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Article: Optimization of influenza vaccine selection

TitleOptimization of influenza vaccine selection
Authors
KeywordsDynamic Programming
Health Care
Issue Date2005
PublisherI N F O R M S. The Journal's web site is located at http://or.pubs.informs.org
Citation
Operations Research, 2005, v. 53 n. 3, p. 456-476 How to Cite?
AbstractThe World Health Organization (WHO) recommends which strains of influenza to include in each year's vaccine to countries around the globe. The current WHO strategy attempts to match the vaccine strains with the expected upcoming epidemic strains, a strategy we refer to as the follow policy. The recently proposed antigenic distance hypothesis suggests that vaccine efficacy can be enhanced by taking into account the antigenic histories of vaccinees. To assess the potential benefit of history-based vaccination, we formulate the annual vaccine-strains selection problem as a stochastic dynamic program using the theory of shape space, which maps each vaccine and epidemic strain into a point in multidimensional space. Computational results show that a near-optimal policy can be derived by approximating the entire antigenic history by a single reduced historical strain, and then solving the multiperiod problem myopically, as a series of single-period problems. The modest suboptimality of the follow policy, together with our current inability to quantitatively link the model's objective function (a measure of cross-reactivity) with actual vaccine efficacy, leads us to recommend the continued use of the follow policy. © 2005 INFORMS.
Persistent Identifierhttp://hdl.handle.net/10722/151612
ISSN
2014 Impact Factor: 1.743
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorWu, JTen_US
dc.contributor.authorWein, LMen_US
dc.contributor.authorPerelson, ASen_US
dc.date.accessioned2012-06-26T06:25:27Z-
dc.date.available2012-06-26T06:25:27Z-
dc.date.issued2005en_US
dc.identifier.citationOperations Research, 2005, v. 53 n. 3, p. 456-476en_US
dc.identifier.issn0030-364Xen_US
dc.identifier.urihttp://hdl.handle.net/10722/151612-
dc.description.abstractThe World Health Organization (WHO) recommends which strains of influenza to include in each year's vaccine to countries around the globe. The current WHO strategy attempts to match the vaccine strains with the expected upcoming epidemic strains, a strategy we refer to as the follow policy. The recently proposed antigenic distance hypothesis suggests that vaccine efficacy can be enhanced by taking into account the antigenic histories of vaccinees. To assess the potential benefit of history-based vaccination, we formulate the annual vaccine-strains selection problem as a stochastic dynamic program using the theory of shape space, which maps each vaccine and epidemic strain into a point in multidimensional space. Computational results show that a near-optimal policy can be derived by approximating the entire antigenic history by a single reduced historical strain, and then solving the multiperiod problem myopically, as a series of single-period problems. The modest suboptimality of the follow policy, together with our current inability to quantitatively link the model's objective function (a measure of cross-reactivity) with actual vaccine efficacy, leads us to recommend the continued use of the follow policy. © 2005 INFORMS.en_US
dc.languageengen_US
dc.publisherI N F O R M S. The Journal's web site is located at http://or.pubs.informs.orgen_US
dc.relation.ispartofOperations Researchen_US
dc.subjectDynamic Programmingen_US
dc.subjectHealth Careen_US
dc.titleOptimization of influenza vaccine selectionen_US
dc.typeArticleen_US
dc.identifier.emailWu, JT:joewu@hkucc.hku.hken_US
dc.identifier.authorityWu, JT=rp00517en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1287/opre.1040.0143en_US
dc.identifier.scopuseid_2-s2.0-25144505774en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-25144505774&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume53en_US
dc.identifier.issue3en_US
dc.identifier.spage456en_US
dc.identifier.epage476en_US
dc.identifier.isiWOS:000230321200006-
dc.publisher.placeUnited Statesen_US
dc.identifier.scopusauthoridWu, JT=7409256423en_US
dc.identifier.scopusauthoridWein, LM=35560766400en_US
dc.identifier.scopusauthoridPerelson, AS=7102363214en_US

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