title: Optimal pandemic influenza vaccine allocation strategies for the Canadian population.
abstract: BACKGROUND
  The world is currently confronting the first influenza pandemic of the 21(st) century. Influenza vaccination is an effective preventive measure, but the unique epidemiological features of swine-origin influenza A (H1N1) (pH1N1) introduce uncertainty as to the best strategy for prioritization of vaccine allocation. We sought to determine optimal prioritization of vaccine distribution among different age and risk groups within the Canadian population, to minimize influenza-attributable morbidity and mortality.
  
  
  RESULTS
  We developed a deterministic, age-structured compartmental model of influenza transmission, with key parameter values estimated from data collected during the initial phase of the epidemic in Ontario, Canada. We examined the effect of different vaccination strategies on attack rates, hospitalizations, intensive care unit admissions, and mortality. In all scenarios, prioritization of high-risk individuals (those with underlying chronic conditions and pregnant women), regardless of age, markedly decreased the frequency of severe outcomes. When individuals with underlying medical conditions were not prioritized and an age group-based approach was used, preferential vaccination of age groups at increased risk of severe outcomes following infection generally resulted in decreased mortality compared to targeting vaccine to age groups with higher transmission, at a cost of higher population-level attack rates. All simulations were sensitive to the timing of the epidemic peak in relation to vaccine availability, with vaccination having the greatest impact when it was implemented well in advance of the epidemic peak.
  
  
  CONCLUSIONS
  Our model simulations suggest that vaccine should be allocated to high-risk groups, regardless of age, followed by age groups at increased risk of severe outcomes. Vaccination may significantly reduce influenza-attributable morbidity and mortality, but the benefits are dependent on epidemic dynamics, time for program roll-out, and vaccine uptake.
authors.affiliation: Department of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.
authors.forename: Ashleigh R
authors.initials: AR
authors.lastname: Tuite
authors.forename: David N
authors.initials: DN
authors.lastname: Fisman
authors.forename: Jeffrey C
authors.initials: JC
authors.lastname: Kwong
authors.forename: Amy L
authors.initials: AL
authors.lastname: Greer
mesh_terms: D017677:Age Distribution; D002138:Calibration; D002170:Canada / Q000453:epidemiology; D004196:Disease Outbreaks / Q000191:economics* / Q000517:prevention & control*; D006297:Health Services Accessibility; D006760:Hospitalization / Q000706:statistics & numerical data; D006801:Humans; D053118:Influenza A Virus, H1N1 Subtype / Q000276:immunology; D007252:Influenza Vaccines / Q000191:economics* / Q000276:immunology*; D007251:Influenza, Human / Q000453:epidemiology* / Q000276:immunology / Q000401:mortality / Q000517:prevention & control*; D007362:Intensive Care Units / Q000706:statistics & numerical data; D018448:Models, Immunological; D040841:Resource Allocation / Q000191:economics*; D012307:Risk Factors; D012680:Sensitivity and Specificity; D013997:Time Factors; D016896:Treatment Outcome; D014611:Vaccination
chemical_list: D007252:Influenza Vaccines
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