Title
Mathematical and Statistical Methods for Microbial Risk Assessment and infectious disease modeling. (Research)
Abstract
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.
Period of project
04 May 2008 - 31 March 2009