Prevalence of SARS-CoV-2 Antibodies in New York City Adults, June-October 2020: A Population-Based Survey

Estimation of SARS-CoV-2 Seroprevalence in Central North Carolina: Accounting for Outcome Misclassification in Complex Sample Designs

BACKGROUND

Population-based seroprevalence studies are crucial to understand community transmission of COVID-19 and guide responses to the pandemic. Seroprevalence is typically measured from diagnostic tests with imperfect sensitivity and specificity. Failing to account for measurement error can lead to biased estimates of seroprevalence. Methods to adjust seroprevalence estimates for the sensitivity and specificity of the diagnostic test have largely focused on estimation in the context of convenience sampling. Many existing methods are inappropriate when data are collected using a complex sample design.

METHODS

We present methods for seroprevalence point estimation and confidence interval construction that account for imperfect test performance for use with complex sample data. We apply these methods to data from the Chatham County COVID-19 Cohort (C4), a longitudinal seroprevalence study conducted in central North Carolina. Using simulations, we evaluate bias and confidence interval coverage for the proposed estimator compared with a standard estimator under a stratified, three-stage cluster sample design.

RESULTS

We obtained estimates of seroprevalence and corresponding confidence intervals for the C4 study. SARS-CoV-2 seroprevalence increased rapidly from 10.4% in January to 95.6% in July 2021 in Chatham County, North Carolina. In simulation, the proposed estimator demonstrates desirable confidence interval coverage and minimal bias under a wide range of scenarios.

CONCLUSION

We propose a straightforward method for producing valid estimates and confidence intervals when data are based on a complex sample design. The method can be applied to estimate the prevalence of other infections when estimates of test sensitivity and specificity are available.

The Longitudinal Analysis of Convergent Antibody VDJ Regions in SARS-CoV-2-Positive Patients Using RNA-Seq

Severe acute respiratory syndrome-related coronavirus-2 (SARS-CoV-2) is an ongoing pandemic that continues to evolve and reinfect individuals. To understand the convergent antibody responses that evolved over the course of the pandemic, we evaluated the immunoglobulin repertoire of individuals infected by different SARS-CoV-2 variants for similarity between patients. We utilized four public RNA-seq data sets collected between March 2020 and March 2022 from the Gene Expression Omnibus (GEO) in our longitudinal analysis. This covered individuals infected with Alpha and Omicron variants. In total, from 269 SARS-CoV-2-positive patients and 26 negative patients, 629,133 immunoglobulin heavy-chain variable region V(D)J sequences were reconstructed from sequencing data. We grouped samples based on the SARS-CoV-2 variant type and/or the time they were collected from patients. Our comparison of patients within each SARS-CoV-2-positive group found 1011 common V(D)Js (same V gene, J gene and CDR3 amino acid sequence) shared by more than one patient and no common V(D)Js in the noninfected group. Taking convergence into account, we clustered based on similar CDR3 sequence and identified 129 convergent clusters from the SARS-CoV-2-positive groups. Within the top 15 clusters, 4 contain known anti-SARS-CoV-2 immunoglobulin sequences with 1 cluster confirmed to cross-neutralize variants from Alpha to Omicron. In our analysis of longitudinal groups that include Alpha and Omicron variants, we find that 2.7% of the common CDR3s found within groups were also present in more than one group. Our analysis reveals common and convergent antibodies, which include anti-SARS-CoV-2 antibodies, in patient groups over various stages of the pandemic.

Dynamics of SARS-CoV-2 seroassay sensitivity: a systematic review and modelling study

BackgroundSerological surveys have been the gold standard to estimate numbers of SARS-CoV-2 infections, the dynamics of the epidemic, and disease severity. Serological assays have decaying sensitivity with time that can bias their results, but there is a lack of guidelines to account for this phenomenon for SARS-CoV-2.AimOur goal was to assess the sensitivity decay of seroassays for detecting SARS-CoV-2 infections, the dependence of this decay on assay characteristics, and to provide a simple method to correct for this phenomenon.MethodsWe performed a systematic review and meta-analysis of SARS-CoV-2 serology studies. We included studies testing previously diagnosed, unvaccinated individuals, and excluded studies of cohorts highly unrepresentative of the general population (e.g. hospitalised patients).ResultsOf the 488 screened studies, 76 studies reporting on 50 different seroassays were included in the analysis. Sensitivity decay depended strongly on the antigen and the analytic technique used by the assay, with average sensitivities ranging between 26% and 98% at 6 months after infection, depending on assay characteristics. We found that a third of the included assays departed considerably from manufacturer specifications after 6 months.ConclusionsSeroassay sensitivity decay depends on assay characteristics, and for some types of assays, it can make manufacturer specifications highly unreliable. We provide a tool to correct for this phenomenon and to assess the risk of decay for a given assay. Our analysis can guide the design and interpretation of serosurveys for SARS-CoV-2 and other pathogens and quantify systematic biases in the existing serology literature.

