Development of a Risk-Based Decision Model for Prioritizing Microbial Risk Mitigation Measures in Drinking Water Systems

Risk management of drinking water systems is crucial since our society relies on these systems to be robust and sustainable to supply safe drinking water now and to future generations. Pathogens may spread in drinking water systems and cause waterborne outbreaks resulting in human suffering and large costs to the society. Thus, mitigating microbial risks is of great importance for provision of safe drinking water in a changing world. Since risk mitigation measures can be costly, there is a need for a transparent and holistic decision support to enable a sound and efficient use of available resources. In this thesis, a risk-based decision model that facilitates evaluation and comparison of microbial risk mitigation measures is presented. The model was developed by combining source characterisation, water quality modelling, quantitative microbial risk assessment and cost-benefit analysis. Uncertainties associated with input variables and output results were analysed by means of Monte Carlo simulations. The decision model puts emphasis on health benefits obtained from reduced microbial risks in drinking water systems and the monetisation of these effects. In addition, the approach also accounts for non-health benefits that occur because of implemented mitigation measures. Such benefits, also if they cannot be monetised, are important to include and carefully consider in the cost-benefit analysis. The probabilistic approach provides an analysis of uncertainties that need to be considered by decision makers. To conclude, this thesis underlines and illustrates the strength of combining methods from several disciplines to create a robust decision support in order to optimise societal benefits