Evidence map›Paper›PMID 34921991›Full record

ArticleAnnals of epidemiology2022

Prevalence of current and past COVID-19 in Ohio adults.

Abigail Norris Turner, David Kline, Alison Norris, W Gene Phillips, Elisabeth Root, Jonathan Wakefield, Zehang Li, Stanley Lemeshow, Morgan Spahnie, Amanda Luff and 8 more

Open access · greenAbstract read
In one paragraph

Article in Annals of epidemiology, 2022. 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
0.3field-weighted citation impact, top 38% of its field
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, 7 citations in OpenAlex.

  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

18 authors at 7 institutions in 2 countries.

Abigail Norris TurnerDivision of Infectious Diseases, Department of Internal Medicine, College of Medicine, Ohio State University, Columbus, OH. Electronic address: ant@osumc.edu.
David KlineDepartment of Biostatistics and Data Science, Division of Public Health Sciences, School of Medicine, Wake Forest University, Winston-Salem, NC.
Alison NorrisDivision of Infectious Diseases, Department of Internal Medicine, College of Medicine, Ohio State University, Columbus, OH; Division of Epidemiology, College of Medicine, Ohio State University, Columbus, OH.
W Gene PhillipsOhio Department of Health, Columbus, OH.
Elisabeth RootDivision of Epidemiology, College of Medicine, Ohio State University, Columbus, OH; Institute for Disease Modeling, The Bill and Melinda Gates Foundation, Seattle, WA.
Jonathan WakefieldDepartment of Statistics, University of Washington, Seattle, WA.
Zehang LiDepartment of Statistics, University of California, Santa Cruz, CA.
Stanley LemeshowDivision of Biostatistics, College of Public Health, Ohio State University, Columbus, OH.
Morgan SpahnieDivision of Epidemiology, College of Medicine, Ohio State University, Columbus, OH.
Amanda LuffDivision of Epidemiology, College of Medicine, Ohio State University, Columbus, OH.
Yue ChuDepartment of Sociology, College of Arts and Sciences, Ohio State University, Columbus, OH.
Mary Kate FrancisOhio Department of Health, Columbus, OH.
Maria GalloDivision of Epidemiology, College of Medicine, Ohio State University, Columbus, OH.
Payal ChakrabortyDivision of Epidemiology, College of Medicine, Ohio State University, Columbus, OH.
Megan LindstromInstitute for Disease Modeling, The Bill and Melinda Gates Foundation, Seattle, WA.
Gerard LozanskiDepartment of Pathology, College of Medicine, Ohio State University, Columbus, OH.
William MillerDivision of Epidemiology, College of Medicine, Ohio State University, Columbus, OH.
Samuel ClarkDepartment of Sociology, College of Arts and Sciences, Ohio State University, Columbus, OH; MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
The Ohio State University · USFlorida State University · USGates Foundation · USOhio Department of Health · USUniversity of California, Santa Cruz · USUniversity of Washington · USWake Forest University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose To estimate the prevalence of current and past COVID-19 in Ohio adults. Methods We used stratified, probability-proportionate-to-size cluster sampling. During July 2020, we enrolled 727 randomly-sampled adult English- and Spanish-speaking participants through a household survey. Participants provided nasopharyngeal swabs and blood samples to detect current and past COVID-19. We used Bayesian latent class models with multilevel regression and poststratification to calculate the adjusted prevalence of current and past COVID-19. We accounted for the potential effects of non-ignorable non-response bias. Results The estimated statewide prevalence of current COVID-19 was 0.9% (95% credible interval: 0.1%-2.0%), corresponding to ∼85,000 prevalent infections (95% credible interval: 6,300-177,000) in Ohio adults during the study period. The estimated statewide prevalence of past COVID-19 was 1.3% (95% credible interval: 0.2%-2.7%), corresponding to ∼118,000 Ohio adults (95% credible interval: 22,000-240,000). Estimates did not change meaningfully due to non-response bias. Conclusions Total COVID-19 cases in Ohio in July 2020 were approximately 3.5 times as high as diagnosed cases. The lack of broad COVID-19 screening in the United States early in the pandemic resulted in a paucity of population-representative prevalence data, limiting the ability to measure the effects of statewide control efforts.

Indexed as

COVID-19AdultBayes TheoremHumansOhioPrevalenceSARS-CoV-2United StatesBayesianCovid-19OhioPopulation-representativeprobability-proportional-to-size cluster samplingSars-cov-2

Identifiers

PMID34921991
PMCPMC9759827
OpenAlexW4200126403

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.