ArticleMicrobiology spectrum2025
Seroprevalence of SARS-CoV-2 IgG antibodies in children seeking medical care in Seattle, WA June 2020 to December 2022.
Article in Microbiology spectrum, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Association Between Social Vulnerability and Infection-Induced SARS-CoV-2 Antibody Seroprevalence Among Children: United States, 2021-2022.Public health reports (Washington, D.C. : 1974) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
Seroprevalence studies play an important role in estimating the number of children infected with SARS-CoV-2. We report SARS-CoV-2 seroprevalence in children seeking medical care for any reason at a free-standing pediatric hospital in Seattle, WA over a 2.5-year period and four distinct pandemic waves. We randomly selected residual serum samples from children and young adults seeking medical care as inpatients and outpatients at Seattle Children's Hospital between June 2020 and December 2022 to test for the presence of anti-nucleocapsid (N) antibodies. Samples were categorized into four distinct pandemic waves based on Washington State epidemiology: Wave 1 (June 2020-October 2020), Wave 2 (November 2020-June 2021), Wave 3 (July 2021-November 2021), and Wave 4 (December 2021-December 2022). Patient characteristics and COVID-19 vaccine status were obtained, and zip codes were used to ascertain the Social Vulnerability Index (SVI). Multivariable Poisson regression models with robust variance estimates were used to examine the relationship between patient characteristics and anti-N-positivity for each wave. Among 8,040 samples from 7,102 patients included in the analyses, seroprevalence rose from 2.4% (95% CI, 2.0%-3.1%) in Wave 1 to 25.5% (95% CI 23.3%-27.8%) in Wave 4 (following the Omicron surge). High SVI, Hispanic ethnicity, or use of government insurance was associated with increased anti-N positivity in most waves. We observed a steady increase in anti-N seroprevalence followed by a sharp increase after the Omicron surge in early 2022. Our data demonstrate the burden of COVID-19 on specific groups with health disparities within our region throughout the pandemic.IMPORTANCEOur results highlight the importance of seropositivity studies as essential tools to provide information on the incidence and prevalence of SARS-CoV-2 seropositivity. Our results also reinforce other reports demonstrating the inequitable burden of COVID-19 on groups with health disparities and that this inequitable burden continued to persist throughout the pandemic, even in a region with high adherence to COVID-19 mitigation efforts. It also highlights SVI's value in identifying communities that must be part of pandemic research, and public health and vaccination strategies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.