Risk-based Estimation Research Articles

Assessing the probability of freedom from pine wood nematode based on 19 years of surveys

Many quarantine pests, such as the pine wood nematode (PWN, Bursaphelenchus xylophilus), are surveyed annually in all EU countries. Although a lot of resources are spent in the surveys, the confidence in pest freedom achieved with them is not commonly analysed. We assessed the probability that Finland is free from PWN, based on the surveys done in 2000–2018. We used the methods employed in the risk-based estimate of system sensitivity tool (RiBESS), which has recently been recommended for quarantine pest applications. We considered two scenarios: 1) the surveys aimed to justify phytosanitary import requirements and to facilitate exports and 2) the surveys aimed to detect invasions early to enable eradication of outbreaks. These differed only in the pest prevalence that the surveys were expected to detect. The surveys appeared to support the assumption that PWN is not present in Finland, but they did not seem extensive enough to ensure early detection of invasions. The sensitivity of the import-export surveys was greater than 0.6 in 13 years, whereas that of the early detection surveys was always below 0.25. The probability of freedom achieved in 2018 following 19 years of surveys increased asymptotically with the mean time between invasions. For the import-export surveys, this probability was at least 0.95 unless the mean time between invasions was less than 13 years. For the early detection surveys, the probability of freedom was less than 0.73 unless the mean time between invasions was 63 years or more. The results were rather robust with respect to the parameters for which exact information was lacking. To improve the assessment, a quantitative estimate of the probability of PWN invasion to Finland and a thorough assessment of the maximum area of an eradicable infestation would be needed. To gain an understanding about the true impact of quarantine pest surveys on biosecurity, more assessments, like the one presented in this paper, are needed.

Risk analysis, ideal observers, and receiver operating characteristic curves for tasks that combine detection and estimation.

Previously published work on joint estimation/detection tasks has focused on the area under the estimation receiver operating characteristic (EROC) curve as a figure of merit (FOM) for these tasks in imaging. Another FOM for these joint tasks is the Bayesian risk, where a cost is assigned to all detection outcomes and to the estimation errors, and then averaged over all sources of randomness in the object ensemble and the imaging system. Important elements of the cost function, which are not included in standard EROC analysis, are that the cost for a false positive depends on the estimate produced for the parameter vector, and the cost for a false negative depends on the true value of the parameter vector. The ideal observer in this setting, which minimizes the risk, is derived for two applications. In the first application, a parameter vector is estimated only in the case of a signal present classification. For the second application, parameter vectors are estimated for either classification, and these vectors may have different dimensions. In both applications, a risk-based estimation receiver operating characteristic curve is defined and an expression for the area under this curve is given. It is also shown that, for some observers, this area may be estimated from a two alternative forced choice test. Finally, if the classifier is optimized for a given estimator, then it is shown that the slope of the risk-based estimation receiver operating characteristic curve at each point is the negative of the ratio of the prior probabilities for the two classes.

PROBABILISTIC TSUNAMI HAZARD ASSESSMENT AND DAMAGE ESTIMATION OF THE BUILT ENVIRONMENT: APPLICATION TO THE CASCADIA SUBDUCTION ZONE AND SEASIDE, OREGON

Risk-based damage estimation to the built environment from future tsunamis is fundamental for developing mitigation and evacuation plans. One of the challenging problems in the evaluation of damage from future tsunamis is that the uncertainty from the nature of tsunami itself (e.g. Magnitude, Epicenter, Fault slip distributions) and the lack of accumulated sufficient observed data for probabilistic studies due to the relatively small frequency of tsunami historical events. Even though tsunami modeling has matured over the past several decades and provides reliable estimation of tsunami hazards such as flow depth, velocity, arrival time, etc., questions remain on how to predict future tsunami hazards and how to estimate tsunami damage, especially for the engineers who want to design shelter-in-plate options or coastal planners who want to estimate the possible damage from future tsunami events on the built environment at community and regional scales. As a case study, we evaluate the probabilistic damage states of an urban coastal city, Seaside, Oregon from future tsunamis generated on the Cascadia Subduction Zone (CSZ). The methodology and the results are separated into two parts: (1) Probabilistic tsunami hazard assessment (Park et al., 2017) and (2) Probabilistic building damage assessment from the tsunamis hazards with a community scale.

