Concepts and methods of quantitative assessment of risk to groundwater resources

This work presents a two-dimensional approach of risk assessment method based on the quantification of the probability of the occurrence of contaminant source terms, as well as the assessment of the resultant impacts. The risk is calculated using Monte Carlo simulation methods whereby synthetic contaminant source terms were generated to the same distribution as historically occurring pollution events or a priori potential probability distribution. The spatial and temporal distributions of the generated contaminant concentrations at pre-defined monitoring points within the aquifer were then simulated from repeated realisations using integrated mathematical models. The number of times when user defined ranges of concentration magnitudes were exceeded is quantified as risk. The utilities of the method were demonstrated using hypothetical scenarios, and the risk of pollution from a number of sources all occurring by chance together was evaluated. The results are presented in the form of charts and spatial maps. The generated risk maps show the risk of pollution at each observation borehole, as well as the trends within the study area. This capability to generate synthetic pollution events from numerous potential sources of pollution based on historical frequency of their occurrence proved to be a great asset to the method, and a large benefit over the contemporary methods.

Towards a Better Modelling and Assessment of Construction Risk: Insights from a Literature Review

This paper reviews the literature of construction risk modelling and assessment. It also reviews the real practice of risk assessment. The review resulted in significant results, summarised as follows. There has been a major shift in risk perception from an estimation variance into a project attribute. Although the Probability–Impact risk model is prevailing, substantial efforts are being put to improving it reflecting the increasing complexity of construction projects. The literature lacks a comprehensive assessment approach capable of capturing risk impact on different project objectives. Obtaining a realistic project risk level demands an effective mechanism for aggregating individual risk assessments. The various assessment tools suffer from low take-up; professionals typically rely on their experience. It is concluded that a simple analytical tool that uses risk cost as a common scale and utilises professional experience could be a viable option to facilitate closing the gap between theory and practice of risk assessment.

The Use of Multi-Criteria Decision Analysis in Performing Alternatives Assessment and Comparative Risk Analysis: The Case Study of Codling Moth Pesticides

Thesis (Ph.D.)--University of Washington, 2016-08

Role of assessment components and recent adverse outcomes in risk estimation and prediction: use of the Short Term Assessment of Risk and Treatability (START) in an adult secure inpatient mental health service

The Short Term Assessment of Risk and Treatability is a structured judgement tool used to inform risk estimation for multiple adverse outcomes. In research, risk estimates outperform the tool's strength and vulnerability scales for violence prediction. Little is known about what its’component parts contribute to the assignment of risk estimates and how those estimates fare in prediction of non-violent adverse outcomes compared with the structured components. START assessment and outcomes data from a secure mental health service (N=84) was collected. Binomial and multinomial regression analyses determined the contribution of selected elements of the START structured domain and recent adverse risk events to risk estimates and outcomes prediction for violence, self-harm/suicidality, victimisation, and self-neglect. START vulnerabilities and lifetime history of violence, predicted the violence risk estimate; self-harm and victimisation estimates were predicted only by corresponding recent adverse events. Recent adverse events uniquely predicted all corresponding outcomes, with the exception of self-neglect which was predicted by the strength scale. Only for victimisation did the risk estimate outperform prediction based on the START components and recent adverse events. In the absence of recent corresponding risk behaviour, restrictions imposed on the basis of START-informed risk estimates could be unwarranted and may be unethical.

Performance of protective factors assessment in risk prediction for adults: systematic review and meta-analysis

Protective factors are neglected in risk assessment in adult psychiatric and criminal justice populations. This review investigated the predictive efficacy of selected tools that assess protective factors. Five databases were searched using comprehensive terms for records up to June 2014, resulting in 17 studies (n = 2,198). Results were combined in a multilevel meta-analysis using the R (R Core Team, R: A Language and Environment for Statistical Computing, Vienna, Austria: R Foundation for Statistical Computing, 2015) metafor package (Viechtbauer, Journal of Statistical Software, 2010, 36, 1). Prediction of outcomes was poor relative to a reference category of violent offending, with the exception of prediction of discharge from secure units. There were no significant differences between the predictive efficacy of risk scales, protective scales, and summary judgments. Protective factor assessment may be clinically useful, but more development is required. Claims that use of these tools is therapeutically beneficial require testing.