Ethnic inequalities in COVID-19 infection, hospitalisation, intensive care admission, and death: a global systematic review and meta-analysis of over 200 million study participants

Background

COVID-19 has exacerbated existing ethnic inequalities in health. Little is known about whether inequalities in severe disease and deaths, observed globally among minoritised ethnic groups, relates to greater infection risk, poorer prognosis, or both. We analysed global data on COVID-19 clinical outcomes examining inequalities between people from minoritised ethnic groups compared to the ethnic majority group.

Methods

Databases (MEDLINE, EMBASE, EMCARE, CINAHL, Cochrane Library) were searched from 1st December 2019 to 3rd October 2022, for studies reporting original clinical data for COVID-19 outcomes disaggregated by ethnicity: infection, hospitalisation, intensive care unit (ICU) admission, and mortality. We assessed inequalities in incidence and prognosis using random-effects meta-analyses, with Grading of Recommendations Assessment, Development, and Evaluation (GRADE) use to assess certainty of findings. Meta-regressions explored the impact of region and time-frame (vaccine roll-out) on heterogeneity. PROSPERO: CRD42021284981.

Findings

77 studies comprising over 200,000,000 participants were included. Compared with White majority populations, we observed an increased risk of testing positive for infection for people from Black (adjusted Risk Ratio [aRR]:1.78, 95% CI:1.59-1.99, I2 = 99.1), South Asian (aRR:3.00, 95% CI:1.59-5.66, I2 = 99.1), Mixed (aRR:1.64, 95% CI:1.02-1.67, I2 = 93.2) and Other ethnic groups (aRR:1.36, 95% CI:1.01-1.82, I2 = 85.6). Black, Hispanic, and South Asian people were more likely to be seropositive. Among population-based studies, Black and Hispanic ethnic groups and Indigenous peoples had an increased risk of hospitalisation; Black, Hispanic, South Asian, East Asian and Mixed ethnic groups and Indigenous peoples had an increased risk of ICU admission. Mortality risk was increased for Hispanic, Mixed, and Indigenous groups. Smaller differences were seen for prognosis following infection. Following hospitalisation, South Asian, East Asian, Black and Mixed ethnic groups had an increased risk of ICU admission, and mortality risk was greater in Mixed ethnic groups. Certainty of evidence ranged from very low to moderate.

Interpretation

Our study suggests that systematic ethnic inequalities in COVID-19 health outcomes exist, with large differences in exposure risk and some differences in prognosis following hospitalisation. Response and recovery interventions must focus on tackling drivers of ethnic inequalities which increase exposure risk and vulnerabilities to severe disease, including structural racism and racial discrimination.

Funding

ESRC:ES/W000849/1.

Pfizer-BioNTech Coronavirus Disease 2019 Vaccine Effectiveness Against Severe Acute Respiratory Syndrome Coronavirus 2 Infection Among Long-term Care Facility Staff With and Without Prior Infection in New York City, January-June 2021

BACKGROUND

Evidence is accumulating of coronavirus disease 2019 (COVID-19) vaccine effectiveness among persons with prior severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection.

METHODS

We evaluated the effect against incident SARS-CoV-2 infection of (1) prior infection without vaccination, (2) vaccination (2 doses of Pfizer-BioNTech COVID-19 vaccine) without prior infection, and (3) vaccination after prior infection, all compared with unvaccinated persons without prior infection. We included long-term care facility staff in New York City aged <65 years with weekly SARS-CoV-2 testing from 21 January to 5 June 2021. Test results were obtained from state-mandated laboratory reporting. Vaccination status was obtained from the Citywide Immunization Registry. Cox proportional hazards models adjusted for confounding with inverse probability of treatment weights.

