Value of inventory information in allocating a limited supply of influenza vaccine during a pandemic.
Identifieur interne : 000205 ( PubMed/Checkpoint ); précédent : 000204; suivant : 000206Value of inventory information in allocating a limited supply of influenza vaccine during a pandemic.
Auteurs : Zihao Li [États-Unis] ; Julie L. Swann [États-Unis] ; Pinar Keskinocak [États-Unis]Source :
- PloS one [ 1932-6203 ] ; 2018.
Descripteurs français
- KwdFr :
- MESH :
- immunologie : Grippe humaine.
- ressources et distribution : Vaccins antigrippaux.
- épidémiologie : Grippe humaine.
- Diffusion de l'information, Grippe humaine, Humains, Pandémies, Programmes de vaccination, Simulation numérique, États-Unis d'Amérique.
- Wicri :
- geographic : États-Unis.
English descriptors
- KwdEn :
- MESH :
- chemical , supply & distribution : Influenza Vaccines.
- geographic : United States.
- epidemiology : Influenza, Human.
- immunology : Influenza, Human.
- prevention & control : Influenza, Human, Pandemics.
- Computer Simulation, Humans, Immunization Programs, Information Dissemination.
Abstract
To understand the value of information on vaccine inventory levels during an influenza pandemic, we propose a simulation study to compare vaccine allocation strategies using: (i) only population information (pro-rata, or population-based, PB), (ii) both population and vaccine inventory information (population and inventory-based, PIB).
DOI: 10.1371/journal.pone.0206293
PubMed: 30359445
Affiliations:
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Swann</name><affiliation wicri:level="2"><nlm:affiliation>Department of Industrial and Systems Engineering, North Carolina State University, Raleigh, North Carolina, United States of America.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Industrial and Systems Engineering, North Carolina State University, Raleigh, North Carolina</wicri:regionArea><placeName><region type="state">Caroline du Nord</region></placeName></affiliation></author><author><name sortKey="Keskinocak, Pinar" sort="Keskinocak, Pinar" uniqKey="Keskinocak P" first="Pinar" last="Keskinocak">Pinar Keskinocak</name><affiliation wicri:level="2"><nlm:affiliation>School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia</wicri:regionArea><placeName><region type="state">Géorgie (États-Unis)</region></placeName></affiliation></author></analytic><series><title level="j">PloS one</title><idno type="eISSN">1932-6203</idno><imprint><date when="2018" type="published">2018</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Computer Simulation</term><term>Humans</term><term>Immunization Programs</term><term>Influenza Vaccines (supply & distribution)</term><term>Influenza, Human (epidemiology)</term><term>Influenza, Human (immunology)</term><term>Influenza, Human (prevention & control)</term><term>Information Dissemination</term><term>Pandemics (prevention & control)</term><term>United States</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Diffusion de l'information</term><term>Grippe humaine ()</term><term>Grippe humaine (immunologie)</term><term>Grippe humaine (épidémiologie)</term><term>Humains</term><term>Pandémies ()</term><term>Programmes de vaccination</term><term>Simulation numérique</term><term>Vaccins antigrippaux (ressources et distribution)</term><term>États-Unis d'Amérique</term></keywords><keywords scheme="MESH" type="chemical" qualifier="supply & distribution" xml:lang="en"><term>Influenza Vaccines</term></keywords><keywords scheme="MESH" type="geographic" xml:lang="en"><term>United States</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="immunologie" xml:lang="fr"><term>Grippe humaine</term></keywords><keywords scheme="MESH" qualifier="immunology" xml:lang="en"><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="prevention & control" xml:lang="en"><term>Influenza, Human</term><term>Pandemics</term></keywords><keywords scheme="MESH" qualifier="ressources et distribution" xml:lang="fr"><term>Vaccins antigrippaux</term></keywords><keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Grippe humaine</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Computer Simulation</term><term>Humans</term><term>Immunization Programs</term><term>Information Dissemination</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Diffusion de l'information</term><term>Grippe humaine</term><term>Humains</term><term>Pandémies</term><term>Programmes de vaccination</term><term>Simulation numérique</term><term>États-Unis d'Amérique</term></keywords><keywords scheme="Wicri" type="geographic" xml:lang="fr"><term>États-Unis</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">To understand the value of information on vaccine inventory levels during an influenza pandemic, we propose a simulation study to compare vaccine allocation strategies using: (i) only population information (pro-rata, or population-based, PB), (ii) both population and vaccine inventory information (population and inventory-based, PIB).