Evidence map›Paper›PMID 33104736›Full record

ArticlePloS one2020

A mathematical model of COVID-19 transmission in a tertiary hospital and assessment of the effects of different intervention strategies.

Yae Jee Baek, Taeyong Lee, Yunsuk Cho, Jong Hoon Hyun, Moo Hyun Kim, Yujin Sohn, Jung Ho Kim, Jin Young Ahn, Su Jin Jeong, Nam Su Ku and 3 more

Erratum issuedAbstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Analysis of HBV and COVID-19 Coinfection Model with Intervention Strategies.Computational and mathematical methods in medicine · 2023
    Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Yae Jee BaekDepartment of Internal Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
Taeyong LeeDepartment of Mathematics, Yonsei University, Seoul, Republic of Korea.ORCID 0000-0002-1940-0210
Yunsuk ChoDepartment of Internal Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
Jong Hoon HyunDepartment of Internal Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
Moo Hyun KimDepartment of Internal Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
Yujin SohnDepartment of Internal Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
Jung Ho KimDepartment of Internal Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
Jin Young AhnDepartment of Internal Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
Su Jin JeongDepartment of Internal Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
Nam Su KuDepartment of Internal Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.ORCID 0000-0002-9717-4327
Joon-Sup YeomDepartment of Internal Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.ORCID 0000-0001-8940-7170
Jeehyun LeeDepartment of Mathematics, Yonsei University, Seoul, Republic of Korea.
Jun Yong ChoiDepartment of Internal Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.ORCID 0000-0002-2775-3315

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Novel coronavirus (named SARS-CoV-2) can spread widely in confined settings including hospitals, cruise ships, prisons, and places of worship. In particular, a healthcare-associated outbreak could become the epicenter of coronavirus disease (COVID-19). This study aimed to evaluate the effects of different intervention strategies on the hospital outbreak within a tertiary hospital. A mathematical model was developed for the COVID-19 transmission within a 2500-bed tertiary hospital of South Korea. The SEIR (susceptible-exposed-infectious-recovered) model with a compartment of doctor, nurse, patient, and caregiver was constructed. The effects of different intervention strategies such as front door screening, quarantine unit for newly admitted patients, early testing of suspected infected people, and personal protective equipment for both medical staff and visitors were evaluated. The model suggested that the early testing (within eight hours) of infected cases and monitoring the quarantine ward for newly hospitalized patients are effective measures for decreasing the incidence of COVID-19 within a hospital (81.3% and 70% decrease of number of incident cases, respectively, during 60 days). Front door screening for detecting suspected cases had only 42% effectiveness. Screening for prohibiting the admission of COVID-19 patients was more effective than the measures for patients before emergency room or outpatient clinic. This model suggests that under the assumed conditions, some effective measures have a great influence on the incidence of COVID-19 within a hospital. The implementation of the preventive measures could reduce the size of a hospital outbreak.

Indexed as

BetacoronavirusModels, TheoreticalPandemicsTertiary Care CentersCaregiversClinical Laboratory TechniquesCoronavirus InfectionsCOVID-19COVID-19 TestingCross InfectionEarly DiagnosisEmergency Service, HospitalHospital DepartmentsHumansIncidenceInfection Control

Identifiers

PMID33104736
PMCPMC7588052

What OpenQuestion holds

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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.