An analysis of pediatric vaccine formulary selection problems

Shane N. Hall, Sheldon H. Jacobson, Edward C. Sewell

Research output: Contribution to journalArticlepeer-review

Abstract

Vaccination against infectious disease is hailed as one of the great achievements in public health. However, the United States Recommended Childhood Immunization Schedule is becoming increasingly complex as it is expanded to cover additional diseases. Moreover, biotechnology advances have allowed vaccine manufacturers to create combination vaccines that immunize against several diseases in a single injection. All these factors are creating a combinatorial explosion of alternatives and choices (each with a different cost) for public health policy makers, pediatricians, and parents/guardians (each with a different perspective). The General Vaccine Formulary Selection Problem (GVFSP) is introduced to model general childhood immunization schedules that can be used to illuminate these alternatives and choices by selecting a vaccine formulary that minimizes the cost of fully immunizing a child and the amount of extraimmunization. Both exact algorithms and heuristics for GVFSP are presented. A computational comparison of these algorithms and heuristics is presented, for the 2006 Recommended Childhood Immunization Schedule, as well as several randomly generated childhood immunization schedules that are likely to be representative of future childhood immunization schedules. The results reported here provide both fundamental insights into the structure of the GVFSP models and algorithms and practical value for the public health community.

Original languageEnglish (US)
Pages (from-to)1348-1365
Number of pages18
JournalOperations Research
Volume56
Issue number6
DOIs
StatePublished - Nov 1 2008

Keywords

  • Analysis of algorithms: computational complexity
  • Health care: pediatric immunization, vaccines
  • Programming: integer algorithms, heuristics, dynamic

ASJC Scopus subject areas

  • Computer Science Applications
  • Management Science and Operations Research

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