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volume 42, issue 2, february 2022
1. title: accounting for precision uncertainty of toxicity testing: methods to define borderline ranges and implications for hazard assessment of chemicals
authors: silke gabbert, miriam mathea, susanne n. kolle, robert landsiedel
abstract: for hazard classifications of chemicals, continuous data from animal- or nonanimal testing methods are often dichotomized into binary positive/negative outcomes by defining classification thresholds (ct). experimental data are, however, subject to biological and technical variability. each test method's precision is limited resulting in uncertainty of the positive/negative outcome if the experimental result is close to the ct. borderline ranges (br) around the ct were suggested, which represent ranges in which the study result is ambiguous, that is, positive or negative results are equally likely. the br reflects a method's precision uncertainty. this article explores and compares different approaches to quantify the br. besides using the pooled standard deviation, we determine the br by means of the median absolute deviation (mad), with a sequential combination of both methods, and by using nonparametric bootstrapping. furthermore, we quantify the br for different hazardous effects, including nonanimal tests for skin corrosion, eye irritation, skin irritation, and skin sensitization as well as for an animal test on skin sensitization (the local lymph node assay, llna). additionally, for one method (direct peptide reactivity assay) the br was determined experimentally and compared to calculated brs. our results demonstrate that (i) the precision of the methods is determining the size of their brs, (ii) there is no �perfect� method to derive a br, alas, (iii) a consensus on br is needed to account for the limited precision of testing methods.
2. title: a suggestion for the quantification of precise and bounded probability to quantify epistemic uncertainty in scientific assessments
authors: ivette raices cruz, matthias c. m. troffaes, ullrika sahlin
abstract: an honest communication of uncertainty about quantities of interest enhances transparency in scientific assessments. to support this communication, risk assessors should choose appropriate ways to evaluate and characterize epistemic uncertainty. a full treatment of uncertainty requires methods that distinguish aleatory from epistemic uncertainty. quantitative expressions for epistemic uncertainty are advantageous in scientific assessments because they are nonambiguous and enable individual uncertainties to be characterized and combined in a systematic way. since 2019, the european food safety authority (efsa) recommends assessors to express epistemic uncertainty in conclusions of scientific assessments quantitatively by subjective probability. a subjective probability can be used to represent an expert judgment, which may or may not be updated using bayes's rule to integrate evidence available for the assessment and could be either precise or approximate. approximate (or bounded) probabilities may be enough for decision making and allow experts to reach agreement on certainty when they struggle to specify precise subjective probabilities. the difference between the lower and upper bound on a subjective probability can also be used to reflect someone's strength of knowledge. in this article, we demonstrate how to quantify uncertainty by bounded probability, and explicitly distinguish between epistemic and aleatory uncertainty, by means of robust bayesian analysis, including standard bayesian analysis through precise probability as a special case. for illustration, the two analyses are applied to an intake assessment.
3. title: uncertainty quantification with experts: present status and research needs
authors: anca m. hanea, victoria hemming, gabriela f. nane
abstract: expert elicitation is deployed when data are absent or uninformative and critical decisions must be made. in designing an expert elicitation, most practitioners seek to achieve best practice while balancing practical constraints. the choices made influence the required time and effort investment, the quality of the elicited data, experts� engagement, the defensibility of results, and the acceptability of resulting decisions. this piece outlines some of the common choices practitioners encounter when designing and conducting an elicitation. we discuss the evidence supporting these decisions and identify research gaps. this will hopefully allow practitioners to better navigate the literature, and will inspire the expert judgment research community to conduct well powered, replicable experiments that properly address the research gaps identified.
4. title: what is a good calibration question?
authors: victoria hemming, anca m. hanea, mark a. burgman
abstract: weighted aggregation of expert judgments based on their performance on calibration questions may improve mathematically aggregated judgments relative to equal weights. however, obtaining validated, relevant calibration questions can be difficult. if so, should analysts settle for equal weights? or should they use calibration questions that are easier to obtain but less relevant? in this article, we examine what happens to the out-of-sample performance of weighted aggregations of the classical model (cm) compared to equal weighted aggregations when the set of calibration questions includes many so-called �irrelevant� questions, those that might ordinarily be considered to be outside the domain of the questions of interest. we find that performance weighted aggregations outperform equal weights on the combined cm score, but not on statistical accuracy (i.e., calibration). importantly, there was no appreciable difference in performance when weights were developed on relevant versus irrelevant questions. experts were unable to adapt their knowledge across vastly different domains, and in-sample validation did not accurately predict out-of-sample performance on irrelevant questions. we suggest that if relevant calibration questions cannot be found, then analysts should use equal weights, and draw on alternative techniques to improve judgments. our study also indicates limits to the predictive accuracy of performance weighted aggregation, and the degree to which expertise can be adapted across domains. we note limitations in our study and urge further research into the effect of question type on the reliability of performance weighted aggregations.