RESULTS

Compared with unvaccinated persons without prior infection, incident SARS-CoV-2 infection risk was lower in all groups: 54.6% (95% confidence interval, 38.0%-66.8%) lower among unvaccinated, previously infected persons; 80.0% (67.6%-87.7%) lower among fully vaccinated persons without prior infection; and 82.4% (70.8%-89.3%) lower among persons fully vaccinated after prior infection.

CONCLUSIONS

Two doses of Pfizer-BioNTech COVID-19 vaccine reduced SARS-CoV-2 infection risk by ≥80% and, for those with prior infection, increased protection from prior infection alone. These findings support recommendations that all eligible persons, regardless of prior infection, be vaccinated against COVID-19.

Estimated SARS-CoV-2 antibody seroprevalence trends and relationship to reported case prevalence from a repeated, cross-sectional study in the 50 states and the District of Columbia, United States-October 25, 2020-February 26, 2022

Background

Sero-surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can reveal trends and differences in subgroups and capture undetected or unreported infections that are not included in case-based surveillance systems.

Methods

Cross-sectional, convenience samples of remnant sera from clinical laboratories from 51 U.S. jurisdictions were assayed for infection-induced SARS-CoV-2 antibodies biweekly from October 25, 2020, to July 11, 2021, and monthly from September 6, 2021, to February 26, 2022. Test results were analyzed for trends in infection-induced, nucleocapsid-protein seroprevalence using mixed effects models that adjusted for demographic variables and assay type.

Findings

Analyses of 1,469,792 serum specimens revealed U.S. infection-induced SARS-CoV-2 seroprevalence increased from 8.0% (95% confidence interval (CI): 7.9%-8.1%) in November 2020 to 58.2% (CI: 57.4%-58.9%) in February 2022. The U.S. ratio of the change in estimated seroprevalence to the change in reported case prevalence was 2.8 (CI: 2.8-2.9) during winter 2020-2021, 2.3 (CI: 2.0-2.5) during summer 2021, and 3.1 (CI: 3.0-3.3) during winter 2021-2022. Change in seroprevalence to change in case prevalence ratios ranged from 2.6 (CI: 2.3-2.8) to 3.5 (CI: 3.3-3.7) by region in winter 2021-2022.

Interpretation

Ratios of the change in seroprevalence to the change in case prevalence suggest a high proportion of infections were not detected by case-based surveillance during periods of increased transmission. The largest increases in the seroprevalence to case prevalence ratios coincided with the spread of the B.1.1.529 (Omicron) variant and with increased accessibility of home testing. Ratios varied by region and season with the highest ratios in the midwestern and southern United States during winter 2021-2022. Our results demonstrate that reported case counts did not fully capture differing underlying infection rates and demonstrate the value of sero-surveillance in understanding the full burden of infection. Levels of infection-induced antibody seroprevalence, particularly spikes during periods of increased transmission, are important to contextualize vaccine effectiveness data as the susceptibility to infection of the U.S. population changes.

Funding

This work was supported by the Centers for Disease Control and Prevention, Atlanta, Georgia.

COVID-19 SeroHub, an online repository of SARS-CoV-2 seroprevalence studies in the United States

Seroprevalence studies provide useful information about the proportion of the population either vaccinated against SARS-CoV-2, previously infected with the virus, or both. Numerous studies have been conducted in the United States, but differ substantially by dates of enrollment, target population, geographic location, age distribution, and assays used. This can make it challenging to identify and synthesize available seroprevalence data by geographic region or to compare infection-induced versus combined infection- and vaccination-induced seroprevalence. To facilitate public access and understanding, the National Institutes of Health and the Centers for Disease Control and Prevention developed the COVID-19 Seroprevalence Studies Hub (COVID-19 SeroHub, https://covid19serohub.nih.gov/), a data repository in which seroprevalence studies are systematically identified, extracted using a standard format, and summarized through an interactive interface. Within COVID-19 SeroHub, users can explore and download data from 178 studies as of September 1, 2022. Tools allow users to filter results and visualize trends over time, geography, population, age, and antigen target. Because COVID-19 remains an ongoing pandemic, we will continue to identify and include future studies.

