Decision making under uncertainty--an example for seismic risk management

Water mains’ prioritisation for small to medium-sized utilities of Canada

Ageing water infrastructure is a major concern for water utilities throughout the world. Due to lack of reliable data, it is challenging to develop an extensive water mains’ renewal programme and predict the performance of water mains. Small and medium-sized water utilities are affected more due to the scarcity of data/information and lack of technical and financial resources. In this study, a life cycle costing (LCC) model is developed for small to medium-sized water utilities of Canada to prioritise repair, rehabilitation and replacement strategies of water mains. The proposed model will guide in establishing a practical and cost-effective renewal programme for new installations or for rehabilitation of damaged water mains. To validate the effectiveness of the LCC model, it is tested and implemented on a medium-sized water utility, namely Greater Vernon Water, British Columbia.

A Framework for Understanding Uncertainty in Seismic Risk Assessment

A better understanding of the uncertainty that exists in models used for seismic risk assessment is critical to improving risk-based decisions pertaining to earthquake safety. Current models estimating the probability of collapse of a building do not consider comprehensively the nature and impact of uncertainty. This article presents a model framework to enhance seismic risk assessment and thus gives decisionmakers a fuller understanding of the nature and limitations of the estimates. This can help ensure that risks are not over- or underestimated and the value of acquiring accurate data is appreciated fully. The methodology presented provides a novel treatment of uncertainties in input variables, their propagation through the model, and their effect on the results. The study presents ranges of possible annual collapse probabilities for different case studies on buildings in different parts of the world, exposed to different levels of seismicity, and with different vulnerabilities. A global sensitivity analysis was conducted to determine the significance of uncertain variables. Two key outcomes are (1) that the uncertainty in ground-motion conversion equations has the largest effect on the uncertainty in the calculation of annual collapse probability; and (2) the vulnerability of a building appears to have an effect on the range of annual collapse probabilities produced, i.e., the level of uncertainty in the estimate of annual collapse probability, with less vulnerable buildings having a smaller uncertainty.

The Impact of Portfolio Location Uncertainty on Probabilistic Seismic Risk Analysis

Probabilistic seismic risk analysis is a well-established method in the insurance industry for modeling portfolio losses from earthquake events. In this context, precise exposure locations are often unknown. However, so far, location uncertainty has not been in the focus of a large amount of research. In this article, we propose a novel framework for treatment of location uncertainty. As a case study, a large number of synthetic portfolios resembling typical real-world cases were created. We investigate the effect of portfolio characteristics such as value distribution, portfolio size, or proportion of risk items with unknown coordinates on the variability of loss frequency estimations. The results indicate that due to loss aggregation effects and spatial hazard variability, location uncertainty in isolation and in conjunction with ground motion uncertainty can induce significant variability to probabilistic loss results, especially for portfolios with a small number of risks. After quantifying its effect, we conclude that location uncertainty should not be neglected when assessing probabilistic seismic risk, but should be treated stochastically and the resulting variability should be visualized and interpreted carefully.

Assessment Method for Combined Structural and Energy Retrofitting in Masonry Buildings

The retrofitting of existing masonry buildings is now a crucial problem for Europe. Indeed, structural safety and energy efficiency should represent the target of any renovation. The proposal of a new synthetic performance parameter is presented and discussed. Following this approach, in this paper, after a review of the main studies available in the literature, a proposal of a new performance parameter approach is presented and discussed. It is capable of taking into account both the structural and thermal aspects of masonry retrofitting. An emblematic set of reinforcements and energy improvements for masonry walls is examined. An example, generalized formulas, and a simultaneous evaluation of the role of multiple structural and thermal parameters on masonry buildings are proposed, with a view to optimize several categories of costs related to the intervention.

The impacts of decision uncertainty on municipal solid waste management

Municipal solid waste treatment options are not necessarily pragmatic if the stakeholders in the system don't mutually agree on their shares of liabilities. Stakeholders will select an option if their benefits are maximized and costs are minimized. A decision support framework is required to assess various waste treatment options and predict the optimal decision, considering multiple criteria and conflicting preferences of multiple stakeholders. Because of the inherent complexity, uncertainty is unavoidable and should be acknowledged to enhance the reliability in the decision-making process. Uncertainties in the cost and benefit estimates, and stakeholders' ability in verbalizing their preferences and their knowledge about each other's priorities can impact the outcome of such environmental management problem. In this study, uncertainty assessment methods such as sensitivity analysis, fuzzy Analytical Hierarchy Process, and Bayesian games have been explored. A case study in Vancouver (BC, Canada) has been used as a proof of concept.

