Multi-criteria decision analysis is a quantitative approach to the drug benefit-risk assessment which allows for consistent comparisons by summarising all benefits and risks in a single score. The multi-criteria decision analysis consists of several components, one of which is the utility (or loss) score function that defines how benefits and risks are aggregated into a single quantity. While a linear utility score is one of the most widely used approach in benefit-risk assessment, it is recognised that it can result in counter-intuitive decisions, for example, recommending a treatment with extremely low benefits or high risks. To overcome this problem, alternative approaches to the scores construction, namely, product, multi-linear and Scale Loss Score models, were suggested. However, to date, the majority of arguments concerning the differences implied by these models are heuristic. In this work, we consider four models to calculate the aggregated utility/loss scores and compared their performance in an extensive simulation study over many different scenarios, and in a case study. It is found that the product and Scale Loss Score models provide more intuitive treatment recommendation decisions in the majority of scenarios compared to the linear and multi-linear models, and are more robust to the correlation in the criteria.

Assessing water supply capacity is crucial to meet stakeholders\' needs, notably in the Mediterranean region. This region has been identified as a climate change hot spot, and as a region where water demand is continuously increasing due to population growth and the expansion of irrigated areas. The Hérault River catchment (2500 km(2), France) is a typical example and a negative trend in discharge has been observed since the 1960s. In this context, local stakeholders need first to understand the processes controlling the evolution of water resources and demands in the past to latter evaluate future water supply capacity and anticipate the tensions users could be confronted to in the future. A modelling framework is proposed at a 10-day time step to assess whether water resources have been able to meet water demands over the last 50 years. Water supply was evaluated using hydrological modelling and a dam management model. Water demand dynamics were estimated for the domestic and agricultural sectors. A water supply capacity index is computed to assess the extent and the frequency to which water demand has been satisfied at the sub-basin scale. Simulated runoff dynamics were in good agreement with observations over the calibration and validation periods. Domestic water demand has increased considerably since the 1980s and is characterized by a seasonal peak in summer. Agricultural demand has increased in the downstream sub-basins and decreased upstream where irrigated areas have decreased. As a result, although most water demands were satisfied between 1961 and 1980, irrigation requirements in summer have sometimes not been satisfied since the 1980s. This work is the first step toward evaluating possible future changes in water allocation capacity in the catchment, using future climate change, dam management and water use scenarios.