Optimization of control strategies for epidemics in heterogeneous populations with symmetric and asymmetric transmission.
Identifieur interne : 001867 ( Main/Exploration ); précédent : 001866; suivant : 001868Optimization of control strategies for epidemics in heterogeneous populations with symmetric and asymmetric transmission.
Auteurs : Martial L Ndeffo Mbah [Royaume-Uni] ; Christopher A. GilliganSource :
- Journal of theoretical biology [ 1095-8541 ] ; 2010.
Descripteurs français
- KwdFr :
- Animaux (MeSH), Arbres (génétique), Contrôle des maladies transmissibles (MeSH), Facteurs temps (MeSH), Humains (MeSH), Interactions hôte-pathogène (MeSH), Maladies des plantes (génétique), Modèles biologiques (MeSH), Modèles théoriques (MeSH), Phytophthora (génétique), Spécificité d'espèce (MeSH), Umbellularia (MeSH), Écosystème (MeSH), Épidémies de maladies (MeSH).
- MESH :
English descriptors
- KwdEn :
- Animals (MeSH), Communicable Disease Control (MeSH), Disease Outbreaks (MeSH), Ecosystem (MeSH), Host-Pathogen Interactions (MeSH), Humans (MeSH), Models, Biological (MeSH), Models, Theoretical (MeSH), Phytophthora (genetics), Plant Diseases (genetics), Species Specificity (MeSH), Time Factors (MeSH), Trees (genetics), Umbellularia (MeSH).
- MESH :
Abstract
There is growing interest in incorporating economic factors into epidemiological models in order to identify optimal strategies for disease control when resources are limited. In this paper we consider how to optimize the control of a pathogen that is capable of infecting multiple hosts with different rates of transmission within and between species. Our objective is to find control strategies that maximize the discounted number of healthy individuals. We consider two classes of host-pathogen system, comprising two host species and a common pathogen, one with asymmetrical and the other with symmetrical transmission rates, applicable to a wide range of SI (susceptible-infected) epidemics of plant and animal pathogens. We motivate the analyses with an example of sudden oak death in California coastal forests, caused by Phytophthora ramorum, in communities dominated by bay laurel (Umbellularia californica) and tanoak (Lithocarpus densiflorus). We show for the asymmetric case that it is optimal to give priority in treating disease to the more infectious species, and to treat the other species only when there are resources left over. For the symmetric case, we show that although a switching strategy is an optimum, in which preference is first given to the species with the lower level of susceptibles and then to the species with the higher level of susceptibles, a simpler strategy that favors treatment of infected hosts for the more susceptible species is a robust alternative for practical application when the optimal switching time is unknown. Finally, since transmission rates are notoriously difficult to estimate, we analyze the robustness of the strategies when the true state with respect to symmetry or otherwise is unknown but one or other is assumed.
DOI: 10.1016/j.jtbi.2009.11.001
PubMed: 19900466
Affiliations:
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In this paper we consider how to optimize the control of a pathogen that is capable of infecting multiple hosts with different rates of transmission within and between species. Our objective is to find control strategies that maximize the discounted number of healthy individuals. We consider two classes of host-pathogen system, comprising two host species and a common pathogen, one with asymmetrical and the other with symmetrical transmission rates, applicable to a wide range of SI (susceptible-infected) epidemics of plant and animal pathogens. We motivate the analyses with an example of sudden oak death in California coastal forests, caused by Phytophthora ramorum, in communities dominated by bay laurel (Umbellularia californica) and tanoak (Lithocarpus densiflorus). We show for the asymmetric case that it is optimal to give priority in treating disease to the more infectious species, and to treat the other species only when there are resources left over. For the symmetric case, we show that although a switching strategy is an optimum, in which preference is first given to the species with the lower level of susceptibles and then to the species with the higher level of susceptibles, a simpler strategy that favors treatment of infected hosts for the more susceptible species is a robust alternative for practical application when the optimal switching time is unknown. Finally, since transmission rates are notoriously difficult to estimate, we analyze the robustness of the strategies when the true state with respect to symmetry or otherwise is unknown but one or other is assumed.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">19900466</PMID><DateCompleted><Year>2010</Year><Month>06</Month><Day>08</Day></DateCompleted><DateRevised><Year>2019</Year><Month>10</Month><Day>08</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1095-8541</ISSN><JournalIssue CitedMedium="Internet"><Volume>262</Volume><Issue>4</Issue><PubDate><Year>2010</Year><Month>Feb</Month><Day>21</Day></PubDate></JournalIssue><Title>Journal of theoretical biology</Title><ISOAbbreviation>J Theor Biol</ISOAbbreviation></Journal><ArticleTitle>Optimization of control strategies for epidemics in heterogeneous populations with symmetric and asymmetric transmission.