Ordered visibility graph average aggregation operator: An application in produced water management

Complex networks are widely used in modeling complex system. How to aggregate data in complex systems is still an open issue. In this paper, an ordered visibility graph average aggregation operator is proposed which is inspired by the complex network theory and Newton's law of universal gravitation. First of all, the argument values are ordered in descending order. Then a new support function is proposed to measure the relationship among values in a visibility graph. After that, a weighted network is constructed to determine the weight of each value. Compared with the other operators, the new operator fully takes into account not only the information of orders but also the correlation degree between the values. Finally, an application of produced water management is illustrated to show the efficiency of the proposed method. The new method provides a universal way to aggregate data in complex systems.

Decision support for risk prioritisation of environmental health hazards in a UK city

BACKGROUND

There is increasing appreciation of the proportion of the health burden that is attributed to modifiable population exposure to environmental health hazards. To manage this avoidable burden in the United Kingdom (UK), government policies and interventions are implemented. In practice, this procedure is interdisciplinary in action and multi-dimensional in context. Here, we demonstrate how Multi Criteria Decision Analysis (MCDA) can be used as a decision support tool to facilitate priority setting for environmental public health interventions within local authorities. We combine modelling and expert elicitation to gather evidence on the impacts and ranking of interventions.

METHODS

To present the methodology, we consider a hypothetical scenario in a UK city. We use MCDA to evaluate and compare the impact of interventions to reduce the health burden associated with four environmental health hazards and rank them in terms of their overall performance across several criteria. For illustrative purposes, we focus on heavy goods vehicle controls to reduce outdoor air pollution, remediation to control levels of indoor radon, carbon monoxide and fitting alarms, and encouraging cycling to target the obesogenic environment. Regional data was included as model evidence to construct a ratings matrix for the city.

RESULTS

When MCDA is performed with uniform weights, the intervention of heavy goods vehicle controls to reduce outdoor air pollution is ranked the highest. Cycling and the obesogenic environment is ranked second.

CONCLUSIONS

We argue that a MCDA based approach provides a framework to guide environmental public health decision makers. This is demonstrated through an online interactive MCDA tool. We conclude that MCDA is a transparent tool that can be used to compare the impact of alternative interventions on a set of pre-defined criteria. In our illustrative example, we ranked the best intervention across the equally weighted selected criteria out of the four alternatives. Further work is needed to test the tool with decision makers and stakeholders.

A review and classification of approaches for dealing with uncertainty in multi-criteria decision analysis for healthcare decisions

Multi-criteria decision analysis (MCDA) is increasingly used to support decisions in healthcare involving multiple and conflicting criteria. Although uncertainty is usually carefully addressed in health economic evaluations, whether and how the different sources of uncertainty are dealt with and with what methods in MCDA is less known. The objective of this study is to review how uncertainty can be explicitly taken into account in MCDA and to discuss which approach may be appropriate for healthcare decision makers. A literature review was conducted in the Scopus and PubMed databases. Two reviewers independently categorized studies according to research areas, the type of MCDA used, and the approach used to quantify uncertainty. Selected full text articles were read for methodological details. The search strategy identified 569 studies. The five approaches most identified were fuzzy set theory (45% of studies), probabilistic sensitivity analysis (15%), deterministic sensitivity analysis (31%), Bayesian framework (6%), and grey theory (3%). A large number of papers considered the analytic hierarchy process in combination with fuzzy set theory (31%). Only 3% of studies were published in healthcare-related journals. In conclusion, our review identified five different approaches to take uncertainty into account in MCDA. The deterministic approach is most likely sufficient for most healthcare policy decisions because of its low complexity and straightforward implementation. However, more complex approaches may be needed when multiple sources of uncertainty must be considered simultaneously.