Overcoming Uncertainties in Risk Analysis: Trade-Offs among Methods of Uncertainty Analysis

2006 ◽  
pp. 287-295
Author(s):  
Y. Elshayeb
Keyword(s):  
Risk Analysis ◽  
Uncertainty Analysis ◽  
Trade Offs

scholarly journals Patient-centered benefit-risk analysis of transcatheter aortic valve replacement

F1000Research ◽  
2021 ◽  
Vol 8 ◽  
pp. 394
Author(s):  
Kevin Marsh ◽  
Natalia Hawken ◽  
Ella Brookes ◽  
Carrie Kuehn ◽  
Barry Liden
Keyword(s):  
Aortic Valve ◽  
Risk Analysis ◽  
Aortic Valve Replacement ◽  
Valve Replacement ◽  
Transcatheter Aortic Valve Replacement ◽  
Pairwise Comparison ◽  
Surgical Aortic Valve Replacement ◽  
Patient Centered ◽  
Transcatheter Aortic Valve ◽  
Trade Offs

Background: Aortic stenosis (AS) treatments include surgical aortic valve replacement (SAVR) and transcatheter aortic valve replacement (TAVR). Choosing between SAVR and TAVR requires patients to trade-off  benefits and risks. The objective of this research was to determine which  TAVR and SAVR outcomes patients consider important, collect quantitative data about how patients weigh benefits and risks, and evaluate patients’ preferences for SAVR or TAVR. Methods: Patients  were recruited from advocacy organization databases. Patients self-reported as being diagnosed with AS, and as either having received AS treatment or as experiencing AS-related physical activity limitations. An online adapted swing weighting (ASW) method – a pairwise comparison of attributes – was used to elicit attribute trade-offs from 219 patients. Survey data were used to estimate patients’ weights for AS treatment attributes, which were incorporated into a quantitative benefit-risk analysis (BRA) to evaluate patients’ preferences for TAVR and SAVR. Results: On average, patients put greater value on attributes that favored TAVR than SAVR. Patients’ valuation of the lower mortality rate, reduced procedural invasiveness, and quicker time to return to normal quality of life associated with TAVR, offset their valuation of the time over which SAVR has been proven to work. There was substantial heterogeneity in patients’ preferences. This was partly explained by age, with differences in preference observed between patients <60 years to those ≥60 years. A Monte Carlo Simulation found that 79.5% of patients prefer TAVR. Conclusions: Most AS patients are willing to tolerate sizable increases in clinical risk in exchange for the benefits of TAVR, resulting in a large proportion of patients preferring TAVR to SAVR. Further work should be undertaken to characterize the heterogeneity in preferences for AS treatment attributes. Shared decision-making tools based on attributes important to patients can support patients’ selection of the procedure that best meets their needs.

scholarly journals ECONOMICS OF RANDOMNESS: BEHAVIORAL ASPECTS OF DECISION MAKING UNDER RISK

2017 ◽  
Vol 9 (2) ◽  
pp. 7-14
Author(s):  
Alexander Krasilnikov
Keyword(s):  
Decision Making ◽  
Risk Analysis ◽  
Uncertainty Analysis ◽  
Expected Utility ◽  
Utility Theory ◽  
Expected Utility Theory ◽  
Probabilistic Methods ◽  
Risk And Uncertainty ◽  
Decision Making Under Risk ◽  
History Of

The paper discusses evolution of the concept of risk in economics. History of probabilistic methods and approaches to risk and uncertainty analysis is considered. Expected utility theory, behavioral approaches, heuristic models and methods of neuroeconomics are analyzed. Author investigates stability of neoclassical program related to risk analysis and suggests further directions of development.

PROTECTING RESOURCES IN THE LAKE WASHINGTON SHIP CANAL USING REAL-TIME ECOLOGICAL RISK ANALYSIS

2001 ◽  
Vol 2001 (2) ◽  
pp. 1535-1540
Author(s):  
David G. Mora
Keyword(s):  
Risk Analysis ◽  
Real Time ◽  
Geographic Area ◽  
Trade Offs ◽  
Resource Protection ◽  
Lake Washington ◽  
Response Plan ◽  
Conflicting Interests ◽  
Response Decisions ◽  
Ecological Risk Analysis

ABSTRACT Response managers and resource protection specialists often face difficult environmental trade-offs. Many decisions are time sensitive so decision-making criteria developed prior to an actual spill event will often hold sway. Despite such planning efforts all too frequently there is great room for doubt and plenty of room for speculation regarding response decisions. Response planners frequently debate environmental trade-offs associated with dispersant applications, shoreline cleanup strategy, etc. Broad assumptions and uncertainty are in large part the fuel for such debates. This paper focuses on the dilemmas associated with developing a particular response plan in a particular geographic area (i.e., for the Lake Washington Ship Canal. Development of this plan is important because of needs for rapid response decisions in an area involving many conflicting interests. This paper suggests an approach for developing this plan utilizing real time risk analysis.

