Evidence map›Paper›PMID 36579373›Full record

ReviewYonsei medical journal2023

Mathematical Modeling of COVID-19 Transmission and Intervention in South Korea: A Review of Literature.

Hyojung Lee, Sol Kim, Minyoung Jeong, Eunseo Choi, Hyeonjeong Ahn, Jeehyun Lee

Abstract readReview
In one paragraph

Review in Yonsei medical journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Human mobility and the infectious disease transmission: A systematic review.Geo-spatial information science = Diqui kongjian xinxi kexue xuebao · 2024
    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

6 authors.

Hyojung LeeDepartment of Statistics, Kyungpook National University, Daegu, Korea.ORCID https://orcid.org/0000-0001-9880-3044
Sol KimSchool of Mathematics and Computing (Mathematics), Yonsei University, Seoul, Korea.ORCID https://orcid.org/0000-0002-9934-4422
Minyoung JeongSchool of Mathematics and Computing (Mathematics), Yonsei University, Seoul, Korea.ORCID https://orcid.org/0000-0002-1922-5192
Eunseo ChoiDepartment of Statistics, Kyungpook National University, Daegu, Korea.ORCID https://orcid.org/0000-0003-1323-9582
Hyeonjeong AhnDepartment of Statistics, Kyungpook National University, Daegu, Korea.ORCID https://orcid.org/0000-0003-0184-0493
Jeehyun LeeSchool of Mathematics and Computing (Mathematics), Yonsei University, Seoul, Korea. ezhyun@yonsei.ac.kr.ORCID https://orcid.org/0000-0001-6143-2294

Funding

Goverment-wide R&D Fund for Infectious Disease Research HG20C0003Korea Disease Control and Prevention Agency 2022-03-008National Research Foundation of Korea NRF-2020R1A2C1A01010775National Research Foundation of Korea NRF-2022R1A2C3011711National Research Foundation of Korea NRF-2022R1A5A1033624
6 · The paper itself

Abstract

South Korea implemented interventions to curb the spread of the novel coronavirus disease 2019 (COVID-19) pandemic with discovery of the first case in early 2020. Mathematical modeling designed to reflect the dynamics of disease transmission has been shown to be an important tool for responding to COVID-19. This study aimed to review publications on the structure, method, and role of mathematical models focusing on COVID-19 transmission dynamics in Korea. In total, 42 papers published between August 7, 2020 and August 21, 2022 were studied and reviewed. This study highlights the construction and utilization of mathematical models to help craft strategies for predicting the course of an epidemic and evaluating the effectiveness of control strategies. Despite the limitations caused by a lack of available epidemiological and surveillance data, modeling studies could contribute to providing scientific evidence for policymaking by simulating various scenarios.

Indexed as

COVID-19HumansModels, TheoreticalPandemicsRepublic of KoreaSARS-CoV-2COVID-19interventionmathematical modelingSouth Koreatransmission dynamics

Identifiers

PMID36579373
PMCPMC9826955

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.