Advancing Retail Food Policy Debates: Estimating the Risk of Contaminated Servings of Food Attributed to Employee Food Handling Practices in Retail Food Establishments

Food employee contamination of ready-to-eat foods through improper food handling practices is an important contributing factor for foodborne illness in retail and food service establishments. Decreasing the incidence of improper food handling practices is a frequent topic of retail food policy deliberations that often involves estimating the degree to which a proposed policy might affect a specific food handling practice. However, the potential reduction in contaminated servings of food, and therefore foodborne illnesses avoided, associated with a given proposed policy change, is all too often uncertain. This article discusses the components, assumptions, and applications of the food handling practices model, a quantitative model that estimates the impact of food handling practices on servings of food moving along three consecutive stages: the contamination stage, the pathogen control stage, and the foodborne illness stage. To our knowledge, this article is the first time the model has been presented in an academic platform, and we also explore unique and interesting aspects of the model not addressed in publicly available documents. Risk-based estimates for contaminated servings of food attributed to changes in one or multiple food handling practices are derived that provide an important link between increased compliance with proper food handling practices and public health. Model estimates show that decreases in the incidence of inappropriate food handling practices lead to varying levels of contaminated food servings avoided, depending on the food handling practice. The ability to derive such estimates provides stakeholders and the general public with a means of understanding the relative impact of proposals to reduce improper food handling and to help inform regulatory food safety policy discussions and decision making.

Towards Risk Based Effort Estimation

Studies have shown that requirement defects are among the major sources of failure constituting 32.65%. It is one of the overlooked aspects in requirements engineering and is generally considered as a potential problem that can affect the projects in a negative way. The main objective of this article is to propose a risk-based effort estimation technique that identifies, analyzes, and classifies risk at requirement engineering phase to restrain them from propagating to the later stages of the project lifecycle. This article extends the scope by integrating both threats and opportunities and their further classification based on extensive requirement analysis. The validation of the proposed approach was conducted on successfully delivered real project data. A survey is also conducted as a part of qualitative analysis for analyzing the applicability of the proposed approach. The results of the proposed method are promising and strongly support findings of literature stating that the effort needed to fix issues at a later stage in project lifecycle are costly as compared to early stages.

SUPPLY CHAIN RISK MANAGEMENT BY MONTE CARLO METHOD

In this paper, the conceptual model of risk-based cost estimation for completing tasks within supply chain is presented. This model is a hybrid. Its main unit is based on Monte Carlo Simulation (MCS). Due to the fact that the important and difficult to evaluate input information is vector of risk-occur probabilities the use of artificial intelligence method was proposed. The model assumes the use of fuzzy logic or artificial neural networks – depending on the availability of historical data. The presented model could provide support to managers in making valuation decisions regarding various tasks in supply chain management.

Risk-based estimate for operational safety in complex projects under uncertainty

This paper presents a hybrid risk-based estimate approach that integrates the fuzzy matter-element theory and Monte Carlo simulation method to assessing the safety risk of operational tailings ponds and sensitivity of influential factors under uncertainty. The fuzzy matter-element theory is used as a reasoning tool to solve contradictory problems with fuzziness and randomness; while the Monte Carlo simulation method acts as a tool for describing and reducing uncertainty by using probability distributions. The novelty lies in an improvement to both the conventional Deterministic Estimate (DE) approach and existing Risk-Based Estimate (RBE) approaches that mainly focus on the project cost/schedule estimate, as the proposed approach can not only estimate the system safety under uncertainty, but also perform sensitivity analysis. A comprehensive index system consisting of 22 influential factors is developed for the assessment of safety risk of tailings ponds in operation. A confidence indicator θ is proposed to verify the reliability of assessment results. A Spearman’s rank correlation coefficient is used as a sensitivity measure to identify significant factors by discovering the sensitivity of the system performance to minor changes in input factors. Six large tailings ponds in China are selected as a case study for assessing the magnitude of safety risk and sensitivity of influential factors, in order to demonstrate the feasibility and applicability of the developed approach. Results indicate that the developed approach is capable of (i) synthesizing multi-source information in decision making, (ii) addressing uncertainty in complex project environments, and (iii) achieving dynamic risk analysis over time. This approach can be used by practitioners in the industry as a decision tool for system safety analysis and assessment under uncertainty, providing insight on improving the safety performance of existing tailings ponds in a continuous manner.

