officials to tailor clinical management, pandemic planning, and resource allocation. Counseling of families with children with comorbid medical conditions should include a discussion of increased risk of severe illness. Health care providers may consider screening for CRP at admission to inform the need for critical care. Additional research should evaluate approaches to mitigate these risk factors and explore associations of ethnicity and COVID-19 in children.
ACKNOWLEDGMENTS
We would like to acknowledge the patients and families affected by COVID-19 and the Children’s Hospital staff working to care for them. We would especially like to acknowledge the Children’s Hospital Colorado Microbiology Laboratory, particularly Kristin Pretty, Darcy Velasquez, and Eric Mwangi for their efforts in early creation and implementation of the SARS-CoV-2 PCR test at CHCO.
REFERENCES
1. American Academy of
Pediatrics (AAP). Children and COVID-19: State-level data report. 2020. Available at:
https://services.aap.org/en/pages/2019-novel-coronavirus-covid-19-infections/children-and-covid-19-state-level-data-report/. Accessed December 4, 2020.
2. Dong Y, Mo X, Hu Y, et al. Epidemiology of COVID-19 among children in China.
Pediatrics. 2020; 145:e20200702
3. Zachariah P, Johnson CL, Halabi KC, et al. Epidemiology, clinical features, and disease severity in patients with coronavirus disease 2019 (COVID-19) in a Children’s Hospital in New York City, New York. JAMA Pediatr. 2020; 174:e202430
4. Parri N, Lenge M, Buonsenso D; Coronavirus Infection in Pediatric Emergency Departments (CONFIDENCE) Research Group. Children with Covid-19 in Pediatric Emergency Departments in Italy. N Engl J Med. 2020; 383:187–190
5. DeBiasi RL, Song X, Delaney M, et al. Severe COVID-19 in children and young adults in the Washington, DC Metropolitan Region. J Pediatr. 2020; 223:199–203.e1
6. Qiu H, Wu J, Hong L, et al. Clinical and epidemiological features of 36 children with coronavirus disease 2019 (COVID-19) in Zhejiang, China: an observational cohort study. Lancet Infect Dis. 2020; 20:689–696
7. Otto WR, Geoghegan S, Posch LC, et al. The epidemiology of
SARS-CoV-2 in a Pediatric Healthcare Network in the United States. J Pediatric Infect Dis Soc. 2020; 9:523–529
8. CDC COVID-Response Team. Coronavirus disease 2019 in children—United States, February 12-April 2, 2020. MMWR Morb Mortal Wkly Rep. 2020; 69:422–426
9. Gold JAW, Wong KK, Szablewski CM, et al. Characteristics and clinical outcomes of adult patients hospitalized with COVID-19—Georgia, March 2020. MMWR Morb Mortal Wkly Rep. 2020; 69:545–550
10. Cruz AT, Zeichner SL. COVID-19 in children: initial characterization of the pediatric disease.
Pediatrics. 2020; 145:e20200834
11. Kim L, Whitaker M, O’Halloran A, et al.; COVID-NET Surveillance Team. Hospitalization rates and characteristics of children aged <18 years hospitalized with laboratory-confirmed COVID-19 - COVID-NET, 14 States, March 1-July 25, 2020. MMWR Morb Mortal Wkly Rep. 2020; 69:1081–1088
12. Cheung EW, Zachariah P, Gorelik M, et al. Multisystem inflammatory syndrome related to COVID-19 in previously healthy children and adolescents in New York City. JAMA. 2020; 324:294–296
13. Chiotos K, Bassiri H, Behrens EM, et al. Multisystem inflammatory syndrome in Children during the COVID-19 pandemic: a case series. J Pediatric Infect Dis Soc. 2020; 9:393–398
14. Abrams JY, Godfred-Cato SE, Oster ME, et al. Multisystem inflammatory syndrome in children associated with severe acute respiratory syndrome Coronavirus 2: a systematic review. J Pediatr. 2020; 226:45–54.e1
15. Zhu N, Zhang D, Wang W, et al.; China Novel Coronavirus Investigating and Research Team. A novel coronavirus from patients with Pneumonia in China, 2019. N Engl J Med. 2020; 382:727–733
