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Semi-parametric estimation of age-time specific infection incidence from serial prevalence data
N Nagelkerke1, S Heisterkamp, M Borgdorff
1National Institute of Public Health and the Environment, Bilthoven, The Netherlands. nico.nagelkerke@rivm.nl
Abstract:
Many infections cause lasting detectable immune responses, whose prevalence can be estimated from cross-sectional surveys. However, such surveys do not provide direct information on the incidence of infection. We address the issue of estimating age and time specific incidence from a series of prevalence surveys under the assumption that incidence changes exponentially with time, but make no assumption about the age specific incidence. We show that these assumptions lead to a proportional hazards model and estimate its parameters using semi-parametric maximum likelihood methods. The method is applied to tuberculin surveys in The Netherlands to explore age dependence of the risk of tuberculous infection in the presence of a strong secular decline in this risk.
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