Safe-by-Design: Stakeholders’ Perceptions and Expectations of How to Deal with Uncertain Risks of Emerging Biotechnologies in the Netherlands

Advanced gene editing techniques such as Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)/Cas have increased the pace of developments in the field of industrial biotechnology. Such techniques imply new possibilities when working with living organisms, possibly leading to uncertain risks. In the Netherlands, current policy fails to address these uncertain risks because risk classification is determined process-wise (i.e., genetically modified organism [GMO] and non-GMO), there is a strong focus on quantifiable risks, and the linearity within current governance (science–policy–society) hinders iterative communication between stakeholders, leaving limited room to anticipate uncertainties at an early stage of development. A suggested concept to overcome these shortcomings is the Safe-by-Design (SbD) approach, which, theoretically, allows stakeholders to iteratively incorporate safety measures throughout a technology's development process, creating a dynamic environment for the anticipation of uncertain risks. Although this concept originates from chemical engineering and is already widely applied in nanotechnology, for the field of biotechnology, there is no agreed upon definition yet. To explore the possibilities of SbD for future governance of biotechnology, we should gain insight in how various stakeholders perceive notions of risk, safety, and inherent safety, and what this implies for the applicability of SbD for risk governance concerning industrial biotechnology. Our empirical research reveals three main themes: (1) diverging expectations with regard to safety and risks, and to establish an acceptable level of risk; (2) different applications of SbD and inherent safety, namely, product- and process-wise; and (3) unclarity in allocating responsibilities to stakeholders in the development process of a biotechnology and within society.     

Incremental Sampling Methodology: Applications for Background Screening Assessments

This article presents the findings from a numerical simulation study that was conducted to evaluate the performance of alternative statistical analysis methods for background screening assessments when data sets are generated with incremental sampling methods (ISMs). A wide range of background and site conditions are represented in order to test different ISM sampling designs. Both hypothesis tests and upper tolerance limit (UTL) screening methods were implemented following U.S. Environmental Protection Agency (USEPA) guidance for specifying error rates. The simulations show that hypothesis testing using two‐sample t ‐tests can meet standard performance criteria under a wide range of conditions, even with relatively small sample sizes. Key factors that affect the performance include unequal population variances and small absolute differences in population means. UTL methods are generally not recommended due to conceptual limitations in the technique when applied to ISM data sets from single decision units and due to insufficient power given standard statistical sample sizes from ISM.     

Evaluation of Multicriteria Decision Analysis Algorithms in Food Safety: A Case Study on Emerging Zoonoses Prioritization

Decision making in food safety is a complex process that involves several criteria of different nature like the expected reduction in the number of illnesses, the potential economic or health-related cost, or even the environmental impact of a given policy or intervention. Several multicriteria decision analysis (MCDA) algorithms are currently used, mostly individually, in food safety to rank different options in a multifactorial environment. However, the selection of the MCDA algorithm is a decision problem on its own because different methods calculate different rankings. The aim of this study was to compare the impact of different uncertainty sources on the rankings of MCDA problems in the context of food safety. For that purpose, a previously published data set on emerging zoonoses in the Netherlands was used to compare different MCDA algorithms: MMOORA, TOPSIS, VIKOR, WASPAS, and ELECTRE III. The rankings were calculated with and without considering uncertainty (using fuzzy sets), to assess the importance of this factor. The rankings obtained differed between algorithms, emphasizing that the selection of the MCDA method had a relevant impact in the rankings. Furthermore, considering uncertainty in the ranking had a high influence on the results. Both factors were more relevant than the weights associated with each criterion in this case study. A hierarchical clustering method was suggested to aggregate results obtained by the different algorithms. This complementary step seems to be a promising way to decrease extreme difference among algorithms and could provide a strong added value in the decision-making process.     

