Application of a quantitative entry assessment model to compare the relative risk of incursion of zoonotic bat-borne viruses into European Union Member States.
Identifieur interne : 000D87 ( PubMed/Checkpoint ); précédent : 000D86; suivant : 000D88Application of a quantitative entry assessment model to compare the relative risk of incursion of zoonotic bat-borne viruses into European Union Member States.
Auteurs : Verity Horigan [Royaume-Uni] ; Paul Gale [Royaume-Uni] ; Rowena D. Kosmider [Royaume-Uni] ; Christopher Minnis [Royaume-Uni] ; Emma L. Snary [Royaume-Uni] ; Andrew C. Breed [Royaume-Uni] ; Robin R L. Simons [Royaume-Uni]Source :
- Microbial risk analysis [ 2352-3530 ] ; 2017.
Abstract
This paper presents a quantitative assessment model for the risk of entry of zoonotic bat-borne viruses into the European Union (EU). The model considers four routes of introduction: human travel, legal trade of products, live animal imports and illegal import of bushmeat and was applied to five virus outbreak scenarios. Two scenarios were considered for Zaire ebolavirus (wEBOV, cEBOV) and other scenarios for Hendra virus, Marburg virus (MARV) and Middle East Respiratory Syndrome Coronavirus (MERS-CoV). The use of the same framework and generic data sources for all EU Member States (MS) allows for a relative comparison of the probability of virus introduction and of the importance of the routes of introduction among MSs. According to the model wEBOV posed the highest risk of an introduction event within the EU, followed by MARV and MERS-CoV. However, the main route of introduction differed, with wEBOV and MERS-CoV most likely through human travel and MARV through legal trade of foodstuffs. The relative risks to EU MSs as entry points also varied between outbreak scenarios, highlighting the heterogeneity in global trade and travel to the EU MSs. The model has the capability to allow for a continual updating of the risk estimate using new data as, and when, it becomes available. The model provides an horizon scanning tool for use when available data are limited and, therefore, the absolute risk estimates often have high uncertainty. Sensitivity analysis suggested virus prevalence in bats has a large influence on the results; a 90% reduction in prevalence reduced the risk of introduction considerably and resulted in the relative ranking of MARV falling below that for MERS-CoV, due to this parameter disproportionately affecting the risk of introduction from the trade route over human travel.
DOI: 10.1016/j.mran.2017.09.002
PubMed: 32289058
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Kosmider</name><affiliation wicri:level="1"><nlm:affiliation>Animal and Plant Health Agency (APHA), Department of Epidemiological Sciences, New Haw, Addlestone, Surrey KT15 3NB, United Kingdom.</nlm:affiliation><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>Animal and Plant Health Agency (APHA), Department of Epidemiological Sciences, New Haw, Addlestone, Surrey KT15 3NB</wicri:regionArea><wicri:noRegion>Surrey KT15 3NB</wicri:noRegion></affiliation></author><author><name sortKey="Minnis, Christopher" sort="Minnis, Christopher" uniqKey="Minnis C" first="Christopher" last="Minnis">Christopher Minnis</name><affiliation wicri:level="1"><nlm:affiliation>The Royal Veterinary College, Royal College Street, London, England NW1 0TU, United Kingdom.</nlm:affiliation><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>The Royal Veterinary College, Royal College Street, London, England NW1 0TU</wicri:regionArea><wicri:noRegion>England NW1 0TU</wicri:noRegion></affiliation></author><author><name sortKey="Snary, Emma L" sort="Snary, Emma L" uniqKey="Snary E" first="Emma L" last="Snary">Emma L. Snary</name><affiliation wicri:level="1"><nlm:affiliation>Animal and Plant Health Agency (APHA), Department of Epidemiological Sciences, New Haw, Addlestone, Surrey KT15 3NB, United Kingdom.</nlm:affiliation><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>Animal and Plant Health Agency (APHA), Department of Epidemiological Sciences, New Haw, Addlestone, Surrey KT15 3NB</wicri:regionArea><wicri:noRegion>Surrey KT15 3NB</wicri:noRegion></affiliation></author><author><name sortKey="Breed, Andrew C" sort="Breed, Andrew C" uniqKey="Breed A" first="Andrew C" last="Breed">Andrew C. Breed</name><affiliation wicri:level="1"><nlm:affiliation>Animal and Plant Health Agency (APHA), Department of Epidemiological Sciences, New Haw, Addlestone, Surrey KT15 3NB, United Kingdom.