Sensitivity Analysis to Evaluate the Impact of Uncertain Factors in a Scenario Tree Model for Classical Swine Fever Introduction

Introduction of classical swine fever virus (CSFV) is a continuing threat to the pig production sector in the European Union. A scenario tree model was developed to obtain more insight into the main risk factors determining the probability of CSFV introduction (P(CSFV)). As this model contains many uncertain input parameters, sensitivity analysis was used to indicate which of these parameters influence model results most. Group screening combined with the statistical techniques of design of experiments and meta-modeling was applied to detect the most important uncertain input parameters among a total of 257 parameters. The response variable chosen was the annual P(CSFV) into the Netherlands. Only 128 scenario calculations were needed to specify the final meta-model. A consecutive one-at-a-time sensitivity analysis was performed with the main effects of this meta-model to explore their impact on the ranking of risk factors contributing most to the annual P(CSFV). The results indicated that model outcome is most sensitive to the uncertain input parameters concerning the expected number of classical swine fever epidemics in Germany, Belgium, and the United Kingdom and the probability that CSFV survives in an empty livestock truck traveling over a distance of 0-900 km.     

A Quantitative Assessment of the Risk for Highly Pathogenic Avian Influenza Introduction into Spain via Legal Trade of Live Poultry

Highly pathogenic avian influenza (HPAI) is considered one of the most important diseases of poultry. During the last 9 years, HPAI epidemics have been reported in Asia, the Americas, Africa, and in 18 countries of the European Union (EU). For that reason, it is possible that the risk for HPAI virus (HPAIV) introduction into Spain may have recently increased. Because of the EU free‐trade policy and because legal trade of live poultry was considered an important route for HPAI spread in certain regions of the world, there are fears that Spain may become HPAIV‐infected as a consequence of the legal introduction of live poultry. However, no quantitative assessment of the risk for HPAIV introduction into Spain or into any other EU member state via the trade of poultry has been published in the peer‐reviewed literature. This article presents the results of the first quantitative assessment of the risk for HPAIV introduction into a free country via legal trade of live poultry, along with estimates of the geographical variation of the risk and of the relative contribution of exporting countries and susceptible poultry species to the risk. The annual mean risk for HPAI introduction into Spain was estimated to be as low as 1.36 × 10⁻³, suggesting that under prevailing conditions, introduction of HPAIV into Spain through the trade of live poultry is unlikely to occur. Moreover, these results support the hypothesis that legal trade of live poultry does not impose a significant risk for the spread of HPAI into EU member states.     

The BSE Risk of Processing Meat and Bone Meal in Nonruminant Feed: A Quantitative Assessment for the Netherlands

The total ban on use of meat and bone meal (MBM) in livestock feed has been very successful in reducing bovine spongiform encephalopathy (BSE) spread, but also implies a waste of high-quality proteins resulting in economic and ecological loss. Now that the BSE epidemic is fading out, a partial lifting of the MBM ban might be considered. The objective of this study was to assess the BSE risk for the Netherlands if MBM derived from animals fit for human consumption, i.e., category 3 MBM, would be used in nonruminant feed. A stochastic simulation model was constructed that calculates (1) the probability that infectivity of undetected BSE-infected cows ends up with calves and (2) the quantity of infectivity ( Q_inf ) consumed by calves in case of such an incident. Three pathways were considered via which infectivity can reach cattle: (1) cross-contamination in the feed mill, (2) cross-contamination on the primary farm, and (3) pasture contamination. Model calculations indicate that the overall probability that infectivity ends up with calves is 3.2%. In most such incidents the Q_inf is extremely small (median = 6.5 × 10⁻¹² ID₅₀; mean = 1.8 × 10⁻⁴ ID₅₀), corresponding to an average probability of 1.3 × 10⁻⁴ that an incident results in ≥1 new BSE infections. Cross-contamination in the feed mill is the most risky pathway. Combining model results with Dutch BSE prevalence estimates for the coming years, it can be concluded that the BSE risk of using category 3 MBM derived from Dutch cattle in nonruminant feed is very low.     

