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Volumn 80, Issue , 2015, Pages 8-18

Beyond QMRA: Modelling microbial health risk as a complex system using Bayesian networks

Author keywords

Bayesian network; Health risk assessment; Microbial risk; Modelling; QMRA; Uncertainty

Indexed keywords

BAYESIAN NETWORKS; COMPLEX NETWORKS; HEALTH; HEALTH RISKS; MODELS; RISK PERCEPTION; UNCERTAINTY ANALYSIS;

EID: 84925433422     PISSN: 01604120     EISSN: 18736750     Source Type: Journal    
DOI: 10.1016/j.envint.2015.03.013     Document Type: Review
Times cited : (40)

References (64)
  • 2
    • 42249095080 scopus 로고    scopus 로고
    • Quantitative risk assessment from farm to fork and beyond: a global Bayesian approach concerning food-borne diseases
    • Albert I., Grenier E., Denis J.B., Rousseau J. Quantitative risk assessment from farm to fork and beyond: a global Bayesian approach concerning food-borne diseases. Risk Anal. 2008, 28:557-571.
    • (2008) Risk Anal. , vol.28 , pp. 557-571
    • Albert, I.1    Grenier, E.2    Denis, J.B.3    Rousseau, J.4
  • 3
    • 0038858509 scopus 로고    scopus 로고
    • Available:, (accessed 21 June 1014)
    • Auyang S. Systems approach Available:, (accessed 21 June 1014). http://www.creatingtechnology.org/sysapp.htm.
    • Systems approach
    • Auyang, S.1
  • 4
    • 67349135009 scopus 로고    scopus 로고
    • Application of Bayesian belief network models to food safety science
    • Kluwer, Dordrecht, The Netherlands, M. van Boekel, A. Stein, H. van Bruggen (Eds.)
    • Barker G.C. Application of Bayesian belief network models to food safety science. Bayesian Statistics and Quality Modeling in the Agri-food Production Chain 2004, 117-130. Kluwer, Dordrecht, The Netherlands. M. van Boekel, A. Stein, H. van Bruggen (Eds.).
    • (2004) Bayesian Statistics and Quality Modeling in the Agri-food Production Chain , pp. 117-130
    • Barker, G.C.1
  • 5
    • 84873100776 scopus 로고    scopus 로고
    • A risk-assessment model for enterotoxigenic Staphylococcus aureus in pasteurized milk: a potential route to source-level inference
    • Barker G., Gomez-Tome N. A risk-assessment model for enterotoxigenic Staphylococcus aureus in pasteurized milk: a potential route to source-level inference. Risk Anal. 2013, 33:249-269.
    • (2013) Risk Anal. , vol.33 , pp. 249-269
    • Barker, G.1    Gomez-Tome, N.2
  • 7
    • 67349215108 scopus 로고    scopus 로고
    • An introduction to biotracing in food chain systems
    • Barker G.C., Gomez N., Smid J. An introduction to biotracing in food chain systems. Trends Food Sci. Technol. 2009, 20:220-226.
    • (2009) Trends Food Sci. Technol. , vol.20 , pp. 220-226
    • Barker, G.C.1    Gomez, N.2    Smid, J.3
  • 9
    • 60849097509 scopus 로고    scopus 로고
    • Available:, (accessed 15 June 2014)
    • Ben-Gal I. Bayesian networks Available:, (accessed 15 June 2014). http://www.eng.tau.ac.il/~bengal/BN.pdf.
    • Bayesian networks
    • Ben-Gal, I.1
  • 10
    • 0003662522 scopus 로고    scopus 로고
    • Food and Agriculture Organization and World Health Organization, Rome, Italy, ([accessed 15 June 2014])
    • Codex Alimentarius Commission Principles and Guidelines for the Conduct of Microbiological Risk Assessment 1999, Food and Agriculture Organization and World Health Organization, Rome, Italy, (Available: http://www.codexalimentarius.net [accessed 15 June 2014]).
