title: Beyond QMRA: Modelling microbial health risk as a complex system using Bayesian networks.
abstract: BACKGROUND
  Quantitative microbial risk assessment (QMRA) is the current method of choice for determining the risk to human health from exposure to microorganisms of concern. However, current approaches are often constrained by the availability of required data, and may not be able to incorporate the many varied factors that influence this risk. Systems models, based on Bayesian networks (BNs), are emerging as an effective complementary approach that overcomes these limitations.
  
  
  OBJECTIVE
  This article aims to provide a comparative evaluation of the capabilities and challenges of current QMRA methods and BN models, and a scoping review of recent published articles that adopt the latter for microbial risk assessment. Pros and cons of systems approaches in this context are distilled and discussed.
  
  
  METHODS
  A search of the peer-reviewed literature revealed 15 articles describing BNs used in the context of QMRAs for foodborne and waterborne pathogens. These studies were analysed in terms of their application, uses and benefits in QMRA.
  
  
  CONCLUSIONS
  The applications were notable in their diversity. BNs were used to make predictions, for scenario assessment, risk minimisation, to reduce uncertainty and to separate uncertainty and variability. Most studies focused on a segment of the exposure pathway, indicating the broad potential for the method in other QMRA steps. BNs offer a number of useful features to enhance QMRA, including transparency, and the ability to deal with poor quality data and support causal reasoning.
  
  
  CONCLUSIONS
  The method has significant untapped potential to describe the complex relationships between microbial environmental exposures and health.
authors.affiliation: Faculty of Health, Queensland University of Technology, Gardens Point Campus, 2 George Street, Brisbane, Queensland 4000, Australia; Institute of Health and Biomedical Innovation (IHBI), Queensland University of Technology, 60 Musk Avenue, Kelvin Grove, Queensland 4059, Australia. Electronic address: d.beaudequin@qut.edu.au.
authors.forename: Denise
authors.initials: D
authors.lastname: Beaudequin
authors.affiliation: Faculty of Health, Queensland University of Technology, Gardens Point Campus, 2 George Street, Brisbane, Queensland 4000, Australia; Institute of Health and Biomedical Innovation (IHBI), Queensland University of Technology, 60 Musk Avenue, Kelvin Grove, Queensland 4059, Australia. Electronic address: fiona.harden@qut.edu.au.
authors.forename: Fiona
authors.initials: F
authors.lastname: Harden
authors.affiliation: School of Medicine, Griffith University, Gold Coast Campus, Parklands Drive, Southport, Queensland 4222, Australia; Smartwater Research Centre, Griffith University, Gold Coast Campus, Edmund Rice Drive, Southport, Queensland 4215, Australia. Electronic address: a.roiko@griffith.edu.au.
authors.forename: Anne
authors.initials: A
authors.lastname: Roiko
authors.affiliation: School of Natural Sciences, Griffith University, Nathan Campus, 170 Kessels Road, Nathan, Queensland 4111, Australia; Smartwater Research Centre, Griffith University, Gold Coast Campus, Edmund Rice Drive, Southport, Queensland 4215, Australia. Electronic address: h.stratton@griffith.edu.au.
authors.forename: Helen
authors.initials: H
authors.lastname: Stratton
authors.affiliation: Griffith School of Engineering, Griffith University, Gold Coast Campus, Parklands Drive, Southport, Queensland 4222, Australia; Smartwater Research Centre, Griffith University, Gold Coast Campus, Edmund Rice Drive, Southport, Queensland 4215, Australia. Electronic address: c.lemckert@griffith.edu.au.
authors.forename: Charles
authors.initials: C
authors.lastname: Lemckert
authors.affiliation: Science and Engineering Faculty, Queensland University of Technology, Gardens Point Campus, 2 George Street, Brisbane, Queensland 4000, Australia; Institute for Future Environments (IFE), Queensland University of Technology, Gardens Point Campus, 2 George Street, Brisbane, Queensland 4000, Australia. Electronic address: k.mengersen@qut.edu.au.
authors.forename: Kerrie
authors.initials: K
authors.lastname: Mengersen
mesh_terms: D001499:Bayes Theorem; D003141:Communicable Diseases / Q000453:epidemiology / Q000382:microbiology; D005516:Food Microbiology / Q000592:standards / Q000706:statistics & numerical data; D006801:Humans; D008962:Models, Theoretical; D011634:Public Health / Q000379:methods* / Q000706:statistics & numerical data; D018570:Risk Assessment / Q000379:methods / Q000706:statistics & numerical data; D035501:Uncertainty; D014871:Water Microbiology / Q000592:standards*
keywords: Bayesian network; Health risk assessment; Microbial risk; Modelling; QMRA; Uncertainty