Application of a Risk Analysis Tool to Middle East Respiratory Syndrome Coronavirus (MERS-CoV) Outbreak in Saudi Arabia.
Identifieur interne : 000162 ( PubMed/Curation ); précédent : 000161; suivant : 000163Application of a Risk Analysis Tool to Middle East Respiratory Syndrome Coronavirus (MERS-CoV) Outbreak in Saudi Arabia.
Auteurs : Xin Chen [Australie] ; Abrar A. Chughtai [Australie] ; Chandini R. Macintyre [Australie]Source :
- Risk analysis : an official publication of the Society for Risk Analysis [ 1539-6924 ] ; 2020.
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.
DOI: 10.1111/risa.13472
PubMed: 32170774
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Chughtai</name><affiliation wicri:level="1"><nlm:affiliation>School of Public Health and Community Medicine, Faculty of Medicine, University of New South Wales, Sydney, NSW, 2052, Australia.</nlm:affiliation><country xml:lang="fr">Australie</country><wicri:regionArea>School of Public Health and Community Medicine, Faculty of Medicine, University of New South Wales, Sydney, NSW, 2052</wicri:regionArea></affiliation></author><author><name sortKey="Macintyre, Chandini R" sort="Macintyre, Chandini R" uniqKey="Macintyre C" first="Chandini R" last="Macintyre">Chandini R. Macintyre</name><affiliation wicri:level="1"><nlm:affiliation>Biosecurity Program, Kirby Institute, Faculty of Medicine, University of New South Wales, Sydney, NSW, 2052, Australia.</nlm:affiliation><country xml:lang="fr">Australie</country><wicri:regionArea>Biosecurity Program, Kirby Institute, Faculty of Medicine, University of New South Wales, Sydney, NSW, 2052</wicri:regionArea></affiliation></author></analytic><series><title level="j">Risk analysis : an official publication of the Society for Risk Analysis</title><idno type="eISSN">1539-6924</idno><imprint><date when="2020" type="published">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">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.</div></front></TEI><pubmed><MedlineCitation Status="Publisher" Owner="NLM"><PMID Version="1">32170774</PMID><DateRevised><Year>2020</Year><Month>03</Month><Day>14</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1539-6924</ISSN><JournalIssue CitedMedium="Internet"><PubDate><Year>2020</Year><Month>Mar</Month><Day>13</Day></PubDate></JournalIssue><Title>Risk analysis : an official publication of the Society for Risk Analysis</Title><ISOAbbreviation>Risk Anal.</ISOAbbreviation></Journal><ArticleTitle>Application of a Risk Analysis Tool to Middle East Respiratory Syndrome Coronavirus (MERS-CoV) Outbreak in Saudi Arabia.</ArticleTitle><ELocationID EIdType="doi" ValidYN="Y">10.1111/risa.13472</ELocationID><Abstract><AbstractText>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.</AbstractText><CopyrightInformation>© 2020 Society for Risk Analysis.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Chen</LastName><ForeName>Xin</ForeName><Initials>X</Initials><Identifier Source="ORCID">https://orcid.org/0000-0002-9905-2307</Identifier><AffiliationInfo><Affiliation>Biosecurity Program, Kirby Institute, Faculty of Medicine, University of New South Wales, Sydney, NSW, 2052, Australia.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Chughtai</LastName><ForeName>Abrar A</ForeName><Initials>AA</Initials><Identifier Source="ORCID">https://orcid.org/0000-0003-4203-7891</Identifier><AffiliationInfo><Affiliation>School of Public Health and Community Medicine, Faculty of Medicine, University of New South Wales, Sydney, NSW, 2052, Australia.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>MacIntyre</LastName><ForeName>Chandini R</ForeName><Initials>CR</Initials><Identifier Source="ORCID">https://orcid.org/0000-0002-3060-0555</Identifier><AffiliationInfo><Affiliation>Biosecurity Program, Kirby Institute, Faculty of Medicine, University of New South Wales, Sydney, NSW, 2052, Australia.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>College of Public Service and Community Solutions, Arizona State University, Tempe, AZ, USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>College of Health Solutions, Arizona State University, Tempe, AZ, USA.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><GrantList CompleteYN="Y"><Grant><GrantID>APP1107393</GrantID><Agency>National Health and Medical Research Council</Agency><Country></Country></Grant></GrantList><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>03</Month><Day>13</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>Risk Anal</MedlineTA><NlmUniqueID>8109978</NlmUniqueID><ISSNLinking>0272-4332</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Algorithm</Keyword><Keyword MajorTopicYN="N">MERS-CoV</Keyword><Keyword MajorTopicYN="N">bioterrorism</Keyword><Keyword MajorTopicYN="N">outbreak investigation</Keyword><Keyword MajorTopicYN="N">risk analysis</Keyword><Keyword MajorTopicYN="N">scoring system</Keyword><Keyword MajorTopicYN="N">unnatural epidemic</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2019</Year><Month>07</Month><Day>02</Day></PubMedPubDate><PubMedPubDate PubStatus="revised"><Year>2020</Year><Month>02</Month><Day>20</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2020</Year><Month>02</Month><Day>26</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>3</Month><Day>15</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2020</Year><Month>3</Month><Day>15</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2020</Year><Month>3</Month><Day>15</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>aheadofprint</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">32170774</ArticleId><ArticleId IdType="doi">10.1111/risa.13472</ArticleId></ArticleIdList><ReferenceList><Title>REFERERNCES</Title><Reference><Citation>Ajisegiri, W. 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