An Integrated Model of Infection Risk in a Health-Care Environment

Certain respiratory tract infections can be transmitted by hand-to-mucous-membrane contact, inhalation, and/or direct respiratory droplet spray. In a room occupied by a patient with such a transmissible infection, pathogens present on textile and nontextile surfaces, and pathogens present in the air, provide sources of exposure for an attending health-care worker (HCW); in addition, close contact with the patient when the latter coughs allows for droplet spray exposure. We present an integrated model of pertinent source-environment-receptor pathways, and represent physical elements in these pathways as "states" in a discrete-time Markov chain model. We estimate the rates of transfer at various steps in the pathways, and their relationship to the probability that a pathogen in one state has moved to another state by the end of a specified time interval. Given initial pathogen loads on textile and nontextile surfaces and in room air, we use the model to estimate the expected pathogen dose to a HCW's mucous membranes and respiratory tract. In turn, using a nonthreshold infectious dose model, we relate the expected dose to infection risk. The system is illustrated with a hypothetical but plausible scenario involving a viral pathogen emitted via coughing. We also use the model to show that a biocidal finish on textile surfaces has the potential to substantially reduce infection risk via the hand-to-mucous-membrane exposure pathway.     

A Framework for Understanding Uncertainty in Seismic Risk Assessment

A better understanding of the uncertainty that exists in models used for seismic risk assessment is critical to improving risk-based decisions pertaining to earthquake safety. Current models estimating the probability of collapse of a building do not consider comprehensively the nature and impact of uncertainty. This article presents a model framework to enhance seismic risk assessment and thus gives decisionmakers a fuller understanding of the nature and limitations of the estimates. This can help ensure that risks are not over- or underestimated and the value of acquiring accurate data is appreciated fully. The methodology presented provides a novel treatment of uncertainties in input variables, their propagation through the model, and their effect on the results. The study presents ranges of possible annual collapse probabilities for different case studies on buildings in different parts of the world, exposed to different levels of seismicity, and with different vulnerabilities. A global sensitivity analysis was conducted to determine the significance of uncertain variables. Two key outcomes are (1) that the uncertainty in ground-motion conversion equations has the largest effect on the uncertainty in the calculation of annual collapse probability; and (2) the vulnerability of a building appears to have an effect on the range of annual collapse probabilities produced, i.e., the level of uncertainty in the estimate of annual collapse probability, with less vulnerable buildings having a smaller uncertainty.     

A Causal Analysis of Large Vehicle Accidents Through Fault-Tree Analysis

Recent trends indicate that vehicle miles traveled for large trucks is increasing at a higher rate than for other vehicles. The resulting competition between large trucks and other vehicles for highway space can be expected to result in more multivehicle collisions involving large trucks. This paper presents the result of an investigation of the causes and the mechanism related to large vehicle accidents. A fault-tree analysis of large vehicle accidents identifies the individual roles played by driver, vehicle, and environmental factors, as well as their interactions in the accident mechanism. Using accident data for 1984-1986, the probabilities for different basic events in the fault tree were assessed. The most likely events leading to a large vehicle accident, as well as the most effective counter measures, were then identified. The result indicate that the most prevalent form of accidents due to driver-related failures is when a normal driver makes an error in judgment and is unsuccessful in his or her evasive action. For vehicle-related failures, the predominant type of failure is equipment failure, and for environmental-related failures, excessive demand on driver and vehicle performance created by the environmental or roadway factors.     

Establishing dominance between strategies with interval judgments of state probabilities

In decision-making under uncertainty, a decision-maker is required to specify, possibly with the help of decision analysts, point estimates of the probabilities of uncertain events. In this setting, it is often difficult to obtain very precise measurements of the decision-maker׳s probabilities on the states of nature particularly when little information is available to evaluate probabilities, available information is not specific enough, or we have to model the conflict case where several information sources are available.In this paper, imprecise probabilities are considered for representing the decision-maker׳s perception or past experience about the states of nature, to be specific, interval probabilities, which can be further categorized as (a) intervals of individual probabilities, (b) intervals of probability differences, and (c) intervals of ratio probabilities. We present a heuristic approach to modeling a wider range of types of probabilities as well as three types of interval probabilities. In particular, the intervals of ratio probabilities, which are widely used in the uncertain AHP context, are analyzed to find extreme points by the use of change of variables, not to mention the first two types of interval probabilities. Finally, we examine how these extreme points can be used to determine an ordering or partial ordering of the expected values of strategies.     

Direct Estimation of the Cost Effectiveness of Tornado Shelters

This article estimates the cost effectiveness of tornado shelters using the annual probability of a tornado and new data on fatalities per building struck by a tornado. This approach differs from recent estimates of the cost effectiveness of tornado shelters in Reference 1 that use historical casualties. Historical casualties combine both tornado risk and resident action. If residents of tornado-prone states take greater precautions, observed fatalities might not be much higher than in states with lower risk. Estimation using the tornado probability avoids this potential bias. Despite the very different method used, the estimates are 68 million US dollars in permanent homes and 6.0 million US dollars in mobile homes in Oklahoma using a 3% real discount rate, within about 10% of estimates based on historical fatalities. The findings suggest that shelters provide cost-effective protection for mobile homes in the most tornado-prone states but not for permanent homes.     

