Bayesian Network and System Thinking Modelling to Manage Water-Related Health Risks from Extreme Events Author Bertone, E, Sahin, O, Richards, R, Roiko, RA Published 2015 Conference Title 2015 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND ENGINEERING MANAGEMENT (IEEM) Version Accepted Manuscript (AM) DOI https://doi.org/10.1109/IEEM.2015.7385852 Copyright Statement © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Downloaded from http://hdl.handle.net/10072/123524 Griffith Research Online https://research-repository.griffith.edu.au Citation: Bertone, E.; Sahin, O.; Richards, R.; Roiko, A. (2015). Bayesian Network and System Thinking modelling to manage water-related health risks from extreme events. IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), Singapore, 6-9 December 2015 Bayesian Network and System Thinking Modelling to Manage Water-Related Health Risks from Extreme Events E. Bertone1, O. Sahin1, R. Richards2, R. A. Roiko3 1 Griffith School of Engineering, Griffith University, Queensland, Australia 2 School of Agriculture and Food Sciences, University of Queensland, Brisbane, Australia 3 Griffith School of Medicine, Griffith University, Queensland, Australia Email:
[email protected] Abstract - A combination of Bayesian Network (BN), system leading to the formation of carcinogen System Dynamics (SD) and participatory modelling to trihalomethanes (THM’s), one of the over 600 develop a risk assessment tool for managing water-related disinfection by-products currently reported in drinking health risks associated with extreme events has been water [2].