Estimating the impact of vaccination using age-time-dependent incidence rates of hepatitis B
Epidemiology and Infection
Center for Statistics, Hasselt University, Campus Diepenbeek, Agoralaan 1, 3590 Diepenbeek, Belgium; Kenya Institute of Medical Research, Nairobi, Kenya; National Center of Infectious and Parasitic diseases, Department of Epidemiology, Sofia, Bulgaria; Centre for the Evaluation of Vaccination, Epidemiology and Community Medicine, University of Antwerp, Antwerp, Belgium
The objective of this study was 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 proposed using 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 non-parametric way. Based on a unique case notification dataset, we have 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, we have 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 years. © 2007 Cambridge University Press.
hepatitis B vaccine; age; article; Bulgaria; conceptual framework; health program; hepatitis B; human; immunization; incidence; infant; infection sensitivity; mathematical model; nonparametric test; regression analysis; risk reduction; sensitivity analysis; stochastic model; time series analysis; vaccination; Bulgaria; Communicable Disease Control; Hepatitis B; Hepatitis B Vaccines; Hepatitis B virus; Humans; Incidence; Models, Statistical; Vaccination