Evidence map›Paper›PMID 28703921›Full record

ArticleInfluenza and other respiratory viruses2017

Estimating and modelling the transmissibility of Middle East Respiratory Syndrome CoronaVirus during the 2015 outbreak in the Republic of Korea.

Xu-Sheng Zhang, Richard Pebody, Andre Charlett, Daniela de Angelis, Paul Birrell, Hunseok Kang, Marc Baguelin, Yoon Hong Choi

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Influenza and other respiratory viruses, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 4 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

20 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
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  5. Article
  6. Global Analysis and Optimal Control Model of COVID-19.Computational and mathematical methods in medicine · 2022
    Article
  7. Article
  8. Review
  9. How can process safety and a risk management approach guide pandemic risk management?Journal of loss prevention in the process industries · 2020
    Article
  10. Exploration of Superspreading Events in 2015 MERS-CoV Outbreak in Korea by Branching Process Models.International journal of environmental research and public health · 2020
    Article
  11. [Quarantine Alone or in Combination with Other Public Health Measures to Control COVID-19: A Rapid Review (Review)].Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany)) · 2020
    Review
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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

8 authors.

Xu-Sheng ZhangNational Infection Service, Centre for Infectious Disease Surveillance and Control, Public Health England, London, UK.ORCID 0000-0002-6596-4500
Richard PebodyNational Infection Service, Centre for Infectious Disease Surveillance and Control, Public Health England, London, UK.
Andre CharlettNational Infection Service, Centre for Infectious Disease Surveillance and Control, Public Health England, London, UK.
Daniela de AngelisNational Infection Service, Centre for Infectious Disease Surveillance and Control, Public Health England, London, UK.
Paul BirrellMedical Research Council Biostatistics Unit, University of Cambridge, Cambridge, UK.
Hunseok KangResearch Centre for Nonlinear Ergodic Theory, Sungkyunkwan University, Suwon, Korea.
Marc BaguelinNational Infection Service, Centre for Infectious Disease Surveillance and Control, Public Health England, London, UK.
Yoon Hong ChoiNational Infection Service, Centre for Infectious Disease Surveillance and Control, Public Health England, London, UK.

Funding

Department of Health 11/46/03Medical Research Council MC_U105260556Medical Research Council MC_UU_00002/11
6 · The paper itself

Abstract

backgroundEmerging respiratory infections represent a significant public health threat. Because of their novelty, there are limited measures available to control their early spread. Learning from past outbreaks is important for future preparation. The Middle Eastern Respiratory Syndrome CoronaVirus (MERS-CoV ) 2015 outbreak in the Republic of Korea (ROK) provides one such opportunity.

objectivesWe demonstrated through quantitative methodologies how to estimate MERS-CoV's transmissibility and identified the effective countermeasures that stopped its spread.

methodsUsing the outbreak data, statistical methods were employed to estimate the basic reproductive number R

resultsR

conclusionsOur estimates were in agreement with others from the ROK outbreak, albeit significantly higher than estimates based on other small outbreaks and sporadic cases of MERS-CoV. The large-scale outbreak in the ROK was jointly due to the high transmissibility in the healthcare-associated setting and the Korean culture-associated contact behaviour. Limiting such behaviour by rapidly identifying and isolating cases and avoiding high-risk contacts effectively stopped further transmission.

Indexed as

Disease OutbreaksModels, StatisticalBayes TheoremCoronavirus InfectionsCross InfectionHospitalizationHumansMiddle East Respiratory Syndrome CoronavirusRepublic of Koreamathematical modellingMiddle Eastern Respiratory Syndrome CoronaVirusparameter estimationSouth Korean outbreakstatistical analysistransmissibility

Identifiers

PMID28703921
PMCPMC5598245

What OpenQuestion holds

Textmetadata
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.