Foot-and-Mouth Disease Entrance Assessment Model Through Air Passenger Violations

This article aims to construct a risk model for the prediction of foot-and-mouth disease (FMD) entrance caused by passengers who illegally carry meat products of cloven-hoofed animals through international airports into a country. The risk that meat contaminated with the FMD virus is formulated as the probabilities of FMD factor events (the prevalence of FMD), the commodity factor event (the transportation, storage, and distribution (TSD) factor event), and the passenger event. Data used for analysis were records of illegal meat product carriers from areas A and B intercepted at an international airport in Taiwan. A risk model was proposed to simulate the probability distributions in disease prevalence, probability of FMD virus existing in the meat products after meat processing, and estimation of survival of virus and time period for TSD. The probability of the passenger event was hypothesized with the odds of intercepted passengers and estimated via logistic regression. The results showed that the odds of passengers being intercepted by beagles were higher than those intercepted by Customs. By conducting Monte Carlo simulations, the probability of FMD virus risk caused by FMD factors from area A was 149 times lower than that from area B. The probability of FMD virus risk caused by the passenger event from area A was four times lower than the corresponding probability from area B. The model provides a contribution to FMD prevention and can be a reference for developing models of other diseases.     

Exploring the Potential for Multivariate Fragility Representations to Alter Flood Risk Estimates

In flood risk analysis, limitations in the multivariate statistical models adopted to model the hydraulic load have restricted the probability of a defense suffering structural failure to be expressed conditionally on a single hydraulic loading variable. This is an issue at the coastal level where multiple loadings act on defenses with the exact combination of loadings dictating their failure probabilities. Recently, a methodology containing a multivariate statistical model with the flexibility to robustly capture the dependence structure between the individual loadings was used to derive extreme nearshore loading conditions. Its adoption will permit the incorporation of more precise representations of a structure's vulnerability in future analyses. In this article, a fragility representation of a shingle beach, where the failure probability is expressed over a three‐dimensional loading parameter space—water level, wave height, and period—is derived at two localities. Within the approach, a Gaussian copula is used to capture any dependencies between the simplified geometric parameters of a beach's shape. Beach profiles are simulated from the copula and the failure probability, given the hydraulic load, determined by the reformulated Bradbury barrier inertia parameter model. At one site, substantial differences in the annual failure probability distribution are observed between the new and existing approaches. At the other, the beach only becomes vulnerable after a significant reduction of the crest height with its mean annual failure probability close to that presently predicted. It is concluded that further application of multivariate approaches is likely to yield more effective flood risk management.     

Methylmercury Risks and EPA + DHA Benefits Associated with Seafood Consumption in Europe

The intake of methyl‐Hg and EPA + DHA through consumption of seafood in Europe as well as the associated probability of exceeding the provisional tolerable weekly intake (PTWI) and the recommended daily intake (RDI), respectively, were estimated by combining methyl‐Hg and EPA + DHA contents in the five most consumed seafood species with hypothesized consumption distributions for eight European countries, chosen on the basis of size and representative significance. Two estimators were used: plug‐in (PI) and tail estimation (TE). The latter was based on the application of the extreme value theory to the intakes distribution curves. Whereas contents data were collected from own database and published scientific papers, consumption data were obtained from statistical sources of the various countries. Seafood consumption levels varied considerably between countries, from 140 in the United Kingdom to 628.5 g/(person.week) in Iceland. The main consumed species were also different between countries. The probability of exceeding the methyl‐Hg PTWI ranged from 0.04% in the United Kingdom to 9.61% in Iceland. Concerning the probability of exceeding the RDI of EPA + DHA, Iceland was third, after Portugal (66.05%) and Spain (61.05%) and the United Kingdom was the last (0.32%). While TE was most accurate for small probabilities, PI yielded best estimates for larger probabilities.     

