Flexible statistical models for microbial risk assessment and infectious diseases

Abstract

The main area of work of this thesis was using data and mathematical and/or statistical models to estimate risks and trends as well as to identify risk factors associated with some bacterial and viral microbial agents in order to enable epidemiologists to improve the understanding of the epidemiology of these infectious diseases and evaluate the impact of intervention programmes against the diseases. It weaves together different research problems and depending on the data at hand different aspects regarding the statistical methods are emphasized. The thesis is divided into three parts which deal, respectively, with modeling data on infectious diseases of humans, dose response models for foodborne infectious diseases and identifying risk factors for Salmonella infection in Belgian chicken flocks. How the various modeling techniques have been integrated into these parts is explained in the following sections.