SIS along a continuum (SIS(c)) epidemiological modelling and control of diseases on directed trade networks.
Identifieur interne : 001446 ( Main/Exploration ); précédent : 001445; suivant : 001447SIS along a continuum (SIS(c)) epidemiological modelling and control of diseases on directed trade networks.
Auteurs : Mathieu Moslonka-Lefebvre [France] ; Tom Harwood ; Mike J. Jeger ; Marco PautassoSource :
- Mathematical biosciences [ 1879-3134 ] ; 2012.
Descripteurs français
- KwdFr :
- MESH :
- isolement et purification : Phytophthora.
- Agriculture, Maladies des plantes, Modèles biologiques, Royaume-Uni, Épidémies.
English descriptors
- KwdEn :
- MESH :
- isolation & purification : Phytophthora.
- Agriculture, Epidemics, Models, Biological, Plant Diseases, United Kingdom.
Abstract
Network theory has been applied to many aspects of biosciences, including epidemiology. Most epidemiological models in networks, however, have used the standard assumption of either susceptible or infected individuals. In some cases (e.g. the spread of Phytophthora ramorum in plant trade networks), a continuum in the infection status of nodes can better capture the reality of epidemics in networks. In this paper, a Susceptible-Infected-Susceptible model along a continuum in the infection status (SIS(c)) is presented, using as a case study directed networks and two parameters governing the epidemic process (probability of infection persistence (p(p)) and of infection transmission (p(t)). The previously empirically reported linear epidemic threshold in a plot of p(p) as a function of p(t) (Pautasso and Jeger, 2008) is derived analytically. Also the previously observed negative correlation between the epidemic threshold and the correlation between links in and out of nodes (Moslonka-Lefebvre et al., 2009) is justified analytically. A simple algorithm to calculate the threshold conditions is introduced. Additionally, a control strategy based on targeting market hierarchical categories such as producers, wholesalers and retailers is presented and applied to a realistic reconstruction of the UK horticultural trade network. Finally, various applications (e.g., seed exchange networks, food trade, spread of ideas) and potential refinements of the SIS(c) model are discussed.
DOI: 10.1016/j.mbs.2012.01.004
PubMed: 22306763
Affiliations:
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Most epidemiological models in networks, however, have used the standard assumption of either susceptible or infected individuals. In some cases (e.g. the spread of Phytophthora ramorum in plant trade networks), a continuum in the infection status of nodes can better capture the reality of epidemics in networks. In this paper, a Susceptible-Infected-Susceptible model along a continuum in the infection status (SIS(c)) is presented, using as a case study directed networks and two parameters governing the epidemic process (probability of infection persistence (p(p)) and of infection transmission (p(t)). The previously empirically reported linear epidemic threshold in a plot of p(p) as a function of p(t) (Pautasso and Jeger, 2008) is derived analytically. Also the previously observed negative correlation between the epidemic threshold and the correlation between links in and out of nodes (Moslonka-Lefebvre et al., 2009) is justified analytically. A simple algorithm to calculate the threshold conditions is introduced. Additionally, a control strategy based on targeting market hierarchical categories such as producers, wholesalers and retailers is presented and applied to a realistic reconstruction of the UK horticultural trade network. Finally, various applications (e.g., seed exchange networks, food trade, spread of ideas) and potential refinements of the SIS(c) model are discussed.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">22306763</PMID><DateCompleted><Year>2012</Year><Month>06</Month><Day>25</Day></DateCompleted><DateRevised><Year>2016</Year><Month>11</Month><Day>25</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1879-3134</ISSN><JournalIssue CitedMedium="Internet"><Volume>236</Volume><Issue>1</Issue><PubDate><Year>2012</Year><Month>Mar</Month></PubDate></JournalIssue><Title>Mathematical biosciences</Title><ISOAbbreviation>Math Biosci</ISOAbbreviation></Journal><ArticleTitle>SIS along a continuum (SIS(c)) epidemiological modelling and control of diseases on directed trade networks.