Risk assessment of airborne infectious diseases in aircraft cabins.
Identifieur interne : 002455 ( Ncbi/Merge ); précédent : 002454; suivant : 002456Risk assessment of airborne infectious diseases in aircraft cabins.
Auteurs : Jitendra K. Gupta [États-Unis] ; Chao-Hsin Lin ; Qingyan ChenSource :
- Indoor air [ 1600-0668 ] ; 2012.
Descripteurs français
- KwdFr :
- MESH :
English descriptors
- KwdEn :
- MESH :
- transmission : Communicable Diseases.
- Air Microbiology, Air Movements, Aircraft, Computer Simulation, Humans, Hydrodynamics, Risk Assessment.
Abstract
Passengers in an aircraft cabin can have different risks of infection from airborne infectious diseases such as influenza, severe acute respiratory syndrome (SARS), and tuberculosis (TB) because of the non-uniform airflow in an aircraft cabin. The current investigation presents a comprehensive approach to assessing the spatial and temporal distributions of airborne infection risk in an aircraft cabin. A case of influenza outbreak was evaluated in a 4-h flight in a twin-aisle, fully occupied aircraft cabin with the index passenger seated at the center of the cabin. The approach considered the characteristics of the exhalation of the droplets carrying infectious agents from the index passenger, the dispersion of these droplets, and the inhalation of the droplets by susceptible passengers. Deterministic and probabilistic approaches were used to quantify the risks based on the amount of inhaled influenza virus RNA particles and quanta, respectively. The probabilistic approach indicated that the number of secondary infection cases can be reduced from 3 to 0 and 20 to 11, for influenza cases if N95 respirator masks are used by the passengers. The approach and methods developed can easily be implemented in other enclosed spaces such as buildings, trains, and buses to assess the infection risk.
DOI: 10.1111/j.1600-0668.2012.00773.x
PubMed: 22313168
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Gupta</name><affiliation wicri:level="2"><nlm:affiliation>National Air Transportation Center of Excellence for Research in the Intermodal Transport Environment-RITE, School of Mechanical Engineering, Purdue University, West Lafayette, IN, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>National Air Transportation Center of Excellence for Research in the Intermodal Transport Environment-RITE, School of Mechanical Engineering, Purdue University, West Lafayette, IN</wicri:regionArea><placeName><region type="state">Indiana</region></placeName></affiliation></author><author><name sortKey="Lin, Chao Hsin" sort="Lin, Chao Hsin" uniqKey="Lin C" first="Chao-Hsin" last="Lin">Chao-Hsin Lin</name></author><author><name sortKey="Chen, Qingyan" sort="Chen, Qingyan" uniqKey="Chen Q" first="Qingyan" last="Chen">Qingyan Chen</name></author></analytic><series><title level="j">Indoor air</title><idno type="eISSN">1600-0668</idno><imprint><date when="2012" type="published">2012</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Air Microbiology</term><term>Air Movements</term><term>Aircraft</term><term>Communicable Diseases (transmission)</term><term>Computer Simulation</term><term>Humans</term><term>Hydrodynamics</term><term>Risk Assessment</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Humains</term><term>Hydrodynamique</term><term>Maladies transmissibles (transmission)</term><term>Microbiologie de l'air</term><term>Mouvements de l'air</term><term>Simulation numérique</term><term>Véhicules de transport aérien</term><term>Évaluation des risques</term></keywords><keywords scheme="MESH" qualifier="transmission" xml:lang="en"><term>Communicable Diseases</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Air Microbiology</term><term>Air Movements</term><term>Aircraft</term><term>Computer Simulation</term><term>Humans</term><term>Hydrodynamics</term><term>Risk Assessment</term></keywords><keywords scheme="MESH" qualifier="transmission" xml:lang="fr"><term>Humains</term><term>Hydrodynamique</term><term>Maladies transmissibles</term><term>Microbiologie de l'air</term><term>Mouvements de l'air</term><term>Simulation numérique</term><term>Véhicules de transport aérien</term><term>Évaluation des risques</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Passengers in an aircraft cabin can have different risks of infection from airborne infectious diseases such as influenza, severe acute respiratory syndrome (SARS), and tuberculosis (TB) because of the non-uniform airflow in an aircraft cabin. The current investigation presents a comprehensive approach to assessing the spatial and temporal distributions of airborne infection risk in an aircraft cabin. A case of influenza outbreak was evaluated in a 4-h flight in a twin-aisle, fully occupied aircraft cabin with the index passenger seated at the center of the cabin. The approach considered the characteristics of the exhalation of the droplets carrying infectious agents from the index passenger, the dispersion of these droplets, and the inhalation of the droplets by susceptible passengers. Deterministic and probabilistic approaches were used to quantify the risks based on the amount of inhaled influenza virus RNA particles and quanta, respectively. The probabilistic approach indicated that the number of secondary infection cases can be reduced from 3 to 0 and 20 to 11, for influenza cases if N95 respirator masks are used by the passengers. The approach and methods developed can easily be implemented in other enclosed spaces such as buildings, trains, and buses to assess the infection risk.