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Although the Caribbean's Small Island Developing States (SIDS) minimally contribute to global greenhouse gas emissions, they face disproportionate climate risks and are particularly susceptible to systemic economic threats posed by climate change and subsequent increases in climate variability. Historically, strategic programs and investments have sought to develop more robust and adaptive engineered systems to absorb climate threats. However, such initiatives are limited and under-resourced in the SIDS' context. This article reviews existing climate strategies in the Caribbean and then critically examines current gaps and barriers relating to climate impact knowledge, needs, and implementation. This examination can assist Caribbean SIDS leadership to identify opportunities to transition from a vulnerability-reducing mindset to one of resilience and transformative adaptation to improve long-term economic outlooks, social welfare, and environmental stewardship despite recurring and escalating climate risks. Integr Environ Assess Manag 2024;20:1237-1255. © 2023 SETAC., (© 2023 SETAC.)

In the last 20 years, the field of biotechnology has made significant progress and attracted substantial investments, leading to different paths of technological modernization among nations. As a result, there is now an international divide in the commercial and intellectual capabilities of biotechnology, and the implications of this divergence are not well understood. This raises important questions about why global actors are motivated to participate in biotechnology modernization, the challenges they face in achieving their goals, and the possible future direction of global biotechnology development. Using the framework of prospect theory, this paper explores the role of risk culture as a fundamental factor contributing to this divergence. It aims to assess the risks and benefits associated with the early adoption of biotechnology and the regulatory frameworks that shape the development and acceptance of biotechnological innovations. By doing so, it provides valuable insights into the future of biotechnology development and its potential impact on the global landscape., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Trump, Cummings, Loschin, Keisler, Wells and Linkov.)

"Modest doubt is call'd the beacon of the wise."-William Shakespeare, Troilus and Cressida. Although the character Hector warns his fellow Trojans with this line not to engage in war against the Greeks, Shakespeare's works are replete with characters who do not incorporate modest doubt, or any consideration of uncertainty, in their risk decisions. Perhaps Shakespeare was simply a keen observer of human nature. Although risk science has developed tremendously over the last five decades (and scientific inquiry over five centuries), the human mind still frequently defaults to conviction about certain beliefs, absent sufficient scientific evidence-which has effects not just on individual lives, but on policy decisions that affect many. This perspective provides background on the Shakespearean quote in its literary and historical context. Then, as this quote is the theme of the 2023 Society for Risk Analysis Annual Meeting, we describe how "modest doubt"-incorporating the notion of uncertainty into risk analysis for individual and policy decisions-is still the "beacon of the wise" today., (© 2023 The Authors. Risk Analysis published by Wiley Periodicals LLC on behalf of Society for Risk Analysis.)

Competing Interests: Declaration of Competing Interest The authors declare no conflicts of interest.

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.

Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Rural areas face well known and distinctive health care challenges that can limit their resilience in the face of health emergencies such as the COVID-19 pandemic. These include problems of sparsity and consequent limited health care provisioning; poverty, inequalities, and distinctive economic structures that limit access to health care; and underlying population health risks and inequalities that can increase vulnerability. Nonetheless, not all rural areas face the same problems, and non-rural areas can have challenges. To be useful in influencing policy, a tool to identify more and less resilient areas is necessary. This Commentary reviews key forms of risk and constructs a county-level index of resilience for the United States which helps to identify countries with limited resilience. Further, it argues that health care resilience should be conceptualized in terms of broader regions than counties since health care facilities' referral regions are larger than individual counties; resilience needs to be understood at that level. The index, read at the level of counties and referral regions, can contribute to identification of immediate problems as well as targets for longer term investment and policy response., Competing Interests: Conflict of interestThe authors declare that they have no conflict of interest., (© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022, Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

State governments in the U.S. have been facing difficult decisions involving tradeoffs between economic and health-related outcomes during the COVID-19 pandemic. Despite evidence of the effectiveness of government-mandated restrictions mitigating the spread of contagion, these orders are stigmatized due to undesirable economic consequences. This tradeoff resulted in state governments employing mandates at widely different ways. We compare the different policies states implemented during periods of restriction ("lockdown") and reopening with indicators of COVID-19 spread and consumer card spending at each state during the first "wave" of the pandemic in the U.S. between March and August 2020. We find that while some states enacted reopening decisions when the incidence rate of COVID-19 was minimal or sustained in its relative decline, other states relaxed socioeconomic restrictions near their highest incidence and prevalence rates experienced so far. Nevertheless, all states experienced similar trends in consumer card spending recovery, which was strongly correlated with reopening policies following the lockdowns and relatively independent from COVID-19 incidence rates at the time. Our findings suggest that consumer card spending patterns can be attributed to government mandates rather than COVID-19 incidence in the states. We estimate the recovery in states that reopened in late April was more than the recovery in states that did not reopen in the same period- 15% for consumer card spending and 18% for spending by high income households. This result highlights the important role of state policies in minimizing health impacts while promoting economic recovery and helps planning effective interventions in subsequent waves and immunization efforts., Competing Interests: The authors have declared that no competing interests exist.