    • (1999) Principles and Guidelines for the Conduct of Microbiological Risk Assessment
  • 12
    • 1542547152 scopus 로고    scopus 로고
    • Modeling the U.S. national distribution of waterborne pathogen concentrations with application to Cryptosporidium parvum
    • Crainiceanu C.M., Stedinger J.R., Ruppert D., Behr C.T. Modeling the U.S. national distribution of waterborne pathogen concentrations with application to Cryptosporidium parvum. Water Resources Research 2003, 39(9):SWC21-SWC215.
    • (2003) Water Resources Research , vol.39 , Issue.9 , pp. SWC21-SWC215
    • Crainiceanu, C.M.1    Stedinger, J.R.2    Ruppert, D.3    Behr, C.T.4
  • 13
    • 31044448847 scopus 로고    scopus 로고
    • Use of Bayesian modeling in risk assessment: application to growth of Listeria monocytogenes and food flora in cold-smoked salmon
    • Delignette-Muller M.L., Cornu M., Pouillot R., Denis J.B. Use of Bayesian modeling in risk assessment: application to growth of Listeria monocytogenes and food flora in cold-smoked salmon. Int. J. Food Microbiol. 2006, 106:195-208.
    • (2006) Int. J. Food Microbiol. , vol.106 , pp. 195-208
    • Delignette-Muller, M.L.1    Cornu, M.2    Pouillot, R.3    Denis, J.B.4
  • 14
    • 72249116698 scopus 로고    scopus 로고
    • Bayesian network for risk of diarrhea associated with the use of recycled water
    • Donald M., Cook A., Mengersen K. Bayesian network for risk of diarrhea associated with the use of recycled water. Risk Anal. 2009, 29:1672-1685.
    • (2009) Risk Anal. , vol.29 , pp. 1672-1685
    • Donald, M.1    Cook, A.2    Mengersen, K.3
  • 15
    • 84892386641 scopus 로고    scopus 로고
    • A review of Bayesian networks as a participatory modeling approach in support of sustainable environmental management
    • Düspohl M., Frank S., Döll P. A review of Bayesian networks as a participatory modeling approach in support of sustainable environmental management. J. Sustain. Dev. 2012, 5:1-18.
    • (2012) J. Sustain. Dev. , vol.5 , pp. 1-18
    • Düspohl, M.1    Frank, S.2    Döll, P.3
  • 17
    • 84925446807 scopus 로고    scopus 로고
    • Available:, (accessed 15 June 2014)
    • Food and Agriculture Organization of the United Nations, World Health Organization Hazard characterisation for pathogens in food and water: guidelines Available:, (accessed 15 June 2014). http://www.who.int/foodsafety/publications/micro/en/pathogen.pdf.
    • Hazard characterisation for pathogens in food and water: guidelines
  • 18
    • 84865992752 scopus 로고    scopus 로고
    • A Bayesian network model to assess the public health risk associated with wet weather sewer overflows discharging into waterways
    • Goulding R., Jayasuriya N., Horan E. A Bayesian network model to assess the public health risk associated with wet weather sewer overflows discharging into waterways. Water Res. 2012, 46:4933-4940.
    • (2012) Water Res. , vol.46 , pp. 4933-4940
    • Goulding, R.1    Jayasuriya, N.2    Horan, E.3
  • 19
    • 84876701706 scopus 로고    scopus 로고
    • Graphical models and Bayesian domains in risk modeling: application in microbiological risk assessment
    • Greiner M., Smid J., Havelaar A.H., Müller-Graf C. Graphical models and Bayesian domains in risk modeling: application in microbiological risk assessment. Prev. Vet. Med. 2013, 110:4-11.
    • (2013) Prev. Vet. Med. , vol.110 , pp. 4-11
    • Greiner, M.1    Smid, J.2    Havelaar, A.H.3    Müller-Graf, C.4
  • 20
    • 78650418410 scopus 로고    scopus 로고
    • Addressing uncertainty in fecal indicator bacteria dark inactivation rates
    • Gronewold A.D., Myers L., Swall J.L., Noble R.T. Addressing uncertainty in fecal indicator bacteria dark inactivation rates. Water Res. 2011, 45:652-664.
