Universal or Specific? A Modeling-Based Comparison of Broad-Spectrum Influenza Vaccines against Conventional, Strain-Matched Vaccines
Identifieur interne : 000272 ( Pmc/Checkpoint ); précédent : 000271; suivant : 000273Universal or Specific? A Modeling-Based Comparison of Broad-Spectrum Influenza Vaccines against Conventional, Strain-Matched Vaccines
Auteurs : Rahul Subramanian [États-Unis] ; Andrea L. Graham [États-Unis] ; Bryan T. Grenfell [États-Unis] ; Nimalan Arinaminpathy [Royaume-Uni]Source :
- PLoS Computational Biology [ 1553-734X ] ; 2016.
Abstract
Despite the availability of vaccines, influenza remains a major public health challenge. A key reason is the virus capacity for immune escape: ongoing evolution allows the continual circulation of seasonal influenza, while novel influenza viruses invade the human population to cause a pandemic every few decades. Current vaccines have to be updated continually to keep up to date with this antigenic change, but emerging ‘universal’ vaccines—targeting more conserved components of the influenza virus—offer the potential to act across all influenza A strains and subtypes. Influenza vaccination programmes around the world are steadily increasing in their population coverage. In future, how might intensive, routine immunization with novel vaccines compare against similar mass programmes utilizing conventional vaccines? Specifically, how might novel and conventional vaccines compare, in terms of cumulative incidence and rates of antigenic evolution of seasonal influenza? What are their potential implications for the impact of pandemic emergence? Here we present a new mathematical model, capturing both transmission dynamics and antigenic evolution of influenza in a simple framework, to explore these questions. We find that, even when matched by per-dose efficacy, universal vaccines could dampen population-level transmission over several seasons to a greater extent than conventional vaccines. Moreover, by lowering opportunities for cross-protective immunity in the population, conventional vaccines could allow the increased spread of a novel pandemic strain. Conversely, universal vaccines could mitigate both seasonal and pandemic spread. However, where it is not possible to maintain annual, intensive vaccination coverage, the duration and breadth of immunity raised by universal vaccines are critical determinants of their performance relative to conventional vaccines. In future, conventional and novel vaccines are likely to play complementary roles in vaccination strategies against influenza: in this context, our results suggest important characteristics to monitor during the clinical development of emerging vaccine technologies.
Url:
DOI: 10.1371/journal.pcbi.1005204
PubMed: 27977667
PubMed Central: 5157952
Affiliations:
- Royaume-Uni, États-Unis
- Angleterre, Grand Londres, Illinois, New Jersey
- Chicago, Londres, Princeton (New Jersey)
- Université de Chicago, Université de Princeton
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PMC:5157952Le document en format XML
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<front><div type="abstract" xml:lang="en"><p>Despite the availability of vaccines, influenza remains a major public health challenge. A key reason is the virus capacity for immune escape: ongoing evolution allows the continual circulation of seasonal influenza, while novel influenza viruses invade the human population to cause a pandemic every few decades. Current vaccines have to be updated continually to keep up to date with this antigenic change, but emerging ‘universal’ vaccines—targeting more conserved components of the influenza virus—offer the potential to act across all influenza A strains and subtypes. Influenza vaccination programmes around the world are steadily increasing in their population coverage. In future, how might intensive, routine immunization with novel vaccines compare against similar mass programmes utilizing conventional vaccines? Specifically, how might novel and conventional vaccines compare, in terms of cumulative incidence and rates of antigenic evolution of seasonal influenza? What are their potential implications for the impact of pandemic emergence? Here we present a new mathematical model, capturing both transmission dynamics and antigenic evolution of influenza in a simple framework, to explore these questions. We find that, even when matched by per-dose efficacy, universal vaccines could dampen population-level transmission over several seasons to a greater extent than conventional vaccines. Moreover, by lowering opportunities for cross-protective immunity in the population, conventional vaccines could allow the increased spread of a novel pandemic strain. Conversely, universal vaccines could mitigate both seasonal and pandemic spread. However, where it is not possible to maintain annual, intensive vaccination coverage, the duration and breadth of immunity raised by universal vaccines are critical determinants of their performance relative to conventional vaccines. In future, conventional and novel vaccines are likely to play complementary roles in vaccination strategies against influenza: in this context, our results suggest important characteristics to monitor during the clinical development of emerging vaccine technologies.</p>
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<front><journal-meta><journal-id journal-id-type="nlm-ta">PLoS Comput Biol</journal-id>
<journal-id journal-id-type="iso-abbrev">PLoS Comput. Biol</journal-id>