Improving risk stratification in non-ST-segment elevation myocardial infarction with combined assessment of GRACE and CRUSADE risk scores

BACKGROUND: Risk assessment is fundamental in the management of acute coronary syndromes (ACS), enabling estimation of prognosis. AIMS: To evaluate whether the combined use of GRACE and CRUSADE risk stratification schemes in patients with myocardial infarction outperforms each of the scores individually in terms of mortality and haemorrhagic risk prediction. METHODS: Observational retrospective single-centre cohort study including 566 consecutive patients admitted for non-ST-segment elevation myocardial infarction. The CRUSADE model increased GRACE discriminatory performance in predicting all-cause mortality, ascertained by Cox regression, demonstrating CRUSADE independent and additive predictive value, which was sustained throughout follow-up. The cohort was divided into four different subgroups: G1 (GRACE<141; CRUSADE<41); G2 (GRACE<141; CRUSADE≥41); G3 (GRACE≥141; CRUSADE<41); G4 (GRACE≥141; CRUSADE≥41). RESULTS: Outcomes and variables estimating clinical severity, such as admission Killip-Kimbal class and left ventricular systolic dysfunction, deteriorated progressively throughout the subgroups (G1 to G4). Survival analysis differentiated three risk strata (G1, lowest risk; G2 and G3, intermediate risk; G4, highest risk). The GRACE+CRUSADE model revealed higher prognostic performance (area under the curve [AUC] 0.76) than GRACE alone (AUC 0.70) for mortality prediction, further confirmed by the integrated discrimination improvement index. Moreover, GRACE+CRUSADE combined risk assessment seemed to be valuable in delineating bleeding risk in this setting, identifying G4 as a very high-risk subgroup (hazard ratio 3.5; P<0.001). CONCLUSIONS: Combined risk stratification with GRACE and CRUSADE scores can improve the individual discriminatory power of GRACE and CRUSADE models in the prediction of all-cause mortality and bleeding. This combined assessment is a practical approach that is potentially advantageous in treatment decision-making.

GIS applied to geotechnical and environmental risk management in a Brazilian oil pipeline

The paper presents the development of a decision support system for the management of geotechnical and environmental risks in oil pipelines using a geographical information system. The system covers a 48.5 km long section of the So Paulo to Brasilia (OSBRA) oil pipeline, which crosses three municipalities in the northeast region of the So Paulo state (Brazil) and represents an area of 205.8 km(2). The spatial database was created using geo-processing procedures, surface and intrusive investigations and geotechnical reports. The risk assessment was based mainly on qualitative models (relative numeric weights and multicriteria decision analysis) and considered pluvial erosion, slope movements, soil corrosion and third party activities. The maps were produced at a scale of 1:10,000.

A randomized and controlled trial of a participative ergonomics intervention to reduce injuries associated with manual tasks: physical risk and legislative

A participative ergonomics approach to reducing injuries associated with manual tasks is widely promoted; however only limited evidence from uncontrolled trials has been available to support the efficacy of such an approach. This paper reports on a randomized and controlled trial of PErforM, a participative ergonomics intervention designed to reduce the risks of injury associated with manual tasks. One hundred and seventeen small to medium sized food, construction, and health workplaces were audited by government inspectors using a manual tasks risk assessment tool (ManTRA). Forty-eight volunteer workplaces were then randomly assigned to Experimental and Control groups with the Experimental group receiving the PErforM program. Inspectors audited the workplaces again, 9 months following the intervention. The results showed a significant decrease in estimates of manual task risk and suggested better legal compliance in the Experimental group.

Absolute risk of breast cancer for Australian women with a family history

Background: The purpose of the present paper was to estimate the absolute risk of breast cancer over the remainder of a lifetime in Australian women with different categories of family history. Methods: Age-specific breast cancer incidence rates were adjusted for screening effects, and rates in those with no family history were estimated using the attributable fraction (AF). Relative risks from a published meta-analysis were applied to obtain incidence rates for different categories of family history, and age-specific incidence was converted to cumulative risk of breast cancer. The risk estimates were based upon Australian population statistics and published relative risks. Breast cancer incidence was from New South Wales women for 1996. The AF was calculated using prevalence of a family history of breast cancer from data on Queensland women. The cumulative absolute risk of breast cancer was calculated from decade and mid-decade ages to age 79 years, not adjusted for competing causes of death. Results: Lifetime risk is approximately 8.6% (1 in 12) for the general population and 7.8% (1 in 13) for those without a family history. Women with one relative affected have lifetime risks of 1 in 6-8 and those with two relatives affected have lifetime risks of 1 in 4-6. The cumulative residual lifetime risk decreases with advancing age; by age 60 years all groups with only one relative affected have well above a 90% probability of not developing breast cancer to age 79 years. Conclusions: These Australian risk statistics are useful for public information and in the clinical setting. Risks given here apply to women with average breast cancer risk from other risk factors.

