Evidence map›Paper›PMID 35711766›Full record

ArticleFrontiers in microbiology2022

High Level of SARS-CoV-2 Infection in Young Population Is a Predictor for Peak Incidence.

Haeyoun Choi, Sun Shin, Seung-Jin Hong, Sang-Uk Seo, Mun-Gan Rhyu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 50% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

5 authors at 1 institution in 1 country.

Haeyoun ChoiDepartment of Microbiology, College of Medicine, The Catholic University of Korea, Seoul, South Korea.
Sun ShinDepartment of Microbiology, College of Medicine, The Catholic University of Korea, Seoul, South Korea.
Seung-Jin HongDepartment of Microbiology, College of Medicine, The Catholic University of Korea, Seoul, South Korea.
Sang-Uk SeoDepartment of Microbiology, College of Medicine, The Catholic University of Korea, Seoul, South Korea.
Mun-Gan RhyuDepartment of Microbiology, College of Medicine, The Catholic University of Korea, Seoul, South Korea.
Catholic University of Korea · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

South Korea adopted stringent preventive measures against Coronavirus virus disease 2019, resulting in three small and one large outbreaks until January 15, 2022. The fatality rate was 2.5-fold higher during peak transmission periods than in base periods. As new variants of severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) are continuously emerging, the need for understanding their epidemic potential remains necessary. In South Korea, the epidemiologic data obtained from mass diagnostic testing enabled investigation of the true number of infected cases, exact incidence, and fatality numbers. Analysis found a similarity between estimated infection rates and confirmed cases. This suggested that the number of confirmed cases had an influence on the fatality rate as a quantitative parameter. The fatality rate decreased even as infection with SARS-CoV-2 variants rose. In comparative analysis, the confirmed cases in young people (ages 20-29) increased prior to every outbreak peak and marked the tipping point in infection spread. These results indicate that a high level of SARS-CoV-2 infection in young population drives peak incidence and mortality across all age groups.

Indexed as

age groupsCOVID-19epidemiologymorbiditySARS-CoV-2true infection

Identifiers

PMID35711766
PMCPMC9195141
OpenAlexW4281890963

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.