Severe Acute Respiratory Syndrome Coronavirus 2 Antibody Prevalence and Associated Risk Factors in a Large Cohort of US Children

Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), was initially identified in Wuhan, China, in December 2019. By March 2020, COVID-19 had spread rapidly around the world, and the World Health Organization declared the outbreak a global pandemic. Epidemiological data from the early stages of the pandemic show that children accounted for a small proportion of COVID-19 cases [1], yet by May 2023, nearly 15.6 million children had tested positive for COVID-19, representing 17.9% of all reported cases in the United States [2]. A key reason for SARS-CoV-2 infection within this demographic are increased exposures and social mobility, as children are more likely to be primary COVID-19 cases and spread the virus to others [3]. Clinical manifestations of SARS-CoV-2 infection range from asymptomatic infection to severe disease. Children generally have a milder clinical course and lower mortality rate than adults [4], yet pediatric complications from SARS-CoV-2 include increased hospitalizations, the onset of multisystem inflammatory syndrome, and increased mortality [5].

Estimating the prevalence of SARS-CoV-2 in the US pediatric population is challenging and prone to underestimation [1]. In many states, it has been estimated that 5 to 9 times more SARS-CoV-2 infections in children and adolescents have occurred compared with those reported in case-based surveillance systems [1]. The use of serosurveys to evaluate SARS-CoV-2 antibody prevalence among children through opportunistic testing of residual serum samples in hospital-based settings lends itself to bias with respect to sample collection from nonhealthy subjects [6]. In comparison, mucosal antibody testing, through the use of oral fluid assays, has been shown to be both accurate and convenient in evaluating humoral immunity compared with circulating antibodies in population-based settings [7–10]. In asymptomatic or mild COVID-19 cases, mucosal antibodies can even be detected in seronegative patients [11]. Thus, serum antibody levels may result in underestimation of immunity; particularly among younger and mildly infected patients [7, 12]. Noninvasive testing methods such as oral fluid assays can also be particularly advantageous in pediatric populations over serum antibody testing since they are easier to perform, do not require specific skills to obtain the sample, are painless, and are more acceptable to participants, which in turn facilitates recruitment [7, 13].

Information on SARS-CoV-2 antibody prevalence among the US pediatric population is scarce and predominantly based on samples selected in the earlier phases of the pandemic. Few studies have examined pediatric antibody prevalence during the era of Omicron, the predominant circulating COVID-19 variant in the United States from early 2022 to the present time [14]. The Omicron variant and its sublineages are characterized by an increased number of mutations, making it highly contagious and more transmissible than previous SARS-CoV-2 variants [15]. In addition, while COVID-19 vaccination was approved for children aged 5–11 years in October 2021 and for those aged 6 months to 4 years in June 2022, the majority of children in New Jersey are unvaccinated [16, 17] and thus potentially susceptible to Omicron infection and illness. A representative assessment of the true prevalence of disease among the US pediatric population is needed given the growing endemicity of COVID-19.

The primary objective of the current study was to determine infection-induced SARS-CoV-2 antibody positivity in predominantly healthy children from the third quarter of 2022 through June 2023. A secondary objective was to identify risk factors associated with SARS-CoV-2 antibody positivity in children during the Omicron variant period.

METHODS

Study Sample

The study took place at 4 clinic-based pediatric practices in Northern and Central New Jersey from 17 August 2022 to 30 June 2023. The practices, in chronological order of participant enrollment, included Robert Wood Johnson Medical School (RWJMS; New Brunswick and Somerset), New Jersey Medical School (NJMS; Newark), Cooperman-Barnabas Medical Center (BMC; Livingston and West Orange), and Atlantic Health Systems (AHS; Morristown, Florham Park, and Scotch Plains).

Children aged 18 months to 11 years were invited to undergo oral swab antibody testing, and their caregivers completed an online electronic survey. In order to estimate infection-induced antibodies, children had no doses of a previous monovalent or bivalent COVID-19 vaccine approved and available before enrollment [18] and no symptoms of acute illness at the time of their appointment. Caregivers and their children were required to be New Jersey residents, and surveys were provided to participants in English or Spanish. More than one child per family could be enrolled. All inclusion and exclusion criteria to determine the eligibility of the study's participants were fulfilled before participation.

