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Article: Robust parameter estimation techniques for stochastic within-host macroparasite models

TitleRobust parameter estimation techniques for stochastic within-host macroparasite models
Authors
Issue Date2003
PublisherAcademic Press. The Journal's web site is located at http://www.elsevier.com/locate/yjtbi
Citation
Journal Of Theoretical Biology, 2003, v. 225 n. 4, p. 419-430 How to Cite?
AbstractWe present a stochastic model of the within-host population dynamics of lymphatic filariasis, and use a simulated goodness-of-fit (GOF) method to estimate immunological parameters and their confidence intervals from experimental data. A variety of deterministic moment closure approximations to the stochastic system are explored and compared with simulation results. For the maximum GOF parameter estimates, none of the methods of closure accurately reproduce the behaviour of the stochastic model. However, direct analysis of the stochastic model demonstrates that the high levels of variation observed in the data can be reproduced without requiring parameters to vary between hosts. This indicates that the observed aggregation of parasite load may be dynamically generated by random variation in the development of an effective immune response against parasite larvae. © 2003 Elsevier Ltd. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/151586
ISSN
2015 Impact Factor: 2.049
2015 SCImago Journal Rankings: 1.089
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorRiley, Sen_US
dc.contributor.authorDonnelly, CAen_US
dc.contributor.authorFerguson, NMen_US
dc.date.accessioned2012-06-26T06:25:00Z-
dc.date.available2012-06-26T06:25:00Z-
dc.date.issued2003en_US
dc.identifier.citationJournal Of Theoretical Biology, 2003, v. 225 n. 4, p. 419-430en_US
dc.identifier.issn0022-5193en_US
dc.identifier.urihttp://hdl.handle.net/10722/151586-
dc.description.abstractWe present a stochastic model of the within-host population dynamics of lymphatic filariasis, and use a simulated goodness-of-fit (GOF) method to estimate immunological parameters and their confidence intervals from experimental data. A variety of deterministic moment closure approximations to the stochastic system are explored and compared with simulation results. For the maximum GOF parameter estimates, none of the methods of closure accurately reproduce the behaviour of the stochastic model. However, direct analysis of the stochastic model demonstrates that the high levels of variation observed in the data can be reproduced without requiring parameters to vary between hosts. This indicates that the observed aggregation of parasite load may be dynamically generated by random variation in the development of an effective immune response against parasite larvae. © 2003 Elsevier Ltd. All rights reserved.en_US
dc.languageengen_US
dc.publisherAcademic Press. The Journal's web site is located at http://www.elsevier.com/locate/yjtbien_US
dc.relation.ispartofJournal of Theoretical Biologyen_US
dc.subject.meshAnimalsen_US
dc.subject.meshBrugia Pahangi - Physiologyen_US
dc.subject.meshComputer Simulationen_US
dc.subject.meshElephantiasis, Filarial - Immunologyen_US
dc.subject.meshHost-Parasite Interactionsen_US
dc.subject.meshLarvaen_US
dc.subject.meshModels, Immunologicalen_US
dc.subject.meshPopulation Dynamicsen_US
dc.subject.meshStochastic Processesen_US
dc.titleRobust parameter estimation techniques for stochastic within-host macroparasite modelsen_US
dc.typeArticleen_US
dc.identifier.emailRiley, S:sriley@hkucc.hku.hk, steven.riley@hku.hken_US
dc.identifier.authorityRiley, S=rp00511en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1016/S0022-5193(03)00266-2en_US
dc.identifier.pmid14615200-
dc.identifier.scopuseid_2-s2.0-0242690987en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0242690987&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume225en_US
dc.identifier.issue4en_US
dc.identifier.spage419en_US
dc.identifier.epage430en_US
dc.identifier.isiWOS:000186790400001-
dc.publisher.placeUnited Kingdomen_US
dc.identifier.scopusauthoridRiley, S=7102619416en_US
dc.identifier.scopusauthoridDonnelly, CA=35468127900en_US
dc.identifier.scopusauthoridFerguson, NM=7103246319en_US

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