Risk-based Decision Research Articles

Using Debiasing Strategies to Manage Cognitive Biases in Construction Risk Management: Recommendations for Practice and Future Research

Construction risk management processes necessarily rely on subjective assessments and heuristic rules. Historic data are desirable, but rarely are available due to the unique nature of individual construction project and the required risk assessments. A comprehensive literature review highlighted the lack of attention by researchers and industry professionals to understanding the influence of cognitive biases on construction risk management processes. The authors reviewed a representative list of 18 relevant cognitive biases from the literature that could influence risk-based perceptions, assessments, and decisions among industry practitioners. This paper discussed the application of empirically validated debiasing strategies and experimental controls for professional and academic settings. The authors also discussed the limitations associated with debiasing strategies to promote a deeper understanding of results and accurate reporting of research validity for future researchers. This work is at the nexus of risk management and behavioral psychology. It provides detailed discussion and impetus for future research to improve the rigor of the risk management process.

Calibration and quantifying uncertainty of daily water quality forecasts for large lakes with a Bayesian joint probability modelling approach

Correcting the systematic bias and quantifying uncertainty associated with the operational water quality forecasts are imperative works for risk-based environmental decision making. This work proposes a post-processing method for addressing both bias correction and total uncertainty quantification for daily forecasts of water quality parameters derived from dynamical lake models. The post-processing is implemented based on a Bayesian Joint Probability (BJP) modeling approach. The BJP model uses a log-sinh transformation to normalize the raw forecasts and corresponding observations, and uses a bivariate Gaussian distribution to characterize the dependence relationship. The posterior distribution of the transformation parameters is inferenced through Metropolis Monte Carlo Markov chain sampling; it generates unbiased probabilistic forecasts that account for uncertainties from all sources. The BJP is used to post-processing raw daily forecasts of dissolved oxygen (DO), ammonium nitrogen (NH), total phosphorus (TP) and total nitrogen (TN) concentrations of Lake Chaohu, the fifth largest lake in China with lead times from 0 to 5 days. Results suggest that an average 93.1% forecast bias has been removed by BJP. The root mean square error in probability skill scores range from 5.8% for NH to 68.2% for TP, and the non-parametric bootstrapping test suggests that 67.7% forecasts are significantly improved averaged across all sampling sites, water quality parameters and lead times. The probabilities of the calibrated forecasts are reasonably consistent with the observed relative frequencies, and have appropriate spread and thus correctly quantify forecast uncertainty. The BJP post-processing method used in this study can be a useful operational tool that help to better realize the potential of water quality forecasts derived from dynamical models.

Integrated Multi-stakeholder Systems Thinking Strategy: Decision-making with Biopharmaceutics Risk Assessment Roadmap (BioRAM) to Optimize Clinical Performance of Drug Products.

Decision-making in drug development benefits from an integrated systems approach, where the stakeholders identify and address the critical questions for the system through carefully designed and performed studies. Biopharmaceutics Risk Assessment Roadmap (BioRAM) is such a systems approach for application of systems thinking to patient focused and timely decision-making, suitable for all stages of drug discovery and development. We described the BioRAM therapy-driven drug delivery framework, strategic roadmap, and integrated risk assessment instrument (BioRAM Scoring Grid) in previous publications (J Pharm Sci 103:3377-97, 2014; J Pharm Sci 105:3243-55, 2016). Integration of systems thinking with pharmaceutical development, manufacturing, and clinical sciences and health care is unique to BioRAM where the developed strategy identifies the system and enables risk characterization and balancing for the entire system. Successful decision-making process in BioRAM starts with the Blueprint (BP) meetings. Through shared understanding of the system, the program strategy is developed and captured in the program BP. Here, we provide three semi-hypothetical examples for illustrating risk-based decision-making in high and moderate risk settings. In the high-risk setting, which is a rare disease area, two completely alternate development approaches are considered (gene therapy and small molecule). The two moderate-risk examples represent varied knowledge levels and drivers for the programs. In one moderate-risk example, knowledge leveraging opportunities are drawn from the manufacturing knowledge and clinical performance of a similar drug substance. In the other example, knowledge on acute tolerance patterns for a similar mechanistic pathway is utilized for identifying markers to inform the drug release profile from the dosage form with the necessary "flexibility" for dosing. All examples illustrate implementation of the BioRAM strategy for leveraging knowledge and decision-making to optimize the clinical performance of drug products for patient benefit.