    • (2011) Water Res. , vol.45 , pp. 652-664
    • Gronewold, A.D.1    Myers, L.2    Swall, J.L.3    Noble, R.T.4
  • 21
    • 84875590153 scopus 로고    scopus 로고
    • Differentiating Enterococcus concentration spatial, temporal, and analytical variability in recreational waters
    • Gronewold A.D., Stow C.A., Vijayavel K., Moynihan M.A., Kashian D.R. Differentiating Enterococcus concentration spatial, temporal, and analytical variability in recreational waters. Water Research 2013, 47(7):2141-2152.
    • (2013) Water Research , vol.47 , Issue.7 , pp. 2141-2152
    • Gronewold, A.D.1    Stow, C.A.2    Vijayavel, K.3    Moynihan, M.A.4    Kashian, D.R.5
  • 22
    • 0036946845 scopus 로고    scopus 로고
    • Progress and data gaps in quantitative microbial risk assessment
    • Haas C.N. Progress and data gaps in quantitative microbial risk assessment. Water Sci. Technol. 2002, 46:277.
    • (2002) Water Sci. Technol. , vol.46 , pp. 277
    • Haas, C.N.1
  • 24
    • 84925422105 scopus 로고    scopus 로고
    • QMRA - a framework for assessing microbiological public health risks
    • Dutch National Institute for Public Health and the Environment (RIVM) and University of Utrecht, Maastricht
    • Havelaar A.H. QMRA - a framework for assessing microbiological public health risks. Proceedings of the ECVPH Annual Scientific Conference 2012, Dutch National Institute for Public Health and the Environment (RIVM) and University of Utrecht, Maastricht.
    • (2012) Proceedings of the ECVPH Annual Scientific Conference
    • Havelaar, A.H.1
  • 25
    • 55249085379 scopus 로고    scopus 로고
    • Challenges of quantitative microbial risk assessment at EU level
    • Havelaar A.H., Eversa E.G., Nauta M.J. Challenges of quantitative microbial risk assessment at EU level. Trends Food Sci. Technol. 2008, 19:S26-S33.
    • (2008) Trends Food Sci. Technol. , vol.19 , pp. S26-S33
    • Havelaar, A.H.1    Eversa, E.G.2    Nauta, M.J.3
  • 28
    • 84868266689 scopus 로고    scopus 로고
    • Integrated Bayesian network framework for modeling complex ecological issues
    • Johnson S., Mengersen K. Integrated Bayesian network framework for modeling complex ecological issues. Integr. Environ. Assess. Manag. 2011, 8:480-490.
    • (2011) Integr. Environ. Assess. Manag. , vol.8 , pp. 480-490
    • Johnson, S.1    Mengersen, K.2
  • 29
    • 72249083546 scopus 로고    scopus 로고
    • An integrated Bayesian network approach to Lyngbya majuscula bloom initiation
    • Johnson S., Fielding F., Hamilton G.S., Mengersen K. An integrated Bayesian network approach to Lyngbya majuscula bloom initiation. Mar. Environ. Res. 2010, 69:27-37.
    • (2010) Mar. Environ. Res. , vol.69 , pp. 27-37
    • Johnson, S.1    Fielding, F.2    Hamilton, G.S.3    Mengersen, K.4
  • 33
    • 0030727148 scopus 로고    scopus 로고
    • An overview of microbial food safety risk assessment
    • Lammerding A.M. An overview of microbial food safety risk assessment. J. Food Prot. 1997, 60:1420-1425.
    • (1997) J. Food Prot. , vol.60 , pp. 1420-1425
    • Lammerding, A.M.1
  • 34
    • 84886388174 scopus 로고    scopus 로고
    • Improvement and application of modular process risk modeling method for microbial risk assessment
    • Liu L., Gao Y., Wang Y. Improvement and application of modular process risk modeling method for microbial risk assessment. J. Chem. Pharm. Res. 2013, 5:434-438.
    • (2013) J. Chem. Pharm. Res. , vol.5 , pp. 434-438
    • Liu, L.1    Gao, Y.2    Wang, Y.3
  • 35
    • 34249904903 scopus 로고    scopus 로고
    • Bayesian belief networks: applications in ecology and natural resource management
    • McCann R.K., Marcot B.G., Ellis R. Bayesian belief networks: applications in ecology and natural resource management. Canadian Journal of Forest Research 2006, 36(12):3053-3062.