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<issn pub-type="ppub">1553-734X</issn>
<issn pub-type="epub">1553-7358</issn>
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<article-meta><article-id pub-id-type="pmid">27977667</article-id>
<article-id pub-id-type="pmc">5157952</article-id>
<article-id pub-id-type="doi">10.1371/journal.pcbi.1005204</article-id>
<article-id pub-id-type="publisher-id">PCOMPBIOL-D-16-00257</article-id>
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</subj-group>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v3"><subject>Biology and Life Sciences</subject>
<subj-group><subject>Immunology</subject>
<subj-group><subject>Vaccination and Immunization</subject>
<subj-group><subject>Vaccines</subject>
<subj-group><subject>Viral Vaccines</subject>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v3"><subject>Medicine and Health Sciences</subject>
<subj-group><subject>Immunology</subject>
<subj-group><subject>Vaccination and Immunization</subject>
<subj-group><subject>Vaccines</subject>
<subj-group><subject>Viral Vaccines</subject>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v3"><subject>Medicine and Health Sciences</subject>
<subj-group><subject>Public and Occupational Health</subject>
<subj-group><subject>Preventive Medicine</subject>
<subj-group><subject>Vaccination and Immunization</subject>
<subj-group><subject>Vaccines</subject>
<subj-group><subject>Viral Vaccines</subject>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v3"><subject>Biology and Life Sciences</subject>
<subj-group><subject>Microbiology</subject>
<subj-group><subject>Virology</subject>
<subj-group><subject>Viral Vaccines</subject>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
</article-categories>
<title-group><article-title>Universal or Specific? A Modeling-Based Comparison of Broad-Spectrum Influenza Vaccines against Conventional, Strain-Matched Vaccines</article-title>
<alt-title alt-title-type="running-head">Universal or Specific? A Comparison of Novel and Conventional Influenza Vaccines</alt-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>Subramanian</surname>
<given-names>Rahul</given-names>
</name>
<xref ref-type="aff" rid="aff001"><sup>1</sup>
</xref>
<xref ref-type="corresp" rid="cor001">*</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Graham</surname>
<given-names>Andrea L.</given-names>
</name>
<xref ref-type="aff" rid="aff002"><sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Grenfell</surname>
<given-names>Bryan T.</given-names>
</name>
<xref ref-type="aff" rid="aff002"><sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Arinaminpathy</surname>
<given-names>Nimalan</given-names>
</name>
<xref ref-type="aff" rid="aff003"><sup>3</sup>
</xref>
</contrib>
</contrib-group>
<aff id="aff001"><label>1</label>
<addr-line>Department of Ecology and Evolution, University of Chicago, Chicago, Illinois, United States of America</addr-line>
</aff>
<aff id="aff002"><label>2</label>
<addr-line>Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, United States of America</addr-line>
</aff>
<aff id="aff003"><label>3</label>
<addr-line>Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom</addr-line>
</aff>
<contrib-group><contrib contrib-type="editor"><name><surname>Regoes</surname>
<given-names>Roland R</given-names>
</name>
<role>Editor</role>
<xref ref-type="aff" rid="edit1"></xref>
</contrib>
</contrib-group>
<aff id="edit1"><addr-line>ETH Zurich, SWITZERLAND</addr-line>
</aff>
<author-notes><fn fn-type="COI-statement" id="coi001"><p>The authors have declared that no competing interests exist.</p>
</fn>
<fn fn-type="con"><p><list list-type="simple"><list-item><p><bold>Conceived and designed the experiments:</bold>
NA ALG BTG.</p>
</list-item>
<list-item><p><bold>Performed the experiments:</bold>
RS.</p>
</list-item>
<list-item><p><bold>Analyzed the data:</bold>
RS ALG NA BTG.</p>
</list-item>
<list-item><p><bold>Wrote the paper:</bold>
RS NA ALG BTG.</p>
</list-item>
</list>
</p>
</fn>
<corresp id="cor001">* E-mail: <email>rsfive@uchicago.edu</email>
</corresp>
</author-notes>
<pub-date pub-type="epub"><day>15</day>
<month>12</month>
<year>2016</year>
</pub-date>
<pub-date pub-type="collection"><month>12</month>
<year>2016</year>
</pub-date>
<volume>12</volume>
<issue>12</issue>
<elocation-id>e1005204</elocation-id>
<history><date date-type="received"><day>16</day>
<month>2</month>
<year>2016</year>
</date>
<date date-type="accepted"><day>15</day>
<month>10</month>
<year>2016</year>
</date>
</history>
<permissions><copyright-statement>© 2016 Subramanian et al</copyright-statement>
<copyright-year>2016</copyright-year>
<copyright-holder>Subramanian 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="pcbi.1005204.pdf"></self-uri>