Cost effectiveness of fire management strategies in southern Australia

2020 ◽  
Vol 29 (5) ◽  
pp. 427 ◽  
Author(s):  
T. D. Penman ◽  
B. A. Cirulis
Keyword(s):  
Risk Analysis ◽  
Prescribed Burning ◽  
Fire Management ◽  
Management Strategies ◽  
Fire Risk ◽  
Simulation Software ◽  
Bayesian Decision ◽  
Fire Simulation ◽  
Trade Offs ◽  
Increased Risk

Fire-management agencies invest significant resources to reduce the impacts of future fires. There has been increasing public scrutiny over how agencies allocate fire-management budgets and, in response, agencies are looking to use quantitative risk-based approaches to make decisions about expenditure in a more transparent manner. Advances in fire-simulation software and computing capacity of fire-agency staff have meant that fire simulators have been increasingly used for quantitative fire-risk analysis. Here we analyse the cost trade-offs of future fire management in the Australian Capital Territory (ACT) and surrounding areas by combining fire simulation with Bayesian Decision Networks. We compare potential future-management approaches considering prescribed burning, suppression and fire exclusion. These data combined costs of treatment and impacts on assets to undertake a quantitative risk analysis. The proposed approach for fuel treatment in ACT and New South Wales (NSW) provided the greatest reduction in risk and the most cost-effective approach to managing fuels in this landscape. Past management decisions have reduced risk in the landscape and the legacy of these treatments will last for at least 3 years. However, an absence of burning will result in an increased risk from fire in this landscape.

Assessing local and spatial uncertainty with HER method

2021 ◽  
Author(s):  
Stephanie Thiesen ◽  
Uwe Ehret
Keyword(s):  
Uncertainty Analysis ◽  
Spatial Configuration ◽  
Order Relation ◽  
Uncertainty Estimation ◽  
Indicator Kriging ◽  
Distribution Functions ◽  
Spatial Uncertainty ◽  
Cumulative Distribution ◽  
Trade Offs ◽  
Entropy Reduction

&lt;p&gt;Uncertainty analysis is a critical subject for many environmental studies. We have previously combined statistical learning and Information Theory in a geostatistical framework for overcoming parameterization with functions and uncertainty trade-offs present in many traditional interpolators (Thiesen et al. 2020). The so-called Histogram via entropy reduction (HER) relaxes normality assumptions, avoiding the risk of adding information not available in the data. The authors showed that, by construction, the method provides a proper framework for uncertainty estimation which accounts for both spatial configuration and data values, while allowing one to introduce or infer properties of the field through the aggregation method. In this study, we explore HER method in the light of uncertainty analysis. In general, uncertainty at any particular unsampled location (local uncertainty) is frequently assessed by nonlinear interpolators such as indicator and multi-gaussian kriging. HER has shown to be a unique approach for dealing with uncertainty estimation in a fine resolution without the need of modeling multiple indicator semivariograms, order-relation violations, interpolation/extrapolation of conditional cumulative distribution functions, or stronger hypotheses of data distribution. In this work, this nonparametric geostatistical framework is adapted to address local and spatial uncertainty in the context of risk mapping. We investigate HER for handling estimations of threshold-exceeding probabilities to map the risk of soil contamination by lead in the well-known dataset of the region of Swiss Jura. Finally, HER method is extended to assess spatial uncertainty (uncertainty when several locations are considered together) through sequential simulation. Its results are compared to indicator kriging and benchmark models available in the literature generated for this particular dataset.&lt;/p&gt;&lt;p&gt;Thiesen S, Vieira DM, M&amp;#228;licke M, Loritz R, Wellmann JF, Ehret U (2020) Histogram via entropy reduction (HER): an information-theoretic alternative for geostatistics. Hydrol Earth Syst Sci 24:4523&amp;#8211;4540. https://doi.org/https://doi.org/10.5194/hess-24-4523-2020&lt;/p&gt;

Validation and uncertainty analysis of the match climates regional algorithm (CLIMEX) for Pest risk analysis

2021 ◽  
Vol 61 ◽  
pp. 101196
Author(s):  
Mariona Roigé ◽  
Craig B. Phillips
Keyword(s):  
Risk Analysis ◽  
Uncertainty Analysis ◽  
Pest Risk Analysis ◽  
Pest Risk

scholarly journals Uncertainty analysis in multi-sector systems: Considerations for risk analysis, projection, and planning for complex systems

