Pediatric Infection-Induced SARS-CoV-2 Seroprevalence Increases and Seroprevalence by Type of Clinical Care-September 2021-February 2022.

BACKGROUND AND OBJECTIVES: Trends in estimates of US pediatric SARS-CoV-2 infection-induced seroprevalence from commercial laboratory specimens may overrepresent children with frequent healthcare needs. We examined seroprevalence trends and compared seroprevalence estimates by testing type and diagnostic coding. METHODS: Cross-sectional convenience samples of residual sera between September 2021 and February 2022 from 52 U.S. jurisdictions were assayed for infection-induced SARS-CoV-2 antibodies; monthly seroprevalence estimates were calculated by age group. Multivariate logistic analyses compared seroprevalence estimates for specimens associated with ICD-10 codes and laboratory orders indicating well-child care with estimates for other pediatric specimens. RESULTS: Infection-induced SARS-CoV-2 seroprevalence increased in each age group; from 30% to 68% (1-4 years), 38% to 77% (5-11 years), and 40% to 74% (12-17 years). On multivariate analysis, patients with well-child ICD-10 codes were seropositive more often than other patients aged 1-17 years (adjusted prevalence ratio [aPR] 1.04; 95% CI 1.02-1.07); children aged 9-11 years receiving standard lipid screening were seropositive more often than those receiving other laboratory tests (1.05; 1.02-1.08). CONCLUSIONS: Infection-induced seroprevalence more than doubled among children under 12 between September 2021 and February 2022, and increased 85% in adolescents. Differences in seroprevalence by care type did not substantially impact US pediatric seroprevalence estimates.

Severity of Covid-19 Lockdown Orders Corresponds to Orthopaedic Trauma Volume.

During the Coronavirus Disease 2019 (COVID-19) pandemic, states implemented social distancing guidelines. This study examines the effect of the severity of lockdown orders on orthopaedic trauma volume. Two institutions, one in a state with strict stay home (SH) orders and one in a state with lax social distancing (SD) orders, were examined. Surgical case counts, total orthopaedic case counts, orthopaedic trauma case counts, institution trauma activations, and mechanism of injury data were collected and compared to control periods. For SH versus SD, total surgical cases decreased 48.6% vs. 62%; orthopaedic cases decreased 51.8% vs. 62%, and orthopaedic trauma cases decreased 34% v. 0%. Orthopaedic trauma cases comprised more of both institutions' total cases. Total surgical cases decreased at both SH and SD, but orthopaedic trauma cases did not decrease at SD. More strict social distancing orders correlate with greater reduction in orthopaedic trauma cases. (Journal of Surgical Orthopaedic Advances 31(4):222-225, 2022).

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 10.13039/100000030Centers for Disease Control and Prevention, Atlanta, Georgia.

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.

The Missing COVID-19 Demographic Data: A Statewide Analysis of COVID-19–Related Demographic Data From Local Government Sources and a Comparison With Federal Public Surveillance Data

Objectives. To collect and standardize COVID-19 demographic data published by local public-facing Web sites and analyze how this information differs from Centers for Disease Control and Prevention (CDC) public surveillance data. Methods. We aggregated and standardized COVID-19 data on cases and deaths by age, gender, race, and ethnicity from US state and territorial governmental sources between May 24 and June 4, 2021. We describe the standardization process and compare it with the CDC's process for public surveillance data. Results. As of June 2021, the CDC's public demographic data set included 80.9% of total cases and 46.7% of total deaths reported by states, with significant variation across jurisdictions. Relative to state and territorial data sources, the CDC consistently underreports cases and deaths among African American and Hispanic or Latino individuals and overreports deaths among people older than 65 years and White individuals. Conclusions. Differences exist in amounts of data included and demographic composition between the CDC's public surveillance data and state and territory reporting, with large heterogeneity across jurisdictions. A lack of standardization and reporting mechanisms limits the production of complete real-time demographic data.

Seroprevalence of Infection-Induced SARS-CoV-2 Antibodies - United States, September 2021-February 2022.

In December 2021, the B.1.1.529 (Omicron) variant of SARS-CoV-2, the virus that causes COVID-19, became predominant in the United States. Subsequently, national COVID-19 case rates peaked at their highest recorded levels.* Traditional methods of disease surveillance do not capture all COVID-19 cases because some are asymptomatic, not diagnosed, or not reported; therefore, the proportion of the population with SARS-CoV-2 antibodies (i.e., seroprevalence) can improve understanding of population-level incidence of COVID-19. This report uses data from CDC's national commercial laboratory seroprevalence study and the 2018 American Community Survey to examine U.S. trends in infection-induced SARS-CoV-2 seroprevalence during September 2021-February 2022, by age group.

COVID-19 data driven planning: The SouthEast Texas approach.