Study Design

Participants who met entry criteria were approached by staff at routine office visits and invited to participate in the study. Caregivers provided consent, and a gingival (oral) swab test (Diabetomics CovAbTM antibody test) was performed on the child according to the instructions outlined in the test package insert. The Diabetomics CovAbTM antibody test is a rapid lateral flow immunoassay that qualitatively detects total antibodies (immunoglobulin G, A, and M to spike protein) to SARS-CoV-2 in oral fluid and gives a positive or negative result within 15 minutes [19]. Practice staff administered the test after the child had abstained from food or drink for ≥30 minutes. A 10–15-minute electronic survey was administered to the caregiver during the waiting period for the swab sample to be read. Antibody test results were communicated to the caregiver by the site researcher at the end of the appointment or by written or verbal communication the next day. This study was approved by the Rowan University and AHS institutional review boards, and it conforms to standards currently applied in the United States.

Measures

Primary Outcome

Antibody positivity to SARS-CoV-2 was measured with the Diabetomics CovAb rapid gingival crevicular fluid test. The test has a sensitivity of 97.6% and a specificity of 98.8% in adult populations, based on results of concomitant reverse-transcription polymerase chain reaction testing [19, 20]. The test can detect antibodies 9 months after symptom onset, but the ability to identify positives wanes beyond 3 months after infection [21, 22].

Explanatory Variables

Predictors of antibody positivity were collected using an electronic survey exploring child COVID-19 diagnoses, household and public exposures, and household vaccination status. Individual- and household-level covariates included sex at birth, age in years, race/ethnicity, socioeconomic status as measured by health insurance status (public [Medicaid or government-sponsored plans], private [employer sponsored], or other/uninsured), and the presence of comorbid conditions or conditions diagnosed by a physician, including asthma, reactive airway disease, other chronic lung disease, diabetes, hypertension, chronic cardiovascular or heart disease, chronic kidney problems, liver problems, cancer, immunosuppressive condition or medication, obesity, attention-deficit/hyperactivity disorder, autism, or other neurologic conditions. Other data collected included the date of enrollment, whether the child had a prior diagnosis of COVID-19 (since January 2020), household adult vaccination status (whether 0, 1, or >1 household adult was fully vaccinated at the time of the survey), the number of household adults who reported having had COVID-19 in the past year, and the frequency of indoor masking on the part of the child.

The frequency of indoor masking was measured on a 5-point scale—never (0), rarely (1), sometimes (2), often (3), and always (4)—for various indoor settings, including social events (without household members), general activities, sports, dining (outside the home), school or daycare, religious events, and at other indoor public places (eg, post office, mall, or supermarket). Scores for each indoor activity were summed to create an indoor masking index for each participant, where the range of index values was 0–32.

Statistical Analyses

Bivariate analyses to assess differences in socioeconomic and clinical characteristics between antibody-positive and antibody-negative individuals were conducted on univariate predictors of antibody positivity. Frequencies and percentages were compared using χ² statistics and Cochran-Armitage trend tests for categorical variables, and means and standard deviations were compared using 2-sample t tests for continuous variables. Siblings who were subsequently enrolled were removed when conducting bivariate statistical analyses on household-level factors to ensure independence of observations; household clustering was adjusted for during multivariable analysis.

A nested logistic regression model was run on individual- and group-level predictors of antibody positivity, controlling for the nesting of participants within study practices and the clustering of siblings within households. A literature- and data-based approach was used in selecting covariates for model entry; in that bivariate associations significant at or below the α = .05 level were included, and key sociodemographic/clinical covariates with known associations were forced in. Generalized estimating equations logistic regression was used for correlated data with a marginal (population mean) model interpretation of the parameter estimates. All analyses were unweighted and 2 tailed and were conducted using SAS software, version 9.4 [23].

RESULTS

An oral test swab sample and corresponding survey were obtained for a total of 870 pediatric participants over the 10-month enrollment period; 121 (14%) were siblings of a primary enrolled child. The total sample included pediatric participants from all 4 pediatric practices, and the enrollment of patients into the study was staggered by practice location/site (Figure 1). RWJMS and NJMS enrolled patients approximately 3 months earlier than the other 2 practices; and each practice enrolled ≥200 participants. Most children (n = 711 [82%]) were enrolled during routine office visits; these included yearly physicals, well-child checkups, follow-up appointments, and non–COVID-19 vaccination visits. Approximately 10% (9.7%) of participants were enrolled during nonacute illness/sick visits, and 9% were enrolled for another patient-selected reason.

Figure 1.

