Reference : NUSAP: a method to evaluate the quality of assumptions in quantitative microbial risk...
Scientific journals : Article
Life sciences : Veterinary medicine & animal health
http://hdl.handle.net/2268/3474
NUSAP: a method to evaluate the quality of assumptions in quantitative microbial risk assessment
English
Boone, Ides mailto [Centre d'Etudes et de Recherches Vétérinaires Agronomiques = Centrum voor Onderzoek in Diergeneeskunde en Agrochemie - CERVA=CODA > CCVD > > >]
Van der Stede, Yves mailto [Centre d'Etudes et de Recherches Vétérinaires Agronomiques = Centrum voor Onderzoek in Diergeneeskunde en Agrochemie - CERVA=CODA > > > >]
Dewulf, Jeroen mailto [Universiteit Gent - Ugent > Fac. Vet. Med. > > >]
Messens, Winy mailto [Instituut voor Landbouw- en Visserijonderzoek = Institute for Agricultural and Fisheries Research > > > >]
Aerts, Marc mailto [Universiteit Hasselt - UH > > > >]
Daube, Georges mailto [Université de Liège - ULg > Département de sciences des denrées alimentaires > Microbiologie des denrées alimentaires >]
Mintiens, Koen mailto [Centre d'Etudes et de Recherches Vétérinaires Agronomiques = Centrum voor Onderzoek in Diergeneeskunde en Agrochemie - CERVA=CODA > > > >]
2010
Journal of Risk Research
Routledge
13
1-16
Yes (verified by ORBi)
International
1366-9877
Abingdon
United Kingdom
[en] Risk Assessment ; Microbial ; Assumptions
[en] implemented to evaluate assumptions in a quantitative microbial risk assessment
(QMRA) model for Salmonella spp. in minced pork meat. This QMRA model
allows the testing of mitigation strategies for the reduction of human salmonellosis
and aims to serve as a basis for science-based policy making. The NUSAP method
was used to assess the subjective component of assumptions in the QMRA model
by a set of four pedigree criteria: ‘the influence of situational limitations’,
‘plausibility’, ‘choice space’ and ‘the agreement among peers’. After identifying
13 key assumptions relevant for the QMRA model, a workshop was organized to
assess the importance of these assumptions on the output of the QMRA. The quality
of the assumptions was visualized using diagnostic and kite diagrams. The
diagnostic diagram pinpointed assumptions with a high degree of subjectivity and
a high ‘expected influence on the model results’ score. Examples of those
assumptions that should be dealt with care are the assumptions regarding the
concentration of Salmonella on the pig carcass at the beginning of the slaughter
process and the assumptions related to the Salmonella prevalence in the slaughter
process. The kite diagrams allowed a clear overview of the pedigree scores for each
assumption as well as a representation of expert (dis)agreement. The evaluation of
the assumptions using the NUSAP system enhanced the debate on the uncertainty
and its communication in the results of a QMRA model. It highlighted the model’s
strong and weak points and was helpful for redesigning critical modules. Since the
evaluation of assumptions allows a more critical approach of the QMRA process,
it is useful for policy makers as it aims to increase the transparency and acceptance
of management decisions based on a QMRA model.
SPF Santé publique
METZOON
Researchers ; Professionals ; Students
http://hdl.handle.net/2268/3474
10.1080/13669870903564574
http://dx.doi.org/10.1080/13669870903564574

File(s) associated to this reference

Fulltext file(s):

FileCommentaryVersionSizeAccess
Restricted access
JRR_2010_NUSAP_Ides.pdfPublisher postprint670.89 kBRequest copy

Bookmark and Share SFX Query

All documents in ORBi are protected by a user license.