Assessing Interventions to Reduce the Risk of Campylobacter Prevalence in Broilers

As part of a comprehensive risk assessment on the Campylobacter prevalence in the chicken production chain (from young born chicken till chicken fillet) in the Netherlands, we formulated a quantitative model on the transmission dynamics of Campylobacter at Dutch broiler farms. This model is used to quantify the risk of Campylobacter prevalence in broilers at the time that flocks leave the farm for processing. To this end, we assumed that the Campylobacter prevalence is primarily determined by two parameters, that is, the within- and between-flock transmission. The within-flock transmission was assessed fitting experimental data to a logistic growth model and the between-flock transmission was assessed fitting field data to a generalized linear model (GLM), which included three possible infection routes: (1) via an infected flock in the previous cycle, (2) via other infected flocks present on the farm, and (3) from other sources. This model was applied to assess the efficacy of three control scenarios; (1) a ban on other livestock on broiler farms, (2) a ban on thinning, and (3) a reduction of the between-flock transmission. In contrast to the other scenarios, the third one was shown to be most effective. Theoretically, this is accomplished by improved biosecurity. However, the impact of improved biosecurity cannot be specified into specific control measures, and therefore it is not clear what investments are needed. Finally, we also assessed the efficacy of scheduled treatment, that is, fresh meat production solely from test-negative flocks. We found that the reliability of negative test results, which is crucial, strongly depends on the length of time between testing and slaughter. The sensitivity and specificity of the test appeared to be of minor importance.     

The Measurement of Subjective Probability: Evaluating the Sensitivity and Accuracy of Various Scales

The RISK of an event generally relates to its expected severity and the perceived probability of its occurrence. In RISK research, however, there is no standard measure for subjective probability estimates. In this study, we compared five commonly used measurement formats—two rating scales, a visual analog scale, and two numeric measures—in terms of their ability to assess subjective probability judgments when objective probabilities are available. We varied the probabilities (low vs. moderate) and severity (low vs. high) of the events to be judged as well as the presentation mode of objective probabilities (sequential presentation of singular events vs. graphical presentation of aggregated information). We employed two complementary goodness‐of‐fit criteria: the correlation between objective and subjective probabilities (sensitivity), and the root mean square deviations of subjective probabilities from objective values (accuracy). The numeric formats generally outperformed all other measures. The severity of events had no effect on the performance. Generally, a rise in probability led to decreases in performance. This effect, however, depended on how the objective probabilities were encoded: pictographs ensured perfect information, which improved goodness of fit for all formats and diminished this negative effect on the performance. Differences in performance between scales are thus caused only in part by characteristics of the scales themselves—they also depend on the process of encoding. Consequently, researchers should take the source of probability information into account before selecting a measure.     

Income determination for corporate tax purposes using IFRS as a starting point: evidence for listed companies within Austria, Germany, and The Netherlands

The internationalisation of financial accounting and the European Commission’s ambition to harmonise corporate taxation have raised the question whether IFRS accounts could be used for tax purposes. In order to quantify the effects of an IFRS-based taxation on corporate tax burdens in different EU member states, we estimate firms’ tax equity using notes on income taxes in IFRS financial statements of companies listed in Austria, Germany, and The Netherlands. The difference between estimated tax equity and IFRS-equity, adjusted for the effect resulting from the recognition of deferred taxes, shows the effect of using IFRS as a tax base on the present value of corporate taxes. We find that estimated tax equity is mostly lower than IFRS-equity, indicating that an IFRS-based taxation would often increase the present value of corporate taxes. The median of estimated tax equity is 5.6 % (Austria), 6.4 % (Germany) and 9.0 % (The Netherlands) below IFRS-equity. However, an IFRS-based taxation does not always induce higher equity as often argued in the literature. In 307 of 1,113 totally analysed firm-years, estimated tax equity exceeds IFRS-equity. To find a further estimation for the effects of tax base reforms we also approximate the total stock of unused tax losses and the amount of useable tax losses. We find that deferred tax assets for unused tax losses are depreciated to a substantial extent.     

Quantitative Assessment of the Risk of Release of Foot‐and‐Mouth Disease Virus via Export of Bull Semen from Israel

Various foot‐and‐mouth disease (FMD) virus strains circulate in the Middle East, causing frequent episodes of FMD outbreaks among Israeli livestock. Since the virus is highly resistant in semen, artificial insemination with contaminated bull semen may lead to the infection of the receiver cow. As a non‐FMD‐free country with vaccination, Israel is currently engaged in trading bull semen only with countries of the same status. The purpose of this study was to assess the risk of release of FMD virus through export of bull semen in order to estimate the risk for FMD‐free countries considering purchasing Israeli bull semen. A stochastic risk assessment model was used to estimate this risk, defined as the annual likelihood of exporting at least one ejaculate of bull semen contaminated with viable FMD virus. A total of 45 scenarios were assessed to account for uncertainty and variability around specific parameter estimates and to evaluate the effect of various mitigation measures, such as performing a preexport test on semen ejaculates. Under the most plausible scenario, the annual likelihood of exporting bull semen contaminated with FMD virus had a median of 1.3 * 10^?7 for an export of 100 ejaculates per year. This corresponds to one infected ejaculate exported every 7 million years. Under the worst‐case scenario, the median of the risk rose to 7.9 * 10^?5, which is equivalent to the export of one infected ejaculate every 12,000 years. Sensitivity analysis indicated that the most influential parameter is the probability of viral excretion in infected bulls.     