The role of housing characteristics in racial and ethnic disparities in SARS-CoV-2 antibody seropositivity among New York City adults: A population representative study

Black and Latino populations have been disproportionately burdened by COVID-19 morbidity and mortality. Subsidized housing, crowding, and neighborhood poverty might be associated with increased COVID-19 transmission and play a role in observed racial and ethnic disparities, yet research is limited. Our study investigated whether these housing variables mediate the relationship between race and ethnicity and SARS-CoV-2 antibody seropositivity among New York City (NYC) adults. We analyzed data from a SARS-CoV-2 serosurvey (n = 1074), nested within the 2020 cross-sectional NYC Community Health Survey (June-October 2020). We defined SARS-CoV-2 seropositivity as either a positive blood test for SARS-CoV-2 antibodies or a self-reported positive test result. We used causal mediation analyses to test whether subsidized housing, crowding, and neighborhood poverty mediate a relationship between race and ethnicity and seropositivity. After controlling for potential confounding, we found elevated prevalence ratios of SARS-CoV-2 seropositivity among Black (APR = 1.74, 95% CI = 1.10-2.73) and Latino (APR = 1.58, 95% CI = 1.05-2.37) residents compared with White residents and for those living in crowded housing (APR = 1.48, 95% CI = 1.03-2.12) and high-poverty neighborhoods (APR = 1.54, 95% CI = 1.12-2.11) but not for subsidized housing. We observed statistically significant natural direct effects for all three mediators. While living in crowded housing and high-poverty neighborhoods contributed to racial and ethnic disparities in seropositivity the estimated contribution from living in subsidized housing was -9% (Black) and - 14% (Latino). Our findings revealed racial and ethnic disparities in seropositivity of SARS-CoV-2 antibodies among NYC adults. Unlike crowding and neighborhood poverty, living in subsidized housing did not explain racial and ethnic disparities in COVID-19.

Comparative hospitalization risk for SARS-CoV-2 Omicron and Delta variant infections, by variant predominance periods and patient-level sequencing results, New York City, August 2021-January 2022

BACKGROUND

Comparing disease severity between SARS-CoV-2 variants among populations with varied vaccination and infection histories can help characterize emerging variants and support healthcare system preparedness.

METHODS

We compared COVID-19 hospitalization risk among New York City residents with positive laboratory-based SARS-CoV-2 tests when ≥98% of sequencing results were Delta (August-November 2021) or Omicron (BA.1 and sublineages, January 2022). A secondary analysis defined variant exposure using patient-level sequencing results during July 2021-January 2022, comprising 1-18% of weekly confirmed cases.

RESULTS

Hospitalization risk was lower among patients testing positive when Omicron (16,025/488,053, 3.3%) than when Delta predominated (8268/158,799, 5.2%). In multivariable analysis adjusting for demographic characteristics and prior diagnosis and vaccination status, patients testing positive when Omicron predominated, compared with Delta, had 0.72 (95% CI: 0.63, 0.82) times the hospitalization risk. In a secondary analysis of patients with sequencing results, hospitalization risk was similar among patients infected with Omicron (2042/29,866, 6.8%), compared with Delta (1780/25,272, 7.0%), and higher among the subset who received two mRNA vaccine doses (adjusted relative risk 1.64; 95% CI: 1.44, 1.87).

CONCLUSIONS

Hospitalization risk was lower among patients testing positive when Omicron predominated, compared with Delta. This finding persisted after adjusting for prior diagnosis and vaccination status, suggesting intrinsic virologic properties, not population-based immunity, explained the lower severity. Secondary analyses demonstrated collider bias from the sequencing sampling frame changing over time in ways associated with disease severity. Representative data collection is necessary to avoid bias when comparing disease severity between previously dominant and newly emerging variants.

Missing science: A scoping study of COVID-19 epidemiological data in the United States

Systematic approaches to epidemiologic data collection are critical for informing pandemic responses, providing information for the targeting and timing of mitigations, for judging the efficacy and efficiency of alternative response strategies, and for conducting real-world impact assessments. Here, we report on a scoping study to assess the completeness of epidemiological data available for COVID-19 pandemic management in the United States, enumerating authoritative US government estimates of parameters of infectious transmission, infection severity, and disease burden and characterizing the extent and scope of US public health affiliated epidemiological investigations published through November 2021. While we found authoritative estimates for most expected transmission and disease severity parameters, some were lacking, and others had significant uncertainties. Moreover, most transmission parameters were not validated domestically or re-assessed over the course of the pandemic. Publicly available disease surveillance measures did grow appreciably in scope and resolution over time; however, their resolution with regards to specific populations and exposure settings remained limited. We identified 283 published epidemiological reports authored by investigators affiliated with U.S. governmental public health entities. Most reported on descriptive studies. Published analytic studies did not appear to fully respond to knowledge gaps or to provide systematic evidence to support, evaluate or tailor community mitigation strategies. The existence of epidemiological data gaps 18 months after the declaration of the COVID-19 pandemic underscores the need for more timely standardization of data collection practices and for anticipatory research priorities and protocols for emerging infectious disease epidemics.

