title: One versus two doses: What is the best use of vaccine in an influenza pandemic?
abstract: Avian influenza A (H7N9), emerged in China in April 2013, sparking fears of a new, highly pathogenic, influenza pandemic. In addition, avian influenza A (H5N1) continues to circulate and remains a threat. Currently, influenza H7N9 vaccines are being tested to be stockpiled along with H5N1 vaccines. These vaccines require two doses, 21 days apart, for maximal protection. We developed a mathematical model to evaluate two possible strategies for allocating limited vaccine supplies: a one-dose strategy, where a larger number of people are vaccinated with a single dose, or a two-dose strategy, where half as many people are vaccinated with two doses. We prove that there is a threshold in the level of protection obtained after the first dose, below which vaccinating with two doses results in a lower illness attack rate than with the one-dose strategy; but above the threshold, the one-dose strategy would be better. For reactive vaccination, we show that the optimal use of vaccine depends on several parameters, with the most important one being the level of protection obtained after the first dose. We describe how these vaccine dosing strategies can be integrated into effective pandemic control plans.
authors.affiliation: Center for Inference and Dynamics of Infectious Diseases, Seattle, WA, USA; Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA. Electronic address: laurama@fredhutch.org.
authors.forename: Laura
authors.initials: L
authors.lastname: Matrajt
authors.affiliation: Department of Mathematics, Stockholm University, Stockholm, Sweden.
authors.forename: Tom
authors.initials: T
authors.lastname: Britton
authors.affiliation: Center for Inference and Dynamics of Infectious Diseases, Seattle, WA, USA; Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA; Department of Biostatistics, University of Washington, Seattle, WA, USA.
authors.forename: M Elizabeth
authors.initials: ME
authors.lastname: Halloran
authors.affiliation: Department of Biostatistics, University of Washington, Seattle, WA, USA; Department of Biostatistics, University of Florida, Gainesville, FL, USA.
authors.forename: Ira M
authors.initials: IM
authors.lastname: Longini
mesh_terms: D004305:Dose-Response Relationship, Drug; D006801:Humans; D064766:Influenza A Virus, H7N9 Subtype / Q000276:immunology*; D007252:Influenza Vaccines / Q000276:immunology / Q000627:therapeutic use*; D007251:Influenza, Human / Q000453:epidemiology* / Q000276:immunology / Q000517:prevention & control*; D058873:Pandemics / Q000706:statistics & numerical data*
chemical_list: D007252:Influenza Vaccines
keywords: Infectious disease modeling; Influenza; Influenza vaccine; Mathematical model