Mathematical and Statistical Methods for Microbial Risk Assessment and infectious disease modeling. (R-1319)

This doctoral dissertation is motivated by the interdisciplinary METZOON-project (R-04/003-METZOON) funded by the Belgian government. METZOON is an acronym for the development of a methodology for quantitative assessment of zoonotic risks in Belgium applied to Salmonella in pork. The main objective of the project is the development of a quantitative microbial risk assessment (QMRA) to assess the risk for human salmonellosis through consumption of pork that allows testing mitigation strategies by means of 'what-if' scenario analysis. This dissertation presents the newly developed QMRA as well as the scenario analysis. An important aspect of quantifying microbial risk is the assessment of the dosis-response relationship, which is the relationship between the amount of microbial organisms ingested and a specific outcome, like infection or illness. We developed a new dosis-illness model for human salmonellosis using outbreak data taking into account different sources of heterogeneity as well as data uncertainty. Additionally, we proposed new statistical methodology to support QMRA's. In particular, we proposed estimating epidemiological parameters directly from serological data making use of underlying mixture models. Finally, we also present epidemiological applications of quantile regression and propose several methodological extensions to estimate (a) smooth isotone quantile curves, (b) smooth quantile surfaces and (c) smooth non-crossing quantile curves.

Keywords:ASSESSMENT, RISK

Disciplines:Information and computing sciences, Biological sciences, Computer engineering, information technology and mathematical engineering, Basic sciences, Clinical sciences, Health sciences, Translational sciences