Evidence map›Paper›PMID 34260777›Full record

SynthesisReviews in medical virology2021

Population-based prevalence surveys during the Covid-19 pandemic: A systematic review.

Vinícius Bonetti Franceschi, Andressa Schneiders Santos, Andressa Barreto Glaeser, Janini Cristina Paiz, Gabriel Dickin Caldana, Carem Luana Machado Lessa, Amanda de Menezes Mayer, Julia Gonçalves Küchle, Paulo Ricardo Gazzola Zen, Alvaro Vigo and 3 more

Abstract readSystematic Review
In one paragraph

Synthesis in Reviews in medical virology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 6 pooled it
–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

31 citing papers in PubMed, 6 syntheses or guidelines pooled it.

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  7. Article
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  10. Inferring COVID-19 testing and vaccination behavior from New Jersey testing data.Proceedings of the National Academy of Sciences of the United States of America · 2024
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  13. Vitamin D status and blood group among severe COVID-19 patients.Annals of medicine and surgery (2012) · 2023
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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

13 authors.

Vinícius Bonetti FranceschiGraduate Program in Cell and Molecular Biology (PPGBCM), Center of Biotechnology, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Rio Grande do Sul, Brazil.ORCID https://orcid.org/0000-0002-0006-9337
Andressa Schneiders SantosUndergraduate Program in Biomedicine, Universidade Federal de Ciências da Saúde de Porto Alegre (UFCSPA), Porto Alegre, Rio Grande do Sul, Brazil.
Andressa Barreto GlaeserGraduate Program in Pathology, Universidade Federal de Ciências da Saúde de Porto Alegre (UFCSPA), Porto Alegre, Rio Grande do Sul, Brazil.
Janini Cristina PaizGraduate Program in Epidemiology, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Rio Grande do Sul, Brazil.
Gabriel Dickin CaldanaGraduate Program in Health Sciences, Universidade Federal de Ciências da Saúde de Porto Alegre (UFCSPA), Porto Alegre, Rio Grande do Sul, Brazil.
Carem Luana Machado LessaGraduate Program in Pathology, Universidade Federal de Ciências da Saúde de Porto Alegre (UFCSPA), Porto Alegre, Rio Grande do Sul, Brazil.
Amanda de Menezes MayerGraduate Program in Cell and Molecular Biology (PPGBCM), Center of Biotechnology, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Rio Grande do Sul, Brazil.
Julia Gonçalves KüchleUndergraduate Program in Biomedical Informatics, Universidade Federal de Ciências da Saúde de Porto Alegre (UFCSPA), Porto Alegre, Rio Grande do Sul, Brazil.
Paulo Ricardo Gazzola ZenGraduate Program in Pathology, Universidade Federal de Ciências da Saúde de Porto Alegre (UFCSPA), Porto Alegre, Rio Grande do Sul, Brazil.
Alvaro VigoGraduate Program in Epidemiology, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Rio Grande do Sul, Brazil.
Ana Trindade WinckDepartment of Exact and Social Applied Sciences, Universidade Federal de Ciências da Saúde de Porto Alegre (UFCSPA), Porto Alegre, Rio Grande do Sul, Brazil.
Liane Nanci RottaGraduate Program in Health Sciences, Universidade Federal de Ciências da Saúde de Porto Alegre (UFCSPA), Porto Alegre, Rio Grande do Sul, Brazil.
Claudia Elizabeth ThompsonGraduate Program in Cell and Molecular Biology (PPGBCM), Center of Biotechnology, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Rio Grande do Sul, Brazil.ORCID https://orcid.org/0000-0003-3639-1851

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Population-based prevalence surveys of Covid-19 contribute to establish the burden of infection, the role of asymptomatic and mild infections in transmission, and allow more precise decisions about reopen policies. We performed a systematic review to evaluate qualitative aspects of these studies, assessing their reliability and compiling practices that can influence the methodological quality. We searched MEDLINE, EMBASE, bioRxiv and medRxiv, and included cross-sectional studies using molecular and/or serological tests to estimate the prevalence of Covid-19 in the general population. Survey quality was assessed using the Joanna Briggs Institute Critical Appraisal Checklist for Prevalence Studies. A correspondence analysis correlated methodological parameters of each study to identify patterns related to higher, intermediate and lower risks of bias. The available data described 37 surveys from 19 countries. The majority were from Europe and America, used antibody testing, and reached highly heterogeneous sample sizes and prevalence estimates. Minority communities were disproportionately affected by Covid-19. Important risk of bias was detected in four domains: sample size, data analysis with sufficient coverage, measurements in standard way and response rate. The correspondence analysis showed few consistent patterns for high risk of bias. Intermediate risk of bias was related to American and European studies, municipal and regional initiatives, blood samples and prevalence >1%. Low risk of bias was related to Asian studies, nationwide initiatives, reverse-transcriptase polymerase chain reaction tests and prevalence <1%. We identified methodological standards applied worldwide in Covid-19 prevalence surveys, which may assist researchers with the planning, execution and reporting of future population-based surveys.

Indexed as

Population SurveillanceCOVID-19COVID-19 TestingHumansMass ScreeningPrevalenceCovid-19cross-sectional studiesepidemiologyinfectious diseasesprevalenceSARS-CoV-2severe acute respiratory syndrome coronavirus 2

Identifiers

PMID34260777
PMCPMC7883186

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.