A Discourse on the Incorporation of Organizational Factors into Probabilistic Risk Assessment: Key Questions and Categorical Review

This article presents a discourse on the incorporation of organizational factors into probabilistic risk assessment (PRA)/probabilistic safety assessment (PSA), a topic of debate since the 1980s that has spurred discussions among industry, regulatory agencies, and the research community. The main contributions of this article include (1) identifying the four key open questions associated with this topic; (2) framing ongoing debates by considering differing perspectives around each question; (3) offering a categorical review of existing studies on this topic to justify the selection of each question and to analyze the challenges related to each perspective; and (4) highlighting the directions of research required to reach a final resolution for each question. The four key questions are: (I) How significant is the contribution of organizational factors to accidents and incidents? (II) How critical, with respect to improving risk assessment, is the explicit incorporation of organizational factors into PRA? (III) What theoretical bases are needed for explicit incorporation of organizational factors into PRA? (IV) What methodological bases are needed for the explicit incorporation of organizational factors into PRA? Questions I and II mainly analyze PRA literature from the nuclear domain. For Questions III and IV, a broader review and categorization is conducted of those existing cross-disciplinary studies that have evaluated the effects of organizational factors on safety (not solely PRA-based) to shed more light on future research needs.     

Adolescents’ and Young Adults’ Online Risk Taking: The Role of Gist and Verbatim Representations

Young people are exposed to and engage in online risky activities, such as disclosing personal information and making unknown friends online. Little research has examined the psychological mechanisms underlying young people's online risk taking. Drawing on fuzzy trace theory, we examined developmental differences in adolescents’ and young adults’ online risk taking and assessed whether differential reliance on gist representations (based on vague, intuitive knowledge) or verbatim representations (based on specific, factual knowledge) could explain online risk taking. One hundred and twenty two adolescents (ages 13–17) and 172 young adults (ages 18–24) were asked about their past online risk‐taking behavior, intentions to engage in future risky online behavior, and gist and verbatim representations. Adolescents had significantly higher intentions to take online risks than young adults. Past risky online behaviors were positively associated with future intentions to take online risks for adolescents and negatively for young adults. Gist representations about risk negatively correlated with intentions to take risks online in both age groups, while verbatim representations positively correlated with online risk intentions, particularly among adolescents. Our results provide novel insights about the underlying mechanisms involved in adolescent and young adults’ online risk taking, suggesting the need to tailor the representation of online risk information to different age groups.     

GIS‐Based Integration of Social Vulnerability and Level 3 Probabilistic Risk Assessment to Advance Emergency Preparedness,Planning, and Response for Severe Nuclear Power Plant Accidents

In the nuclear power industry, Level 3 probabilistic risk assessment (PRA) is used to estimate damage to public health and the environment if a severe accident leads to large radiological release. Current Level 3 PRA does not have an explicit inclusion of social factors and, therefore, it is not possible to perform importance ranking of social factors for risk‐informing emergency preparedness, planning, and response (EPPR). This article offers a methodology for adapting the concept of social vulnerability, commonly used in natural hazard research, in the context of a severe nuclear power plant accident. The methodology has four steps: (1) calculating a hazard‐independent social vulnerability index for the local population; (2) developing a location‐specific representation of the maximum radiological hazard estimated from current Level 3 PRA, in a geographic information system (GIS) environment; (3) developing a GIS‐based socio‐technical risk map by combining the social vulnerability index and the location‐specific radiological hazard; and (4) conducting a risk importance measure analysis to rank the criticality of social factors based on their contribution to the socio‐technical risk. The methodology is applied using results from the 2012 Surry Power Station state‐of‐the‐art reactor consequence analysis. A radiological hazard model is generated from MELCOR accident consequence code system, translated into a GIS environment, and combined with the Center for Disease Control social vulnerability index (SVI). This research creates an opportunity to explicitly consider and rank the criticality of location‐specific SVI themes based on their influence on risk, providing input for EPPR.     