16. Wu Q, Xing Y, Shi L, et al. Coinfection and other clinical characteristics of COVID-19 in children.
Pediatrics. 2020; 146:e20200961
17. Xu L, Mao Y, Chen G. Risk factors for 2019 novel coronavirus disease (COVID-19) patients progressing to critical illness: a systematic review and meta-analysis. Aging (Albany NY). 2020; 12:12410–12421
18. Cen Y, Chen X, Shen Y, et al. Risk factors for disease progression in patients with mild to moderate coronavirus disease 2019-a multi-centre observational study. Clin Microbiol Infect. 2020; 26:1242–1247
19. Rod JE, Oviedo-Trespalacios O, Cortes-Ramirez J. A brief-review of the risk factors for covid-19 severity. Rev Saude Publica. 2020; 54:60
20. CDC COVID-Response Team. Preliminary estimates of the prevalence of selected underlying health conditions among patients with coronavirus disease 2019 - United States, February 12-March 28, 2020. MMWR Morb Mortal Wkly Rep. 2020; 69:382–386
21. Lu X, Zhang L, Du H, et al.; Chinese Pediatric Novel Coronavirus Study Team.
SARS-CoV-2 infection in children. N Engl J Med. 2020; 382:1663–1665
22. Colorado Department of Public Health and the Environment (CDPHE). Colorado COVID-19 updates: case data. 2020. Available at:
https://covid19.colorado.gov/data/case-data. Accessed December 7, 2020
23. Gulati AK, Kaplan DW, Daniels SR. Clinical tracking of severely obese children: a new growth chart.
Pediatrics. 2012; 130:1136–1140
24. Centers for Disease Control and Prevention (CDC). Defining childhood obesity. 2018. Available at:
https://www.cdc.gov/obesity/childhood/defining.html. Accessed September 30, 2020
25. Foust AM, Phillips GS, Chu WC, et al. International expert consensus statement on chest imaging in pediatric COVID-19 patient management: imaging findings, imaging study reporting and imaging study recommendations. Radiology. 2020; 2::e200214
26. Caro-Dominguez P, Shelmerdine SC, Toso S, et al.; Collaborators of the European Society of Paediatric Radiology Cardiothoracic Task Force. Thoracic imaging of coronavirus disease 2019 (COVID-19) in children: a series of 91 cases. Pediatr Radiol. 2020; 50:1354–1368
27. Flood SM, Osborne CM, Martin B, et al. Severe
SARS-CoV-2 infection in a pediatric patient requiring extracorporeal membrane oxygenation. Case Rep Pediatr. 2020; 2020:8885022
28. Leibowitz J, Krief W, Barone S, et al. Comparison of clinical and epidemiologic characteristics of young febrile infants with and without
SARS-CoV-2 infection. J Pediatr. 2020; 229:41.e1–47.e1
29. Götzinger F, Santiago-García B, Noguera-Julián A, et al.; ptbnet COVID-19 Study Group. COVID-19 in children and adolescents in Europe: a multinational, multicentre cohort study. Lancet Child Adolesc Health. 2020; 4:653–661
