IDEAS home Printed from https://ideas.repec.org/a/wly/riskan/v33y2013i5p877-892.html
   My bibliography  Save this article

Inferring an Augmented Bayesian Network to Confront a Complex Quantitative Microbial Risk Assessment Model with Durability Studies: Application to Bacillus Cereus on a Courgette Purée Production Chain

Author

Listed:
  • Clémence Sophie Rigaux Ancelet
  • Frédéric Carlin
  • Christophe Nguyen‐thé
  • Isabelle Albert

Abstract

The Monte Carlo (MC) simulation approach is traditionally used in food safety risk assessment to study quantitative microbial risk assessment (QMRA) models. When experimental data are available, performing Bayesian inference is a good alternative approach that allows backward calculation in a stochastic QMRA model to update the experts’ knowledge about the microbial dynamics of a given food‐borne pathogen. In this article, we propose a complex example where Bayesian inference is applied to a high‐dimensional second‐order QMRA model. The case study is a farm‐to‐fork QMRA model considering genetic diversity of Bacillus cereus in a cooked, pasteurized, and chilled courgette purée. Experimental data are Bacillus cereus concentrations measured in packages of courgette purées stored at different time‐temperature profiles after pasteurization. To perform a Bayesian inference, we first built an augmented Bayesian network by linking a second‐order QMRA model to the available contamination data. We then ran a Markov chain Monte Carlo (MCMC) algorithm to update all the unknown concentrations and unknown quantities of the augmented model. About 25% of the prior beliefs are strongly updated, leading to a reduction in uncertainty. Some updates interestingly question the QMRA model.

Suggested Citation

  • Clémence Sophie Rigaux Ancelet & Frédéric Carlin & Christophe Nguyen‐thé & Isabelle Albert, 2013. "Inferring an Augmented Bayesian Network to Confront a Complex Quantitative Microbial Risk Assessment Model with Durability Studies: Application to Bacillus Cereus on a Courgette Purée Production Chain," Risk Analysis, John Wiley & Sons, vol. 33(5), pages 877-892, May.
  • Handle: RePEc:wly:riskan:v:33:y:2013:i:5:p:877-892
    DOI: 10.1111/j.1539-6924.2012.01888.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1539-6924.2012.01888.x
    Download Restriction: no