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">22313168</PMID><DateCompleted><Year>2013</Year><Month>02</Month><Day>07</Day></DateCompleted><DateRevised><Year>2013</Year><Month>05</Month><Day>20</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1600-0668</ISSN><JournalIssue CitedMedium="Internet"><Volume>22</Volume><Issue>5</Issue><PubDate><Year>2012</Year><Month>Oct</Month></PubDate></JournalIssue><Title>Indoor air</Title><ISOAbbreviation>Indoor Air</ISOAbbreviation></Journal><ArticleTitle>Risk assessment of airborne infectious diseases in aircraft cabins.</ArticleTitle><Pagination><MedlinePgn>388-95</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1111/j.1600-0668.2012.00773.x</ELocationID><Abstract><AbstractText Label="UNLABELLED">Passengers in an aircraft cabin can have different risks of infection from airborne infectious diseases such as influenza, severe acute respiratory syndrome (SARS), and tuberculosis (TB) because of the non-uniform airflow in an aircraft cabin. The current investigation presents a comprehensive approach to assessing the spatial and temporal distributions of airborne infection risk in an aircraft cabin. A case of influenza outbreak was evaluated in a 4-h flight in a twin-aisle, fully occupied aircraft cabin with the index passenger seated at the center of the cabin. The approach considered the characteristics of the exhalation of the droplets carrying infectious agents from the index passenger, the dispersion of these droplets, and the inhalation of the droplets by susceptible passengers. Deterministic and probabilistic approaches were used to quantify the risks based on the amount of inhaled influenza virus RNA particles and quanta, respectively. The probabilistic approach indicated that the number of secondary infection cases can be reduced from 3 to 0 and 20 to 11, for influenza cases if N95 respirator masks are used by the passengers. The approach and methods developed can easily be implemented in other enclosed spaces such as buildings, trains, and buses to assess the infection risk.</AbstractText><AbstractText Label="PRACTICAL IMPLICATIONS" NlmCategory="CONCLUSIONS">Airborne infectious disease transmission could take place in enclosed environments such as buildings and transport vehicles. The infection risk is difficult to estimate, and very few mitigation methods are available. This study used a 4-h flight as an example in analyzing the infection risk from influenza and in mitigating the risk with an N95 mask. The results will be useful to the airline industry in providing necessary protection to passengers and crew, and the results can also be used for other enclosed spaces.</AbstractText><CopyrightInformation>© 2012 John Wiley & Sons A/S.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Gupta</LastName><ForeName>Jitendra K</ForeName><Initials>JK</Initials><AffiliationInfo><Affiliation>National Air Transportation Center of Excellence for Research in the Intermodal Transport Environment-RITE, School of Mechanical Engineering, Purdue University, West Lafayette, IN, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Lin</LastName><ForeName>Chao-Hsin</ForeName><Initials>CH</Initials></Author><Author ValidYN="Y"><LastName>Chen</LastName><ForeName>Qingyan</ForeName><Initials>Q</Initials></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2012</Year><Month>03</Month><Day>10</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>Indoor Air</MedlineTA><NlmUniqueID>9423515</NlmUniqueID><ISSNLinking>0905-6947</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000391" MajorTopicYN="Y">Air Microbiology</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000392" MajorTopicYN="Y">Air Movements</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000401" MajorTopicYN="Y">Aircraft</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D003141" MajorTopicYN="N">Communicable Diseases</DescriptorName><QualifierName UI="Q000635" MajorTopicYN="Y">transmission</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D003198" MajorTopicYN="N">Computer Simulation</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D057446" MajorTopicYN="N">Hydrodynamics</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D018570" MajorTopicYN="N">Risk Assessment</DescriptorName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="entrez"><Year>2012</Year><Month>2</Month><Day>9</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2012</Year><Month>2</Month><Day>9</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2013</Year><Month>2</Month><Day>8</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">22313168</ArticleId><ArticleId IdType="doi">10.1111/j.1600-0668.2012.00773.x</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>États-Unis</li></country><region><li>Indiana</li></region></list><tree><noCountry><name sortKey="Chen, Qingyan" sort="Chen, Qingyan" uniqKey="Chen Q" first="Qingyan" last="Chen">Qingyan Chen</name><name sortKey="Lin, Chao Hsin" sort="Lin, Chao Hsin" uniqKey="Lin C" first="Chao-Hsin" last="Lin">Chao-Hsin Lin</name></noCountry><country name="États-Unis"><region name="Indiana"><name sortKey="Gupta, Jitendra K" sort="Gupta, Jitendra K" uniqKey="Gupta J" first="Jitendra K" last="Gupta">Jitendra K. 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