    • (2006) Canadian Journal of Forest Research , vol.36 , Issue.12 , pp. 3053-3062
    • McCann, R.K.1    Marcot, B.G.2    Ellis, R.3
  • 36
    • 84863998551 scopus 로고    scopus 로고
    • Variance in Bacillus anthracis virulence assessed through Bayesian hierarchical dose-response modeling
    • Mitchell-Blackwood J., Gurian P.L., Lee R., Thran B. Variance in Bacillus anthracis virulence assessed through Bayesian hierarchical dose-response modeling. J. Appl. Microbiol. 2012, 113:265-275.
    • (2012) J. Appl. Microbiol. , vol.113 , pp. 265-275
    • Mitchell-Blackwood, J.1    Gurian, P.L.2    Lee, R.3    Thran, B.4
  • 37
    • 61349184579 scopus 로고    scopus 로고
    • (accessed 15 June 2014)
    • National Research Council Science and decisions: advancing risk assessment Available:, (accessed 15 June 2014). http://www.nap.edu.ezp01.library.qut.edu.au/openbook.php?record_id=12209.
    • Science and decisions: advancing risk assessment
  • 38
    • 0004170187 scopus 로고    scopus 로고
    • A modular process risk model structure for quantitative microbiological risk assessment and its application in an exposure assessment of Bacillus cereus in a REPFED
    • National Institute of Public Health and the Environment, Bilthoven, The Netherlands, ([accessed 21 June 2014])
    • Nauta M.J. A modular process risk model structure for quantitative microbiological risk assessment and its application in an exposure assessment of Bacillus cereus in a REPFED. Quantitative Safety Aspect of Pathogens in Foods 2001, National Institute of Public Health and the Environment, Bilthoven, The Netherlands, (Available: http://www.rivm.nl/dsresource?objectid=rivmp:10491&type=org&disposition=inline&ns_nc=1 [accessed 21 June 2014]).
    • (2001) Quantitative Safety Aspect of Pathogens in Foods
    • Nauta, M.J.1
  • 39
    • 35448952451 scopus 로고    scopus 로고
    • A risk assessment model for Campylobacter in broiler meat
    • Nauta M.J., Jacobs-Reitsma W.F., Havelaar A.H. A risk assessment model for Campylobacter in broiler meat. Risk Anal. 2007, 27:845-861.
    • (2007) Risk Anal. , vol.27 , pp. 845-861
    • Nauta, M.J.1    Jacobs-Reitsma, W.F.2    Havelaar, A.H.3
  • 40
    • 84892865471 scopus 로고    scopus 로고
    • Bayesian belief networks in environmental modeling: a review of recent progress
    • Nova Science Publishers Inc., New York, P.N. Findley (Ed.)
    • Newton A.C. Bayesian belief networks in environmental modeling: a review of recent progress. Environmental Modeling: New Research 2009, 13-50. Nova Science Publishers Inc., New York. P.N. Findley (Ed.).
    • (2009) Environmental Modeling: New Research , pp. 13-50
    • Newton, A.C.1
  • 41
    • 34249887900 scopus 로고    scopus 로고
    • Using Bayesian belief networks in adaptive management
    • Nyberg J.B., Marcot B.G., Sulyma R. Using Bayesian belief networks in adaptive management. Can. J. For. Res. 2006, 36:3104-3116.
    • (2006) Can. J. For. Res. , vol.36 , pp. 3104-3116
    • Nyberg, J.B.1    Marcot, B.G.2    Sulyma, R.3
  • 42
    • 11144283676 scopus 로고    scopus 로고
    • A comparison of three modeling approaches for quantitative risk assessment using the case study of Salmonella spp. in poultry meat
    • Parsons D.J., Orton T.G., D'Souza J., Moore A., Jones R., Dodd C.E.R. A comparison of three modeling approaches for quantitative risk assessment using the case study of Salmonella spp. in poultry meat. Int. J. Food Microbiol. 2005, 98:35-51.