30. Gonzalez-Dambrauskas S, Vasquez-Hoyos P, Camporesi A, et al. Pediatric critical care and COVID-19.
Pediatrics. 2020; 146e20201766
31. United States Census Bureau. U.S. Census 2010. 2012. Annie E. Kasey Foundation: Kids Count Data Center; Available at:
https://www.census.gov/topics/population/language-use/about.html. Accessed July 1, 2020
32. Rentsch CT, Kidwai-Khan F, Tate JP, et al. Covid-19 by race and ethnicity: a national cohort study of 6 million United States Veterans. medRxiv. 2020
33. Raifman MA, Raifman JR. Disparities in the population at risk of severe illness from COVID-19 by race/ethnicity and income. Am J Prev Med. 2020; 59:137–139
34. Price-Haywood EG, Burton J, Fort D, et al. Hospitalization and mortality among black patients and white patients with Covid-19. N Engl J Med. 2020; 382:2534–2543
35. Centers for Disease Control and Prevention. COVID-19 in racial and ethnic minority groups. 2020. Available at:
https://www.cdc.gov/coronavirus/2019-ncov/need-extra-precautions/racial-ethnic-minorities.html. Accessed July 7, 2020
36. Holmes L Jr, Enwere M, Williams J, et al. Black-white risk differentials in COVID-19 (SARS-COV2) transmission, mortality and case fatality in the united states: translational epidemiologic perspective and challenges. Int J Environ Res Public Health. 2020; 17:4322
37. Bixler D, Miller A, Mattison CP, et al.
SARS-CoV-2–associated deaths among persons aged <21 years—United States, February 12–July 31, 2020. MMWR Morb Mortal Wkly Rep. 2020; 69:1324–1329
38. Hawkins D. Differential occupational risk for COVID-19 and other infection exposure according to race and ethnicity. Am J Ind Med. 2020; 63:817–820
39. Gorenstein D. Hard to Reach. June 11, 2020. Podcast. Available at:
https://tradeoffs.org/2020/06/11/hard-to-reach/. Accessed July 15, 2020.
40. Cyrus E, Clarke R, Hadley D, et al. The impact of COVID-19 on African American Communities in the United States. Health Equity. 2020; 4:476–483
41. Colorado Department of Public Health and the Environment (CDPHE). Survey to inform the COVID-19 Health Equity Response Team’s decision-making. 2020. Available at:
https://drive.google.com/file/d/18hyE8ZwM5YR6hy_JpiUYm1QehWSdBQeb/view. Accessed July 7, 2020
42. Shekerdemian LS, Mahmood NR, Wolfe KK, et al. Characteristics and outcomes of children with coronavirus disease 2019 (COVID-19) infection admitted to US and Canadian pediatric intensive care units. JAMA Pediatr. 2020; 174:868–873
43. Richardson S, Hirsch JS, Narasimhan M, et al.; the Northwell COVID-19 Research Consortium. Presenting characteristics, comorbidities, and outcomes among 5700 patients hospitalized with COVID-19 in the New York City Area. JAMA. 2020; 323:2052–2059
44. Fadini GP, Morieri ML, Longato E, et al. Prevalence and impact of diabetes among people infected with
SARS-CoV-2. J Endocrinol Invest. 2020; 43:867–869
45. Simonnet A, Chetboun M, Poissy J, et al.; LICORN and the Lille COVID-19 and Obesity study group. High prevalence of obesity in severe acute respiratory syndrome Coronavirus-2 (
SARS-CoV-2) requiring invasive mechanical ventilation. Obesity (Silver Spring). 2020; 28:1195–1199
46. Townsend MJ, Kyle TK, Stanford FC. Outcomes of COVID-19: disparities in obesity and by ethnicity/race. Int J Obes (Lond). 2020; 44:1807–1809
47. Woo Baidal JA, Chang J, Hulse E, et al. Zooming toward a telehealth solution for vulnerable children with obesity during coronavirus disease 2019. Obesity (Silver Spring). 2020; 28:1184–1186
48. Robert Wood Johnson Foundation. State of childhood obesity. 2018. Available at:
https://stateofchildhoodobesity.org/states/co/#:~:text=Colorado,and%20the%20District%20of%20Columbia. Accessed September 30, 2020
49. Kaushik S, Aydin SI, Derespina KR, et al. Multisystem inflammatory syndrome in children associated with severe acute respiratory syndrome Coronavirus 2 infection (MIS-C): a multi-institutional study from New York City. J Pediatr. 2020; 224:24–29
50. Chao JY, Derespina KR, Herold BC, et al. Clinical characteristics and outcomes of hospitalized and critically ill children and adolescents with coronavirus disease 2019 (COVID-19) at a Tertiary Care Medical Center in New York City. J Pediatr. 2020; 223:14–19.e2