공동주택 리모델링 초기 단계 의사결정을 위한 확률론적 리스크 기반 비용 예측 모델 개발

공동주택 리모델링 초기 단계 의사결정을 위한 확률론적 리스크 기반 비용 예측 모델 개발

Reviewing estimates of the economic efficiency of disaster risk management: opportunities and limitations of using risk-based cost–benefit analysis

There is a lot of rhetoric suggesting that disaster risk reduction (DRR) pays, yet surprisingly little in the way of hard facts. This review paper examines the evidence regarding the economic efficiency of DRM based on CBA. Specifically, it addresses the following questions: What can be said about current and best practice regarding CBA for DRR including limitations and alternatives? And, what, if at all, can be said in terms of quantitative insight for informing policy and practice? The review compares the documented evidence on the net benefits over a range of disaster management interventions, such as risk reduction, preparedness and risk financing. The review also critically discusses the applicability of cost–benefit analysis as well as other economic decision-supporting tools for assessing the efficiency of certain DRM interventions. Disaster risk is characterized by variability, which requires a risk-based assessment. As a key best practice criterion, and in order to avoid overestimating the benefits and returns on investment, the review focuses on studies that provide a risk-based estimate of benefits. This review shows that for the limited evidence reported the economic case for DRM across a range of hazards is strong and that the benefits of investing in DRM outweigh the costs of doing so on average, by about four times the cost in terms of avoided and reduced losses. In an age of austerity, cost–benefit analysis continues to be an important tool for prioritizing efficient DRM measures but with a shifting emphasis from infrastructure-based options (hard resilience) to preparedness and systemic interventions (soft resilience), other tools such as cost-effectiveness analysis, multi-criteria analysis and robust decision-making approaches deserve more attention.

Achieving ‘best value’ for the community by deployment of risk based cost estimation using Monte-Carlo Simulation to rate-payer-funded capital intensive road projects.

This paper presents the application and validation of a new tool developed by the first author for accurate risk-based estimation of project budgets. Typical capital intensive projects to which this tool can be applied include road reconstruction, road resheet and road rehabilitation projects. Quantitative risk analysis and stochastic modeling using Monte -Carlo simulation is embedded in the algorithms of the computer code. The tool forecasts a range of possible project costs and the probability of the occurrence of those costs by taking into account uncertainties and associated risks. Application of the tool to capital intensive road projects designed by the second author and constructed in 2011 & 2012 demonstrates its validity and utility. Comparisons of forecasted estimates using this tool with actual costs and with traditional deterministic methods of cost estimation (such as --point base-case estimates inclusive of contingency) provide valuable insights that can aid management in evaluating alternatives and in making informed decisions when estimating and allocating budgets to a portfolio of road projects.

A risk-based availability estimation using Markov method

Purpose – Asset intensive process industries are under immense pressure to achieve promised return on investments and production targets. This can be accomplished by ensuring the highest level of availability, reliability and utilization of the critical equipment in processing facilities. In order to achieve designed availability, asset characterization and maintainability play a vital role. The most appropriate and effective way to characterize the assets in a processing facility is based on risk and consequence of failure. The paper aims to discuss these issues. Design/methodology/approach – In this research, a risk-based stochastic modeling approach using a Markov decision process is investigated to assess a processing unit's availability, which is referred as the risk-based availability Markov model (RBAMM). RBAMM will not only provide a realistic and effective way to identify critical assets in a plant but also a method to estimate availability for efficient planning purposes and resource optimization. Findings – A unique risk matrix and methodology is proposed to determine the critical equipment with direct impact on the availability, reliability and safety of the process. A functional block diagram is then developed using critical equipment to perform efficient modeling. A Markov process is utilized to establish state diagrams and create steady-state equations to calculate the availability of the process. RBAMM is applied to natural gas absorption process to validate the proposed methodology. In the conclusion, other benefits and limitations of the proposed methodology are discussed. Originality/value – A new risk-based methodology integrated with Markov model application of the methodology is demonstrated using a real-life application.

