The impact of contact structure on infectious disease control: influenza and antiviral agents
Identifieur interne : 000686 ( Pmc/Corpus ); précédent : 000685; suivant : 000687The impact of contact structure on infectious disease control: influenza and antiviral agents
Auteurs : H.-P. Duerr ; M. Schwehm ; C. C. Leary ; S. J. De Vlas ; M. EichnerSource :
- Epidemiology and Infection [ 0950-2688 ] ; 2007.
Abstract
Planning adequate public health responses against emerging infectious diseases requires predictive tools to evaluate the impact of candidate intervention strategies. With current interest in pandemic influenza very high, modelling approaches have suggested antiviral treatment combined with targeted prophylaxis as an effective first-line intervention against an emerging influenza pandemic. To investigate how the effectiveness of such interventions depends on contact structure, we simulate the effects in networks with variable degree distributions. The infection attack rate can increase if the number of contacts per person is heterogeneous, implying the existence of high-degree individuals who are potential super-spreaders. The effectiveness of a socially targeted intervention suffers from heterogeneous contact patterns and depends on whether infection is predominantly transmitted to close or casual contacts. Our findings imply that the various contact networks' degree distributions as well as the allocation of contagiousness between close and casual contacts should be examined to identify appropriate strategies of disease control measures.
Url:
DOI: 10.1017/S0950268807007959
PubMed: 17288643
PubMed Central: 2870680
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PMC:2870680Le document en format XML
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<author><name sortKey="Schwehm, M" sort="Schwehm, M" uniqKey="Schwehm M" first="M." last="Schwehm">M. Schwehm</name>
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<affiliation><nlm:aff id="aff002">Department of Mathematics, State University of New York at Geneseo, USA</nlm:aff>
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<author><name sortKey="De Vlas, S J" sort="De Vlas, S J" uniqKey="De Vlas S" first="S. J." last="De Vlas">S. J. De Vlas</name>
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<series><title level="j">Epidemiology and Infection</title>
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<front><div type="abstract" xml:lang="en"><title>SUMMARY</title>
<p>Planning adequate public health responses against emerging infectious diseases requires predictive tools to evaluate the impact of candidate intervention strategies. With current interest in pandemic influenza very high, modelling approaches have suggested antiviral treatment combined with targeted prophylaxis as an effective first-line intervention against an emerging influenza pandemic. To investigate how the effectiveness of such interventions depends on contact structure, we simulate the effects in networks with variable degree distributions. The infection attack rate can increase if the number of contacts per person is heterogeneous, implying the existence of high-degree individuals who are potential super-spreaders. The effectiveness of a socially targeted intervention suffers from heterogeneous contact patterns and depends on whether infection is predominantly transmitted to close or casual contacts. Our findings imply that the various contact networks' degree distributions as well as the allocation of contagiousness between close and casual contacts should be examined to identify appropriate strategies of disease control measures.</p>
</div>
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<pmc article-type="research-article"><pmc-comment>The publisher of this article does not allow downloading of the full text in XML form.</pmc-comment>
<front><journal-meta><journal-id journal-id-type="nlm-ta">Epidemiol Infect</journal-id>
<journal-id journal-id-type="publisher-id">HYG</journal-id>
<journal-title>Epidemiology and Infection</journal-title>
<issn pub-type="ppub">0950-2688</issn>
<issn pub-type="epub">1469-4409</issn>
<publisher><publisher-name>Cambridge University Press</publisher-name>
<publisher-loc>Cambridge, UK</publisher-loc>
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<article-id pub-id-type="publisher-id">00795</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject>
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<title-group><article-title>The impact of contact structure on infectious disease control: influenza and antiviral agents</article-title>
<alt-title alt-title-type="left-running">H.-P. Duerr and others</alt-title>
<alt-title alt-title-type="right-running">Influenza and network structure</alt-title>
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<contrib-group><contrib contrib-type="author"><name><surname>DUERR</surname>
<given-names>H.-P.</given-names>
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<xref ref-type="aff" rid="aff001">1</xref>
<xref ref-type="corresp" rid="cor001">*</xref>
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<contrib contrib-type="author"><name><surname>SCHWEHM</surname>
<given-names>M.</given-names>
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<contrib contrib-type="author"><name><surname>LEARY</surname>
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<xref ref-type="aff" rid="aff001">1</xref>
<xref ref-type="aff" rid="aff002">2</xref>
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<contrib contrib-type="author"><name><surname>De Vlas</surname>
<given-names>S. J.</given-names>
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<xref ref-type="aff" rid="aff003">3</xref>
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<contrib contrib-type="author"><name><surname>EICHNER</surname>
<given-names>M.</given-names>
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<xref ref-type="aff" rid="aff001">1</xref>
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<aff id="aff001"><label>1</label>
Department of Medical Biometry, University of Tübingen, Germany</aff>
<aff id="aff002"><label>2</label>
Department of Mathematics, State University of New York at Geneseo, USA</aff>
<aff id="aff003"><label>3</label>
Department of Public Health, Erasmus MC, University Medical Center Rotterdam, The Netherlands</aff>
<author-notes><corresp id="cor001"><label>*</label>
Author for correspondence: Dr H.-P. Duerr, Institut für Medizinische Biometrie, Westbahnhofstr. 55, D-72070 Tübingen, Germany. (Email: <email xlink:href="hans-peter.duerr@uni-tuebingen.de">hans-peter.duerr@uni-tuebingen.de</email>
)</corresp>
</author-notes>
<pub-date pub-type="ppub"><month>10</month>
<year>2007</year>
</pub-date>
<pub-date pub-type="epub"><day>09</day>
<month>2</month>
<year>2007</year>
</pub-date>
<volume>135</volume>
<issue>7</issue>
<fpage>1124</fpage>
<lpage>1132</lpage>
<history><date date-type="accepted"><day>04</day>
<month>12</month>
<year>2006</year>
</date>
</history>
<copyright-statement>© Cambridge University Press 2007</copyright-statement>
<copyright-year>2007</copyright-year>
<self-uri xlink:title="pdf" xlink:type="simple" xlink:href="S0950268807007959a.pdf"></self-uri>
<abstract abstract-type="normal"><title>SUMMARY</title>
<p>Planning adequate public health responses against emerging infectious diseases requires predictive tools to evaluate the impact of candidate intervention strategies. With current interest in pandemic influenza very high, modelling approaches have suggested antiviral treatment combined with targeted prophylaxis as an effective first-line intervention against an emerging influenza pandemic. To investigate how the effectiveness of such interventions depends on contact structure, we simulate the effects in networks with variable degree distributions. The infection attack rate can increase if the number of contacts per person is heterogeneous, implying the existence of high-degree individuals who are potential super-spreaders. The effectiveness of a socially targeted intervention suffers from heterogeneous contact patterns and depends on whether infection is predominantly transmitted to close or casual contacts. Our findings imply that the various contact networks' degree distributions as well as the allocation of contagiousness between close and casual contacts should be examined to identify appropriate strategies of disease control measures.</p>
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