During the coronavirus pandemic, policy makers need to interpret available public health data to make decisions affecting public health. However, the United States' coronavirus response faced data gaps, inadequate and inconsistent definitions of data across different governmental jurisdictions, ambiguous timing in reporting, problems in accessing data, and changing interpretations from scientific institutions. These present numerous problems for the decision makers relying on this information. This paper documents some of the data pitfalls in coronavirus public health data reporting, as identified by the authors in the course of supporting data management for New England's coronavirus response. We provide recommendations for individuals to collect data more effectively during emergency situations such as a COVID-19 surge, as well as recommendations for institutions to provide more meaningful data for various users to access. Through this, we hope to motivate action to avoid data pitfalls during public health responses in the future., Competing Interests: The authors declare no competing interests., (© 2021 Elsevier Ltd. All rights reserved.)

Many efforts to predict the impact of COVID-19 on hospitalization, intensive care unit (ICU) utilization, and mortality rely on age and comorbidities. These predictions are foundational to learning, policymaking, and planning for the pandemic, and therefore understanding the relationship between age, comorbidities, and health outcomes is critical to assessing and managing public health risks. From a US government database of 1.4 million patient records collected in May 2020, we extracted the relationships between age and number of comorbidities at the individual level to predict the likelihood of hospitalization, admission to intensive care, and death. We then applied the relationships to each US state and a selection of different countries in order to see whether they predicted observed outcome rates. We found that age and comorbidity data within these geographical regions do not explain much of the international or within-country variation in hospitalization, ICU admission, or death. Identifying alternative explanations for the limited predictive power of comorbidities and age at the population level should be considered for future research., Competing Interests: Dr Zachary A Collier reports personal fees from US Army ERDC, during the conduct of the study. Professor Holly Jarman reports grants from US Army Engineer Research Development Center, during the conduct of the study. The authors reported no other potential conflicts of interest for this work. The views and opinions expressed in this article are those of the individual authors and not those of the U.S. Army, FEMA, HHS or other sponsor organizations., (© 2021 Cegan et al.)

The emergence of COVID-19 in the United States has overwhelmed local hospitals, produced shortages in critical protective supplies for medical staff, and created backlogs in burials and cremations. Because systemic disruptions occur most acutely at a local scale, facilitating resource coordination across a broad region can assist local responses to COVID-19 surges. This article describes a structured systems approach for coordinating COVID-19 resource distribution across the six New England states of the United States. The framework combines modeling tools to anticipate resource shortages in medical supplies, personnel needs, and fatality management for individual states. The approach allows decision makers to understand the magnitude of local outbreaks and equitably allocate resources within a region based on the present and future needs. This model contributed to determining material distribution in New England as the 2020 COVID-19 surges unfolded in the spring and fall seasons. Using a systems analysis, the model demonstrates the translation of anticipated COVID-19 cases into resource demands to enable regional coordination of scarce resources.

Desirable system performance in the face of threats has been characterized by various management concepts. Through semistructured interviews with editors of journals in the fields of emergency response and systems management, a literature review, and professional judgment, we identified nine related and often interchangeably used system performance concepts: adaptability, agility, reliability, resilience, resistance, robustness, safety, security, and sustainability. A better understanding of these concepts will allow system planners to pursue management strategies best suited to their unique system dynamics and specific objectives of good performance. We analyze expert responses and review the linguistic definitions and mathematical framing of these concepts to understand their applications. We find a lack of consensus on their usage between interview subjects, but by using the mathematical framing to enrich the linguistic definitions, we formulate comparative visualizations and propose distinct definitions for the nine concepts. We present a conceptual framing to relate the concepts for management purposes., (© 2020 Society for Risk Analysis.)

The fast-paced field of synthetic biology is fundamentally changing the global biosecurity framework. Current biosecurity regulations and strategies are based on previous governance paradigms for pathogen-oriented security, recombinant DNA research, and broader concerns related to genetically modified organisms (GMOs). Many scholarly discussions and biosecurity practitioners are therefore concerned that synthetic biology outpaces established biosafety and biosecurity measures to prevent deliberate and malicious or inadvertent and accidental misuse of synthetic biology's processes or products. This commentary proposes three strategies to improve biosecurity: Security must be treated as an investment in the future applicability of the technology; social scientists and policy makers should be engaged early in technology development and forecasting; and coordination among global stakeholders is necessary to ensure acceptable levels of risk., (© 2020 The Authors. Published under the terms of the CC BY 4.0 license.)