A Quantitative Release Assessment for the Noncommercial Movement of Companion Animals: Risk of Rabies Reintroduction to the United Kingdom

In 2004, the European Union (EU) implemented a pet movement policy (referred to here as the EUPMP) under EU regulation 998/2003. The United Kingdom (UK) was granted a temporary derogation from the policy until December 2011 and instead has in place its own Pet Movement Policy (Pet Travel Scheme (PETS)). A quantitative risk assessment (QRA) was developed to estimate the risk of rabies introduction to the UK under both schemes to quantify any change in the risk of rabies introduction should the UK harmonize with the EU policy. Assuming 100 % compliance with the regulations, moving to the EUPMP was predicted to increase the annual risk of rabies introduction to the UK by approximately 60‐fold, from 7.79 × 10^?5 (5.90 × 10^?5, 1.06 × 10^?4) under the current scheme to 4.79 × 10^?3 (4.05 × 10^?3, 5.65 × 10^?3) under the EUPMP. This corresponds to a decrease from 13,272 (9,408, 16,940) to 211 (177, 247) years between rabies introductions. The risks associated with both the schemes were predicted to increase when less than 100 % compliance was assumed, with the current scheme of PETS and quarantine being shown to be particularly sensitive to noncompliance. The results of this risk assessment, along with other evidence, formed a scientific evidence base to inform policy decision with respect to companion animal movement.     

SENSITIVITY ANALYSIS IN DECISION THEORY

This paper explores linear programming-like sensitivity analysis in decision theory. In particular, the paper considers the sensitivity of an optimal decision to changes in probabilities of the states of nature and the development of “confidence spheres” to bound arbitrary parametric changes in the probability vector. Such information can be used to assess the accuracy required in assigning probabilities and the confidence in the maximumutility decision.     

Which Fire to Extinguish First? A Risk‐Informed Approach to Emergency Response in Oil Terminals

The performance of fire protection measures plays a key role in the prevention and mitigation of fire escalation (fire domino effect) in process plants. In addition to passive and active safety measures, the intervention of firefighting teams can have a great impact on fire propagation. In the present study, we have demonstrated an application of dynamic Bayesian network to modeling and safety assessment of fire domino effect in oil terminals while considering the effect of safety measures in place. The results of the developed dynamic Bayesian network—prior and posterior probabilities—have been combined with information theory, in the form of mutual information, to identify optimal firefighting strategies, especially when the number of fire trucks is not sufficient to handle all the vessels in danger.     

Estimating Preventable Fractions of Disease Caused by a Specified Biological Mechanism: PAHs in Smoking Lung Cancers as an Example

Epidemiology textbooks often interpret population attributable fractions based on 2 x 2 tables or logistic regression models of exposure-response associations as preventable fractions, i.e., as fractions of illnesses in a population that would be prevented if exposure were removed. In general, this causal interpretation is not correct, since statistical association need not indicate causation; moreover, it does not identify how much risk would be prevented by removing specific constituents of complex exposures. This article introduces and illustrates an approach to calculating useful bounds on preventable fractions, having valid causal interpretations, from the types of partial but useful molecular epidemiological and biological information often available in practice. The method applies probabilistic risk assessment concepts from systems reliability analysis, together with bounding constraints for the relationship between event probabilities and causation (such as that the probability that exposure X causes response Y cannot exceed the probability that exposure X precedes response Y, or the probability that both X and Y occur) to bound the contribution to causation from specific causal pathways. We illustrate the approach by estimating an upper bound on the contribution to lung cancer risk made by a specific, much-discussed causal pathway that links smoking to a polycyclic aromatic hydrocarbon (PAH) (specifically, benzo(a)pyrene diol epoxide-DNA) adducts at hot spot codons at p53 in lung cells. The result is a surprisingly small preventable fraction (of perhaps 7% or less) for this pathway, suggesting that it will be important to consider other mechanisms and non-PAH constituents of tobacco smoke in designing less risky tobacco-based products.