</ArticleTitle><Pagination><MedlinePgn>757-63</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1016/j.jtbi.2009.11.001</ELocationID><Abstract><AbstractText>There is growing interest in incorporating economic factors into epidemiological models in order to identify optimal strategies for disease control when resources are limited. In this paper we consider how to optimize the control of a pathogen that is capable of infecting multiple hosts with different rates of transmission within and between species. Our objective is to find control strategies that maximize the discounted number of healthy individuals. We consider two classes of host-pathogen system, comprising two host species and a common pathogen, one with asymmetrical and the other with symmetrical transmission rates, applicable to a wide range of SI (susceptible-infected) epidemics of plant and animal pathogens. We motivate the analyses with an example of sudden oak death in California coastal forests, caused by Phytophthora ramorum, in communities dominated by bay laurel (Umbellularia californica) and tanoak (Lithocarpus densiflorus). We show for the asymmetric case that it is optimal to give priority in treating disease to the more infectious species, and to treat the other species only when there are resources left over. For the symmetric case, we show that although a switching strategy is an optimum, in which preference is first given to the species with the lower level of susceptibles and then to the species with the higher level of susceptibles, a simpler strategy that favors treatment of infected hosts for the more susceptible species is a robust alternative for practical application when the optimal switching time is unknown. Finally, since transmission rates are notoriously difficult to estimate, we analyze the robustness of the strategies when the true state with respect to symmetry or otherwise is unknown but one or other is assumed.</AbstractText><CopyrightInformation>(c) 2009 Elsevier Ltd. All rights reserved.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Mbah</LastName><ForeName>Martial L Ndeffo</ForeName><Initials>ML</Initials><AffiliationInfo><Affiliation>Department of Plant Sciences, University of Cambridge, Downing Street, Cambridge CB2 3EA, UK. mln25@cam.ac.uk</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Gilligan</LastName><ForeName>Christopher A</ForeName><Initials>CA</Initials></Author></AuthorList><Language>eng</Language><GrantList CompleteYN="Y"><Grant><GrantID>BB/B502379/1</GrantID><Agency>Biotechnology and Biological Sciences Research Council</Agency><Country>United Kingdom</Country></Grant></GrantList><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2009</Year><Month>11</Month><Day>10</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>J Theor Biol</MedlineTA><NlmUniqueID>0376342</NlmUniqueID><ISSNLinking>0022-5193</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000818" MajorTopicYN="N">Animals</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D003140" MajorTopicYN="Y">Communicable Disease Control</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D004196" MajorTopicYN="N">Disease Outbreaks</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D017753" MajorTopicYN="N">Ecosystem</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D054884" MajorTopicYN="N">Host-Pathogen Interactions</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008954" MajorTopicYN="N">Models, Biological</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008962" MajorTopicYN="N">Models, Theoretical</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D010838" MajorTopicYN="N">Phytophthora</DescriptorName><QualifierName UI="Q000235" MajorTopicYN="N">genetics</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D010935" MajorTopicYN="N">Plant Diseases</DescriptorName><QualifierName UI="Q000235" MajorTopicYN="Y">genetics</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D013045" MajorTopicYN="N">Species Specificity</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D013997" MajorTopicYN="N">Time Factors</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D014197" MajorTopicYN="N">Trees</DescriptorName><QualifierName UI="Q000235" MajorTopicYN="N">genetics</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D027422" MajorTopicYN="N">Umbellularia</DescriptorName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2009</Year><Month>08</Month><Day>19</Day></PubMedPubDate><PubMedPubDate PubStatus="revised"><Year>2009</Year><Month>10</Month><Day>23</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2009</Year><Month>11</Month><Day>02</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2009</Year><Month>11</Month><Day>11</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2009</Year><Month>11</Month><Day>11</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2010</Year><Month>6</Month><Day>9</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">19900466</ArticleId><ArticleId IdType="pii">S0022-5193(09)00527-X</ArticleId><ArticleId IdType="doi">10.1016/j.jtbi.2009.11.001</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>Royaume-Uni</li></country><region><li>Angleterre</li><li>Angleterre de l'Est</li></region><settlement><li>Cambridge</li></settlement><orgName><li>Université de Cambridge</li></orgName></list><tree><noCountry><name sortKey="Gilligan, Christopher A" sort="Gilligan, Christopher A" uniqKey="Gilligan C" first="Christopher A" last="Gilligan">Christopher A. Gilligan</name></noCountry><country name="Royaume-Uni"><region name="Angleterre"><name sortKey="Mbah, Martial L Ndeffo" sort="Mbah, Martial L Ndeffo" uniqKey="Mbah M" first="Martial L Ndeffo" last="Mbah">Martial L Ndeffo Mbah</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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