<abstract><p>Despite the availability of vaccines, influenza remains a major public health challenge. A key reason is the virus capacity for immune escape: ongoing evolution allows the continual circulation of seasonal influenza, while novel influenza viruses invade the human population to cause a pandemic every few decades. Current vaccines have to be updated continually to keep up to date with this antigenic change, but emerging ‘universal’ vaccines—targeting more conserved components of the influenza virus—offer the potential to act across all influenza A strains and subtypes. Influenza vaccination programmes around the world are steadily increasing in their population coverage. In future, how might intensive, routine immunization with novel vaccines compare against similar mass programmes utilizing conventional vaccines? Specifically, how might novel and conventional vaccines compare, in terms of cumulative incidence and rates of antigenic evolution of seasonal influenza? What are their potential implications for the impact of pandemic emergence? Here we present a new mathematical model, capturing both transmission dynamics and antigenic evolution of influenza in a simple framework, to explore these questions. We find that, even when matched by per-dose efficacy, universal vaccines could dampen population-level transmission over several seasons to a greater extent than conventional vaccines. Moreover, by lowering opportunities for cross-protective immunity in the population, conventional vaccines could allow the increased spread of a novel pandemic strain. Conversely, universal vaccines could mitigate both seasonal and pandemic spread. However, where it is not possible to maintain annual, intensive vaccination coverage, the duration and breadth of immunity raised by universal vaccines are critical determinants of their performance relative to conventional vaccines. In future, conventional and novel vaccines are likely to play complementary roles in vaccination strategies against influenza: in this context, our results suggest important characteristics to monitor during the clinical development of emerging vaccine technologies.</p>
</abstract>
<abstract abstract-type="summary"><title>Author Summary</title>
<p>Influenza vaccines used today offer good protection, but have limitations: they have to be updated regularly, to remain effective in the face of ongoing virus evolution, and they cannot be used in advance of an influenza pandemic. In this study we considered how such ‘conventional’ vaccines might compare on the population level against new ‘universal’ vaccines currently being developed, that may protect against a broad spectrum of influenza viruses. We developed a mathematical model to capture the interactions between vaccination, influenza transmission, and viral evolution. The model suggests that annual vaccination with universal vaccines could control annual influenza epidemics more efficiently than conventional vaccines. In doing so they could slow viral evolution, rather than promoting it, while maintaining the broadly protective immunity that could mitigate against the emergence of a pandemic. These effects depend sensitively on the duration of protection that universal vaccines can afford, an important quantity to monitor in their development. In future, it is likely that conventional and universal vaccines would be deployed in tandem: we suggest that they could fulfill distinct roles, with universal vaccines being prioritised for managing transmission and evolution, and conventional vaccines being focused on protecting specific risk groups.</p>
</abstract>
<funding-group><award-group id="award001"><funding-source><institution>Center for Health and Wellbeing, Princeton University (US)</institution>
</funding-source>
<principal-award-recipient><name><surname>Subramanian</surname>
<given-names>Rahul</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/10.13039/100007084</institution-id>
<institution>Princeton Environmental Institute, Princeton University</institution>
</institution-wrap>
</funding-source>
<principal-award-recipient><name><surname>Subramanian</surname>
<given-names>Rahul</given-names>
</name>
</principal-award-recipient>
</award-group>
<funding-statement>This work was supported by: Health Grand Challenges Program, Center for Health and Wellbeing, Princeton University (RS); and Bob and Cathy Solomon Undergraduate Research Fund, Princeton Environmental Institute, Princeton University (RS); and MRC Centre for Outbreak Analysis and Modelling, MR/K010174/1B (NA). 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="5"></fig-count>
<table-count count="1"></table-count>
<page-count count="17"></page-count>
</counts>
<custom-meta-group><custom-meta id="data-availability"><meta-name>Data Availability</meta-name>
<meta-value>Full materials and methods are supplied in the supporting materials.</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
<notes><title>Data Availability</title>
<p>Full materials and methods are supplied in the supporting materials.</p>
</notes>
</front>
</pmc>
<affiliations><list><country><li>Royaume-Uni</li>
<li>États-Unis</li>
</country>
<region><li>Angleterre</li>
<li>Grand Londres</li>
<li>Illinois</li>
<li>New Jersey</li>
</region>
<settlement><li>Chicago</li>
<li>Londres</li>
<li>Princeton (New Jersey)</li>
</settlement>
<orgName><li>Université de Chicago</li>
<li>Université de Princeton</li>
</orgName>
</list>
<tree><country name="États-Unis"><region name="Illinois"><name sortKey="Subramanian, Rahul" sort="Subramanian, Rahul" uniqKey="Subramanian R" first="Rahul" last="Subramanian">Rahul Subramanian</name>
</region>
<name sortKey="Graham, Andrea L" sort="Graham, Andrea L" uniqKey="Graham A" first="Andrea L." last="Graham">Andrea L. Graham</name>
<name sortKey="Grenfell, Bryan T" sort="Grenfell, Bryan T" uniqKey="Grenfell B" first="Bryan T." last="Grenfell">Bryan T. Grenfell</name>
</country>
<country name="Royaume-Uni"><region name="Angleterre"><name sortKey="Arinaminpathy, Nimalan" sort="Arinaminpathy, Nimalan" uniqKey="Arinaminpathy N" first="Nimalan" last="Arinaminpathy">Nimalan Arinaminpathy</name>
</region>
</country>
</tree>
</affiliations>
</record>
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