After implementing restrictions to curb the spread of coronavirus, governments in the United States and around the world are trying to identify the path to social and economic recovery. The White House and the Centers for Disease Control and Prevention have published guidelines to assist US states, counties, and territories in planning these efforts. As the impact of the coronavirus pandemic has not been uniform, these central guidelines need to be translated into practice in ways that recognize variation among jurisdictions. We present a core methodology to assist governments in this task, presenting a case for appropriate actions at each stage of recovery based on scientific data and analysis. Specifically, 3 types of data are needed: data on the spread of disease should be analyzed alongside data on the overall health of the population and data on infrastructure-for example, the capacity of health systems. Local circumstances will produce different needs and present different setbacks, and governments may need to reinstate as well as relax restrictions. Transparent, defensible analysis can assist in making these decisions and communicating them to the public. In the absence of a widely administered vaccine, analysis remains one of our most important tools in addressing the coronavirus pandemic.

Emerging technologies research often covers various perspectives in disciplines and research areas ranging from hard sciences, engineering, policymaking, and sociology. However, the interrelationship between these different disciplinary domains, particularly the physical and social sciences, often occurs many years after a technology has matured and moved towards commercialization. Synthetic biology may serve an exception to this idea, where, since 2000, the physical and the social sciences communities have increasingly framed their research in response to various perspectives in biological engineering, risk assessment needs, governance challenges, and the social implications that the technology may incur. This paper reviews a broad collection of synthetic biology literature from 2000-2016, and demonstrates how the co-development of physical and social science communities has grown throughout synthetic biology's earliest stages of development. Further, this paper indicates that future co-development of synthetic biology scholarship will assist with significant challenges of the technology's risk assessment, governance, and public engagement needs, where an interdisciplinary approach is necessary to foster sustainable, risk-informed, and societally beneficial technological advances moving forward.

When dealing with public policy in the field of safety, security, and environmental health, legitimacy or illegitimacy is often evoked as a challenge that determines whether a policy will be embraced over time. Scholarly literature points to key variables of public support as well as the use of subject matter experts to build legitimacy in the policy process, yet few articles unpack the meaning and application of legitimacy in a manner that accounts for unique political, institutional, and cultural considerations. This article offers a holistic understanding of the various drivers and challenges behind the legitimacy principle. Specifically, this article reviews how policy successes and failures in France were driven at least in part by a perception of policy legitimacy by policymakers, stakeholders, and the general public., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Various emerging technologies challenge existing governance processes to identify, assess, and manage risk. Though the existing risk-based paradigm has been essential for assessment of many chemical, biological, radiological, and nuclear technologies, a complementary approach may be warranted for the early-stage assessment and management challenges of high uncertainty technologies ranging from nanotechnology to synthetic biology to artificial intelligence, among many others. This paper argues for a risk governance approach that integrates quantitative experimental information alongside qualitative expert insight to characterize and balance the risks, benefits, costs, and societal implications of emerging technologies. Various articles in scholarly literature have highlighted differing points of how to address technological uncertainty, and this article builds upon such knowledge to explain how an emerging technology risk governance process should be driven by a multi-stakeholder effort, incorporate various disparate sources of information, review various endpoints and outcomes, and comparatively assess emerging technology performance against existing conventional products in a given application area. At least in the early stages of development when quantitative data for risk assessment remain incomplete or limited, such an approach can be valuable for policymakers and decision makers to evaluate the impact that such technologies may have upon human and environmental health.

Shared ownership of property and resources is a longstanding challenge throughout history that has been amplifying with the increasing development of industrial and postindustrial societies. Where governments, project planners, and commercial developers seek to develop new infrastructure, industrial projects, and various other land-and resource-intensive tasks, veto power shared by various local stakeholders can complicate or halt progress. Risk communication has been used as an attempt to address stakeholder concerns in these contexts, but has demonstrated shortcomings. These coordination failures between project planners and stakeholders can be described as a specific kind of social dilemma that we describe as the "tragedy of the anticommons." To overcome such dilemmas, we demonstrate how a two-step process can directly address public mistrust of project planners and public perceptions of limited decision-making authority. This approach is examined via two separate empirical field experiments in Portugal and Tunisia, where public resistance and anticommons problems threatened to derail emerging industrial projects. In both applications, an intervention is undertaken to address initial public resistance to such projects, where specific public stakeholders and project sponsors collectively engaged in a hypothesis-testing process to identify and assess human and environmental health risks associated with proposed industrial facilities. These field experiments indicate that a rigorous attempt to address public mistrust and perceptions of power imbalances and change the pay-off structure of the given dilemma may help overcome such anticommons problems in specific cases, and may potentially generate enthusiasm and support for such projects by local publics moving forward., (© 2017 Society for Risk Analysis.)

