PandemieGrippaleV1, Hal, Curation, bibRecord, 000235

Fluctuation effects in metapopulation models: percolation and pandemic threshold

Identifieur interne : 000235 ( Hal/Curation ); précédent : 000234; suivant : 000236

Fluctuation effects in metapopulation models: percolation and pandemic threshold

Auteurs : Marc Barthélemy [France] ; Claude Godrèche [France] ; Jean-Marc Luck [France]

Source :

Journal of Theoretical Biology [ 0022-5193 ] ; 2010-11-03.

RBID : Hal:hal-00637809

English descriptors

mix :
- Epidemic spread, Metapopulation, Pandemic threshold, Percolation.

Abstract

Metapopulation models provide the theoretical framework for describing disease spread between different populations connected by a network. In particular, these models are at the basis of most simulations of pandemic spread. They are usually studied at the mean-field level by neglecting fluctuations. Here we include fluctuations in the models by adopting fully stochastic descriptions of the corresponding processes. This level of description allows to address analytically, in the SIS and SIR cases, problems such as the existence and the calculation of an effective threshold for the spread of a disease at a global level. We show that the possibility of the spread at the global level is described in terms of (bond) percolation on the network. This mapping enables us to give an estimate (lower bound) for the pandemic threshold in the SIR case for all values of the model parameters and for all possible networks.

Url:

https://hal.archives-ouvertes.fr/hal-00637809

DOI: 10.1016/j.jtbi.2010.09.015

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Le document en format XML

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<front><div type="abstract" xml:lang="en">              <p>Metapopulation models provide the theoretical framework for describing disease spread between different populations connected by a network. In particular, these models are at the basis of most simulations of pandemic spread. They are usually studied at the mean-field level by neglecting fluctuations. Here we include fluctuations in the models by adopting fully stochastic descriptions of the corresponding processes. This level of description allows to address analytically, in the SIS and SIR cases, problems such as the existence and the calculation of an effective threshold for the spread of a disease at a global level. We show that the possibility of the spread at the global level is described in terms of (bond) percolation on the network. This mapping enables us to give an estimate (lower bound) for the pandemic threshold in the SIR case for all values of the model parameters and for all possible networks.</p>
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            <note type="peer" n="1">Yes</note>
          </notesStmt>
          <sourceDesc>            <biblStruct>              <analytic>                <title xml:lang="en">Fluctuation effects in metapopulation models: percolation and pandemic threshold</title>
                <author role="crp">                  <persName>                    <forename type="first">Marc</forename>
                    <surname>Barthélemy</surname>
                  </persName>
                  <email type="md5">8515bc02080df4077f4c1105e5be3489</email>
                  <email type="domain">cea.fr</email>
                  <idno type="halauthorid">655460</idno>
                  <affiliation ref="#struct-53952"></affiliation>
                </author>
                <author role="aut">                  <persName>                    <forename type="first">Claude</forename>
                    <surname>Godrèche</surname>
                  </persName>
                  <idno type="halauthorid">215384</idno>
                  <affiliation ref="#struct-53952"></affiliation>
                </author>
                <author role="aut">                  <persName>                    <forename type="first">Jean-Marc</forename>
                    <surname>Luck</surname>
                  </persName>
                  <idno type="halauthorid">655461</idno>
                  <affiliation ref="#struct-53952"></affiliation>
                </author>
              </analytic>
              <monogr>                <idno type="halJournalId" status="VALID">16404</idno>
                <idno type="issn">0022-5193</idno>
                <idno type="eissn">1095-8541</idno>
                <title level="j">Journal of Theoretical Biology</title>
                <imprint>                  <publisher>Elsevier</publisher>
                  <biblScope unit="volume">267</biblScope>
                  <biblScope unit="issue">4</biblScope>
                  <biblScope unit="pp">554</biblScope>
                  <date type="datePub">2010-11-03</date>
                </imprint>
              </monogr>
              <idno type="doi">10.1016/j.jtbi.2010.09.015</idno>
            </biblStruct>
          </sourceDesc>
          <profileDesc>            <langUsage>              <language ident="en">English</language>
            </langUsage>
            <textClass>              <keywords scheme="author">                <term xml:lang="en">Epidemic spread</term>
                <term xml:lang="en">Metapopulation</term>
                <term xml:lang="en">Percolation</term>
                <term xml:lang="en">Pandemic threshold</term>
              </keywords>
              <classCode scheme="halTypology" n="ART">Journal articles</classCode>
            </textClass>
            <abstract xml:lang="en">              <p>Metapopulation models provide the theoretical framework for describing disease spread between different populations connected by a network. In particular, these models are at the basis of most simulations of pandemic spread. They are usually studied at the mean-field level by neglecting fluctuations. Here we include fluctuations in the models by adopting fully stochastic descriptions of the corresponding processes. This level of description allows to address analytically, in the SIS and SIR cases, problems such as the existence and the calculation of an effective threshold for the spread of a disease at a global level. We show that the possibility of the spread at the global level is described in terms of (bond) percolation on the network. This mapping enables us to give an estimate (lower bound) for the pandemic threshold in the SIR case for all values of the model parameters and for all possible networks.</p>
            </abstract>
          </profileDesc>
        </hal>
</record>

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Fluctuation effects in metapopulation models: percolation and pandemic threshold

Fluctuation effects in metapopulation models: percolation and pandemic threshold

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