Estimated Infection and Vaccine Induced SARS-CoV-2 Seroprevalence in Israel among Adults, January 2020-July 2021

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) emerged in Israel in February 2020 and spread from then. In December 2020, the FDA approved an emergency use authorization of the Pfizer-BioNTech vaccine, and on 20 December, an immunization campaign began among adults in Israel. We characterized seropositivity for IgG anti-spike antibodies against SARS-CoV-2 between January 2020 and July 2021, before and after the introduction of the vaccine in Israel among adults. We tested 9520 serum samples, collected between January 2020 and July 2021. Between January and August 2020, seropositivity rates were lower than 5.0%; this rate increased from September 2020 (6.3%) to April 2021 (84.9%) and reached 79.1% in July 2021. Between January and December 2020, low socio-economic rank was an independent, significant correlate for seropositivity. Between January and July 2021, the 40.00–64.99-year-old age group, Jews and others, and residents of the Northern district were significantly more likely to be seropositive. Our findings indicate a slow, non-significant increase in the seropositivity rate to SARS-CoV-2 between January and December 2020. Following the introduction of the Pfizer-BioNTech vaccine in Israel, a significant increase in seropositivity was observed from January until April 2021, with stable rates thereafter, up to July 2021.

SARS-CoV-2 pandemic in New York metropolitan area: The view from a major urgent care provider

Purpose

Tracking severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing and positivity trends is crucial for understanding the trajectory of the pandemic. We describe demographic and clinical characteristics, testing, and positivity rates for SARS-CoV-2 among 2.8 million patients evaluated at an urgent care provider.

Methods

We conducted a retrospective study of patients receiving a diagnostic or serologic test for SARS-CoV-2 between March 1, 2020 and July 20, 2021 at 115 CityMD locations in the New York metropolitan area. Temporal trends in SARS-CoV-2 positivity by diagnostic and serologic tests stratified by age, sex, race/ethnicity, and borough of residence were assessed.

Results

During the study period, 6.1 million COVID diagnostic and serological tests were performed on 2.8 million individuals. Testing levels were higher among 20–29-year-old, non-Hispanic White, and female patients compared with other groups. About 35% were repeat testers. Reverse transcriptase polymerase chain reaction positivity was higher in non-Hispanic Black (7.9%), Hispanic (8.2%), and Native American (8.2%) compared to non-Hispanic White (5.7%) patients. Overall seropositivity was estimated to be 22.1% (95% confidence interval: 22.0–22.2) and was highest among 10–14 year olds (27.9%), and non-Hispanic Black (26.0%) and Hispanic (31.0%) testers.

Conclusion

Urgent care centers can provide broad access to diagnostic testing and critical evaluation for ambulatory patients during pandemics, especially in population-dense, urban epicenters.  Urgent care center electronic medical records data can provide in-depth surveillance during pandemics complementary to citywide health department data sources.

Prevalence of SARS-CoV-2 antibodies during phased access to vaccination: results from a population-based survey in New York City, September 2020-March 2021

Repeated serosurveys are an important tool for understanding trends in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and vaccination. During 1 September 2020–20 March 2021, the NYC Health Department conducted a population-based SARS-CoV-2 antibody prevalence survey of 2096 NYC adults who either provided a blood specimen or self-reported the results of a previous antibody test. The serosurvey, the second in a series of surveys conducted by the NYC Health Department, aimed to estimate SARS-CoV-2 antibody prevalence across the city and for different groups at higher risk for adverse health outcomes. Weighted citywide prevalence was 23.5% overall (95% confidence interval (CI) 20.1–27.4) and increased from 19.2% (95% CI 14.7–24.6) before coronavirus disease 2019 vaccines were available to 31.3% (95% CI 24.5–39.0) during the early phases of vaccine roll-out. We found no differences in antibody prevalence by age, race/ethnicity, borough, education, marital status, sex, health insurance coverage, self-reported general health or neighbourhood poverty. These results show an overall increase in population-level seropositivity in NYC following the introduction of SARS-CoV-2 vaccines and highlight the importance of repeated serosurveys in understanding the pandemic's progression.

