| Title |
Characterization of the Human Risk of Salmonellosis Related to Consumption of Pork Products in Different E.U. Countries Based on a QMRA
|
|---|---|
| Published in |
Risk Analysis: An International Journal, February 2016
|
| DOI | 10.1111/risa.12499 |
| Pubmed ID | |
| Authors |
Håkan Vigre, Kristen Barfoed, Arno N Swart, Robin R L Simons, Andrew A Hill, Emma L Snary, Tine Hald |
| Abstract |
In response to the European Food Safety Authority's wish to assess the reduction of human cases of salmonellosis by implementing control measures at different points in the farm-to-consumption chain for pork products, a quantitative microbiological risk assessment (QMRA) was developed. The model simulated the occurrence of Salmonella from the farm to consumption of pork cuts, minced meat, and fermented ready-to-eat sausage, respectively, and a dose-response model was used to estimate the probability of illness at consumption. The QMRA has a generic structure with a defined set of variables, whose values are changed according to the E.U. member state (MS) of interest. In this article we demonstrate the use of the QMRA in four MSs, representing different types of countries. The predicted probability of illness from the QMRA was between 1 in 100,000 and 1 in 10 million per serving across all three product types. Fermented ready-to-eat sausage imposed the highest probability of illness per serving in all countries, whereas the risks per serving of minced meat and pork chops were similar within each MS. For each of the products, the risk varied by a factor of 100 between the four MSs. The influence of lack of information for different variables was assessed by rerunning the model with alternative, more extreme, values. Out of the large number of uncertain variables, only a few of them have a strong influence on the probability of illness, in particular those describing the preparation at home and consumption. |
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Mendeley demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Denmark | 1 | 2% |
| Unknown | 41 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 21% |
| Researcher | 7 | 17% |
| Student > Master | 6 | 14% |
| Other | 2 | 5% |
| Student > Doctoral Student | 2 | 5% |
| Other | 5 | 12% |
| Unknown | 11 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 8 | 19% |
| Veterinary Science and Veterinary Medicine | 6 | 14% |
| Medicine and Dentistry | 3 | 7% |
| Biochemistry, Genetics and Molecular Biology | 2 | 5% |
| Nursing and Health Professions | 2 | 5% |
| Other | 7 | 17% |
| Unknown | 14 | 33% |