FLAME: A Parametric Fire Risk Assessment Method Supporting Performance Based Approaches

A fire risk assessment has always been a challenging task. Performance-based approaches to fire engineering have shown that risk-based decisions and fire scenarios are fundamental elements that must be considered in fire safety strategies. A correct assessment of the fire risk allows all the involved stakeholders to identify a specific strategy from among a variety of possibilities. A risk assessment is the best tool to identify comparable fire protection strategies and to measure the reduction in fire risk that can be obtained with each specific prevention and protection measure, i.e., by means of different fire safety strategies. The present paper illustrates a method that takes into account several well-known methods, even some that were developed as far back as in the early seventies. The method is named “FLAME” (Fire Risk Assessment Method for Enterprises). FLAME considers fundamental fire safety aspects instead of making use of sophisticated and time-consuming methods like CFD. FLAME uses the “Fire Safety Concept Tree”, which is explained in detail in the NFPA 550 Standard, as a reference scheme. The method allows the risk to the occupants to be evaluated separately from the risk to the building. Over the years, we have tested the method considering different kinds of buildings and occupancies. We here report the results of an application of the FLAME method to hospitals and health-care facilities. Overall, about 300 compartments (overall size of about 60,000 m2) were analysed, including two hospitals of about 200,000 m2 each. The results of the risk estimation with the FLAME code have been found to be coherent with Italian fire code prescriptions. About 44% of the compartments were defined as being at a Medium risk and 39% as being at a high risk (according to the Italian Fire Code). More than 60% of the hospital compartments were defined as being at a High risk. A good agreement was obtained between the RSET results with those of the method proposed in FLAME when using the current performance-based regulation criteria. The RSET estimation in FLAME considers the occupants’ behaviour and the actual characteristics of the occupants in clinics or hospitals, who often have difficulties due to reduced mobility or an incapacity to understand emergency instructions.

Risk-based decision making in rats: Modulation by sex and amphetamine

Decision-making is a complex process essential to daily adaptation in many species. Risk is an inherent aspect of decision-making and it is influenced by gonadal hormones. Testosterone and 17β-estradiol may modulate decision making and impact the mesocorticolimbic dopamine pathway. Here, we explored sex differences, the effect of gonadal hormones and the dopamine agonist amphetamine on risk-based decision making. Intact or gonadectomised (GDX) male and female rats underwent to a probabilistic discounting task. High and low doses of testosterone propionate (1.0 or 0.2 mg) and 17β-estradiol benzoate (0.3 μg) were administered to assess acute effects on risk-based decision making. After 3-days of washout period, intact and GDX rats received high or low (0.5 or 0.125 mg/kg) doses of amphetamine and re-tested in the probabilistic discounting task. Under baseline conditions, males made more risky choices during probability discounting compared to female rats, particularly in the lower probability blocks, but GDX did not influence risky choice. The high, but not the low dose, of testosterone modestly reduced risky decision making in GDX male rats. Conversely, 17β-estradiol had no significant effect on risky choice regardless of GDX status in either sex. Lastly, a higher dose of amphetamine increased risky decision making in both intact males and females, but had no effect in GDX rats. These findings demonstrated sex differences in risk-based decision making, with males showing a stronger bias toward larger, uncertain rewards. GDX status influenced the effects of amphetamine, suggesting different dopaminergic regulation in risk-based choices among males and females.