</ArticleTitle><Pagination><MedlinePgn>44-52</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1016/j.mbs.2012.01.004</ELocationID><Abstract><AbstractText>Network theory has been applied to many aspects of biosciences, including epidemiology. Most epidemiological models in networks, however, have used the standard assumption of either susceptible or infected individuals. In some cases (e.g. the spread of Phytophthora ramorum in plant trade networks), a continuum in the infection status of nodes can better capture the reality of epidemics in networks. In this paper, a Susceptible-Infected-Susceptible model along a continuum in the infection status (SIS(c)) is presented, using as a case study directed networks and two parameters governing the epidemic process (probability of infection persistence (p(p)) and of infection transmission (p(t)). The previously empirically reported linear epidemic threshold in a plot of p(p) as a function of p(t) (Pautasso and Jeger, 2008) is derived analytically. Also the previously observed negative correlation between the epidemic threshold and the correlation between links in and out of nodes (Moslonka-Lefebvre et al., 2009) is justified analytically. A simple algorithm to calculate the threshold conditions is introduced. Additionally, a control strategy based on targeting market hierarchical categories such as producers, wholesalers and retailers is presented and applied to a realistic reconstruction of the UK horticultural trade network. Finally, various applications (e.g., seed exchange networks, food trade, spread of ideas) and potential refinements of the SIS(c) model are discussed.</AbstractText><CopyrightInformation>Copyright © 2012 Elsevier Inc. All rights reserved.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Moslonka-Lefebvre</LastName><ForeName>Mathieu</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>INRA, UR 341 Mathématiques et Informatique Appliquées, 78350 Jouy-en-Josas, France. mathieu.moslonka-lefebvre@jouy.inra.fr</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Harwood</LastName><ForeName>Tom</ForeName><Initials>T</Initials></Author><Author ValidYN="Y"><LastName>Jeger</LastName><ForeName>Mike J</ForeName><Initials>MJ</Initials></Author><Author ValidYN="Y"><LastName>Pautasso</LastName><ForeName>Marco</ForeName><Initials>M</Initials></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2012</Year><Month>01</Month><Day>28</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>Math Biosci</MedlineTA><NlmUniqueID>0103146</NlmUniqueID><ISSNLinking>0025-5564</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000383" MajorTopicYN="N">Agriculture</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D058872" MajorTopicYN="Y">Epidemics</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008954" MajorTopicYN="Y">Models, Biological</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D010838" MajorTopicYN="N">Phytophthora</DescriptorName><QualifierName UI="Q000302" MajorTopicYN="N">isolation & purification</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D010935" MajorTopicYN="Y">Plant Diseases</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D006113" MajorTopicYN="N">United Kingdom</DescriptorName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2011</Year><Month>02</Month><Day>24</Day></PubMedPubDate><PubMedPubDate PubStatus="revised"><Year>2012</Year><Month>01</Month><Day>11</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2012</Year><Month>01</Month><Day>13</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2012</Year><Month>2</Month><Day>7</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2012</Year><Month>2</Month><Day>7</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2012</Year><Month>6</Month><Day>26</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">22306763</ArticleId><ArticleId IdType="pii">S0025-5564(12)00006-5</ArticleId><ArticleId IdType="doi">10.1016/j.mbs.2012.01.004</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>France</li></country><region><li>Île-de-France</li></region><settlement><li>Jouy-en-Josas</li></settlement></list><tree><noCountry><name sortKey="Harwood, Tom" sort="Harwood, Tom" uniqKey="Harwood T" first="Tom" last="Harwood">Tom Harwood</name><name sortKey="Jeger, Mike J" sort="Jeger, Mike J" uniqKey="Jeger M" first="Mike J" last="Jeger">Mike J. Jeger</name><name sortKey="Pautasso, Marco" sort="Pautasso, Marco" uniqKey="Pautasso M" first="Marco" last="Pautasso">Marco Pautasso</name></noCountry><country name="France"><region name="Île-de-France"><name sortKey="Moslonka Lefebvre, Mathieu" sort="Moslonka Lefebvre, Mathieu" uniqKey="Moslonka Lefebvre M" first="Mathieu" last="Moslonka-Lefebvre">Mathieu Moslonka-Lefebvre</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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