Abstract
This chapter discusses several parametric models for the seroprevalence and the force of infection. In the first section we give a brief historical overview of the first parametric models used to model the force of infection, including polynomial and nonlinear models. In the second section we introduce the family of fractional polynomials as a natural extension of polynomial models, circumventing some of the limitations inherent to classical polynomials. These models can be easily fitted to seroprevalence data with R or, e.g., SAS. As usual, we focus on the use of R, with the functions glm and mle. SAS offers similar functionality with the GENMOD and NLMIXED procedure.
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© 2012 Springer Science+Business Media New York
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Hens, N., Shkedy, Z., Aerts, M., Faes, C., Van Damme, P., Beutels, P. (2012). Parametric Approaches to Model the Prevalence and Force of Infection. In: Modeling Infectious Disease Parameters Based on Serological and Social Contact Data. Statistics for Biology and Health, vol 63. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-4072-7_6
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DOI: https://doi.org/10.1007/978-1-4614-4072-7_6
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Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-4071-0
Online ISBN: 978-1-4614-4072-7
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