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Deriving effective vaccine allocation strategies for pandemic influenza: Comparison of an agent-based simulation and a compartmental model

Identifieur interne : 000D52 ( Ncbi/Merge ); précédent : 000D51; suivant : 000D53

Deriving effective vaccine allocation strategies for pandemic influenza: Comparison of an agent-based simulation and a compartmental model

Auteurs : Özden O. Dalg Ç [Canada] ; Osman Y. Özalt N [États-Unis] ; William A. Ciccotelli [Canada] ; Fatih S. Erenay [Canada]

Source :

RBID : PMC:5319753

Abstract

Individuals are prioritized based on their risk profiles when allocating limited vaccine stocks during an influenza pandemic. Computationally expensive but realistic agent-based simulations and fast but stylized compartmental models are typically used to derive effective vaccine allocation strategies. A detailed comparison of these two approaches, however, is often omitted. We derive age-specific vaccine allocation strategies to mitigate a pandemic influenza outbreak in Seattle by applying derivative-free optimization to an agent-based simulation and also to a compartmental model. We compare the strategies derived by these two approaches under various infection aggressiveness and vaccine coverage scenarios. We observe that both approaches primarily vaccinate school children, however they may allocate the remaining vaccines in different ways. The vaccine allocation strategies derived by using the agent-based simulation are associated with up to 70% decrease in total cost and 34% reduction in the number of infections compared to the strategies derived by using the compartmental model. Nevertheless, the latter approach may still be competitive for very low and/or very high infection aggressiveness. Our results provide insights about potential differences between the vaccine allocation strategies derived by using agent-based simulations and those derived by using compartmental models.


