title: Economics of influenza vaccine administration timing for children.
abstract: OBJECTIVE
  To determine how much should be invested each year to encourage and operationalize the administration of influenza vaccine to children before November and how late the vaccine should be offered each year.
  
  
  METHODS
  Monte Carlo decision analytic computer simulation models.
  
  
  METHODS
  The children's influenza vaccination timing model quantified the incremental economic value of vaccinating a child earlier in the influenza season and the incremental cost of delaying vaccination. The children's monthly influenza vaccination decision model evaluated the cost-effectiveness of vaccinating versus not vaccinating for every month of the influenza season.
  
  
  RESULTS
  Getting children vaccinated by the end of October rather than when they are currently getting vaccinated could save society between $6.4 million and $9.2 million plus 653 and 926 quality-adjusted life-years (QALYs) and third-party payers between $4.1 million and $6.1 million plus 647 to 942 QALYs each year. Decision makers may want to continue offering influenza vaccination to children at least through the end of December. Vaccinating with trivalent inactivated virus vaccine was more cost-effective than vaccinating with live attenuated influenza vaccine for every month.
  
  
  CONCLUSIONS
  Policymakers could invest up to $6 million to $9 million a year to get children vaccinated in September or October without expending any net costs.
authors.affiliation: Public Health Computation and Operations Research (PHICOR) Group, University of Pittsburgh, Pittsburgh, PA 15213, USA. byl1@pitt.edu
authors.forename: Bruce Y
authors.initials: BY
authors.lastname: Lee
authors.forename: Julie H Y
authors.initials: JH
authors.lastname: Tai
authors.forename: Rachel R
authors.initials: RR
authors.lastname: Bailey
authors.forename: Kenneth J
authors.initials: KJ
authors.lastname: Smith
authors.forename: Andrew J
authors.initials: AJ
authors.lastname: Nowalk
mesh_terms: D000293:Adolescent; D000367:Age Factors; D002648:Child; D002675:Child, Preschool; D003198:Computer Simulation; D003362:Cost-Benefit Analysis; D003661:Decision Support Techniques; D005260:Female; D006801:Humans; D007115:Immunization Schedule; D053118:Influenza A Virus, H1N1 Subtype / Q000276:immunology*; D007252:Influenza Vaccines / Q000008:administration & dosage / Q000191:economics*; D007251:Influenza, Human / Q000453:epidemiology / Q000517:prevention & control*; D008297:Male; D009010:Monte Carlo Method; D019057:Quality-Adjusted Life Years; D012621:Seasons; D012680:Sensitivity and Specificity; D013997:Time Factors; D014611:Vaccination
chemical_list: D007252:Influenza Vaccines