This coautoethnographic case study used the Open-Source Public Health Intelligence process to explore and share the South East Texas Regional Advisory Councils' (SETRAC) experience in collecting, processing, disseminating/visualizing, and analyzing COVID-19 data during the pandemic in the largest national medical setting in the United States. Specifically, it details the production of Business Intelligence reports powered by PowerBI both with general publics and with Regional Healthcare Preparedness Program (HPP) Coalition Coordinators, County Judges and City Mayors, Texas Department of State Health Services (DSHS) executive leadership, the Offices of the Texas Governor, and the Federal Pandemic Task Force led by the US Vice President, in order to provide a foundation for situational awareness, inter-regional collaboration, allocation of scare resources, and local, regional, and state policy decisions. It highlights best practices in risk and crisis communications during the COVID-19 response, underscores cross-sector collaboration and standardization of data collection for effective planning and response, discusses pervasive data revealed during the analysis, and evaluates collaborative and feedback processes that have implications for the Health Care System and Homeland Security Enterprise information sharing.

Estimated SARS-CoV-2 Seroprevalence in the US as of September 2020.

Importance: Case-based surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection likely underestimates the true prevalence of infections. Large-scale seroprevalence surveys can better estimate infection across many geographic regions. Objective: To estimate the prevalence of persons with SARS-CoV-2 antibodies using residual sera from commercial laboratories across the US and assess changes over time. Design, Setting, and Participants: This repeated, cross-sectional study conducted across all 50 states, the District of Columbia, and Puerto Rico used a convenience sample of residual serum specimens provided by persons of all ages that were originally submitted for routine screening or clinical management from 2 private clinical commercial laboratories. Samples were obtained during 4 collection periods: July 27 to August 13, August 10 to August 27, August 24 to September 10, and September 7 to September 24, 2020. Exposures: Infection with SARS-CoV-2. Main Outcomes and Measures: The proportion of persons previously infected with SARS-CoV-2 as measured by the presence of antibodies to SARS-CoV-2 by 1 of 3 chemiluminescent immunoassays. Iterative poststratification was used to adjust seroprevalence estimates to the demographic profile and urbanicity of each jurisdiction. Seroprevalence was estimated by jurisdiction, sex, age group (0-17, 18-49, 50-64, and ≥65 years), and metropolitan/nonmetropolitan status. Results: Of 177 919 serum samples tested, 103 771 (58.3%) were from women, 26 716 (15.0%) from persons 17 years or younger, 47 513 (26.7%) from persons 65 years or older, and 26 290 (14.8%) from individuals living in nonmetropolitan areas. Jurisdiction-level seroprevalence over 4 collection periods ranged from less than 1% to 23%. In 42 of 49 jurisdictions with sufficient samples to estimate seroprevalence across all periods, fewer than 10% of people had detectable SARS-CoV-2 antibodies. Seroprevalence estimates varied between sexes, across age groups, and between metropolitan/nonmetropolitan areas. Changes from period 1 to 4 were less than 7 percentage points in all jurisdictions and varied across sites. Conclusions and Relevance: This cross-sectional study found that as of September 2020, most persons in the US did not have serologic evidence of previous SARS-CoV-2 infection, although prevalence varied widely by jurisdiction. Biweekly nationwide testing of commercial clinical laboratory sera can play an important role in helping track the spread of SARS-CoV-2 in the US.

The National COVID Cohort Collaborative (N3C): Rationale, design, infrastructure, and deployment.

OBJECTIVE: Coronavirus disease 2019 (COVID-19) poses societal challenges that require expeditious data and knowledge sharing. Though organizational clinical data are abundant, these are largely inaccessible to outside researchers. Statistical, machine learning, and causal analyses are most successful with large-scale data beyond what is available in any given organization. Here, we introduce the National COVID Cohort Collaborative (N3C), an open science community focused on analyzing patient-level data from many centers. MATERIALS AND METHODS: The Clinical and Translational Science Award Program and scientific community created N3C to overcome technical, regulatory, policy, and governance barriers to sharing and harmonizing individual-level clinical data. We developed solutions to extract, aggregate, and harmonize data across organizations and data models, and created a secure data enclave to enable efficient, transparent, and reproducible collaborative analytics. RESULTS: Organized in inclusive workstreams, we created legal agreements and governance for organizations and researchers; data extraction scripts to identify and ingest positive, negative, and possible COVID-19 cases; a data quality assurance and harmonization pipeline to create a single harmonized dataset; population of the secure data enclave with data, machine learning, and statistical analytics tools; dissemination mechanisms; and a synthetic data pilot to democratize data access. CONCLUSIONS: The N3C has demonstrated that a multisite collaborative learning health network can overcome barriers to rapidly build a scalable infrastructure incorporating multiorganizational clinical data for COVID-19 analytics. We expect this effort to save lives by enabling rapid collaboration among clinicians, researchers, and data scientists to identify treatments and specialized care and thereby reduce the immediate and long-term impacts of COVID-19.