title: Strategies for pandemic and seasonal influenza vaccination of schoolchildren in the United States.
abstract: Vaccinating school-aged children against influenza can reduce age-specific and population-level illness attack rates. Using a stochastic simulation model of influenza transmission, the authors assessed strategies for vaccinating children in the United States, varying the vaccine type, coverage level, and reproductive number R (average number of secondary cases produced by a typical primary case). Results indicated that vaccinating children can substantially reduce population-level illness attack rates over a wide range of scenarios. The greatest absolute reduction in influenza illness cases per season occurred at R values ranging from 1.2 to 1.6 for a given vaccine coverage level. The indirect, total, and overall effects of vaccinating children were strong when transmission intensity was low to intermediate. The indirect effects declined rapidly as transmission intensity increased. In a mild influenza season (R = 1.1), approximately 19 million influenza cases could be prevented by vaccinating 70% of children. At most, nearly 100 million cases of influenza illness could be prevented, depending on the proportion of children vaccinated and the transmission intensity. Given the current worldwide threat of novel influenza A (H1N1), with an estimated R of 1.4-1.6, health officials should consider strategies for vaccinating children against novel influenza A (H1N1) as well as seasonal influenza.
authors.affiliation: Department of Epidemiology,School of Public Health, University of Washington, Seattle,Washington, USA.
authors.forename: Nicole E
authors.initials: NE
authors.lastname: Basta
authors.forename: Dennis L
authors.initials: DL
authors.lastname: Chao
authors.forename: M Elizabeth
authors.initials: ME
authors.lastname: Halloran
authors.forename: Laura
authors.initials: L
authors.lastname: Matrajt
authors.forename: Ira M
authors.initials: IM
authors.lastname: Longini
mesh_terms: D000293:Adolescent; D002140:California / Q000453:epidemiology; D002648:Child; D003198:Computer Simulation; D004196:Disease Outbreaks / Q000517:prevention & control* / Q000706:statistics & numerical data; D006801:Humans; D017589:Immunization Programs / Q000379:methods* / Q000706:statistics & numerical data; D053118:Influenza A Virus, H1N1 Subtype / Q000276:immunology*; D007252:Influenza Vaccines; D007251:Influenza, Human / Q000453:epidemiology / Q000517:prevention & control* / Q000635:transmission; D032541:Mass Vaccination / Q000706:statistics & numerical data; D015233:Models, Statistical; D011634:Public Health; D012574:Schools; D012621:Seasons; D013269:Stochastic Processes; D013334:Students; D013997:Time Factors; D014481:United States
chemical_list: D007252:Influenza Vaccines
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