title: Modelling age-dependent force of infection from prevalence data using fractional polynomials.
abstract: The force of infection is one of the primary epidemiological parameters of infectious diseases. For many infectious diseases it is assumed that the force of infection is age-dependent. Although the force of infection can be estimated directly from a follow up study, it is much more common to have cross-sectional seroprevalence data from which the prevalence and the force of infection can be estimated. In this paper, we propose to model the force of infection within the framework of fractional polynomials. We discuss several parametric examples from the literature and show that all of these examples can be expressed as special cases of fractional polynomial models. We illustrate the method on five seroprevalence samples, two of Hepatitis A, and one of Rubella, Mumps and Varicella.
authors.affiliation: Center for Statistics, Limburgs Universitair Centrum, Universitaire Campus-gebouw D, B-3590 Diepenbeek, Belgium. ziv.shkedy@luc.ac.be
authors.forename: Z
authors.initials: Z
authors.lastname: Shkedy
authors.forename: M
authors.initials: M
authors.lastname: Aerts
authors.forename: G
authors.initials: G
authors.lastname: Molenberghs
authors.forename: Ph
authors.initials: P
authors.lastname: Beutels
authors.forename: P
authors.initials: P
authors.lastname: Van Damme
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D002648:Child; D002675:Child, Preschool; D003141:Communicable Diseases / Q000453:epidemiology* / Q000821:virology; D006801:Humans; D007223:Infant; D008875:Middle Aged; D015233:Models, Statistical; D015995:Prevalence; D016036:Seroepidemiologic Studies; D014777:Virus Diseases / Q000453:epidemiology