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Bayesian model for tracing Salmonella contamination in the pig feed chain
- Source :
- Food Microbiology. 71:82-92
- Publication Year :
- 2018
- Publisher :
- Elsevier BV, 2018.
-
Abstract
- Salmonella infections in pigs are in most cases asymptomatic, posing a risk of salmonellosis for pork consumers. Salmonella can transmit to pigs from various sources, including contaminated feed. We present an approach for quantifying the risk to pigs from contaminations in the feed chain, based on a Bayesian model. The model relies on Salmonella surveillance data and other information from surveys, reports, registries, statistics, legislation and literature regarding feed production and pig farming. Uncertainties were probabilistically quantified by synthesizing evidence from the available information over a categorically structured flow chain of ingredients mixed for feeds served to pigs. Model based probability for infection from feeds together with Salmonella subtyping data, were used to estimate the proportion of Salmonella infections in pigs attributable to feed. The results can be further used in assessments considering the human health risk linked to animal feed via livestock. The presented methods can be used to predict the effect of changes in the feed chain, and they are generally applicable to other animals and pathogens.
- Subjects :
- 0301 basic medicine
Salmonella
Swine
040301 veterinary sciences
Animal feed
030106 microbiology
Food Contamination
Tracing
Biology
medicine.disease_cause
Bayesian inference
Microbiology
0403 veterinary science
03 medical and health sciences
medicine
Animals
Pig farming
Swine Diseases
Salmonella Infections, Animal
business.industry
Bayes Theorem
04 agricultural and veterinary sciences
Contamination
Animal Feed
Subtyping
Biotechnology
Livestock
business
Food Science
Subjects
Details
- ISSN :
- 07400020
- Volume :
- 71
- Database :
- OpenAIRE
- Journal :
- Food Microbiology
- Accession number :
- edsair.doi.dedup.....6ea7a4101bf8e1dc4e9583501d5df9ca
- Full Text :
- https://doi.org/10.1016/j.fm.2017.04.017