Evidence map›Paper›PMID 35180375›Full record

ArticleEmerging infectious diseases2022

SARS-CoV-2 IgG Seroprevalence among Blood Donors as a Monitor of the COVID-19 Epidemic, Brazil.

Daniel Gonçalves Chaves, Ricardo Hiroshi Caldeira Takahashi, Felipe Campelo, Maria Clara Fernandes da Silva Malta, Isabelle Rocha de Oliveira, Edel Figueiredo Barbosa-Stancioli, Maísa Aparecida Ribeiro, Marina Lobato Martins

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Article in Emerging infectious diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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

8 authors.

Daniel Gonçalves Chaves
Ricardo Hiroshi Caldeira Takahashi
Felipe Campelo
Maria Clara Fernandes da Silva Malta
Isabelle Rocha de Oliveira
Edel Figueiredo Barbosa-Stancioli
Maísa Aparecida Ribeiro
Marina Lobato Martins

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

During epidemics, data from different sources can provide information on varying aspects of the epidemic process. Serology-based epidemiologic surveys could be used to compose a consistent epidemic scenario. We assessed the seroprevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) IgG in serum samples collected from 7,837 blood donors in 7 cities of Brazil during March-December 2020. Based on our results, we propose a modification in a compartmental model that uses reported number of SARS-CoV-2 cases and serology results from blood donors as inputs and delivers estimates of hidden variables, such as daily values of SARS-CoV-2 transmission rates and cumulative incidence rate of reported and unreported SARS-CoV-2 cases. We concluded that the information about cumulative incidence of a disease in a city's population can be obtained by testing serum samples collected from blood donors. Our proposed method also can be extended to surveillance of other infectious diseases.

Indexed as

COVID-19EpidemicsAntibodies, ViralBlood DonorsBrazilHumansImmunoglobulin GSARS-CoV-2Seroepidemiologic StudiesAntibodies, ViralImmunoglobulin Gblood donorBrazilcoronaviruscoronavirus diseaseCOVID-19epidemic modelrespiratory infectionsSARSSARS-CoV-2seroprevalencesevere acute respiratory syndrome coronavirus 2viruseszoonoses

Identifiers

PMID35180375
PMCPMC8962887

What OpenQuestion holds

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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.