Article: Optimization of influenza vaccine selection
| Title | Optimization of influenza vaccine selection |
|---|---|
| Authors | Wu, JT2 3 Wein, LM1 Perelson, AS |
| Keywords | Dynamic Programming Health Care |
| Issue Date | 2005 |
| Publisher | I 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?] DOI: http://dx.doi.org/10.1287/opre.1040.0143 |
| Abstract | The 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. |
| ISSN | 0030-364X 2011 Impact Factor: 1.665 2011 SCImago Journal Rankings: 0.073 |
| DOI | http://dx.doi.org/10.1287/opre.1040.0143 |
| ISI Accession Number ID | WOS:000230321200006 |
| References | References in Scopus |
| dc.contributor.author | Wu, JT |
|---|---|
| dc.contributor.author | Wein, LM |
| dc.contributor.author | Perelson, AS |
| dc.date.accessioned | 2012-06-26T06:25:27Z |
| dc.date.available | 2012-06-26T06:25:27Z |
| dc.date.issued | 2005 |
| dc.description.abstract | The 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. |
| dc.description.nature | Link_to_subscribed_fulltext |
| dc.identifier.citation | Operations Research, 2005, v. 53 n. 3, p. 456-476 [How to Cite?] DOI: http://dx.doi.org/10.1287/opre.1040.0143 |
| dc.identifier.doi | http://dx.doi.org/10.1287/opre.1040.0143 |
| dc.identifier.epage | 476 |
| dc.identifier.isi | WOS:000230321200006 |
| dc.identifier.issn | 0030-364X 2011 Impact Factor: 1.665 2011 SCImago Journal Rankings: 0.073 |
| dc.identifier.issue | 3 |
| dc.identifier.scopus | eid_2-s2.0-25144505774 |
| dc.identifier.spage | 456 |
| dc.identifier.uri | http://hdl.handle.net/10722/151612 |
| dc.identifier.volume | 53 |
| dc.language | eng |
| dc.publisher | I N F O R M S. The Journal's web site is located at http://or.pubs.informs.org |
| dc.publisher.place | United States |
| dc.relation.ispartof | Operations Research |
| dc.relation.references | References in Scopus |
| dc.subject | Dynamic Programming |
| dc.subject | Health Care |
| dc.title | Optimization of influenza vaccine selection |
| dc.type | Article |
Author Affiliations
- Stanford University
- Georgia Institute of Technology
- Los Alamos National Laboratory