Serotypes, antibiotic resistance, and molecular characterization of non-typhoidal salmonella isolated from diarrheic patients in Guangxi Zhuang Autonomous Region, China, 2014–2017

The serotype, antimicrobial resistance, and molecular typing of 843 Salmonella isolates recovered from diarrheic patients in Guangxi Zhuang Autonomous Region (Guangxi), China from 2014 to 2017 were investigated. Among these 843 isolates, a total of 67 Salmonella serotypes and four un-typable isolates were detected by the slide agglutination method. The most prevalence serotype was Salmonella 1,4,[5],12:i:- (27.4%, 231/843), followed by S. Enteritidis (20.8%) and S. Typhimurium (16.1%). Many of these isolates (86.2%, 727/843) were resistant to more than one antibiotic. The rate of resistance to early generation antimicrobial agents was high (AMP [73.8%], TET [65.5%], and NAL [43.2%]). Moreover, the rate of resistance to clinically important antimicrobial agents was of great concern (CIP [21.6%], CTX [12.9%], and AZM [5.7%]). Importantly, 34 (4.0%) isolates of nine serovars were resistant to both CIP and CTX, which included 14 (1.7%) that were also resistant to AZM. In addition, 74.9% (631/843) of nontyphoidal Salmonella isolates demonstrated decreased susceptibility to ciprofloxacin with S. Enteritidis as the dominant serovar. Overall, 393 (46.6%) isolates were identified as multidrug resistance (MDR) with resistance to three or more classes of antimicrobials, of which MDR S. 1,4,[5],12:i:- accounted for the highest proportion (31.6%, 124/393). Genotypic analyses by pulsed-field gel electrophoresis of 447 isolates containing the three most common serotypes revealed a high diversity, suggesting that the majority human salmonellosis cases are attributed to sporadic events. These results highlighted the diversity of Salmonella serotypes and the high prevalence of emerging MDR Salmonella. 1,4,[5],12:i:- isolates in Guangxi. Therefore, surveillance of these emerging MDR isolates should be enhanced to monitor antimicrobial resistant Salmonella in the food chain and to inform risk-based decisions to protect public health.

A holistic approach to risk-based decision on inspection and design of fatigue-sensitive structures

Design and operation of large welded structural systems (e.g. ship and offshore structures) are challenging due to numerous fatigue-sensitive details, limited available budgets, uncertainties in fatigue damages, inspection & maintenance activities, etc. Traditionally, fatigue design and maintenance planning have been almost disconnected, which restricts coherent decision-making and optimum safety management. Structural design optimization, without quantitatively incorporating the effects of operational maintenance, can hardly result in a structural plan that is optimum in terms of life cycle costs. Also, if the design of a structure is not optimum, maintenance optimization alone cannot really yield a optimum maintenance plan. As operational inspections and maintenance are essential, there are merits to utilize their effects on structural design and meanwhile optimize them at the initial design stage when impacts of decisions are greater. This paper proposes a risk-based approach to holistic decision-making enveloping decisions and uncertainties affecting design, inspection and maintenance of fatigue-sensitive components. Decisions variables in structural scantling and operational maintenance are obtained holistically at the structural design stage by risk-based optimization, based on quantitative assessment of the effectiveness of both structural scantling and maintenance interventions. Optimum fatigue reliability level is also obtained, informed by the effects of uncertainties and failure consequences. The method captures combined benefits of structural scantling and operational maintenance to fatigue reliability and risk mitigation and achieves optimum resource utilization and life cycle cost reduction. Advantages of the proposed method have been demonstrated via a numerical example, in comparison to alternative methods.

Nutrition and physical activity recommendations from the United States and European cardiovascular guidelines: a comparative review.

A healthy lifestyle throughout one's lifespan is the core foundation for both primary and secondary prevention of cardiovascular disease (CVD). Risk-based decisions for pharmacological therapy is added on-top of lifestyle management. Thus, understanding lifestyle-based recommendations is central to CVD prevention. In 2018 and 2019, the American Heart Association (AHA) and American College of Cardiology (ACC) published new guidelines for lipid management and primary prevention of cardiovascular disease (CVD), respectively. The European Society of Cardiology (ESC) and European Atherosclerosis Society (EAS) published new guidelines on lipids and diabetes management in 2019. These guidelines provide recommendations on diet and lifestyle for reducing cardiovascular risk. Both encourage heart-healthy diets consistent with Mediterranean, DASH, or healthy vegetarian patterns. Both provide guidance for recommended physical activity levels but acknowledge any physical activity, even less than recommended, is better than inactivity. Although both ACC/AHA and ESC/EAS guidelines have similar approaches to achieve the same goal of CVD prevention, there were some differences between them. In this review, we discussed similarities and differences between the American and European guidelines to familiarize clinicians with both sets of lifestyle recommendations in an effort to provide best practices in individualized patient-care for CVD prevention.