Discussion on road infrastructure asset management practices

The objective of this study is to discuss and compare the practices of Road Infrastructure Asset Management System (RIAMS) adopted in different countries. This discussion mainly focuses on the pavement management system. Internationally, the RIAMS approach is moving from the condition-based towards the service-based approach focusing on the customer-driven priorities. This service-based approach needs to be balanced with the budget constraints, level of service and risk tolerance. The transportation agencies have not yet addressed the integrated land use and transportation modelling, the comparison of the relative advantages between capital and operating investments, the risk-based estimation, and the identification of a range of costs associated with the failure within the RIAMS. The transportation agencies should develop a performance-based RIAMS ensuring the serviceability, accountability, stewardship, long-term financial plans, and transparent investments. The RIAMS is still emerging and needs to incorporate the local mission, budget and other constraints within the scope of the local context.

Up-scaling of impact dependent loss distributions: a hybrid convolution approach for flood risk in Europe

This paper introduces a new method to up-scale dependent loss distributions from natural hazards to higher spatial levels, explicitly incorporating their dependency structure over the aggregation process. The method is applied for flood risk in Europe. Based on this “hybrid convolution” approach, flood loss distributions for nearly all European countries are calculated and presented. Such risk-based estimates of extreme event losses are useful for determining suitable risk management strategies on various spatial levels for different risk bearers. The method is not only applicable for natural disaster risk but can be extended for other cases as well, i.e., where comonotonic risks have to be “summed up” without loss of risk information.

Cigarette smoking impairs pancreatic duct cell bicarbonate secretion.

To compare pancreatic duct cell function in smokers (current and past) and never smokers by measurement of secretin-stimulated peak bicarbonate concentration ([HCO3-]) in endoscopic collected pancreatic fluid (PF). This retrospective study was cross-sectional in design, recording demographic information (age, gender, etc.), smoking status (former, current, never), alcohol intake, clinical data (imaging, endoscopy), and laboratory results (peak PF [HCO3-]) from subjects evaluated for pancreatic disease at a tertiary pancreas center. Univariate and multivariate statistical analysis (SAS Version 9.2, Cary, NC, USA) was performed to assess the relationship between cigarette smoking and secretin-stimulated pancreatic fluid bicarbonate concentration. A total of 131 subjects underwent pancreatic fluid collection (endoscopic pancreatic function test, ePFT) for bicarbonate analysis: 25.2% (33 out of 131) past smokers, 31.3% (41 out of 131) current smokers, and 43.5% (57 out of 131) were never smokers. Measures of Association: The mean peak PF [HCO3-] in never smokers (81.3 ± 18.5 mEq/L) was statistically higher (indicating better duct cell function) when compared to past smokers (66.8 ± 24.7 mEq/L, P=0.005) and current smokers (70.0 ± 20.2 mEq/L, P=0.005). However, the mean peak [HCO3-] in past smokers was not statistically different from that in current smokers (P=0.575), and therefore, the two smoking groups were combined to form a single "smokers cohort". When compared to the never smokers, the smokers cohort was older (P=0.037) and had a greater proportion of subjects with definite chronic pancreatitis imaging (P=0.010), alcohol consumption ≥20 g/day (P=0.012), and abnormal peak PF [HCO3-] (P<0.001). Risk-Based Estimates: Cigarette smoking (risk ratio, RR: 2.2, 95% CI: 1.3-3.5; P<0.001), diagnosis of definite chronic pancreatitis imaging (RR: 2.2, 95% CI: 1.6-3.2; P<0.001) and alcohol consumption ≥20 g/day (RR: 1.6, 95% CI: 1.1-2.4; P=0.033) were all associated with low mean peak PF [HCO3-] (indicating duct cell secretory dysfunction). Multivariate Analysis: Smoking (odds ratio, OR: 3.8, 95% CI: 1.6-9.1; P=0.003) and definite chronic pancreatitis imaging (OR: 5.7, 95% CI: 2.2-14.8; P<0.001) were determined to be independent predictors of low peak PF [HCO3-], controlling for age, gender, and alcohol intake. Furthermore there was no interaction between smoking status and alcohol intake in predicting duct cell dysfunction (P=0.571). Measurement of pancreatic fluid bicarbonate in smokers reveals that cigarette smoking (past and current) is an independent risk factor for pancreatic duct cell secretory dysfunction (low PF [HCO3-]). Furthermore, the risk of duct cell dysfunction in subjects who smoked was approximately twice the risk (RR: 2.2) in never smokers. Further in depth, translational research approaches to pancreatic fluid analysis may help unravel mechanisms of cigarette smoking induced pancreatic duct cell injury.