5. title: precise yet uncertain: broadening understandings of uncertainty and policy in the bpa controversy
authors: dafne lemus, zora kovacic
abstract: bisphenol a (bpa) is one of the most studied and most controversial chemicals used by the food packaging industry, because of its endocrine disruptive properties. part of the controversy is due to the uncertainty that surrounds the effects of bpa on the endocrine system. uncertainty includes data gaps, methodological hurdles, incompatibilities between toxicology and endocrinology-based approaches, and so on. in this article, we analyze how uncertainty has been conceptualized and treated. we focus on the european food safety authority assessments of bpa, and study how exposure and hazard assessments have evolved over time, how uncertainty has been analyzed, and how the agency responded to controversies. results show that in the attempt to reduce knowledge gaps, assessments have become progressively larger, including more references, evidence, and effects. there is a tendency toward greater precisions and specification of results, and toward protocolization of all processes included in the assessment (from literature review, to uncertainty assessments, and public consultation). yet, the uncertainty has not diminished following the increase in evidence. we argue that the strategy used to reduce uncertainty within risk assessment, namely including more variables, studies, data, and methods, amplifies the uncertainty linked to indeterminacy (as more results increase the fragmentation of the knowledge base due to the open-ended nature of complex issues) and ambiguity (as complexity gives way to multiple nonequivalent interpretations of results). for this reason, it is important to consider different types of uncertainty and how these uncertainties interact with each other.
6. title: global sensitivity analysis with mixtures: a generalized functional anova approach
authors: emanuele borgonovo, genyuan li, john barr, elmar plischke, herschel rabitz
abstract: this work investigates aspects of the global sensitivity analysis of computer codes when alternative plausible distributions for the model inputs are available to the analyst. analysts may decide to explore results under each distribution or to aggregate the distributions, assigning, for instance, a mixture. in the first case, we lose uniqueness of the sensitivity measures, and in the second case, we lose independence even if the model inputs are independent under each of the assigned distributions. removing the unique distribution assumption impacts the mathematical properties at the basis of variance-based sensitivity analysis and has consequences on result interpretation as well. we analyze in detail the technical aspects. from this investigation, we derive corresponding recommendations for the risk analyst. we show that an approach based on the generalized functional anova expansion remains theoretically grounded in the presence of a mixture distribution. numerically, we base the construction of the generalized function anova effects on the diffeomorphic modulation under observable response preserving homotopy regression. our application addresses the calculation of variance-based sensitivity measures for the well-known nordhaus' dice model, when its inputs are assigned a mixture distribution. a discussion of implications for the risk analyst and future research perspectives closes the work.
7. title: risk factor analysis of children's exposure to microbial pathogens in playgrounds
authors: ioanna p. chatziprodromidou, stella chatziantoniou, george vantarakis, apostolos vantarakis
abstract: bacteria are commonly found in soil and may cause health risks to children playing in the outdoor playgrounds with soil, mainly via hand to mouth and pica behaviors. our study concerned with the risk analysis of infection of a child playing in urban playgrounds in the cities of patras and pyrgos in greece. the presence of escherichia coli, staphylococcus aureus, and pseudomonas aeruginosa were analyzed in soil samples of these playgrounds. a standardized questionnaire depicted the individual characteristics of each playground and recorded risk factors in playgrounds related to bacterial infections. furthermore, the distributions of e. coli, s. aureus and p. aeruginosa were analyzed in soil samples. our results were investigated with beta-poisson models using the quantitative microbial risk assessment wiki models to evaluate and construct a probability model of infection for each of these bacteria. the risk of infection was higher during the wet period. the risk was higher for p. aeruginosa infection compared to e. coli and s. aureus ones. nevertheless, the bacterial concentration was higher for e. coli than p. aeruginosa and s. aureus in both wet and dry periods. our results provide new data that could contribute in assessing the risks associated with playgrounds where children can unaware play in urban parks.