Performance-based post-earthquake decision making for instrumented buildings

This paper develops a decision making framework for post-earthquake assessment of instrumented buildings in a manner consistent with performance-based design criteria. This framework is achieved by simultaneously combining and advancing existing knowledge from seismic structural health monitoring and performance-based earthquake engineering paradigms. The framework consists of (1) measurement, (2) uncertainty modeling, (3) dynamic response reconstruction, (4) damage estimation, and (5) performance-based assessment and decision making. In particular, the main objective is to reconstruct inter-story drifts with a probabilistic measure of exceeding performance-based acceptance limits and determine the post-earthquake re-occupancy classification of the instrumented building of interest. Since the proposed framework is probabilistic, the outcome can be used to obtain the probability of losses based on the defined decision variables and be integrated into a risk-based decision making process by city officials, building owners, and emergency managers. The framework is illustrated using data from the Van Nuys hotel testbed, a seven-story reinforced concrete building instrumented by the California Strong Motion Instrumentation Program (CSMIP Station 24386).

Meat Safety in Northern Tanzania: Inspectors' and Slaughter Workers' Risk Perceptions and Management.

Through a social scientific lens, this paper considers the risk perceptions and “risk-based decision-making” of two key groups in a northern Tanzanian context: (1) frontline government meat inspectors and health officers charged with ensuring that red meat sold commercially is safe for people to consume, and (2) the workers who slaughter and process cattle and red meat prior to its sale in rural butcheries. In contrast to techno-scientific understandings of disease risk and “rational” approaches to its management, this paper foregrounds the role of social, economic and institutional context in shaping the perceptions and practices around meat safety of these actors whose daily, close proximity to meat means they play a significant role in mitigating potential meat-borne disease. We show how limited resources, and a combination of scientific and local knowledge and norms result in “situated expertise” and particular forms of risk perception and practice which both enhance and compromise meat safety in different ways. Actors' shared concerns with what is visible, ensures that visibly unsafe or abnormal meat is excluded from sale, and that infrastructure and meat is kept “clean” and free of certain visible contaminants such as soil or, on occasion, feces. While such contaminants serve as a good proxy for pathogen presence, meat inspectors and especially slaughter workers were much less aware of or concerned with invisible pathogens that may compromise meat safety. The role of process and meat handling did not figure very strongly in their concerns. Microorganisms such as Salmonella and Campylobacter, which can easily be transferred onto meat and persist in slaughter and meat sale environments, went unacknowledged. Although health officers expressed more concern with hygiene and meat handling, their influence over slaughter process and butchery operations was unclear. Ultimately, recognizing the perceptions and practices of frontline actors who engage with meat, and the ways in which social, material and institutional realities shape these, is important for understanding how decisions about risk and meat safety are made in the complexity and context of everyday life, and thus for finding effective ways to support them to further enhance their work.

RETRACTED: Fault-Event Trees Based Probabilistic Safety Analysis of a Boiling Water Nuclear Reactor’s Core Meltdown and Minor Damage Frequencies

A systematic probabilistic safety assessment for a boiling water nuclear reactor core is performed using fault trees and event trees analysis models. Based on a survey of the BWR’s safety systems against potential hazards, eight independent failure modes (initiating events) triggered scenarios are modelled and evaluated in the assembled fault-event trees, obtaining the two key outcome probabilities of interest, i.e., complete core meltdown (CCMD) frequency and minor core damage (MCD) frequency. The analysis results indicate that the complete loss of heat sink accounts for the initiating accident most vulnerable to CCMD (with a frequency of 1.8 × 10 − 5 per year), while the large break in the reactor pressure vessel is the least susceptible one (with a frequency of 2.9 × 10 − 12 per year). The quantitative risk assessment and independent review conducted in this case study contributed a reference reliability model for defense-in-depth core optimizations with reduced costs, informing risk-based policy decision making, licensing, and public understanding in nuclear safety systems.