Risk-based damage potential and loss estimation of earthquake scenarios in the moderate endangered Austrian Federal Province of Tyrol

Although geophysical hazards like earthquakes can lead to tremendous losses, they are often neglected or not considered in risk analyses within an Alpine context. However, lately and especially in the framework of multi-risk analyses, earthquake risk studies are being increasingly implemented within an Alpine relation too. The presented study was conducted to quantitatively estimate potential consequences of earthquake events in the Austrian Province of Tyrol. The methodological study framework integrates the general risk components (i) hazard, (ii) elements at risk, and (iii) vulnerability. They are considered on a regional scale, accepting pragmatic approaches with simplified procedures and assumptions. Scenarios for different potential epicentres were calculated based on two different macroseismic hazard maps derived from punctual ground motion values of the building code and microzonation studies. The maps take into account the design event definitions of existing building code and a, thereupon based, simple and mono-causal Maximum Credible Earthquake assumption. Corresponding elements at risk and damage potentials were identified and potential losses were estimated under consideration of different vulnerability approaches. It can be shown that most scenarios based on the design event definition of the Austrian and European building codes, respectively have the potential of building and inventory losses solely of some hundred million up to approximately €4 billion. Additional, building and inventory losses of maximum credible events can lead to losses of more than €7 billion merely in connection with the primary earthquake event neglecting all other cascading effects.

Risk-based Estimate of Effect of Foodborne Diseases on Public Health, Greece

The public health effects of illness caused by foodborne pathogens in Greece during 1996-2006 was quantified by using publicly available surveillance data, hospital statistics, and literature. Results were expressed as the incidence of different disease outcomes and as disability-adjusted life years (DALY), a health indicator combining illness and death estimates into a single metric. It has been estimated that each year ≈370,000 illnesses/million inhabitants are likely caused because of eating contaminated food; 900 of these illnesses are severe and 3 fatal, corresponding to 896 DALY/million inhabitants. Ill-defined intestinal infections accounted for the greatest part of reported cases and 27% of the DALY. Brucellosis, echinococcosis, salmonellosis, and toxoplasmosis were found to be the most common known causes of foodborne illnesses, being responsible for 70% of the DALY. Overall, the DALY metric provided a quantitative perspective on the impact of foodborne illness that may be useful for prioritizing food safety management targets.

Calculating Loss Reserves in a Multistate Model for Income Insurance

This article proposes a method to estimate a sufficient loss reserve for insurance companies, such that they can cover income insurance claims filed by self-employed workers. The first step involves a multistate mixed proportional hazards (MPH) approach to model self-employed workers’ disability durations, together with changes in their health conditions during their incapacity. Combining the multistate MPH model with Monte Carlo simulations reveals risk-based estimates of loss reserves for claim portfolios. To assess the quality of the estimated loss reserves, this study quantifies the amount of process and parameter uncertainty involved with the estimates and performs an out-of-sample prediction exercise.

Risk-based damage potential and loss estimation of extreme flooding scenarios in the Austrian Federal Province of Tyrol

