title: Pertussis models to inform vaccine policy.
abstract: Pertussis remains a challenging public health problem with many aspects of infection, disease and immunity poorly understood. Initially controlled by mass vaccination, pertussis resurgence has occurred in some countries with well-established vaccination programs, particularly among adolescents and young adults. Several studies have used mathematical models to investigate drivers of pertussis epidemiology and predict the likely impact of different vaccination strategies. We reviewed a number of these models to evaluate their suitability to answer questions of public health importance regarding optimal vaccine scheduling. We critically discuss the approaches adopted and the impact of chosen model structures and assumptions on study conclusions. Common limitations were a lack of contemporary, population relevant data for parameterization and a limited understanding of the relationship between infection and disease. We make recommendations for future model development and suggest epidemiologic data collections that would facilitate efforts to reduce uncertainty and improve the robustness of model-derived conclusions.
authors.affiliation: a Melbourne School of Population and Global Health; The University of Melbourne ; Parkville , Australia.
authors.forename: Patricia T
authors.initials: PT
authors.lastname: Campbell
authors.forename: James M
authors.initials: JM
authors.lastname: McCaw
authors.forename: Jodie
authors.initials: J
authors.lastname: McVernon
mesh_terms: D000293:Adolescent; D004812:Epidemiologic Methods; D006291:Health Policy; D006801:Humans; D007115:Immunization Schedule; D015233:Models, Statistical; D014917:Whooping Cough / Q000453:epidemiology* / Q000517:prevention & control*; D055815:Young Adult
keywords: AIC, Akaike information criterion; E, infected but not yet infectious compartment; I, infectious compartment; POLYMOD, European Union funded project; R, removed/immune compartment; S, susceptible compartment; UK, United Kingdom; US, United States; W, waned immunity compartment; WAIFW, who acquires infection from whom; WHO, World Health Organization; infectious disease dynamics; mathematical modeling; pertussis; transmission; vaccines; λ or FOI, force of infection