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COST ACTION 920 |
Inventory of QMRA Studies in Europe |
Data sheet
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Pathogen |
Salmonella |
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Country or region |
The Netherlands |
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Transmission route |
From |
Pigs |
To |
Carcasses |
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Specific product(s) |
Pork |
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End-point(s) |
Cost-effectiveness of control on prevalence in different stages of the pork chain (prevalence of Salmonella in the pork chain) |
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Reports or publications
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Bibliographic reference |
-
M.A.
van der Gaag, 2004. Epidemiological and
economic simulation of Salmonella in the pork supply chain. PhD thesis ISBN
90-5808-973-8 -
M.A.
van der Gaag, F. Vos, H.W. Saatkamp , M.van Boven, P. van Beek and R. B.M.
Huirne, 2004. A state-transition
simulation model for the spread of Salmonella in the pork supply chain
European Journal of Operational Research, 156-3:1 ,pp 782-798 -
M.A.
van der Gaag, H.W. Saatkamp, G.B.C. Backus, P. van Beek and R.B.M. Huirne,
2004. Cost-effectiveness of
controlling Salmonella in the pork chain -
M.A.
van der Gaag and R.B.M. Huirne, 2002. Elicitation
of expert knowledge on controlling Salmonella in the pork chain Journal on
Chain and Network Science 2-2, pp. 135-147 - Several conference papers |
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Abstract |
Pork can be regarded as an important source for food borne salmonellosis. Salmonella bacteria can be introduced and spread in every stage of the pork supply chain and cause a risk for food safety. The objective of this research is to gain insight into the epidemiological and economic effects of different strategies in the finishing, transport, lairage and slaughtering stages to improve the food safety of pork with respect to Salmonella. To collect information on possible control measures and on details of the course of infection and contamination, a survey among experts in the Netherlands and Denmark was carried out. The knowledge about the interaction and relations between the epidemiological and economic aspects was limited. Therefore, two separate models were designed, one for the epidemiological aspects and one for the economic aspects of Salmonella control in the pork supply chain. The epidemiological model to simulate the introduction and spread of Salmonella in the pork supply chain is a detailed stochastic state transition model. The economic model is a deterministic simulation model. For each control measure in the finishing to slaughtering stages, the costs and revenues have been calculated using the technique of partial budgeting. Since it is not feasible in practice to implement all possible control measures, for each stage a package of measures has been defined by selecting feasible measures, which in the main do not overlap each other. The net costs for these packages per stage were calculated per pig. In the finishing stage, the net costs for the control package are € 2.99, for the transportation stage € 0.65, for the lairage € 0.40 and for the slaughtering stage € 1.47. Combining the results of the epidemiological and the economic models allowed comparison of the cost-effectiveness of different control strategies for Salmonella in stages of the pork supply chain. The research has revealed the importance of a chain approach instead of considering each stage individually. The effectiveness of Salmonella reduction depends on the efforts of all participants in a stage. A small number of poorly performing participants can disproportionately reduce the effectiveness of the efforts of the other participants. A payment system based on the Salmonella prevalence of the supplied animals or carcasses is a promising strategy to improve food safety. Strategic management principles have been applied to define aspects that are important for the design and implementation of a Salmonella control programme in a pork supply chain. Such a programme should achieve the right balance between the costs of the programme and to the reduction of the risk to food safety. |
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Status |
Published |
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Availability |
In journals Thesis at http://library.wur.nl/wda/ |
Project group
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Institute |
1.
Business Economics of Social Sciences Group of Wageningen University, the
Netherlands 2. Applied research of the Animal Sciences Group of WUR, Lelystad, the Netherlands |
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Contact person |
Monique van der Gaag (Monique.vanderGaag@wur.nl) |
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Partners |