Abstract. Within the last decades serious flooding events occurred in many parts of Europe and especially in 2005 the Austrian Federal Province of Tyrol was serious affected. These events in general and particularly the 2005 event have sensitised decision makers and the public. Beside discussions pertaining to protection goals and lessons learnt, the issue concerning potential consequences of extreme and severe flooding events has been raised. Additionally to the general interest of the public, decision makers of the insurance industry, public authorities, and responsible politicians are especially confronted with the question of possible consequences of extreme events. Answers thereof are necessary for the implementation of preventive appropriate risk management strategies. Thereby, property and liability losses reflect a large proportion of the direct tangible losses. These are of great interest for the insurance sector and can be understood as main indicators to interpret the severity of potential events. The natural scientific-technical risk analysis concept provides a predefined and structured framework to analyse the quantities of affected elements at risk, their corresponding damage potentials, and the potential losses. Generally, this risk concept framework follows the process steps hazard analysis, exposition analysis, and consequence analysis. Additionally to the conventional hazard analysis, the potential amount of endangered elements and their corresponding damage potentials were analysed and, thereupon, concrete losses were estimated. These took the specific vulnerability of the various individual elements at risk into consideration. The present flood risk analysis estimates firstly the general exposures of the risk indicators in the study area and secondly analyses the specific exposures and consequences of five extreme event scenarios. In order to precisely identify, localize, and characterize the relevant risk indicators of buildings, dwellings and inventory, vehicles, and individuals, a detailed geodatabase of the existing stock of elements and values was established on a single object level. Therefore, the localized and functional differentiated stock of elements was assessed monetarily on the basis of derived representative mean insurance values. Thus, well known difference factors between the analysis of the stock of elements and values on local and on regional scale could be reduced considerably. The spatial join of the results of the hazard analysis with the stock of elements and values enables the identification and quantification of the elements at risk and their corresponding damage potential. Thereupon, Extreme Scenario Losses (ESL) were analysed under consideration of different vulnerability approaches which describe the individual element's specific susceptibility. This results in scenario-specific ranges of ESL rather than in single values. The exposure analysis of the general endangerment in Tyrol identifies (i) 105 330 individuals, (ii) 20 272 buildings and 50 157 dwellings with a corresponding damage potential of approx. EUR 20 bn. and (iii) 62 494 vehicles with a corresponding damage potential of EUR 1 bn. Depending on the individual extreme event scenarios, the ESL solely to buildings and inventory vary between EUR 0.9–1.3 bn. for the scenario with the least ESL and EUR 2.2–2.5 bn. for the most serious scenarios. The correlation of the private property losses to buildings and inventory with further direct tangible loss categories on the basis of investigation after the event in 2005, results in potential direct tangible ESL of up to EUR 7.6 bn. Apart from the specific study results a general finding shows that beside the further development of modelling capabilities and scenario concepts, the key to considerably decrease uncertainties of integral flood risk analyses is the development and implementation of more precise methods. These are to determine the stock of elements and values and to evaluate the vulnerability or susceptibility of affected structures to certain flood characteristics more differentiated.

Analytical Framework for a Risk-based Estimation of Climate Change Effects on Mine Site Runoff Water Quality

A conceptual analytical framework was developed for the risk-based estimation of climate change effects on mine waste runoff water quality. The modeling approach incorporates temporal variability in both precipitation and temperature using trend analyses from historical datasets and the resulting effects on water balances and geochemical weathering rates. A case-study method was used to develop and present the model for regions near the city of Yellowknife, Northwest Territories, Canada. Time-resolved relative precipitation and weathering factors can be calculated using climate data and site-specific estimates regarding mine waste properties. Interpretation of these factors allows an assessment of when the period of highest analyte concentrations are expected to occur under a given risk scenario over a modeling timeframe, whether low precipitation or warming effects are more important in determining water quality issues, and the relative magnitudes of water quality under differing risk scenarios.

Food control officers perception of the challenges in implementing new food control requirements in Finland

In addition to the food control officers’ former tasks, new EU and Finnish legislations have established new obligations for them, such as building up a quality system, amending a control plan and expanding the collection of fees to cover all the control targets. In order to study the implementation of these new tasks, an electronic survey was sent to the local food control officials in Finland. Our study shows that there will be significant differences in implementing the new food control requirements in Finland by our local units when we take into consideration the time of implementation, the approach and content of control plans, and the quality systems or fees. Especially the risk-based estimation of the control objects seems to have created a challenge in both the quality systems and in the control plans; in only 16% of the municipalities, the risk estimations had been calculated for each control object and in most cases, this estimation was made and the control frequency was decided on solely by their own inspector of the object alone. Furthermore, the amount of the planned fees per hour varied from 21 Euros to 45 Euros. Several respondents also expressed that they had no knowledge of the grounds for the charges of future inspections or the amount of fees. What is apparent is that the new approach will be implemented relatively slowly in Finland and there is a risk of the different treatment of business operators depending on their geographical location.