title: Deriving effective vaccine allocation strategies for pandemic influenza: Comparison of an agent-based simulation and a compartmental model.
abstract: Individuals are prioritized based on their risk profiles when allocating limited vaccine stocks during an influenza pandemic. Computationally expensive but realistic agent-based simulations and fast but stylized compartmental models are typically used to derive effective vaccine allocation strategies. A detailed comparison of these two approaches, however, is often omitted. We derive age-specific vaccine allocation strategies to mitigate a pandemic influenza outbreak in Seattle by applying derivative-free optimization to an agent-based simulation and also to a compartmental model. We compare the strategies derived by these two approaches under various infection aggressiveness and vaccine coverage scenarios. We observe that both approaches primarily vaccinate school children, however they may allocate the remaining vaccines in different ways. The vaccine allocation strategies derived by using the agent-based simulation are associated with up to 70% decrease in total cost and 34% reduction in the number of infections compared to the strategies derived by using the compartmental model. Nevertheless, the latter approach may still be competitive for very low and/or very high infection aggressiveness. Our results provide insights about potential differences between the vaccine allocation strategies derived by using agent-based simulations and those derived by using compartmental models.
authors.affiliation: Department of Management Sciences, University of Waterloo, Waterloo, Ontario, Canada.
authors.forename: Özden O
authors.initials: ÖO
authors.lastname: Dalgıç
authors.affiliation: Edward P. Fitts Department of Industrial and Systems Engineering, North Carolina State University, Raleigh, North Carolina, United States of America.
authors.forename: Osman Y
authors.initials: OY
authors.lastname: Özaltın
authors.affiliation: Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario, Canada.|Grand River Hospital, Kitchener, Ontario, Canada.
authors.forename: William A
authors.initials: WA
authors.lastname: Ciccotelli
authors.affiliation: Department of Management Sciences, University of Waterloo, Waterloo, Ontario, Canada.
authors.forename: Fatih S
authors.initials: FS
authors.lastname: Erenay
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D002648:Child; D002675:Child, Preschool; D003198:Computer Simulation; D018562:Disease Transmission, Infectious / Q000706:statistics & numerical data; D006801:Humans; D007223:Infant; D007252:Influenza Vaccines / Q000600:supply & distribution*; D007251:Influenza, Human / Q000453:epidemiology / Q000517:prevention & control* / Q000635:transmission; D008875:Middle Aged; D008962:Models, Theoretical; D058873:Pandemics / Q000517:prevention & control*; D040841:Resource Allocation; D012306:Risk; D013597:Systems Analysis; D013997:Time Factors; D014505:Urban Population; D014861:Washington; D055815:Young Adult
chemical_list: D007252:Influenza Vaccines