The Mediated Amplification of a Crisis: Communicating the A/H1N1 Pandemic in Press Releases and Press Coverage in Europe

In the aftermath of the A/H1N1 pandemic, health authorities were criticized for failures in crisis communication efforts, and the media were accused of amplifying the pandemic. Considering these criticisms, A/H1N1 provides a suitable case for examining risk amplification processes that may occur in the transfer of information from press releases to print news media during a health crisis. We integrated the social amplification of risk framework with theories of news decisions (news values, framing) in an attempt to contribute to existing research both theoretically and empirically. We conducted a quantitative content analysis of press releases disseminated by health and governmental authorities, as well as the quality and tabloid press in 10 European countries between March 2009 and March 2011. Altogether 243 press releases, 1,243 quality press articles, and 834 tabloid press articles were coded. Consistent with research on news values and framing the results suggest that quality and tabloid papers alike amplified A/H1N1 risks by emphasizing conflict and damage, presenting information in a more dramatized way, and using risk‐amplifying frames to a greater extent and risk‐attenuating frames to a lesser extent than press releases. To some extent, the quality and tabloid press differed in how risk information was presented. While tabloid press articles seemed to follow the leading quality press with regards to content and framing of health crisis coverage, they exhibited a stronger emphasis on drama and emotion in the way they presented information.     

Characterizing Risk for Cumulative Risk Assessments

In assessing environmental health risks, the risk characterization step synthesizes information gathered in evaluating exposures to stressors together with dose–response relationships, characteristics of the exposed population, and external environmental conditions. This article summarizes key steps of a cumulative risk assessment (CRA) followed by a discussion of considerations for characterizing cumulative risks. Cumulative risk characterizations differ considerably from single chemical‐ or single source‐based risk characterization. CRAs typically focus on a specific population instead of a pollutant or pollutant source and should include an evaluation of all relevant sources contributing to the exposures in the population and other factors that influence dose–response relationships. Second, CRAs may include influential environmental and population‐specific conditions, involving multiple chemical and nonchemical stressors. Third, a CRA could examine multiple health effects, reflecting joint toxicity and the potential for toxicological interactions. Fourth, the complexities often necessitate simplifying methods, including judgment‐based and semi‐quantitative indices that collapse disparate data into numerical scores. Fifth, because of the higher dimensionality and potentially large number of interactions, information needed to quantify risk is typically incomplete, necessitating an uncertainty analysis. Three approaches that could be used for characterizing risks in a CRA are presented: the multiroute hazard index, stressor grouping by exposure and toxicity, and indices for screening multiple factors and conditions. Other key roles of the risk characterization in CRAs are also described, mainly the translational aspect of including a characterization summary for lay readers (in addition to the technical analysis), and placing the results in the context of the likely risk‐based decisions.     

Trends in cardiovascular diseases and associated risks in sub-Saharan Africa: a review of the evidence for Ghana,Nigeria, South Africa,Sudan and Tanzania

Background: Sub-Saharan Africa (SSA) countries are facing an epidemiological shift from infectious disease to chronic diseases, such as cardiovascular diseases (CVDs). CVDs incidence in SSA are frequently attributed to the prevalence of hypertension, diabetes, and overweight/obesity. Nevertheless, some researchers contend that CVDs are not a priority public health problem in SSA.

Method: This paper systematically reviews the evidence on CVDs and their relation with hypertension, diabetes mellitus and obesity/overweight in Ghana, Nigeria, South Africa, Sudan and Tanzania. The publication’s content was analyzed qualitatively using the directed content analysis method and the results were presented in a tabular format.

Result: The paper illustrates the rising prevalence of CVDs as well as the three related risk conditions in the selected SSA countries.

Conclusion: The review indicates a poor health system response to the increasing risk of CVDs in SSA. The conditions and major drivers that contribute to this underlying increasing trend need to be further studied.     

Modeling Finite‐Time Failure Probabilities in Risk Analysis Applications

In this article, we introduce a framework for analyzing the risk of systems failure based on estimating the failure probability. The latter is defined as the probability that a certain risk process, characterizing the operations of a system, reaches a possibly time‐dependent critical risk level within a finite‐time interval. Under general assumptions, we define two dually connected models for the risk process and derive explicit expressions for the failure probability and also the joint probability of the time of the occurrence of failure and the excess of the risk process over the risk level. We illustrate how these probabilistic models and results can be successfully applied in several important areas of risk analysis, among which are systems reliability, inventory management, flood control via dam management, infectious disease spread, and financial insolvency. Numerical illustrations are also presented.