Hierarchical risk scale of agribusiness activities

This study aims to elaborate a hierarchical risk scale (HRS) of agricultural and cattle breeding activities and to classify the main agricultural crops and cattle breeding activities according to their risk levels. The research is characterized as exploratory and quantitative and was based on previous risk assessment (MARKOWITZ, 1952) and capital cost calculation (SHARPE, 1964) work for other business segments. The calculations on agricultural and cattle breeding data were processed for the period from 2000 to 2006. The used methods considers simplifications and adaptations needed to achieve the proposed objective. The final result, pioneering and embryonic, provides support to improve the management of these activities that are so essential to produce food for society.

Comparing predictions of extinction risk using models and subjective judgement

Models of population dynamics are commonly used to predict risks in ecology, particularly risks of population decline. There is often considerable uncertainty associated with these predictions. However, alternatives to predictions based on population models have not been assessed. We used simulation models of hypothetical species to generate the kinds of data that might typically be available to ecologists and then invited other researchers to predict risks of population declines using these data. The accuracy of the predictions was assessed by comparison with the forecasts of the original model. The researchers used either population models or subjective judgement to make their predictions. Predictions made using models were only slightly more accurate than subjective judgements of risk. However, predictions using models tended to be unbiased, while subjective judgements were biased towards over-estimation. Psychology literature suggests that the bias of subjective judgements is likely to vary somewhat unpredictably among people, depending on their stake in the outcome. This will make subjective predictions more uncertain and less transparent than those based on models. (C) 2004 Elsevier SAS. All rights reserved.

Validation of a strategy to diagnose coronary artery disease and predict cardiac events in high-risk renal transplant candidates

Background We validated a strategy for diagnosis of coronary artery disease ( CAD) and prediction of cardiac events in high-risk renal transplant candidates ( at least one of the following: age >= 50 years, diabetes, cardiovascular disease). Methods A diagnosis and risk assessment strategy was used in 228 renal transplant candidates to validate an algorithm. Patients underwent dipyridamole myocardial stress testing and coronary angiography and were followed up until death, renal transplantation, or cardiac events. Results The prevalence of CAD was 47%. Stress testing did not detect significant CAD in 1/3 of patients. The sensitivity, specificity, and positive and negative predictive values of the stress test for detecting CAD were 70, 74, 69, and 71%, respectively. CAD, defined by angiography, was associated with increased probability of cardiac events [log-rank: 0.001; hazard ratio: 1.90, 95% confidence interval (CI): 1.29-2.92]. Diabetes (P=0.03; hazard ratio: 1.58, 95% CI: 1.06-2.45) and angiographically defined CAD (P=0.03; hazard ratio: 1.69, 95% CI: 1.08-2.78) were the independent predictors of events. Conclusion The results validate our observations in a smaller number of high-risk transplant candidates and indicate that stress testing is not appropriate for the diagnosis of CAD or prediction of cardiac events in this group of patients. Coronary angiography was correlated with events but, because less than 50% of patients had significant disease, it seems premature to recommend the test to all high-risk renal transplant candidates. The results suggest that angiography is necessary in many high-risk renal transplant candidates and that better noninvasive methods are still lacking to identify with precision patients who will benefit from invasive procedures. Coron Artery Dis 21: 164-167 (C) 2010 Wolters Kluwer Health vertical bar Lippincott Williams & Wilkins.

Sensitivity and uncertainty analyses for burden of disease and risk factor estimates

Epidemiological studies report confidence or uncertainty intervals around their estimates. Estimates of the burden of diseases and risk factors are subject to a broader range of uncertainty because of the combination of multiple data sources and value choices. Sensitivity analysis can be used to examine the effects of social values that have been incorporated into the design of the disability–adjusted life year (DALY). Age weight, where a year of healthy life lived at one age is valued differently from at another age, is the most controversial value built into the DALY. The discount rate, which addresses the difference in value of current versus future health benefits, also has been criticized. The distribution of the global disease burden and rankings of various conditions are largely insensitive to alternate assumptions about the discount rate and age weighting. The major effects of discounting and age weighting are to enhance the importance of neuropsychiatric conditions and sexually transmitted infections. The Global Burden of Disease study also has been criticized for estimating mortality and disease burden for regions using incomplete and uncertain data. Including uncertain results, with uncertainty quantified to the extent possible, is preferable, however, to leaving blank cells in tables intended to provide policy makers with an overall assessment of burden of disease. No estimate is generally interpreted as no problem. Greater investment in getting the descriptive epidemiology of diseases and injuries correct in poor countries will do vastly more to reduce uncertainty in disease burden assessments than a philosophical debate about the appropriateness of social value