Efficient or Fair? Operationalizing Ethical Principles in Flood Risk Management: A Case Study on the Dutch-German Rhine.

Flood risk management decisions in many countries are based on decision‐support frameworks which rely on cost‐benefit analyses. Such frameworks are seldom informative about the geographical distribution of risk, raising questions on the fairness of the proposed policies. In the present work, we propose a new decision criterion that accounts for the distribution of risk reduction and apply it to support flood risk management decisions on a transboundary stretch of the Rhine River. Three types of interventions are considered: embankment heightening, making Room for the River, and changing the discharge distribution of the river branches. The analysis involves solving a flood risk management problem according to four alternative formulations, based on different ethical principles. Formulations based on cost optimization lead to very poor performances in some areas for the sake of reducing the overall aggregated costs. Formulations that also include equity criteria have different results depending on how these are defined. When risk reduction is distributed equally, very poor economic performance is achieved. When risk is distributed equally, results are in line with formulations based on cost optimization, while a fairer risk distribution is achieved. Risk reduction measures also differ, with the cost optimization approach strongly favoring the leverage of changing the discharge distribution and the alternative formulations spending more on embankment heightening and Room for the River, to rebalance inequalities in risk levels. The proposed method advances risk‐based decision‐making by allowing to consider risk distribution aspects and their impacts on the choice of risk reduction measures.

Assembling and Customizing Multiple Fire Weather Forecasts for Burn Probability and Other Fire Management Applications in Ontario, Canada

Weather forecasts are needed in fire management to support risk-based decision-making that considers both the probability of an outcome and its potential impact. These decisions are complicated by the large amount of uncertainty surrounding many aspects of the decision, such as weather forecasts. Wildland fires in Ontario, Canada can burn and actively spread for days, weeks, or even months, or be naturally limited or extinguished by rain. Conventional fire weather forecasts have typically been a single scenario for a period of one to five days. These forecasts have two limitations: they are not long enough to inform some fire management decisions, and they do not convey any uncertainty to inform risk-based decision-making. We present an overview of a method for the assembly and customization of forecasts that (1) combines short-, medium-, and long-term forecasts of different types, (2) calculates Fire Weather Indices and Fire Behaviour Predictions, including modelling seasonal weather station start-up and shutdown, (3) resolves differing spatial resolutions, and (4) communicates forecasts. It is used for burn probability modelling and other fire management applications.

"Hot Zones" for Otolaryngologists: Assessing the geographic distribution of aerosol-generating procedures amidst the COVID-19 pandemic.

ObjectiveGiven high COVID-19 viral load and aerosolization in the head and neck, otolaryngologists are subject to uniquely elevated viral exposure in most of their inpatient and outpatient procedures and interventions. While elective activity has halted across the board nationally, the slow plateau of COVID-19 case rates prompts the question of timing of resumption of clinical activity. We sought to prospectively predict geographical “hot zones” for otolaryngological exposure to COVID-19 based on procedural volumes data from 2013 to 2017.MethodsOtolaryngologic CPT codes were stratified based on risk-level, according to recently published specialty-specific guidelines. Using the Medicare POSPUF database, aerosol-generating procedures (AGPs) were mapped based on hospital referral regions, against up-to-date COVID-19 case distribution data, as of April 24, 2020.ResultsThe most common AGPs were diagnostic flexible laryngoscopy, diagnostic nasal endoscopy, and flexible laryngoscopy with stroboscopy. The regions with the most AGPs per otolaryngologist were Iowa City, IA, Detroit, MI, and Burlington, VT, while the states with the most COVID-19 cases as of April 24th are New York, New Jersey, and Massachusetts.ConclusionsOur study provides a model for predicting possible “hot zones” for otolaryngologic exposure based on both COVID-19 case density and AGP-density. As the focus shifts to resuming elective procedures, these potential “hot zones” need to be evaluated for appropriate risk-based decision-making, such as “reopening strategies” and allocation of resources.