Participant Enrollment Metrics. Excluded subjects were those ineligible, declined, refused, or rejected. Dates are given in day/month/year format, and numbers of siblings represent siblings of primary enrolled children. Routine visits include well-child visits, checkups, vaccinations, follow-up appointments, diagnostics, and screening; nonacute illness/sick visits include checkups for chronic illness and visits for injuries or trauma; and visits for “other reasons,” include accompanying siblings and medication-related visits. Abbreviations: AHS, Atlantic Health Systems; BMC, Cooperman-Barnabas Medical Center; NJMS, New Jersey Medical School; RWJMS, Robert Wood Johnson Medical School.

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Site-specific and overall antibody positivity and the percentage of circulating Omicron subvariants in New Jersey during each study enrollment month [24] are detailed in Figure 2. Overall antibody positivity across the study enrollment period, calculated as the number of positive results divided by the total number of enrolled patients, was 61.4%, 68.2%, 73.3%, and 69% for RWJMS, NJMS, BMC, and the AHS, respectively. The overall antibody positivity of the sample was 67.7% (95% confidence interval [CI], 64.9%–70.3%). Test density was the highest during the first 3 months of enrollment, from 17 August to 17 November 2022 (n = 453 [52.1%]), and enrollment slowed during the start of the winter and early spring, coinciding with higher rates of acute respiratory illness in the state. The relative percentage of circulating Omicron subvariant strains also changed during this time. Whereas subvariant BA.5 made up approximately 75% of infections in New Jersey during the first 3 months of enrollment, the majority of infections were due to XBB1.5 after December 2022 [24]. Overall sample antibody positivity subsequently increased after December 2022 as well.

Figure 2.

Antibody Positivity and Omicron Subvariants During the Study Period [24]. Abbreviations: AHS, Atlantic Health System; BMC, Cooperman-Barnabas Medical Center; NJMS, New Jersey Medical School; RWJMS, Robert Wood Johnson Medical School; and CI, 95% confidence interval.

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The sociodemographic and clinical characteristics of the total sample are displayed in Table 1. The sample was predominantly Hispanic/Latino (n = 316 [37%]) or non-Hispanic black (n = 257 [30%]), Medicaid or publicly insured (n = 432 [55%]), and had a mean age of, 5.7 years. The majority of participants (83%) were from households where ≥1 adult was fully vaccinated, with an average household size of approximately 4 individuals. Nearly 27% of participants were from households with >1 child enrolled in the study.

In bivariate associations, significantly more female participants were antibody positive than were antibody negative (48.9% vs 41.7%), as were significantly more Hispanics/Latino participants and those enrolled after 17 November 2022 (41% vs 29.2% and 51% vs 42% respectively.) Children from households where ≥1 household adult was fully vaccinated were significantly less likely to be antibody positive than antibody negative (79.5% vs 91%). While only 34% of the total sample reported ≥1 COVID-19 diagnosis since January 2020, there was no difference in antibody positivity according to whether or not COVID-19 had been diagnosed, and although 75% (n = 208) of those with a COVID-19 diagnosis reported having symptoms, there was no difference in antibody positivity according to the presence or absence of COVID-19 symptoms. Older children were slightly more likely to be antibody positive than negative (mean age, 5.73 years for antibody-positive vs 5.58 years for antibody-negative participants), but not significantly so. Antibody-positive children had a slightly lower indoor masking index score than antibody-negative children, but this difference was not significant. There was no significant difference in household size by antibody status.

Key individual and household characteristics as a function of antibody positivity are outlined in Figure 3. Female participants had 1.73 times the odds of being antibody positive compared with males (adjusted odds ratio [aOR], 1.73 [95% CI, 1.22–2.45]). Hispanics were >2 times more likely and non-Hispanic blacks close to 2 times more likely to be antibody positive than non-Hispanic whites (aOR, 2.29, [95% CI, 1.37–3.8] and 1.95 [1.11–3.43], respectively). Later enrollment in the study resulted in increases in antibody positivity; specifically, each subsequent appointment day increased antibody positivity by 0.4% (P < .001). Vaccination of household adults was a significant protective factor; children from households with ≥1 vaccinated adults were 62% less likely to test positive than those from households in which no adults were vaccinated (aOR, 0.38 [95% CI, .20–.69]). Children with ≥1 comorbid condition were equally likely to test positive, and older children were marginally more likely to be antibody positive.

Figure 3.