</nlm:affiliation><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>Animal and Plant Health Agency (APHA), Department of Epidemiological Sciences, New Haw, Addlestone, Surrey KT15 3NB</wicri:regionArea><wicri:noRegion>Surrey KT15 3NB</wicri:noRegion></affiliation></author><author><name sortKey="Simons, Robin R L" sort="Simons, Robin R L" uniqKey="Simons R" first="Robin R L" last="Simons">Robin R L. Simons</name><affiliation wicri:level="1"><nlm:affiliation>Animal and Plant Health Agency (APHA), Department of Epidemiological Sciences, New Haw, Addlestone, Surrey KT15 3NB, United Kingdom.</nlm:affiliation><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>Animal and Plant Health Agency (APHA), Department of Epidemiological Sciences, New Haw, Addlestone, Surrey KT15 3NB</wicri:regionArea><wicri:noRegion>Surrey KT15 3NB</wicri:noRegion></affiliation></author></analytic><series><title level="j">Microbial risk analysis</title><idno type="eISSN">2352-3530</idno><imprint><date when="2017" type="published">2017</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">This paper presents a quantitative assessment model for the risk of entry of zoonotic bat-borne viruses into the European Union (EU). The model considers four routes of introduction: human travel, legal trade of products, live animal imports and illegal import of bushmeat and was applied to five virus outbreak scenarios. Two scenarios were considered for <i>Zaire ebolavirus</i> (wEBOV, cEBOV) and other scenarios for Hendra virus, Marburg virus (MARV) and Middle East Respiratory Syndrome Coronavirus (MERS-CoV). The use of the same framework and generic data sources for all EU Member States (MS) allows for a relative comparison of the probability of virus introduction and of the importance of the routes of introduction among MSs. According to the model wEBOV posed the highest risk of an introduction event within the EU, followed by MARV and MERS-CoV. However, the main route of introduction differed, with wEBOV and MERS-CoV most likely through human travel and MARV through legal trade of foodstuffs. The relative risks to EU MSs as entry points also varied between outbreak scenarios, highlighting the heterogeneity in global trade and travel to the EU MSs. The model has the capability to allow for a continual updating of the risk estimate using new data as, and when, it becomes available. The model provides an horizon scanning tool for use when available data are limited and, therefore, the absolute risk estimates often have high uncertainty. Sensitivity analysis suggested virus prevalence in bats has a large influence on the results; a 90% reduction in prevalence reduced the risk of introduction considerably and resulted in the relative ranking of MARV falling below that for MERS-CoV, due to this parameter disproportionately affecting the risk of introduction from the trade route over human travel.</div></front></TEI><pubmed><MedlineCitation Status="PubMed-not-MEDLINE" Owner="NLM"><PMID Version="1">32289058</PMID><DateRevised><Year>2020</Year><Month>04</Month><Day>17</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">2352-3530</ISSN><JournalIssue CitedMedium="Internet"><Volume>7</Volume><PubDate><Year>2017</Year><Month>Dec</Month></PubDate></JournalIssue><Title>Microbial risk analysis</Title><ISOAbbreviation>Microb Risk Anal</ISOAbbreviation></Journal><ArticleTitle>Application of a quantitative entry assessment model to compare the relative risk of incursion of zoonotic bat-borne viruses into European Union Member States.</ArticleTitle><Pagination><MedlinePgn>8-28</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1016/j.mran.2017.09.002</ELocationID><Abstract><AbstractText>This paper presents a quantitative assessment model for the risk of entry of zoonotic bat-borne viruses into the European Union (EU). The model considers four routes of introduction: human travel, legal trade of products, live animal imports and illegal import of bushmeat and was applied to five virus outbreak scenarios. Two scenarios were considered for <i>Zaire ebolavirus</i> (wEBOV, cEBOV) and other scenarios for Hendra virus, Marburg virus (MARV) and Middle East Respiratory Syndrome Coronavirus (MERS-CoV). The use of the same framework and generic data sources for all EU Member States (MS) allows for a relative comparison of the