Accounting for Unexpected Risk Events in Drinking Water Systems

Unexpected risk events in drinking water systems, such as heavy rain or manure spill accidents, can cause waterborne outbreaks of gastrointestinal disease. Using a scenario-based approach, these unexpected risk events were included in a risk-based decision model aimed at evaluating risk reduction alternatives. The decision model combined quantitative microbial risk assessment and cost–benefit analysis and investigated four risk reduction alternatives. Two drinking water systems were compared using the same set of risk reduction alternatives to illustrate the effect of unexpected risk events. The first drinking water system had a high pathogen base load and a high pathogen log10 reduction in the treatment plant, whereas the second drinking water system had a low pathogen base load and a low pathogen Log10 reduction in the treatment plant. Four risk reduction alternatives were evaluated on their social profitability: (A1) installation of pumps and back-up power supply, to remove combined sewer overflows; (A2) installation of UV treatment in the drinking water treatment plant; (A3) connection of 25% of the OWTSs in the catchment area to the WWTP; and (A4) a combination of A1–A3. Including the unexpected risk events changed the probability of a positive net present value for the analysed alternatives in the decision model and the alternative that is likely to have the highest net present value. The magnitude of the effect of unexpected risk events is dependent on the local preconditions in the drinking water system. For the first drinking water system, the unexpected risk events increase risk to a lesser extent compared to the second drinking water system. The main conclusion was that it is important to include unexpected risk events in decision models for evaluating microbial risk reduction, especially in a drinking water system with a low base load and a low pathogen log10 reduction in the drinking water treatment plant.

A nonparametric statistical framework using a kernel density estimator to approximate flood marginal distributions – a case study for the Kelantan River Basin in Malaysia

Abstract Floods are becoming the most challenging hydrologic issue in the Kelantan River basin in Malaysia. All three flood characteristics, i.e. peak flow, flood volume and flood duration, are important when formulating actions and measures to manage flood risk. Therefore, estimating the multivariate designs and their associated return periods is an essential element of making informed risk-based decisions in this river basin. In this paper, the efficacy of a kernel density estimator is tested by assessing the adequacy of kernel functions for capturing flood marginal density of 50 years (from 1961 to 2016) of daily streamflow data collected at Gulliemard Bridge gauge station in the Kelantan River basin. Tests for stationarity or the existence of serial correlation within the flood series is often a pre-requisite before introducing the random samples into a univariate or a multivariate framework. It was found that homogeneity existed within the flood vector series. It was concluded therefore that time series of the flood vectors do not exhibit any significant trend. Based on analytically based fitness measures, it was concluded that it is likely that Triweight kernel function is the best-fitted distribution for defining the marginal distribution of peak flows, flood volumes and flood durations in the Kelantan River basin.

A Comparison of Fire Weather Indices with MODIS Fire Days for the Natural Regions of Alaska

Research Highlights: Flammability of wildland fuels is a key factor influencing risk-based decisions related to preparedness, response, and safety in Alaska. However, without effective measures of current and expected flammability, the expected likelihood of active and problematic wildfires in the future is difficult to assess and prepare for. This study evaluates the effectiveness of diverse indices to capture high-risk fires. Indicators of drought and atmospheric drivers are assessed along with the operational Canadian Forest Fire Danger Rating System (CFFDRS). Background and Objectives: In this study, 13 different indicators of atmospheric conditions, fuel moisture, and flammability are compared to determine how effective each is at identifying thresholds and trends for significant wildfire activity. Materials and Methods: Flammability indices are compared with remote sensing characterizations that identify where and when fire activity has occurred. Results: Among these flammability indicators, conventional tools calibrated to wildfire thresholds (Duff Moisture Code (DMC) and Buildup Index (BUI)), as well as measures of atmospheric forcing (Vapor Pressure Deficit (VPD)), performed best at representing the conditions favoring initiation and size of significant wildfire events. Conventional assessments of seasonal severity and overall landscape flammability using DMC and BUI can be continued with confidence. Fire models that incorporate BUI in overall fire potential and fire behavior assessments are likely to produce effective results throughout boreal landscapes in Alaska. One novel result is the effectiveness of VPD throughout the state, making it a potential alternative to FFMC among the short-lag/1-day indices. Conclusions: This study demonstrates the societal value of research that joins new academic research results with operational needs. Developing the framework to do this more effectively will bring science to action with a shorter lag time, which is critical as we face growing challenges from a changing climate.