Predictors of antibody positivity. Abbreviations: aOR, adjusted odds ratio; CI, 95% confidence interval.

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DISCUSSION

This study found that in a sample of predominantly healthy unvaccinated children from a densely populated region of the United States, both individual and household factors were associated with SARS-CoV-2 antibody status among children <12 years of age. The overall antibody positivity among children in this sample was 68%. This is lower than pediatric infection-induced seroprevalence estimates in New Jersey and in the United States [25, 26] but higher than mucosal fluid antibody prevalence estimates in other studies [13]. As of February 2022, the seroprevalence of infection-induced antibodies among children aged 0–11 years was 81% in New Jersey [25] and close to 75% for children <12 years old in the United States, based on commercial laboratory data [26], However, our antibody prevalence estimate is higher than the 40.1% oral fluid assay antibody prevalence among children aged 4–11 years in the United Kingdom in 2021 [13]. Our higher oral fluid study estimate was obtained during the Omicron variant wave in New Jersey, whereas the UK study was conducted before this period. Regional and international patterns of subvariant spread can also affect observed antibody positivity to a large degree. Our slightly lower estimates relative to blood serum antibody samples obtained in New Jersey during the same time period can be explained by the real-world administration of an oral swab test among a pediatric sample.

Non-Hispanic black and Hispanic children had nearly 2 times and >2 times the odds of a positive test result, respectively, when compared with non-Hispanic whites, consistent with the elevated infection rates among minorities apparent in previous meta-analyses and hospital data [27]. We did not, however, find a strong relationship between socioeconomic status as measured by public versus employer-based health insurance and antibody positivity, perhaps due in part to our use of insurance status rather than more stable indicators of socioeconomic status, such as education. Older children were slightly more likely to test positive for antibodies than younger children, perhaps due to increased sources of exposure, such as school-based or other extracurricular activities. Parents and caregivers may also be more relaxed in implementing masking and other preventive measures for older children, particularly if they have already had COVID-19.

As with prior research, the current findings suggest a lower rate of indoor household transmission when either the patient or primary contact, such as a household adult, was fully vaccinated [28, 29]. Past COVID-19 infection (measured by prior COVID-19 diagnosis) did not seem to be a significant predictor of antibody positivity among children in our findings. While children may be just as likely as adults to be infected with SARS-CoV-2, they are more likely to present with mild illness that may be treated at home [30]. Likewise, among children who do experience symptoms, it has become increasingly difficult in COVID-19–endemic times to differentiate COVID-19 from other child respiratory (or gastrointestinal) illnesses [31]. Certain school attendance policies following a positive SARS-CoV-2 test also made it prohibitive for parents to seek a COVID-19 diagnosis when a child was ill [32, 33].

We found that later enrollment in the study was a significant predictor of antibody positivity in children. There are several reasons for this; viral, host, and exogenous factors play a role. With the emergence of more infectious subvariants, waves of increased SARS-CoV-2 transmission can infect susceptible hosts, resulting in higher antibody positivity rates, but this may be balanced by waning immunity and diminishing infection-induced antibodies in others. Circulation of SARS-CoV-2 is also seasonal, with noted increases in infection rates occurring during the winter of 2022–2023, along with simultaneous increases in other respiratory pathogens [34, 35]. In the current study, overall and site-specific antibody positivity increased after the winter months with the arrival of the Omicron XBB1.5 substrain in particular. Omicron XBB1.5 has a high number of mutations and more easily evades immunity, making one susceptible to XBB1.5 reinfection even if already infected with an earlier Omicron variant [36]. These elevated antibody positivity rates held until the end of the enrollment period. As has been suggested with other viral infections, mitigation measures implemented during the early part of the pandemic may have reduced overall exposure to respiratory infections and created immunity deficits within the population, leading to a larger population of susceptible hosts during the Omicron period. Other geographic and climate factors also interact over time in complex ways [37, 38].

A number of limitations to the current study deserve mention. Our method of outcome ascertainment, the oral swab test, can potentially detect antibodies for 9 months after SARS-CoV-2 infection, but the ability to pick up positives decreased 3 months after infection [7], such that positive test results may have been missed given the timing of the appointment. Furthermore, the test can produce unreliable results depending on whether the patient consumed food or drink for up to 30 minutes before administration [20]. Although parents were asked whether the child had anything to eat or drink during the 30 minutes before swab sampling, there may have been unreported consumption of foods or beverages. Therefore, our antibody positivity estimates likely underestimate true infection-induced antibody positivity rates among children over time.

