Estimating the impact of vaccination using age-time dependent incidence rates of hepatitis B

Abstract

The objective of this study is to model the age-time dependent incidence of hepatitis B while estimating the impact of vaccination. While stochastic models/time series have been used before to model hepatitis B cases in the absence of knowledge on the number of susceptibles, this paper proposes to use a method that fits into the generalized additive model framework. Generalized additive models with penalized regression splines are used to exploit the underlying continuity of both age and time in a flexible nonparametric way. Based on a unique case notification dataset, it is shown that the implemented immunization programme in Bulgaria resulted in a significant decrease in incidence for infants in their first year of life with 82% (79%-84%). Moreover, it is shown that conditional on an assumed baseline susceptibility percentage; a smooth force of infection profile can be obtained from which two local maxima were observed at ages 9 and 24.