Effectiveness Of Risk Reduction Measures Research Articles

Occupational Health and Safety Statistics as an Indicator of Worker Physical Health in South African Industry.

Operations in general industry, including manufacturing, expose employees to a myriad of occupational health hazards. To prevent exposure, occupational health and safety regulations were enacted, with both employers and workers instituting various risk reduction measures. The analysis of available occupational disease and injury statistics (indicators of worker physical health) can be used to infer the effectiveness of risk reduction measures and regulations in preventing exposure. Thus, using the READ approach, analyses of occupational disease and injury statistics from South African industry, derived from annual reports of the Compensation Fund, were conducted. The publicly available database of occupational disease and injury statistics from the South African general industry is unstructured, and the data are inconsistently reported. This data scarcity, symptomatic of an absence of a functional occupational disease surveillance system, complicates judgement making regarding the effectiveness of implemented risk reduction measures, enacted occupational health and safety regulations and the status of worker physical health from exposure to workplace hazards. The statistics, where available, indicate that workers continue to be exposed to occupational health impacts within general industry, notwithstanding risk reduction measures and enacted regulations. In particular, worker physical health continues to be impacted by occupational injuries and noise-induced hearing loss. This is suggestive of shortcomings and inefficiencies in industry-implemented preventive measures and the regulatory state. A robust national occupational disease surveillance system is a regulatory tool that should detect and direct policy responses to identified occupational health hazards.

Identifying local oil spill risk factors: An application of Hazard Identification within the International Maritime Organization Formal Safety Assessment framework in Washington State

Abstract Number 677002 Oil spills from commercial vessels are low probability, high consequence events that threaten economic, ecological, cultural, and natural resources. Washington State Department of Ecology Spill's Program (Ecology) has a robust risk assessment program that focuses on identifying and reducing oil spill risks to Washington waters. In 2017-2018, Ecology developed and implemented a novel application of the International Maritime Organization (IMO) Formal Safety Assessment process to lead a collaborative Hazard Identification for oil spill risk in Grays Harbor, Washington. This use of the IMO Formal Safety Assessment Process to assess oil spill risk was a first for Washington State and appears to be unique among US state governments. Working with area tribes, government agencies, and stakeholders, Ecology modified the IMO Formal Safety Assessment process to focus on local factors that could contribute to oil spill risks. Ecology facilitated structured brainstorming discussions during two workshops to complete Hazard Identification. Focusing on local factors fostered collaborative discussion among workshop participants, and allowed the process to benefit from local expertise about the characteristics of waterway and operational practices. The workshops resulted in the identification of 43 local factors related to oil spill risks, 34 recommendations to reduce risks based on current vessel traffic, and 10 recommendations to consider if vessel traffic increases in the future. The recommendations from this assessment are directly informing operations in Grays Harbor; in 2019, the Grays Harbor Safety Committee voted to adopt the risk assessment final report as an addendum to their Harbor Safety Plan. Ecology is also working with area tribes, government agencies, and stakeholders to review and prioritize the risk assessment recommendations with a goal of developing implementation plans for selected measures. This application of the IMO Formal Safety Assessment process represents a repeatable, scalable, and defensible method for conducting oil spill risk assessments. Ecology plans to use this process in other state waterways, and invites other organizations to consider adopting these methods. The presentation will walk through how to apply this process for localized waterway risk assessments and discuss best practices for success. Additionally, Ecology will discuss new risk analysis initiatives directed by the Washington State Legislature, including development of a quantitative model for evaluating oil spill risk and the potential effect of risk reduction measures.

Connected and autonomous vehicles: A cyber-risk classification framework

The proliferation of technologies embedded in connected and autonomous vehicles (CAVs) increases the potential of cyber-attacks. The communication systems between vehicles and infrastructure present remote attack access for malicious hackers to exploit system vulnerabilities. Increased connectivity combined with autonomous driving functions pose a considerable threat to the vast socioeconomic benefits promised by CAVs. However, the absence of historical information on cyber-attacks mean that traditional risk assessment methods are rendered ineffective. This paper proposes a proactive CAV cyber-risk classification model which overcomes this issue by incorporating known software vulnerabilities contained within the US National Vulnerability Database into model building and testing phases. This method uses a Bayesian Network (BN) model, premised on the variables and causal relationships derived from the Common Vulnerability Scoring Scheme (CVSS), to represent the probabilistic structure and parameterisation of CAV cyber-risk. The resulting BN model is validated with an out-of-sample test demonstrating nearly 100% prediction accuracy of the quantitative risk score and qualitative risk level. The model is then applied to the use-case of GPS systems of a CAV with and without cryptographic authentication. In the use case, we demonstrate how the model can be used to predict the effect of risk reduction measures.