2022 ◽  
Author(s):  
Vivek Srikrishnan ◽  
David C Lafferty ◽  
Tony E Wong ◽  
Jonathan R. Lamontagne ◽  
Julianne D Quinn ◽  
...  
Keyword(s):  
Risk Analysis ◽  
Complex Systems ◽  
Uncertainty Analysis

Quantitative assessment of risks on construction projects using fault tree analysis with hybrid uncertainties

2019 ◽  
Vol 19 (1) ◽  
pp. 48-70 ◽  
Author(s):  
Shahab Shoar ◽  
Farnad Nasirzadeh ◽  
Hamid Reza Zarandi
Keyword(s):  
Risk Analysis ◽  
Uncertainty Analysis ◽  
Fuzzy Set ◽  
Fault Tree ◽  
Analysis Method ◽  
Content Type ◽  
Quantitative Risk Analysis ◽  
Probability Of Occurrence ◽  
Hybrid Uncertainty ◽  
The Impact

Purpose The purpose of this paper is to present a fault tree (FT)-based approach for quantitative risk analysis in the construction industry that can take into account both objective and subjective uncertainties. Design/methodology/approach In this research, the identified basic events (BEs) are first categorized based on the availability of historical data into probabilistic and possibilistic. The probabilistic and possibilistic events are represented by probability distributions and fuzzy numbers, respectively. Hybrid uncertainty analysis is then performed through a combination of Monte Carlo simulation and fuzzy set theory. The probability of occurrence of the top event is finally calculated using the proposed FT-based hybrid uncertainty analysis method. Findings The efficiency of the proposed method is demonstrated by implementing in a real steel structure project. A quantitative risk assessment is performed for weld cracks, taking into account of both types of uncertainties. An importance analysis is finally performed to evaluate the contribution of each BE to the probability of occurrence of weld cracks and adopt appropriate response strategies. Research limitations/implications In this research, the impact of objective (aleatory) dependence between the occurrences of different BEs and subjective (epistemic) dependence between estimates of the epistemically uncertain probabilities of some BEs are not considered. Moreover, there exist limitations to the application of fuzzy set rules, which were used for aggregating experts’ opinions and ranking purposes of the BEs in the FT model. These limitations can be investigated through further research. Originality/value It is believed that the proposed hybrid uncertainty analysis method presents a robust and powerful tool for quantitative risk analysis, as both types of uncertainties are taken into account appropriately.

scholarly journals Uncertainty analysis of trade-offs between multiple responses using hypervolume

2017 ◽  
Vol 33 (8) ◽  
pp. 2343-2360
Author(s):  
Yongtao Cao ◽  
Lu Lu ◽  
Christine M. Anderson-Cook
Keyword(s):  
Uncertainty Analysis ◽  
Multiple Responses ◽  
Trade Offs

Novel players fine-tune plant trade-offs

2015 ◽  
Vol 58 ◽  
pp. 83-100 ◽  
Author(s):  
Selena Gimenez-Ibanez ◽  
Marta Boter ◽  
Roberto Solano
Keyword(s):  
Ubiquitin Ligase ◽  
Feedback Loop ◽  
Molecular Level ◽  
26S Proteasome ◽  
Signalling Molecules ◽  
Transcriptional Reprogramming ◽  
Trade Offs ◽  
Jaz Proteins ◽  
Regulatory Feedback Loop ◽  
Fine Tune

Jasmonates (JAs) are essential signalling molecules that co-ordinate the plant response to biotic and abiotic challenges, as well as co-ordinating several developmental processes. Huge progress has been made over the last decade in understanding the components and mechanisms that govern JA perception and signalling. The bioactive form of the hormone, (+)-7-iso-jasmonyl-l-isoleucine (JA-Ile), is perceived by the COI1–JAZ co-receptor complex. JASMONATE ZIM DOMAIN (JAZ) proteins also act as direct repressors of transcriptional activators such as MYC2. In the emerging picture of JA-Ile perception and signalling, COI1 operates as an E3 ubiquitin ligase that upon binding of JA-Ile targets JAZ repressors for degradation by the 26S proteasome, thereby derepressing transcription factors such as MYC2, which in turn activate JA-Ile-dependent transcriptional reprogramming. It is noteworthy that MYCs and different spliced variants of the JAZ proteins are involved in a negative regulatory feedback loop, which suggests a model that rapidly turns the transcriptional JA-Ile responses on and off and thereby avoids a detrimental overactivation of the pathway. This chapter highlights the most recent advances in our understanding of JA-Ile signalling, focusing on the latest repertoire of new targets of JAZ proteins to control different sets of JA-Ile-mediated responses, novel mechanisms of negative regulation of JA-Ile signalling, and hormonal cross-talk at the molecular level that ultimately determines plant adaptability and survival.

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