The clinical impact of the Covid-19 pandemic first wave on patients with cystic fibrosis in New York

BACKGROUND

People with cystic fibrosis (pwCF) may be at risk of complications from COVID-19 but the impact of COVID-19 on pwCF remains unknown.

METHODS

We conducted a multicenter retrospective cohort study to assess the impact of the COVID-19 pandemic first wave on pwCF in the New York metropolitan area (NY) from March 1, 2020 to August 31, 2020. Objectives were to determine (1) the prevalence of COVID-19 by PCR and IgG antibody testing, (2) the clinical characteristics of COVID-19, (3) delay in routine outpatient care, and (4) the effect on anxiety and depression in pwCF.

RESULTS

There were 26 COVID-19 cases diagnosed by PCR or antibody testing among the study cohort of 810 pwCF. The prevalence of COVID-19 by PCR (1.6%) and IgG antibody (12.2%) testing was low. 58% of cases were asymptomatic and 82% were managed at home. 8% were hospitalized and 1 person died. 89% of pwCF experienced delay in care. The prevalence of anxiety increased from 43% baseline to 58% during the pandemic (P<0.01). In post-hoc analysis, the proportion of patients with diabetes (38% versus 16%, P<0.01) and pancreatic insufficiency (96% versus 66%, P<0.01) were higher while CFTR modulator use was lower (46% versus 65%, P = 0.05) in pwCF who tested positive for COVID-19.

CONCLUSIONS

The prevalence of COVID-19 among pwCF in NY during the pandemic first wave was low and most cases were managed at home. CFTR modulators may be protective. PwCF experienced delay in routine care and increased anxiety.

Assessing the burden of COVID-19 in developing countries: systematic review, meta-analysis and public policy implications

INTRODUCTION

The infection fatality rate (IFR) of COVID-19 has been carefully measured and analysed in high-income countries, whereas there has been no systematic analysis of age-specific seroprevalence or IFR for developing countries.

METHODS

We systematically reviewed the literature to identify all COVID-19 serology studies in developing countries that were conducted using representative samples collected by February 2021. For each of the antibody assays used in these serology studies, we identified data on assay characteristics, including the extent of seroreversion over time. We analysed the serology data using a Bayesian model that incorporates conventional sampling uncertainty as well as uncertainties about assay sensitivity and specificity. We then calculated IFRs using individual case reports or aggregated public health updates, including age-specific estimates whenever feasible.

RESULTS

In most locations in developing countries, seroprevalence among older adults was similar to that of younger age cohorts, underscoring the limited capacity that these nations have to protect older age groups.Age-specific IFRs were roughly 2 times higher than in high-income countries. The median value of the population IFR was about 0.5%, similar to that of high-income countries, because disparities in healthcare access were roughly offset by differences in population age structure.

CONCLUSION

The burden of COVID-19 is far higher in developing countries than in high-income countries, reflecting a combination of elevated transmission to middle-aged and older adults as well as limited access to adequate healthcare. These results underscore the critical need to ensure medical equity to populations in developing countries through provision of vaccine doses and effective medications.

Severe respiratory viral infections in children with history of asymptomatic or mild COVID-19

IMPORTANCE

The spectrum of complications of COVID-19 in children, including the effect of COVID-19 on later viral infection, is not known.

OBJECTIVE

To examine the features of children hospitalized for respiratory illness with history of prior COVID-19.

DESIGN

Retrospective observational case series at a single pediatric quaternary medical center in New York City. Data were obtained from review of medical records.

PARTICIPANTS

Children with prior mild or asymptomatic COVID-19 and no known risk factors for severe respiratory disease, who were hospitalized at our center for acute respiratory illness from October 2020 to May 2021, were reviewed.

MAIN OUTCOMES AND MEASURES

Co-morbidities, history of prior COVID-19 symptoms, respiratory viral panel findings, acuity of illness, degree of respiratory decompensation based on support and interventions required, duration of hospitalization, and overall clinical course were assessed from the medical record.