probability of virus introduction and of the importance of the routes of introduction among MSs. According to the model wEBOV posed the highest risk of an introduction event within the EU, followed by MARV and MERS-CoV. However, the main route of introduction differed, with wEBOV and MERS-CoV most likely through human travel and MARV through legal trade of foodstuffs. The relative risks to EU MSs as entry points also varied between outbreak scenarios, highlighting the heterogeneity in global trade and travel to the EU MSs. The model has the capability to allow for a continual updating of the risk estimate using new data as, and when, it becomes available. The model provides an horizon scanning tool for use when available data are limited and, therefore, the absolute risk estimates often have high uncertainty. Sensitivity analysis suggested virus prevalence in bats has a large influence on the results; a 90% reduction in prevalence reduced the risk of introduction considerably and resulted in the relative ranking of MARV falling below that for MERS-CoV, due to this parameter disproportionately affecting the risk of introduction from the trade route over human travel.</AbstractText><CopyrightInformation>Crown Copyright © 2017 Published by Elsevier B.V. All rights reserved.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Horigan</LastName><ForeName>Verity</ForeName><Initials>V</Initials><AffiliationInfo><Affiliation>Animal and Plant Health Agency (APHA), Department of Epidemiological Sciences, New Haw, Addlestone, Surrey KT15 3NB, United Kingdom.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Gale</LastName><ForeName>Paul</ForeName><Initials>P</Initials><AffiliationInfo><Affiliation>Animal and Plant Health Agency (APHA), Department of Epidemiological Sciences, New Haw, Addlestone, Surrey KT15 3NB, United Kingdom.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Kosmider</LastName><ForeName>Rowena D</ForeName><Initials>RD</Initials><AffiliationInfo><Affiliation>Animal and Plant Health Agency (APHA), Department of Epidemiological Sciences, New Haw, Addlestone, Surrey KT15 3NB, United Kingdom.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Minnis</LastName><ForeName>Christopher</ForeName><Initials>C</Initials><AffiliationInfo><Affiliation>The Royal Veterinary College, Royal College Street, London, England NW1 0TU, United Kingdom.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Snary</LastName><ForeName>Emma L</ForeName><Initials>EL</Initials><AffiliationInfo><Affiliation>Animal and Plant Health Agency (APHA), Department of Epidemiological Sciences, New Haw, Addlestone, Surrey KT15 3NB, United Kingdom.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Breed</LastName><ForeName>Andrew C</ForeName><Initials>AC</Initials><AffiliationInfo><Affiliation>Animal and Plant Health Agency (APHA), Department of Epidemiological Sciences, New Haw, Addlestone, Surrey KT15 3NB, United Kingdom.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Simons</LastName><ForeName>Robin R L</ForeName><Initials>RRL</Initials><AffiliationInfo><Affiliation>Animal and Plant Health Agency (APHA), Department of Epidemiological Sciences, New Haw, Addlestone, Surrey KT15 3NB, United Kingdom.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2017</Year><Month>10</Month><Day>02</Day></ArticleDate></Article><MedlineJournalInfo><Country>Netherlands</Country><MedlineTA>Microb Risk Anal</MedlineTA><NlmUniqueID>101728821</NlmUniqueID><ISSNLinking>2352-3522</ISSNLinking></MedlineJournalInfo></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2017</Year><Month>05</Month><Day>24</Day></PubMedPubDate><PubMedPubDate PubStatus="revised"><Year>2017</Year><Month>09</Month><Day>29</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2017</Year><Month>09</Month><Day>29</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>4</Month><Day>15</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2017</Year><Month>12</Month><Day>1</Day><Hour>0</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2017</Year><Month>12</Month><Day>1</Day><Hour>0</Hour><Minute>1</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">32289058</ArticleId><ArticleId IdType="doi">10.1016/j.mran.2017.09.002</ArticleId><ArticleId IdType="pii">S2352-3522(17)30140-8</ArticleId><ArticleId IdType="pmc">PMC7103962</ArticleId></ArticleIdList><pmc-dir>pmcsd</pmc-dir>
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