Url:
DOI: 10.1371/journal.pone.0172261
PubMed: 28222123
PubMed Central: 5319753

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PMC:5319753

Le document en format XML

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<article-id pub-id-type="doi">10.1371/journal.pone.0172261</article-id>
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<subj-group>
<subject>Immunology</subject>
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<subject>Epidemiology</subject>
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<title-group>
<article-title>Deriving effective vaccine allocation strategies for pandemic influenza: Comparison of an agent-based simulation and a compartmental model</article-title>
<alt-title alt-title-type="running-head">Deriving effective vaccine allocation strategies for pandemic influenza</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Dalgıç</surname>
<given-names>Özden O.</given-names>
</name>
<xref ref-type="aff" rid="aff001">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Özaltın</surname>
<given-names>Osman Y.</given-names>
</name>
<xref ref-type="aff" rid="aff002">
<sup>2</sup>
</xref>
<xref ref-type="corresp" rid="cor001">*</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Ciccotelli</surname>
<given-names>William A.</given-names>
</name>
<xref ref-type="aff" rid="aff003">
<sup>3</sup>
</xref>
<xref ref-type="aff" rid="aff004">
<sup>4</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Erenay</surname>
<given-names>Fatih S.</given-names>
</name>
<xref ref-type="aff" rid="aff001">
<sup>1</sup>
</xref>
</contrib>
</contrib-group>
<aff id="aff001">
<label>1</label>
<addr-line>Department of Management Sciences, University of Waterloo, Waterloo, Ontario, Canada</addr-line>
</aff>
<aff id="aff002">
<label>2</label>
<addr-line>Edward P. Fitts Department of Industrial and Systems Engineering, North Carolina State University, Raleigh, North Carolina, United States of America</addr-line>
</aff>
<aff id="aff003">
<label>3</label>
<addr-line>Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario, Canada</addr-line>
</aff>
<aff id="aff004">
<label>4</label>
<addr-line>Grand River Hospital, Kitchener, Ontario, Canada</addr-line>
</aff>
<contrib-group>
<contrib contrib-type="editor">
<name>
<surname>Shaman</surname>
<given-names>Jeffrey</given-names>
</name>
<role>Editor</role>
<xref ref-type="aff" rid="edit1"></xref>
</contrib>
</contrib-group>
<aff id="edit1">
<addr-line>Columbia University, UNITED STATES</addr-line>
</aff>
<author-notes>
<fn fn-type="COI-statement" id="coi001">
<p>
<bold>Competing Interests: </bold>
The authors have declared that no competing interests exist.</p>
</fn>
<fn fn-type="con">
<p>
<list list-type="simple">
<list-item>
<p>
<bold>Conceptualization:</bold>
OD OO FE.</p>
</list-item>
<list-item>
<p>
<bold>Formal analysis:</bold>
OD.</p>
</list-item>
<list-item>
<p>
<bold>Funding acquisition:</bold>
OO FE.</p>
</list-item>
<list-item>
<p>
<bold>Methodology:</bold>
OD OO FE.</p>
</list-item>
<list-item>
<p>
<bold>Project administration:</bold>
OO FE.</p>
</list-item>
<list-item>
<p>
<bold>Software:</bold>
OD OO.</p>
</list-item>
<list-item>
<p>
<bold>Supervision:</bold>
OO FE WC.</p>
</list-item>
<list-item>
<p>
<bold>Writing – original draft:</bold>
OD OO FE.</p>
</list-item>
<list-item>
<p>
<bold>Writing – review & editing:</bold>
OD OO FE.</p>
</list-item>
</list>
</p>
</fn>
<corresp id="cor001">* E-mail:
<email>oyozalti@ncsu.edu</email>
</corresp>
</author-notes>
<pub-date pub-type="collection">
<year>2017</year>
</pub-date>
<pub-date pub-type="epub">
<day>21</day>
<month>2</month>
<year>2017</year>
</pub-date>
<volume>12</volume>
<issue>2</issue>
<elocation-id>e0172261</elocation-id>
<history>
<date date-type="received">
<day>20</day>
<month>9</month>
<year>2016</year>
</date>
<date date-type="accepted">
<day>2</day>
<month>2</month>
<year>2017</year>
</date>
</history>
<permissions>
<copyright-statement>© 2017 Dalgıç et al</copyright-statement>
<copyright-year>2017</copyright-year>
<copyright-holder>Dalgıç et al</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<license-p>This is an open access article distributed under the terms of the
<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License</ext-link>
, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</license-p>
</license>
</permissions>
<self-uri content-type="pdf" xlink:href="pone.0172261.pdf"></self-uri>
<abstract>
<p>Individuals are prioritized based on their risk profiles when allocating limited vaccine stocks during an influenza pandemic. Computationally expensive but realistic agent-based simulations and fast but stylized compartmental models are typically used to derive effective vaccine allocation strategies. A detailed comparison of these two approaches, however, is often omitted. We derive age-specific vaccine allocation strategies to mitigate a pandemic influenza outbreak in Seattle by applying derivative-free optimization to an agent-based simulation and also to a compartmental model. We compare the strategies derived by these two approaches under various infection aggressiveness and vaccine coverage scenarios. We observe that both approaches primarily vaccinate school children, however they may allocate the remaining vaccines in different ways. The vaccine allocation strategies derived by using the agent-based simulation are associated with up to 70% decrease in total cost and 34% reduction in the number of infections compared to the strategies derived by using the compartmental model. Nevertheless, the latter approach may still be competitive for very low and/or very high infection aggressiveness. Our results provide insights about potential differences between the vaccine allocation strategies derived by using agent-based simulations and those derived by using compartmental models.</p>
</abstract>
<funding-group>
<award-group id="award001">
<funding-source>
<institution-wrap>
<institution-id institution-id-type="funder-id">http://dx.doi.org/10.13039/501100000038</institution-id>
<institution>Natural Sciences and Engineering Research Council of Canada</institution>
</institution-wrap>
</funding-source>
<award-id>DG 113788</award-id>
<principal-award-recipient>
<name>
<surname>Erenay</surname>
<given-names>Fatih S</given-names>
</name>
</principal-award-recipient>
</award-group>
<award-group id="award002">
<funding-source>
<institution-wrap>
<institution-id institution-id-type="funder-id">http://dx.doi.org/10.13039/501100000038</institution-id>
<institution>Natural Sciences and Engineering Research Council of Canada</institution>
</institution-wrap>
</funding-source>
<award-id>DG 113790</award-id>
<principal-award-recipient>
<name>
<surname>Özaltın</surname>
<given-names>Osman Y</given-names>
</name>
</principal-award-recipient>
</award-group>
<funding-statement>This work was supported by the Natural Sciences and Engineering Research Council of Canada (DG 113788 and DG 113790). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</funding-statement>
</funding-group>
<counts>
<fig-count count="3"></fig-count>
<table-count count="5"></table-count>
<page-count count="19"></page-count>
</counts>
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<custom-meta id="data-availability">
<meta-name>Data Availability</meta-name>
<meta-value>All relevant data are within the paper and its Supporting Information files.</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
<notes>
<title>Data Availability</title>
<p>All relevant data are within the paper and its Supporting Information files.</p>
</notes>
</front>
</pmc>
<affiliations>
<list>
<country>
<li>Canada</li>
<li>États-Unis</li>
</country>
<region>
<li>Caroline du Nord</li>
<li>Ontario</li>
</region>
<settlement>
<li>Hamilton (Ontario)</li>
</settlement>
<orgName>
<li>Université McMaster</li>
</orgName>
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<name sortKey="Erenay, Fatih S" sort="Erenay, Fatih S" uniqKey="Erenay F" first="Fatih S." last="Erenay">Fatih S. Erenay</name>
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<region name="Caroline du Nord">
<name sortKey="Ozalt N, Osman Y" sort="Ozalt N, Osman Y" uniqKey="Ozalt N O" first="Osman Y." last="Özalt N">Osman Y. Özalt N</name>
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