    File URL: https://libkey.io/10.1111/j.1539-6924.2012.01888.x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. G. C. Barker & N. Goméz‐Tomé, 2013. "A Risk Assessment Model for Enterotoxigenic Staphylococcus aureus in Pasteurized Milk: A Potential Route to Source‐Level Inference," Risk Analysis, John Wiley & Sons, vol. 33(2), pages 249-269, February.
    2. H. Christopher Frey & David E. Burmaster, 1999. "Methods for Characterizing Variability and Uncertainty: Comparison of Bootstrap Simulation and Likelihood‐Based Approaches," Risk Analysis, John Wiley & Sons, vol. 19(1), pages 109-130, February.
    3. Isabelle Albert & Emmanuel Grenier & Jean‐Baptiste Denis & Judith Rousseau, 2008. "Quantitative Risk Assessment from Farm to Fork and Beyond: A Global Bayesian Approach Concerning Food‐Borne Diseases," Risk Analysis, John Wiley & Sons, vol. 28(2), pages 557-571, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Bonnie C. Wintle & Ann Nicholson, 2014. "Exploring Risk Judgments in a Trade Dispute Using Bayesian Networks," Risk Analysis, John Wiley & Sons, vol. 34(6), pages 1095-1111, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Christian P. Robert & Judith Rousseau, 2010. "On Bayesian Data Analysis," Working Papers 2010-31, Center for Research in Economics and Statistics.
    2. McKenna, Claire & Chalabi, Zaid & Epstein, David & Claxton, Karl, 2010. "Budgetary policies and available actions: A generalisation of decision rules for allocation and research decisions," Journal of Health Economics, Elsevier, vol. 29(1), pages 170-181, January.
    3. Nicolas Miconnet & Marie Cornu & Annie Beaufort & Laurent Rosso & Jean‐Baptiste Denis, 2005. "Uncertainty Distribution Associated with Estimating a Proportion in Microbial Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 25(1), pages 39-48, February.
    4. Régis Pouillot & Nicolas Miconnet & Anne‐Laure Afchain & Marie Laure Delignette‐Muller & Annie Beaufort & Laurent Rosso & Jean‐Baptiste Denis & Marie Cornu, 2007. "Quantitative Risk Assessment of Listeria monocytogenes in French Cold‐Smoked Salmon: I. Quantitative Exposure Assessment," Risk Analysis, John Wiley & Sons, vol. 27(3), pages 683-700, June.
    5. J. H. Smid & A. N. Swart & A. H. Havelaar & A. Pielaat, 2011. "A Practical Framework for the Construction of a Biotracing Model: Application to Salmonella in the Pork Slaughter Chain," Risk Analysis, John Wiley & Sons, vol. 31(9), pages 1434-1450, September.
    6. Kimberley Kolb Ayre & Colleen A. Caldwell & Jonah Stinson & Wayne G. Landis, 2014. "Analysis of Regional Scale Risk of Whirling Disease in Populations of Colorado and Rio Grande Cutthroat Trout Using a Bayesian Belief Network Model," Risk Analysis, John Wiley & Sons, vol. 34(9), pages 1589-1605, September.
    7. Xavier Romão & Esmeralda Paupério, 2016. "A framework to assess quality and uncertainty in disaster loss data," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(2), pages 1077-1102, September.
    8. Michael Greenberg & Karen Lowrie, 2011. "Celebrating Three Decades of Public Policy‐Oriented Interdisciplinary Research," Risk Analysis, John Wiley & Sons, vol. 31(1), pages 7-11, January.
    9. Pieter Busschaert & Annemie H. Geeraerd & Mieke Uyttendaele & Jan F. Van Impe, 2011. "Sensitivity Analysis of a Two‐Dimensional Quantitative Microbiological Risk Assessment: Keeping Variability and Uncertainty Separated," Risk Analysis, John Wiley & Sons, vol. 31(8), pages 1295-1307, August.
    10. Arwa S. Sayegh & Richard D. Connors & James E. Tate, 2018. "Uncertainty Propagation from the Cell Transmission Traffic Flow Model to Emission Predictions: A Data-Driven Approach," Service Science, INFORMS, vol. 52(6), pages 1327-1346, December.
    11. Régis Pouillot & Véronique Goulet & Marie Laure Delignette‐Muller & Aurélie Mahé & Marie Cornu, 2009. "Quantitative Risk Assessment of Listeria monocytogenes in French Cold‐Smoked Salmon: II. Risk Characterization," Risk Analysis, John Wiley & Sons, vol. 29(6), pages 806-819, June.
    12. Isabelle Albert & Emmanuelle Espié & Henriette de Valk & Jean‐Baptiste Denis, 2011. "A Bayesian Evidence Synthesis for Estimating Campylobacteriosis Prevalence," Risk Analysis, John Wiley & Sons, vol. 31(7), pages 1141-1155, July.
    13. Bonnie C. Wintle & Ann Nicholson, 2014. "Exploring Risk Judgments in a Trade Dispute Using Bayesian Networks," Risk Analysis, John Wiley & Sons, vol. 34(6), pages 1095-1111, June.
    14. Nicola Pedroni & Enrico Zio & Alberto Pasanisi & Mathieu Couplet, 2017. "A critical discussion and practical recommendations on some issues relevant to the non-probabilistic treatment of uncertainty in engineering risk assessment," Post-Print hal-01652230, HAL.
    15. Jason R. W. Merrick & J. Rene Van Dorp & Varun Dinesh, 2005. "Assessing Uncertainty in Simulation‐Based Maritime Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 25(3), pages 731-743, June.
    16. Jason R. W. Merrick & Rene Van Dorp, 2006. "Speaking the Truth in Maritime Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 26(1), pages 223-237, February.
    17. Carolina Plaza Rodríguez & Guido Correia Carreira & Annemarie Käsbohrer, 2018. "A Probabilistic Transmission Model for the Spread of Extended‐Spectrum‐β‐Lactamase and AmpC‐β‐Lactamase‐Producing Escherichia Coli in the Broiler Production Chain," Risk Analysis, John Wiley & Sons, vol. 38(12), pages 2659-2682, December.
    18. Modarres, Reza & Nayak, Tapan K. & Gastwirth, Joseph L., 2002. "Estimation of upper quantiles under model and parameter uncertainty," Computational Statistics & Data Analysis, Elsevier, vol. 39(4), pages 529-554, June.
    19. Chalabi, Zaid & Epstein, David & McKenna, Claire & Claxton, Karl, 2008. "Uncertainty and value of information when allocating resources within and between healthcare programmes," European Journal of Operational Research, Elsevier, vol. 191(2), pages 530-539, December.
    20. Nicola Pedroni & Enrico Zio & Alberto Pasanisi & Mathieu Couplet, 2017. "A Critical Discussion and Practical Recommendations on Some Issues Relevant to the Nonprobabilistic Treatment of Uncertainty in Engineering Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 37(7), pages 1315-1340, July.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:riskan:v:33:y:2013:i:5:p:877-892. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1111/(ISSN)1539-6924 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.