Evidence map›Paper›PMID 34640359›Full record

ArticleJournal of clinical medicine2021

Understanding the Patterns of Serological Testing for COVID-19 Pre- and Post-Vaccination Rollout in Michigan.

Zhangchen Zhao, Stephen Salerno, Xu Shi, Seunggeun Lee, Bhramar Mukherjee, Lars G Fritsche

Abstract read
In one paragraph

Article in Journal of clinical medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Zhangchen ZhaoDepartment of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA.ORCID 0000-0002-7990-2589
Stephen SalernoDepartment of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA.ORCID 0000-0003-2763-0494
Xu ShiDepartment of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA.ORCID 0000-0001-8566-9552
Seunggeun LeeDepartment of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA.
Bhramar MukherjeeDepartment of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA.
Lars G FritscheDepartment of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA.ORCID 0000-0002-2110-1690

Funding

Statistical and computational methods for rare variant association analysisR01HG008773 · NHGRI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MUKHERJEE, BHRAMAR · 2016 to 2020
$1.9M
Accounting for Hidden Bias in Vaccine Studies: A Negative Control FrameworkR01GM139926 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI SHI, XU, TCHETGEN TCHETGEN, ERIC JOEL · 2021 to 2024
$1.5M
National Research Foundation of Korea 2020H1D3A2A03100666National Science Foundation DMS 1712933NHGRI NIH HHS R01 HG008773NIGMS NIH HHS R01 GM139926NIH HHS NCI P30 CA 046592-30-S3NIH HHS NHGRI R01 HG 008773
6 · The paper itself

Abstract

Testing for SARS-CoV-2 antibodies is commonly used to determine prior COVID-19 infections and to gauge levels of infection- or vaccine-induced immunity. Michigan Medicine, a primary regional health center, provided an ideal setting to understand serologic testing patterns over time. Between 27 April 2020 and 3 May 2021, characteristics for 10,416 individuals presenting for SARS-CoV-2 antibody tests (10,932 tests in total) were collected. Relative to the COVID-19 vaccine roll-out date, 14 December 2020, the data were split into a pre- (8026 individuals) and post-vaccine launch (2587 individuals) period and contrasted with untested individuals to identify factors associated with tested individuals and seropositivity. Exploratory analysis of vaccine-mediated seropositivity was performed in 347 fully vaccinated individuals. Predictors of tested individuals included age, sex, smoking, neighborhood variables, and pre-existing conditions. Seropositivity in the pre-vaccine launch period was 9.2% and increased to 46.7% in the post-vaccine launch period. In the pre-vaccine launch period, seropositivity was significantly associated with age (10 year; OR = 0.80 (0.73, 0.89)), ever-smoker status (0.49 (0.35, 0.67)), respiratory disease (4.38 (3.13, 6.12)), circulatory disease (2.09 (1.48, 2.96)), liver disease (2.06 (1.11, 3.84)), non-Hispanic Black race/ethnicity (2.18 (1.33, 3.58)), and population density (1.10 (1.03, 1.18)). Except for the latter two, these associations remained statistically significant in the post-vaccine launch period. The positivity rate of fully vaccinated individual was 296/347(85.3% (81.0%, 88.8%)).

Indexed as

coronavirus disease 2019disease prevalenceimmunityserologic testingvaccination

Identifiers

PMID34640359
PMCPMC8509702

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Registered trials

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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.