Value of inventory information in allocating a limited supply of influenza vaccine during a pandemic
Identifieur interne : 000451 ( Main/Exploration ); précédent : 000450; suivant : 000452Value 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).
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.
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.
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.
Url:
DOI: 10.1371/journal.pone.0206293
PubMed: 30359445
PubMed Central: 6201932
Affiliations:
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Le document en format XML
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Swann</name><affiliation wicri:level="2"><nlm:aff id="aff002"><addr-line>Department of Industrial and Systems Engineering, North Carolina State University, Raleigh, North Carolina, United States of America</addr-line></nlm:aff><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:aff id="aff001"><addr-line>School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America</addr-line></nlm:aff><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">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"><sec id="sec001"><title>Objective</title><p>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).</p></sec><sec id="sec002"><title>Methods</title><p>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.</p></sec><sec id="sec003"><title>Findings</title><p>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.</p></sec><sec id="sec004"><title>Conclusions</title><p>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.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Taubenberger, Jk" uniqKey="Taubenberger J">JK Taubenberger</name></author><author><name sortKey="Morens, Dm" uniqKey="Morens D">DM Morens</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Dawood, Fs" uniqKey="Dawood F">FS Dawood</name></author><author><name sortKey="Iuliano, Ad" uniqKey="Iuliano A">AD Iuliano</name></author><author><name sortKey="Reed, C" uniqKey="Reed C">C Reed</name></author><author><name sortKey="Meltzer, Mi" uniqKey="Meltzer M">MI Meltzer</name></author><author><name sortKey="Shay, Dk" uniqKey="Shay D">DK Shay</name></author><author><name sortKey="Cheng, Py" uniqKey="Cheng P">PY 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Skrip</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Glazner, Je" uniqKey="Glazner J">JE Glazner</name></author><author><name sortKey="Beaty, B" uniqKey="Beaty B">B Beaty</name></author><author><name sortKey="Berman, S" uniqKey="Berman S">S Berman</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Kansagra, Sm" uniqKey="Kansagra S">SM Kansagra</name></author><author><name sortKey="Mcginty, Md" uniqKey="Mcginty M">MD McGinty</name></author><author><name sortKey="Morgenthau, Bm" uniqKey="Morgenthau B">BM Morgenthau</name></author><author><name sortKey="Marquez, Ml" uniqKey="Marquez M">ML Marquez</name></author><author><name sortKey="Rosselli Fraschilla, A" uniqKey="Rosselli Fraschilla A">A Rosselli-Fraschilla</name></author><author><name sortKey="Zucker, Jr" uniqKey="Zucker J">JR Zucker</name></author></analytic></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct></listBibl></div1></back></TEI><affiliations><list><country><li>États-Unis</li></country><region><li>Caroline du Nord</li><li>Géorgie (États-Unis)</li></region></list><tree><country name="États-Unis"><region name="Géorgie (États-Unis)"><name sortKey="Li, Zihao" sort="Li, Zihao" uniqKey="Li Z" first="Zihao" last="Li">Zihao Li</name></region><name sortKey="Keskinocak, Pinar" sort="Keskinocak, Pinar" uniqKey="Keskinocak P" first="Pinar" last="Keskinocak">Pinar Keskinocak</name><name sortKey="Swann, Julie L" sort="Swann, Julie L" uniqKey="Swann J" first="Julie L." last="Swann">Julie L. 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