    • (2005) Int. J. Food Microbiol. , vol.98 , pp. 35-51
    • Parsons, D.J.1    Orton, T.G.2    D'Souza, J.3    Moore, A.4    Jones, R.5    Dodd, C.E.R.6
  • 43
    • 0004213845 scopus 로고    scopus 로고
    • Cambridge University Press, Cambridge, United Kingdom
    • Pearl J. Causality 2000, Cambridge University Press, Cambridge, United Kingdom.
    • (2000) Causality
    • Pearl, J.1
  • 45
    • 84858641717 scopus 로고    scopus 로고
    • Bayesian decision networks - going beyond expert elicitation for parameterisation and evaluation of ecological endpoints
    • Water Studies Centre, Monash University, Clayton, Victoria, Burlington, USA, A. Voinov, A.J. Jakeman, A. Rizzoli, P.A. Sleigh (Eds.)
    • Pollino C.A., Hart B.T. Bayesian decision networks - going beyond expert elicitation for parameterisation and evaluation of ecological endpoints. Third Biennial Meeting: Summit on Environmental Modeling and Software 2005, Water Studies Centre, Monash University, Clayton, Victoria, Burlington, USA. A. Voinov, A.J. Jakeman, A. Rizzoli, P.A. Sleigh (Eds.).
    • (2005) Third Biennial Meeting: Summit on Environmental Modeling and Software
    • Pollino, C.A.1    Hart, B.T.2
  • 47
    • 0037088890 scopus 로고    scopus 로고
    • Estimation of uncertainty and variability in bacterial growth using Bayesian inference. Application to Listeria monocytogenes
    • Pouillot R., Albert I., Cornu M., Denis J.B. Estimation of uncertainty and variability in bacterial growth using Bayesian inference. Application to Listeria monocytogenes. Int. J. Food Microbiol. 2003, 81:87-104.
    • (2003) Int. J. Food Microbiol. , vol.81 , pp. 87-104
    • Pouillot, R.1    Albert, I.2    Cornu, M.3    Denis, J.B.4
  • 48
    • 84877600243 scopus 로고    scopus 로고
    • 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
    • Rigaux C., Ancelet S., Carlin F., Nguyen-thé C., Albert I. 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 Anal. 2012, 33:877-892.
    • (2012) Risk Anal. , vol.33 , pp. 877-892
    • Rigaux, C.1    Ancelet, S.2    Carlin, F.3    Nguyen-thé, C.4    Albert, I.5
  • 49
    • 84871868369 scopus 로고    scopus 로고
    • A meta-analysis accounting for sources of variability to estimate heat resistance reference parameters of bacteria using hierarchical Bayesian modeling: estimation of D at 121.1°C and pH7, zT and zpH of Geobacillus stearothermophilus
    • Rigaux C., Denis J.B., Albert I., Carlin F. A meta-analysis accounting for sources of variability to estimate heat resistance reference parameters of bacteria using hierarchical Bayesian modeling: estimation of D at 121.1°C and pH7, zT and zpH of Geobacillus stearothermophilus. Int. J. Food Microbiol. 2012, 161:112-120.
    • (2012) Int. J. Food Microbiol. , vol.161 , pp. 112-120
    • Rigaux, C.1    Denis, J.B.2    Albert, I.3    Carlin, F.4
  • 51
    • 77952639016 scopus 로고    scopus 로고
    • Strengths and weaknesses of Monte Carlo simulation models and Bayesian belief networks in microbial risk assessment
    • Smid J.H., Verloo D., Barker G.C., Havelaar A.H. Strengths and weaknesses of Monte Carlo simulation models and Bayesian belief networks in microbial risk assessment. Int. J. Food Microbiol. 2010, 139(Supplement 1):S57-S63.
    • (2010) Int. J. Food Microbiol. , vol.139 , pp. S57-S63
    • Smid, J.H.1    Verloo, D.2    Barker, G.C.3    Havelaar, A.H.4
  • 52
    • 80053386109 scopus 로고    scopus 로고
    • A practical framework for the construction of a biotracing model: application to Salmonella in the pork slaughter chain
    • Smid J.H., Swart A.N., Havelaar A.H., Pielaat A. A practical framework for the construction of a biotracing model: application to Salmonella in the pork slaughter chain. Risk Anal. 2011, 31:1434-1450.