Annual landslide risk and effectiveness of risk reduction measures in Shihmen watershed, Taiwan

Landslide risk analysis procedures in this study could evaluate annual landslide risk, and assess the effectiveness of measures. Risk analysis encompassing landslide hazard, vulnerability, and resilience capacity was used to evaluate annual landslide risk. First, landslide spatial, temporal, and area probabilities were joined to estimate annual probability of landslides with an area exceeding a certain threshold in each slope unit. Second, different elements were assigned corresponding values and vulnerabilities to calculate the expected property and life losses. Third, the resilience capacities of communities were calculated based on the scores obtained through community checklists and the weights of items, including “the participation experience of disaster prevention drill,” “real-time monitoring mechanism of community,” “autonomous monitoring of residents,” and “disaster prevention volunteer.” Finally, the annual landslide probabilities, expected losses, and resilience capacities were combined to evaluate annual landslide risk in Shihmen watershed. In addition, annual risks before and after the implementation of measures were compared to determine the benefits of measures, and subsequently benefit–cost analysis was performed. Communities with high benefit–cost ratios included Hualing, Yisheng, Siouluan, and Gaoyi. The watershed as a whole had a benefit–cost ratio far greater than 1, indicating the effectiveness of measures was greater than the investment cost. The results of factor sensitivity analysis revealed changes in vulnerabilities and mortality rates would increase the uncertainty of risk, and that raise in annual interest rates or reduction in life cycle of measures would decrease the benefit–cost ratio. However, these changes did not reverse the cost-effective inference.

A review of layer of protection analysis techniques for oil and gas industry

The paper indicates advantages (and disadvantages) of layer of protection analysis (LOPA) over other methods to support its paramount position among different process safety analysis (PSA) methods in use today. Its simplicity (using order-of-magnitude estimates for all elements that constitute an accident scenario), universality (easy adaptation to particular needs), directness to indicate the effect of risk reduction measures as well as to assess the total level of risk to be compared with the company risk tolerance criteria are strong arguments for wider application of LOPA. However, the method may have some limitations (disadvantages) in comparison to other methods and therefore different extended approaches of LOPA have been developed to overcome the problem. Those approaches include an inclusion of an expert system into accident scenario identification (ExSysLOPA), new approach to deal with uncertainty connected with input data (fuzzy LOPA) as well as for explosion at workplace risk assessment (ExLOPA). Some of these combined techniques will be presented here and they support and extend the applications of layer of protection analysis, especially for safety assurance assessment of risk-based determination that is used in oil and gas process industries.

Layer of protection analysis for reactive chemical risk assessment

Reactive chemical hazards have been a significant concern for the chemical process industries (CPI). Without sufficient control and mitigation of chemical reaction hazards, reactive incidents have led to severe consequences, such as release of flammable and toxic materials, fires and explosions, and threats to human lives, properties, and the environment. Consequence of reactive hazards can be well understood through calorimetric testing and computational techniques. However, risks of incidents caused by reactive chemicals have not been well addressed due partly to sparse failure frequency data. In this paper, the semi-quantitative layer of protection analysis (LOPA) approach is used to estimate reactive chemical risk, and the probabilities or frequencies of failure scenarios are addressed. Using LOPA, reactive risks can be evaluated with respect to predefined criteria, and the effectiveness of risk reduction measures can be assessed. The hydroxylamine (HA) production system is employed as a case study to demonstrate the application of LOPA to reactive chemical risk assessment.

Overconfident Physician Opinion on the Effectiveness of BRCA1 Risk Reduction Measures

We explored whether clinicians are overconfident in their judgments about the effectiveness of risk reduction measures in women with mutations in the BRCA1 gene. In this context, "overconfidence" is defined as the expression of too much certainty in subjective estimates, regardless of whether estimates are large or small. We asked physicians to estimate the percent decrease in the lifetime probability of breast and ovarian cancer in carriers who received various prophylactic interventions. Respondents were also asked to indicate their 90% plausibility interval. Subjects were breast cancer clinicians and principal investigators on NCI-sponsored Specialized Programs in Oncology Research and Education (SPOREs) in breast cancer at six US cancer centers. Clinicians varied widely in their estimates of effectiveness. Many had plausibility intervals that did not include the best estimate offered by other clinicians. It was not uncommon to find two clinicians with plausibility intervals that did not overlap. In addition, many clinicians expressed 90%-plausibility intervals that were so narrow that they did not capture findings from large robust studies of the effectiveness of prophylaxis. While, by definition, 10% of clinicians should have been surprised to learn that a scientific finding was outside their 90% plausibility interval, we found that 34-67% would have been surprised. This is because their plausibility intervals were too narrow. We found that clinicians are overconfident in their estimates of the effectiveness of BRCA1 risk-reduction measures.