RESULTS

This study included 5 patients (median age, 4 years; age range: 0.8-9 years; 4 [80%] male). All had positive COVID-19 serology, 1 (20%) had mild symptoms, while the others had no symptoms of prior Sars-CoV-2 infection, 3 (60%) had asthma, and the remaining had no co-morbidities. All were admitted between April and May 2021. Two were re-admitted for respiratory symptoms in the subsequent 3 months.

CONCLUSIONS AND RELEVANCE

This case series describes a possible association between severe lower respiratory tract infection and prior mild COVID-19 in children. Larger cohort studies describing the respiratory effects of prior COVID-19 in children are needed.

SARS-CoV-2 Seroprevalence and Reported COVID-19 Cases in U.S. Children, August 2020—May 2021

Background

Case-based surveillance of pediatric coronavirus disease 2019 (COVID-19) cases underestimates the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections among children and adolescents. Our objectives were to estimate monthly SARS-CoV-2 antibody seroprevalence and calculate ratios of SARS-CoV-2 infections to reported COVID-19 cases among children and adolescents in 8 US states.

Methods

Using data from the Nationwide Commercial Laboratory Seroprevalence Survey, we estimated monthly SARS-CoV-2 antibody seroprevalence among children aged 0–17 years from August 2020 through May 2021. We calculated and compared cumulative incidence of SARS-CoV-2 infection extrapolated from population-standardized seroprevalence of antibodies to SARS-CoV-2, cumulative COVID-19 case reports since March 2020, and infection-to-case ratios among persons of all ages and children aged 0–17 years for each state.

Results

Of 41 583 residual serum specimens tested, children aged 0–4, 5–11, and 12–17 years accounted for 1619 (3.9%), 10 507 (25.3%), and 29 457 (70.8%), respectively. Median SARS-CoV-2 antibody seroprevalence among children increased from 8% (range, 6%–20%) in August 2020 to 37% (range, 26%–44%) in May 2021. Estimated ratios of SARS-CoV-2 infections to reported COVID-19 cases in May 2021 ranged by state from 4.7–8.9 among children and adolescents to 2.2–3.9 for all ages combined.

Conclusions

Through May 2021 in selected states, the majority of children with serum specimens included in serosurveys did not have evidence of prior SARS-CoV-2 infection. Case-based surveillance underestimated the number of children infected with SARS-CoV-2 more than among all ages. Continued monitoring of pediatric SARS-CoV-2 antibody seroprevalence should inform prevention and vaccination strategies.

Socioeconomic Disparities in Severe Acute Respiratory Syndrome Coronavirus 2 Serological Testing and Positivity in New York City

Background

We characterized severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody test prevalence and positive test prevalence across New York City (NYC) in order to investigate disparities in testing outcomes by race and socioeconomic status (SES).

Methods

Serologic data were downloaded from the NYC Coronavirus data repository (August 2020–December 2020). Area-level characteristics for NYC neighborhoods were downloaded from United States census data and a socioeconomic vulnerability index was created. Spatial generalized linear mixed models were performed to examine the association between SES and antibody testing and positivity.

Results

The proportion of Hispanic population (posterior median, 0.001 [95% credible interval, 0.0003–0.002]), healthcare workers (0.003 [0.0001–0.006]), essential workers (0.003 [0.001–0.005]), age ≥65 years (0.003 [0.00002–0.006]), and high SES (SES quartile 3 vs 1: 0.034 [0.003–0.062]) were positively associated with antibody tests per 100000 residents. The White proportion (–0.002 [–0.003 to –0.001]), SES index (quartile 3 vs 1, –0.068 [–0.115 to –0.017]; quartile 4 vs 1, –0.077 [–0.134 to –0.018]) and age ≥65 years (–0.005 [–0.009 to –0.002]) were inversely associated with positive test prevalence (%), whereas the Hispanic (0.004 [0.002–0.006]) and essential worker (0.008 [0.003–0.012]) proportions had positive coefficients.

Conclusions

Disparities in serologic testing and seropositivity exist on SES and race/ethnicity across NYC, indicative of excess coronavirus disease burden in vulnerable and marginalized populations.

