Evidence map›Paper›PMID 38590673›Full record

ArticleArchives of Razi Institute2023

Seroprevalence of Anti-SARS-CoV-2 IgG and IgM Antibodies among Government Employees in Iran.

Zabeh Jazi Mohammad Hossein, Dabaghian Mehran

Abstract read
In one paragraph

Article in Archives of Razi Institute, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

2 authors.

Zabeh Jazi Mohammad HosseinDepartment of Venomous Animals and Antivenom Production, Razi Vaccine and Serum Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran.
Dabaghian MehranDepartment of Venomous Animals and Antivenom Production, Razi Vaccine and Serum Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 disease emerged in Wuhan, China, in December 2019 and quickly became a global health threat. Around 6,947,192 people have been killed around the world so far, including 146,292 in Iran. In addition to the definitive diagnosis of the disease by RT-PCR, immunological and serological tests can check the anti-SARS-CoV-2 N protein antibody titer in people at different stages of infection with acceptable sensitivity and specificity. The serological examination is an effective and efficient method for determining the prevalence of the disease, especially when asymptomatic cases are present or the diagnosis of symptomatic cases is incomplete. The study examined the seroprevalence of COVID-19 at the Razi Vaccine and Serum Research Institute (RVSRI) and the Agricultural Research, Education, and Extension Organization (AREEO). A total of 493 blood samples were collected from volunteers in June 2020 in AREEO, and 380 samples were collected in June and July 2020 in RVSRI. The total number of volunteers from both organizations was 873. Standard ELISA kits were used to measure IgG and IgM antibodies against SARS-CoV-2. A statistical analysis of the obtained data was conducted using SPSS (version 22.0). Among the total 873 volunteers examined in RVSRI and AREEO, 10.5% had elevated serum titers either for IgM or IgG, 3.55% of whom were women and 6.95% were men. Generally, 8.8% of people tested positive for IgM, which showed a recent infection with COVID-19 in people at that time and partially indicated the start of a new wave of COVID-19. In RVSRI, 3.42% of people with positive IgM titers (positive or negative IgG titers) were women and 5.53% were men. In AREEO, 3.02% were women and 5.72% were men. The seroprevalence rate of COVID-19 in RVSRI was 11.6%, 4.2% of which were women and 7.35% were men, with no significant difference between women and men. The COVID-19 seroprevalence in AREEO was 9.7%, 3.22% of which were women and 6.5% were men, with no significant difference between women and men.

Indexed as

COVID-19Government EmployeesAntibodies, ViralFemaleHumansImmunoglobulin GImmunoglobulin MIranMaleSARS-CoV-2Seroepidemiologic StudiesAntibodies, ViralImmunoglobulin GImmunoglobulin MELISAIgGIgMSARS-CoV-2Seroprevalence

Identifiers

PMID38590673
PMCPMC10998939

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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.