Synthetic biology is an emerging technology with potential benefits to various fields, yet also contains potential risks to human and environmental health. The field remains in an emerging state with limited quantitative guidance and a small but growing population of international researchers that conduct work within this field. Given the uncertain nature of this technology, an adaptive and anticipatory governance framework may be necessary to balance the potential benefits that may accrue from the technology's continued research alongside a desire to reduce or eliminate potential risks that may arise. However, such developments must account for the unique political and institutional factors that form a government's risk culture - something that can facilitate or impede the development of adaptive synthetic biology governance moving forward. The TAPIC framework helps illustrate those factors that are essential to develop good governance for emerging technologies like synthetic biology. Specifically, an application of TAPIC to synthetic biology governance indicates that the factors of accountability, participation, and integrity must be bolstered to improve technology governance in governments like with the United States, European Union, and Singapore., (Copyright © 2017. Published by Elsevier B.V.)

Two analytic perspectives on environmental assessment dominate environmental policy and decision-making: risk analysis (RA) and life-cycle assessment (LCA). RA focuses on management of a toxicological hazard in a specific exposure scenario, while LCA seeks a holistic estimation of impacts of thousands of substances across multiple media, including non-toxicological and non-chemically deleterious effects. While recommendations to integrate the two approaches have remained a consistent feature of environmental scholarship for at least 15 years, the current perception is that progress is slow largely because of practical obstacles, such as a lack of data, rather than insurmountable theoretical difficulties. Nonetheless, the emergence of nanotechnology presents a serious challenge to both perspectives. Because the pace of nanomaterial innovation far outstrips acquisition of environmentally relevant data, it is now clear that a further integration of RA and LCA based on dataset completion will remain futile. In fact, the two approaches are suited for different purposes and answer different questions. A more pragmatic approach to providing better guidance to decision-makers is to apply the two methods in parallel, integrating only after obtaining separate results.

Emerging technologies present significant challenges to researchers, decision-makers, industry professionals, and other stakeholder groups due to the lack of quantitative risk, benefit, and cost data associated with their use. Multi-criteria decision analysis (MCDA) can support early decisions for emerging technologies when data is too sparse or uncertain for traditional risk assessment. It does this by integrating expert judgment with available quantitative and qualitative inputs across multiple criteria to provide relative technology scores. Here, an MCDA framework provides preliminary insights on the suitability of emerging technologies for environmental remediation by comparing nanotechnology and synthetic biology to conventional remediation methods. Subject matter experts provided judgments regarding the importance of criteria used in the evaluations and scored the technologies with respect to those criteria. The results indicate that synthetic biology may be preferred over nanotechnology and conventional methods for high expected benefits and low deployment costs but that conventional technology may be preferred over emerging technologies for reduced risks and development costs. In the absence of field data regarding the risks, benefits, and costs of emerging technologies, structuring evidence-based expert judgment through a weighted hierarchy of topical questions may be helpful to inform preliminary risk governance and guide emerging technology development and policy.

This 'Christmas Issue'-type paper uses the framework of 'A Christmas Carol' to tell about the evolution of decision-making in evidence-based medicine (EBM). The Ghost of the Past represents paternalistic medicine, the Ghost of the Present symbolises EBM, while the Ghost of the Future serves as a patient-centred system where research data and tools of decision science are jointly used to make optimal medical decisions for individual patients. We argue that this shift towards a patient-centred approach to EBM and medical care is the next step in the evolution of medical decision-making, which would help to empower patients with the capability to make educated decisions throughout the course of their medical treatment.

Among other things, the wide-scale development and use of nanomaterials is expected to produce costly regulatory and civil liabilities for nanomanufacturers due to lingering uncertainties, unanticipated effects, and potential toxicity. The life-cycle environmental, health, and safety (EHS) risks of nanomaterials are currently being studied, but the corresponding legal risks have not been systematically addressed. With the aid of a systematic approach that holistically evaluates and accounts for uncertainties about the inherent properties of nanomaterials, it is possible to provide an order of magnitude estimate of liability risks from regulatory and litigious sources based on current knowledge. In this work, we present a conceptual framework for integrating estimated legal liabilities with EHS risks across nanomaterial life-cycle stages using empirical knowledge in the field, scientific and legal judgment, probabilistic risk assessment, and multicriteria decision analysis. Such estimates will provide investors and operators with a basis to compare different technologies and practices and will also inform regulatory and legislative bodies in determining standards that balance risks with technical advancement. We illustrate the framework through the hypothetical case of a manufacturer of nanoscale titanium dioxide and use the resulting expected legal costs to evaluate alternative risk-management actions.