</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">30359445</PMID><DateCompleted><Year>2019</Year><Month>04</Month><Day>10</Day></DateCompleted><DateRevised><Year>2019</Year><Month>04</Month><Day>10</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Electronic">1932-6203</ISSN><JournalIssue CitedMedium="Internet"><Volume>13</Volume><Issue>10</Issue><PubDate><Year>2018</Year></PubDate></JournalIssue><Title>PloS one</Title><ISOAbbreviation>PLoS ONE</ISOAbbreviation></Journal><ArticleTitle>Value of inventory information in allocating a limited supply of influenza vaccine during a pandemic.</ArticleTitle><Pagination><MedlinePgn>e0206293</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1371/journal.pone.0206293</ELocationID><Abstract><AbstractText Label="OBJECTIVE">To understand the value of information on vaccine inventory levels during an influenza pandemic, we propose a simulation study to compare vaccine allocation strategies using: (i) only population information (pro-rata, or population-based, PB), (ii) both population and vaccine inventory information (population and inventory-based, PIB).</AbstractText><AbstractText Label="METHODS">We adapt an agent-based simulation model to predict the spread of the disease both geographically and temporally. We study PB and PIB when uptake rates vary geographically. The simulation study is done from 2015 to 2017, using population and commuting data from the state of Georgia from the United States census.</AbstractText><AbstractText Label="FINDINGS">Compared to PB under reasonable scenarios, PIB reduces the infection attack rate from 23.4% to 22.4%, decreases the amount of leftover inventory from 827 to 152 thousand, and maintains or increases the percentage of vaccinated population.</AbstractText><AbstractText Label="CONCLUSIONS">Our results indicate the need for greater vaccine inventory visibility in public health supply chains, especially when supply is limited, and uptake rates vary geographically. Such visibility has a potential to decrease the number of infections, help identify locations with low uptake rates and to motivate public awareness efforts.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Li</LastName><ForeName>Zihao</ForeName><Initials>Z</Initials><AffiliationInfo><Affiliation>School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Swann</LastName><ForeName>Julie L</ForeName><Initials>JL</Initials><AffiliationInfo><Affiliation>Department of Industrial and Systems Engineering, North Carolina State University, Raleigh, North Carolina, United States of America.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Keskinocak</LastName><ForeName>Pinar</ForeName><Initials>P</Initials><Identifier Source="ORCID">0000-0003-2686-546X</Identifier><AffiliationInfo><Affiliation>School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America.</Affiliation></AffiliationInfo></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>2018</Year><Month>10</Month><Day>25</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>PLoS One</MedlineTA><NlmUniqueID>101285081</NlmUniqueID><ISSNLinking>1932-6203</ISSNLinking></MedlineJournalInfo><ChemicalList><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D007252">Influenza Vaccines</NameOfSubstance></Chemical></ChemicalList><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D003198" MajorTopicYN="N">Computer Simulation</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D017589" MajorTopicYN="N">Immunization Programs</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D007252" MajorTopicYN="N">Influenza Vaccines</DescriptorName><QualifierName UI="Q000600" MajorTopicYN="Y">supply & distribution</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D007251" MajorTopicYN="N">Influenza, Human</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="Y">epidemiology</QualifierName><QualifierName UI="Q000276" MajorTopicYN="N">immunology</QualifierName><QualifierName UI="Q000517" MajorTopicYN="N">prevention & control</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D033181" MajorTopicYN="N">Information Dissemination</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D058873" MajorTopicYN="N">Pandemics</DescriptorName><QualifierName UI="Q000517" MajorTopicYN="Y">prevention & control</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D014481" MajorTopicYN="N" Type="Geographic">United States</DescriptorName></MeshHeading></MeshHeadingList><CoiStatement>The authors have declared that no competing interests exist.</CoiStatement></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2017</Year><Month>12</Month><Day>28</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2018</Year><Month>10</Month><Day>10</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2018</Year><Month>10</Month><Day>26</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2018</Year><Month>10</Month><Day>26</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2019</Year><Month>4</Month><Day>11</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>epublish</PublicationStatus><ArticleIdList><ArticleId 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