8. title: risk assessment of norovirus illness from consumption of raw oysters in the united states and in canada
authors: r�gis pouillot, mark smith, jane m. van doren, angela catford, jennifer holtzman, kevin r. calci, robyn edwards, gregory goblick, christopher roberts, jeffrey stobo, john white, jacquelina woods, angelo depaola jr., enrico buenaventura, william burkhardt iii
abstract: human norovirus (nov) is the leading cause of foodborne illness in the united states and canada. bivalve molluscan shellfish is one commodity commonly identified as being a vector of nov. bivalve molluscan shellfish are grown in waters that may be affected by contamination events, tend to bioaccumulate viruses, and are frequently eaten raw. in an effort to better assess the elements that contribute to potential risk of nov infection and illness from consumption of bivalve molluscan shellfish, the u.s. department of health and human services/food and drug administration (fda), health canada (hc), the canadian food inspection agency (cfia), and environment and climate change canada (eccc) collaborated to conduct a quantitative risk assessment for nov in bivalve molluscan shellfish, notably oysters. this study describes the model and scenarios developed and results obtained to assess the risk of nov infection and illness from consumption of raw oysters harvested from a quasi-steady-state situation. among the many factors that influence the risk of nov illness for raw oyster consumers, the concentrations of nov in the influent (raw, untreated) and effluent (treated) of wastewater treatment plants (wwtp) were identified to be the most important. thus, mitigation and control strategies that limit the influence from human waste (wwtp outfalls) in oyster growing areas have a major influence on the risk of illness from consumption of those oysters.
9. title: preferences for prevention: people assume expensive problems have expensive solutions
authors: talbot m. andrews, john barry ryan
abstract: people support inefficient spending on preventing disasters, and these preferences are translated into inefficient policies as elected officials try to appeal to their constituents. here, we find preferences for prevention spending are biased by the �cost conflation� mechanism, where people assume expensive problems have expensive solutions. in this article, we present a formal model of collective action, and illustrate how cost conflation causes people to deviate from the equilibria. we test for these hypothesized deviations using an incentivized experiment. the experimental subjects engage in cost conflation�they believe the costs of disaster prevention are positively related to the costs of disaster damages, even when explicitly told otherwise. as a result, they fail to prevent smaller disasters and pay too much to prevent large disasters when cheap solutions exist. furthermore, we provide evidence that overemphasizing disaster damages undermines successful disaster prevention because people view these disasters as too big to solve.
10. title: assessing the risk of robbery in bank branches to reduce impact on personnel
authors: mar�a pilar de la cruz l�pez, juan jos� cartelle barros, alfredo del ca�o gochi, mar�a concepci�n garaboa fern�ndez, jes�s blanco leis
abstract: according to existing literature, bank robberies can have a considerable impact on the people involved (employees, customers, and police officers), even if the direct economic losses are negligible. consequently, this article presents a model to assess the risk of bank robbery, with the aim of reducing the impact on the people and prioritizing the investments in security measures. it is based on the mives (spanish acronym for the integrated value model for sustainability assessment) method and it was combined with monte carlo simulation as a way of taking into account the uncertainty. correlations were also modeled, for simulation purposes. indicators for addressing issues related to security features, employees, operational procedures, and physical and social environment were defined. the model was applied to two fictitious but realistic sets of cases. the first simulation provides a quick overview of the risk level of a fictitious bank, before collecting the full set of data from hundreds or thousands of branches. the second simulation analyzes the risk variation of a specific bank branch over time. the model was also used to assess the risk index of 636 real branches belonging to a spanish bank. all the results are presented and discussed in depth. the model allows the user to identify the weak points of a branch, so that corrective measures can be taken.
11. title: system analysis of wildfire-water supply risk in colorado, usa with monte carlo wildfire and rainfall simulation
authors: benjamin m. gannon, yu wei, matthew p. thompson, joe h. scott, karen c. short
abstract: water supply impairment from increased contaminant mobilization and transport after wildfire is a major concern for communities that rely on surface water from fire-prone watersheds. in this article we present a monte carlo simulation method to quantify the likelihood of wildfire impairing water supplies by combining stochastic representations of annual wildfire and rainfall activity. water quality impairment was evaluated in terms of turbidity limits for treatment by modeling wildfire burn severity, postfire erosion, sediment transport, and suspended sediment dilution in receiving waterbodies. water supply disruption was analyzed at the system level based on the impairment status of water supply components and their contributions to system performance. we used this approach to assess wildfire-water supply impairment and disruption risks for a system of water supply reservoirs and diversions in the front range mountains of colorado, usa. our results indicate that wildfire may impair water quality in a concerning 15.7�19.4% of years for diversions from large watersheds. reservoir impairment should be rare for off-network reservoirs�ranging from at most 0.01% of years for large reservoirs to nearly 2% of years for small reservoirs. system redundancy meaningfully reduced disruption risk for alternative conveyance routes (4.3�25.0% reduction) and almost eliminated disruption risk for a pair of substitutable terminal sources (99.9% reduction). in contrast, dependency among reservoirs on a conveyance route nearly doubled risk of disruption. our results highlight the importance of considering water system characteristics when evaluating wildfire-water supply risks.
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12. title: fixing food: an fda insider unravels the myths and the solutions. richard a. williams. post hill press, new york, 2021. 288 pp.
authors: felicia wu
abstract: the article reviews the book �fixing food: an fda insider unravels the myths and the solutions� by richard a. williams ph.d.
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