Evidence map›Paper›PMID 34066512›Full record

ArticleInternational journal of environmental research and public health2021

Estimation of Undetected Asymptomatic COVID-19 Cases in South Korea Using a Probabilistic Model.

Chanhee Lee, Catherine Apio, Taesung Park

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Role of Asymptomatic COVID-19 Cases in Viral Transmission: Findings From a Hierarchical Community Contact Network Model.IEEE transactions on automation science and engineering : a publication of the IEEE Robotics and Automation Society · 2022
    Article
  5. 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

3 authors.

Chanhee LeeInterdisciplinary Program in Bioinformatics, Seoul National University, Seoul 08826, Korea.ORCID 0000-0001-9643-7159
Catherine ApioInterdisciplinary Program in Bioinformatics, Seoul National University, Seoul 08826, Korea.ORCID 0000-0003-0240-794X
Taesung ParkInterdisciplinary Program in Bioinformatics, Seoul National University, Seoul 08826, Korea.ORCID 0000-0002-8294-590X

Funding

Science and Technology Policy Institute of Korea 0409-20200222
6 · The paper itself

Abstract

Increasing evidence shows that many infections of COVID-19 are asymptomatic, becoming a global challenge, since asymptomatic infections have the same infectivity as symptomatic infections. We developed a probabilistic model for estimating the proportion of undetected asymptomatic COVID-19 patients in the country. We considered two scenarios: one is conservative and the other is nonconservative. By combining the above two scenarios, we gave an interval estimation of 0.0001-0.0027 and in terms of the population, 5200-139,900 is the number of undetected asymptomatic cases in South Korea as of 2 February 2021. In addition, we provide estimates for total cases of COVID-19 in South Korea. Combination of undetected asymptomatic cases and undetected symptomatic cases to the number of confirmed cases (78,844 cases on 2 February 2021) shows that 0.17-0.42% (89,244-218,744) of the population have COVID-19. In conclusion, to control and understand the true ongoing reality of the pandemic, it is of outermost importance to focus on the ratio of undetected asymptomatic cases in the total population.

Indexed as

COVID-19Asymptomatic InfectionsHumansModels, StatisticalPandemicsRepublic of KoreaSARS-CoV-2asymptomaticCOVID-19probabilistic modelSARS-CoV-2screeningundetected

Identifiers

PMID34066512
PMCPMC8124955

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.