Statistical Modelling 10 (2010), 6987
Causal hidden variable model of pathogenic contamination from pig to pork
Jukka Ranta
Risk Assessment Unit
Finnish Food Safety Authority Evira
Mustialankatu 3
FI00790 Helsinki
Finland
eMail: jukka.ranta@evira.fi
Kirsi-Maarit Siekkinen
Risk Assessment Unit
Finnish Food Safety Authority Evira
Helsinki
Finland
Lasse Nuotio
Centre for Military Medicine, and for Biological Threat Preparedness
Finnish Defence Forces
Riikka Laukkanen, Sanna Hellström, Hannu Korkeala, and Riitta Maijala
Department of Food, Hygiene and Environmental Health
Faculty of Veterinary Medicine
University of Helsinki
Abstract:
Risk assessments relating to food safety over more than one step
along a production chain are frequently hampered by lack of
detailed quantitative data. This study set out to develop a
Bayesian hidden variable model to integrate available limited
data of the combined occurrence of three bacterial pathogens,
Listeria monocytogenes, Yersinia enterocolitica and Yersinia
pseudotuberculosis, with causal assumptions along three steps
of pork production chain. The pathogen occurrence data were
animal specific both on conventional and organic pig farms
and at the abattoir, but merely farm specific at meat cutting
plants. The model was able to incorporate all data concerning
different types of testing at different steps of the chain,
and missing data values were dealt with in a straightforward
manner. It provides a tool for quantitative risk assessments
and for estimating the causal risk mitigation effects by
combining external data with the specific follow-up data.
Intervention effects are provided with Bayesian credible
intervals indicating the uncertainty due to all information
sources included in the model. Combined prevalence in Finnish
pork was estimated to be 1–11% and it could be reduced to 0–2%
if head was removed intact and rectum sealed off.
Keywords:
Bayesian causal model; food safety; Listeria; pork production;
risk assessment; Yersinia
Downloads:
Example data, Matlab- and WinBugs-code in
zipped archive.
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