PhD Defense Emanuele Del Fava - UHasselt

Title PhD dissertation: Statistical methods for modeling infectious diseases with applications to the epidemiology of drug-related and childhood infections

Promotor: Prof. dr. Ziv Shkedy

Abstract: This Phd focusses on three different topics, all of them related to the general topic of statistical modeling of infectious diseases.
The first part deals with modeling hepatitis C virus (HCV) and human immunodeficiency virus (HIV) infections in injecting drug users (IDUs). Using HCV and HIV cross-sectional prevalence data collected and provided by the EMCDDA, I investigated the co-infection between HCV and HIV in IDUs, both using individual and repeated population data. In the first case, I fitted a series of joint models in order to estimate the prevalence and the force of infection (FOI) of HCV and HIV infections, taking into account the hierarchical nature of data. In the second case, I estimated the prevalence of HCV and HIV infections at the population level over time, accounting for both clustering and overdispersion phenomena.
The second part deals with mixture modeling for infectious diseases. I developed a method to fit hierarchical Bayesian mixture models to antibody count data for childhood infections, in order to classify the individuals either as susceptible or as immune and to estimate the prevalence and the FOI, simultaneously, without using any given cut-off point. In such a way, it is possible to elicit more information from the data about the epidemiology of the studied infections, in comparison with the standard approach based only on current status data.
Finally, the third part of my PhD consists in my contribution to an ECDC project about modeling varicella zoster virus (VZV) infection in Europe.
The final aim of the project is to provide policy makers with some indications about the implementation of a VZV vaccine in Europe. My work is devoted to the estimation of important epidemiological parameters (prevalence, FOI, basic reproduction number R0 and vaccination threshold) using cross-sectional prevalence data from a number of European countries and to the evaluation of the impact of different contact matrices on these epidemiological parameters.

GENERAL INFORMATION
Sep 28, 2012

Location:
Hasselt University , Agoralaan - Building D , 3590 Diepenbeek
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DEL FAVA Emanuele