Would treatment decisions about secondary prevention of CVD based on estimated lifetime benefit rather than 10-year risk reduction be cost-effective?

ObjectiveTo test the hypothesis that treatment decisions (treatment with a PCSK9-mAb versus no treatment) are both more effective and more cost-effective when based on estimated lifetime benefit than when based on estimated risk reduction over 10 years.MethodsA microsimulation model was constructed for 10,000 patients with stable cardiovascular disease (CVD). Costs and quality-adjusted life years (QALYs) due to recurrent cardiovascular events and (non)vascular death were estimated for lifetime benefit-based compared to 10-year risk-based treatment, with PCSK9 inhibition as an illustration example. Lifetime benefit in months gained and 10-year absolute risk reduction were estimated using the SMART-REACH model, including an individualized treatment effect of PCSK9 inhibitors based on baseline low-density lipoprotein cholesterol. For the different numbers of patients treated (i.e. the 5%, 10%, and 20% of patients with the highest estimated benefit of both strategies), cost-effectiveness was assessed using the incremental cost-effectiveness ratio (ICER), indicating additional costs per QALY gain.ResultsLifetime benefit-based treatment of 5%, 10%, and 20% of patients with the highest estimated benefit resulted in an ICER of €36,440/QALY, €39,650/QALY, or €41,426/QALY. Ten-year risk-based treatment decisions of 5%, 10%, and 20% of patients with the highest estimated risk reduction resulted in an ICER of €48,187/QALY, €53,368/QALY, or €52,390/QALY.ConclusionTreatment decisions (treatment with a PCSK9-mAb versus no treatment) are both more effective and more cost-effective when based on estimated lifetime benefit than when based on estimated risk reduction over 10 years

Risk-based decision-making on corrosion delay for ship hull tankers

Corrosion addition, as defined by the International Association of Classification Societies (IACS), is a proactive design measure against corrosion-induced structural deterioration. In conjunction with regular dry-docking maintenance (e.g., coating and steel renewal), corrosion addition is aimed to sustain the intended functionality of a corroding ship toward the end of its service life. It is expected that corrosion addition can improve hull strength and save the lifetime maintenance cost. However, the benefit of upfront steel investment in corrosion addition on the ship’s life-cycle cost, including construction, dry-docking maintenance, and failure consequence, remains unclear. Obtaining such knowledge is very helpful in ship design and lifetime dry-docking planning. This paper presents a risk-based approach to study the most economically optimal corrosion addition. The method is illustrated on a very large crude carrier (VLCC) and the benefit analysis takes into account different magnitudes of the construction, dry-docking, steel renewal, and failure costs. The results show that corrosion addition by IACS may not be economically optimal; the reduction in the life-cycle cost through corrosion addition and the optimal corrosion addition achieving the maximum benefit varies with the item costs specified.

Striking a balance between science and politics: understanding the risk-based policy-making process during the outbreak of COVID-19 epidemic in China

The outbreak of the COVID-19 epidemic in China is, essentially, a public health emergency. Therefore, it becomes a critical issue to make policies by using scientific knowledge in a highly uncertain and unpredictable context. The key issue of risk-based decision-making (RBDM) is how to strike a balance between science and politics. After reviewing existing literature and practice, three main approaches to risk-based decision-making (RBDM) can be summarized: politics-based, science-led, and the integration and negotiation of science and politics. On the basis of public reports from current mass media, this article focuses on the time period from the releasing of the first COVID-19 case in Wuhan to the lockdown policy made by Wuhan municipal government, and we divide important stakeholders in early stage into two groups：scientist group and politician group. It finds that the RBDM process of Wuhan municipal government against COVID-19 demonstrated that politics intertwined tightly with science. Its RBDM process could be categorized into three phases: politics-based, science-involved, and science-led. We conclude six main characteristics of RBDM mechanisms in contemporary China. Finally, we argue that Chinese governments should establish institutionalized mechanisms for the negotiation and cooperation of science and politics in its RBDM process like COVID-19 epidemic. Five policy recommendations have been discussed to improve its RBDM quality in China’s context.