    • (2011) Risk Anal. , vol.31 , pp. 1434-1450
    • Smid, J.H.1    Swart, A.N.2    Havelaar, A.H.3    Pielaat, A.4
  • 53
    • 84856317848 scopus 로고    scopus 로고
    • A biotracing model of Salmonella in the pork production chain
    • Smid J.H., Heres L., Havelaar A.H., Pielaat A. A biotracing model of Salmonella in the pork production chain. J. Food Prot. 2012, 75:270-280.
    • (2012) J. Food Prot. , vol.75 , pp. 270-280
    • Smid, J.H.1    Heres, L.2    Havelaar, A.H.3    Pielaat, A.4
  • 54
    • 84879111352 scopus 로고    scopus 로고
    • Variability and uncertainty analysis of the cross-contamination ratios of Salmonella during pork cutting
    • Smid J., de Jonge R., Havelaar A.H., Pielaat A. Variability and uncertainty analysis of the cross-contamination ratios of Salmonella during pork cutting. Risk Anal. 2013, 33:1100-1115.
    • (2013) Risk Anal. , vol.33 , pp. 1100-1115
    • Smid, J.1    de Jonge, R.2    Havelaar, A.H.3    Pielaat, A.4
  • 55
    • 84925396311 scopus 로고    scopus 로고
    • (accessed 22 September 2013)
    • Soller J. An introduction to quantitative microbial risk assessment Available:, (accessed 22 September 2013). http://water.epa.gov/scitech/swguidance/standards/criteria/health/recreation/upload/2008_04_09_criteria_recreation_feb2008_risk-assessment.pdf.
    • An introduction to quantitative microbial risk assessment
    • Soller, J.1
  • 57
    • 84865999759 scopus 로고    scopus 로고
    • Assessment of sources of human pathogens and fecal contamination in a Florida freshwater lake
    • Staley C., Reckhow K.H., Lukasik J., Harwood V.J. Assessment of sources of human pathogens and fecal contamination in a Florida freshwater lake. Water Res. 2012, 46:5799-5812.
    • (2012) Water Res. , vol.46 , pp. 5799-5812
    • Staley, C.1    Reckhow, K.H.2    Lukasik, J.3    Harwood, V.J.4
  • 58
    • 0020751755 scopus 로고
    • Normative predicates of next-generation management support systems
    • Sutherland J. Normative predicates of next-generation management support systems. IEEE Trans. Syst. Man Cybern. SMC 1983, 13:279-297.
    • (1983) IEEE Trans. Syst. Man Cybern. SMC , vol.13 , pp. 279-297
    • Sutherland, J.1
  • 61
    • 34047185270 scopus 로고    scopus 로고
    • Advantages and challenges of Bayesian networks in environmental modeling
    • Uusitalo L. Advantages and challenges of Bayesian networks in environmental modeling. Ecol. Model. 2007, 203:312-318.
    • (2007) Ecol. Model. , vol.203 , pp. 312-318
    • Uusitalo, L.1
  • 62
    • 0033565273 scopus 로고    scopus 로고
    • Learning Bayesian decision analysis by doing: lessons from environmental and natural resources management
    • Varis O., Kuikka S. Learning Bayesian decision analysis by doing: lessons from environmental and natural resources management. Ecol. Model. 1999, 119:177-195.
    • (1999) Ecol. Model. , vol.119 , pp. 177-195
    • Varis, O.1    Kuikka, S.2
  • 64
    • 10644223216 scopus 로고    scopus 로고
    • Guidelines for Drinking-water Quality: Incorporating 1st and 2nd Addenda
    • World Health Organisation, Geneva
    • World Health Organisation Guidelines for Drinking-water Quality: Incorporating 1st and 2nd Addenda. Recommendations 2008, vol.1. World Health Organisation, Geneva. 3rd ed.
    • (2008) Recommendations , vol.1


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