During the study period, -19 vaccination coverage among children aged 6 months to 4 years in New Jersey was approximately 10% for a single dose and about 5% for series completion. Among those 5–11 years old, the percentage of children who completed a 2-dose series averaged <40% [16, 17]. While the selection of unvaccinated children in our study sample was representative of most children in the state, it limited our ability to assess potential differences in exposure, contact, and masking behaviors between unvaccinated and vaccinated populations that may affect antibody positivity. While vaccination was encouraged by all sites, the vaccine may not have been as readily available at some sites due to supply issues at the time of enrollment. However, given substantial COVID-19 pediatric vaccine hesitancy among this population [39, 40] and underlying state-wide vaccination rates for this age group [16, 17], families of participants likely had already chosen not to vaccinate their children.

The 4 clinics enrolled patients in a staggered format over time, with no site having continuously enrolled patients over the course of the entire 10-month period. Some sites ended the bulk of their participant enrollment before noted increases in SARS-CoV-2 infection rates, while others started enrolling patients after this wave of infections passed. While we controlled for sibling and site-level clustering in our regression modeling procedure, collinearity and unmeasured confounding between date of enrollment and site may nonetheless remain. Finally, as with all patient-reported data, responses may be subject to difficulties in recall, particularly with respect to prior COVID-19 diagnoses and symptoms; however, any recall issues were unlikely to differentially affect caregivers of antibody-positive or antibody-negative children.

This study also has several key strengths. Participants were predominantly healthy children >18 months of age, excluding the possibility of maternal passive immunity, a parameter that can introduce selection bias. Our combined sample was racially and ethnically diverse. Because patients were primarily recruited during routine office visits with their physicians, the sociodemographic composition of the sample is likely representative of the communities that comprise the study setting. In addition to demonstrated benefits in test accuracy and sensitivity [11, 12], the use of a noninvasive oral swab test for antibody evaluation made enrollment of pediatric patients easier, allowing for a more robust study sample and greater representation of the pediatric population at large.

In conclusion, the observed 68% antibody prevalence rate among unvaccinated children in the current study is well above levels at which herd immunity has been estimated to occur [41], notwithstanding extra protection conferred by vaccinated children. However, it is not yet known whether the high proportion of antibody positivity at the present time predicts sustained population-level protection against future SARS-CoV-2 transmission, infection, or severe outcomes in children. Household vaccination is associated with lower SARS-CoV-2 infection and reinfection, and the importance of adult vaccination status cannot be underplayed as a key factor in helping mitigate COVID-19 infection among children in household settings. This can be likened to the idea of “cocooning,” in that vaccinated parents or other adults confer immunization benefits that envelop children and vulnerable individuals within the same household unit [42, 43].

This study provides insight into the antibody positivity of children during times of endemic COVID-19 infection in the Omicron era and during seasonal waves of increased disease activity. It is also among the few studies conducted in the latter period of COVID-19 pandemic, providing a comprehensive estimation of the overall infection burden. The findings also have considerable public health implications with respect to the vaccination of vulnerable groups. Given the apparent role of adult vaccination in reducing SARS-CoV-2 infection within the household, providers should encourage adults and other primary caregivers to be vaccinated and stay up to date on vaccines to help reduce COVID-19 transmission among children.

Acknowledgments

The authors acknowledge Reed Magleby, MD, MS for his contribution to study inception and design and this manuscript, and Nagla Bayoumi, DrPH, MPH and Edward Lifshitz, MD for their manuscript review. The authors also thank Elsie Roca-Puccini, MD, Mehek Saikh, MD, Mawanda Hussein, MD, Harin Morrisetty, MD, Godfrey Grayland II, MD, Hajitha Noor, MD, Christian Suarez, and Rhea Mathews for their contributions to participant enrollment and data collection efforts.

Disclaimer. The contents are those of the authors and do not necessarily represent the official views of, nor an endorsement by, the Centers for Disease Control and Prevention, US Department of Health and Human Services, or the US Government.

Financial support. This work was supported by the Centers for Disease Control and Prevention (CDC) and the US Department of Health and Human Services (HHS) as part of a financial assistance award totaling $10,658,181.44 USD with 100 percent funded by CDC/HHS. The contents are those of the authors and do not necessarily represent the official views of, nor an endorsement by, CDC/HHS, or the US government.

References

Author notes