Adapting Survey Data Collection to Respond to the COVID-19 Pandemic: Experiences From a Local Health Department

The New York City (NYC) Department of Health and Mental Hygiene ("Health Department") conducts routine surveys to describe the health of NYC residents. During the COVID-19 pandemic, the Health Department adjusted existing surveys and developed new ones to improve our understanding of the impact of the pandemic on physical health, mental health, and social determinants of health and to incorporate more explicit measures of racial inequities. The longstanding Community Health Survey was adapted in 2020 to ask questions about COVID-19 and recruit respondents for a population-based severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) serosurvey. A new survey panel, Healthy NYC, was launched in June 2020 and is being used to collect data on COVID-19, mental health, and social determinants of health. In addition, 7 Health Opinion Polls were conducted from March 2020 through March 2021 to learn about COVID-19-related knowledge, attitudes, and opinions, including vaccine intentions. We describe the contributions that survey data have made to the emergency response in NYC in ways that address COVID-19 and the profound inequities of the pandemic. (Am J Public Health. 2021;111(12):2176-2185. https://doi.org/10.2105/AJPH.2021.306515).

Assessment of SARS-CoV-2 Seroprevalence by Community Survey and Residual Specimens, Denver, Colorado, July-August 2020

OBJECTIVES

The number of SARS-CoV-2 infections is underestimated in surveillance data. Various approaches to assess the seroprevalence of antibodies to SARS-CoV-2 have different resource requirements and generalizability. We estimated the seroprevalence of antibodies to SARS-CoV-2 in Denver County, Colorado, via a cluster-sampled community survey.

METHODS

We estimated the overall seroprevalence of antibodies to SARS-CoV-2 via a community seroprevalence survey in Denver County in July 2020, described patterns associated with seroprevalence, and compared results with cumulative COVID-19 incidence as reported to the health department during the same period. In addition, we compared seroprevalence as assessed with a temporally and geographically concordant convenience sample of residual clinical specimens from a commercial laboratory.

RESULTS

Based on 404 specimens collected through the community survey, 8.0% (95% CI, 3.9%-15.7%) of Denver County residents had antibodies to SARS-CoV-2, an infection rate of about 7 times that of the 1.1% cumulative reported COVID-19 incidence during this period. The estimated infection-to-reported case ratio was highest among children (34.7; 95% CI, 11.1-91.2) and males (10.8; 95% CI, 5.7-19.3). Seroprevalence was highest among males of Black race or Hispanic ethnicity and was associated with previous COVID-19-compatible illness, a previous positive SARS-CoV-2 test result, and close contact with someone who had confirmed SARS-CoV-2 infection. Testing of 1598 residual clinical specimens yielded a seroprevalence of 6.8% (95% CI, 5.0%-9.2%); the difference between the 2 estimates was 1.2 percentage points (95% CI, -3.6 to 12.2 percentage points).

CONCLUSIONS

Testing residual clinical specimens provided a similar seroprevalence estimate yet yielded limited insight into the local epidemiology of COVID-19 and might be less representative of the source population than a cluster-sampled community survey. Awareness of the limitations of various sampling strategies is necessary when interpreting findings from seroprevalence assessments.

Seroprevalence of Severe Acute Respiratory Syndrome Coronavirus 2 Following the Largest Initial Epidemic Wave in the United States: Findings From New York City, 13 May to 21 July 2020

Background

New York City (NYC) was the U.S. epicenter of the Spring 2020 COVID-19 pandemic. We present seroprevalence of SARS-CoV-2 infection and correlates of seropositivity immediately after the first wave.

Methods

From a serosurvey of adult NYC residents (May 13-July 21, 2020), we calculated the prevalence of SARS-CoV-2 antibodies stratified by participant demographics, symptom history, health status, and employment industry. We used multivariable regression models to assess associations between participant characteristics and seropositivity.

Results

Seroprevalence among 45,367 participants was 23.6% (95% CI, 23.2%-24.0%). High seroprevalence (>30%) was observed among Black and Hispanic individuals, people from high poverty neighborhoods, and people in health care or essential worker industry sectors. COVID-19 symptom history was associated with seropositivity (adjusted relative risk=2.76; 95% CI, 2.65-2.88). Other risk factors included sex, age, race/ethnicity, residential area, employment sector, working outside the home, contact with a COVID-19 case, obesity, and increasing numbers of household members.

Conclusions

Based on a large serosurvey in a single U.S. jurisdiction, we estimate that just under one-quarter of NYC adults were infected in the first few months of the COVID-19 epidemic. Given disparities in infection risk, effective interventions for at-risk groups are needed during ongoing transmission.