Evidence map›Paper›PMID 32170774›Full record

ArticleRisk analysis : an official publication of the Society for Risk Analysis2020

Application of a Risk Analysis Tool to Middle East Respiratory Syndrome Coronavirus (MERS-CoV) Outbreak in Saudi Arabia.

Xin Chen, Abrar A Chughtai, Chandini R MacIntyre

Abstract read
In one paragraph

Article in Risk analysis : an official publication of the Society for Risk Analysis, 2020. 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. Article
  4. The COVID-19 pandemic: Virus transmission and risk assessment.Current opinion in environmental science & health · 2022
    Review
  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.

Xin ChenBiosecurity Program, Kirby Institute, Faculty of Medicine, University of New South Wales, Sydney, NSW, 2052, Australia.ORCID 0000-0002-9905-2307
Abrar A ChughtaiSchool of Public Health and Community Medicine, Faculty of Medicine, University of New South Wales, Sydney, NSW, 2052, Australia.ORCID 0000-0003-4203-7891
Chandini R MacIntyreBiosecurity Program, Kirby Institute, Faculty of Medicine, University of New South Wales, Sydney, NSW, 2052, Australia.ORCID 0000-0002-3060-0555

Funding

National Health and Medical Research Council APP1107393
6 · The paper itself

Abstract

The Grunow-Finke assessment tool (GFT) is an accepted scoring system for determining likelihood of an outbreak being unnatural in origin. Considering its high specificity but low sensitivity, a modified Grunow-Finke tool (mGFT) has been developed with improved sensitivity. The mGFT has been validated against some past disease outbreaks, but it has not been applied to ongoing outbreaks. This study is aimed to score the outbreak of Middle East respiratory syndrome coronavirus (MERS-CoV) in Saudi Arabia using both the original GFT and mGFT. The publicly available data on human cases of MERS-CoV infections reported in Saudi Arabia (2012-2018) were sourced from the FluTrackers, World Health Organization, Saudi Ministry of Health, and published literature associated with MERS outbreaks investigations. The risk assessment of MERS-CoV in Saudi Arabia was analyzed using the original GFT and mGFT criteria, algorithms, and thresholds. The scoring points for each criterion were determined by three researchers to minimize the subjectivity. The results showed 40 points of total possible 54 points using the original GFT (likelihood: 74%), and 40 points of a total possible 60 points (likelihood: 67%) using the mGFT, both tools indicating a high likelihood that human MERS-CoV in Saudi Arabia is unnatural in origin. The findings simply flag unusual patterns in this outbreak, but do not prove unnatural etiology. Proof of bioattacks can only be obtained by law enforcement and intelligence agencies. This study demonstrated the value and flexibility of the mGFT in assessing and predicting the risk for an ongoing outbreak with simple criteria.

Indexed as

Disease OutbreaksMiddle East Respiratory Syndrome CoronavirusAdolescentAdultAgedAged, 80 and overAlgorithmsBioterrorismChildChild, PreschoolCoronavirus InfectionsData CollectionFemaleHumansInfantInfant, NewbornAlgorithmbioterrorismMERS-CoVoutbreak investigationrisk analysisscoring systemunnatural epidemic

Identifiers

PMID32170774
PMCPMC7228232

What OpenQuestion holds

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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.