Sensitivity analysis for a participatory approach to enhance the climate resilience of Venice, Italy.

Increases in the magnitudes and frequencies of climate-related extreme events are redistributing risk across coastal systems, including their environmental, economic, and social components. Consequently, stakeholders (SHs) are faced with long-term challenges and complex information when managing assets, services, and uses of the coast. In this context, SH engagement is a key step for risk management and in the preparation of resilience plans to respond and adapt to climate change. This paper develops a participatory method to identify and prioritize a set of risk measures, combining multi-criteria analysis with sensitivity analysis. The process involved local and regional authorities of the Veneto region testing the method, including national, regional, and local government, catchment officers, research organizations, natural parks managers and Non-Governmental Organizations (NGOs). SHs identified and ranked a range of adaptation measures to increase climate resilience, with a focus on coastal risk in the Venice lagoon. Results demonstrate that the sensitivity analysis provides useful information on how different sectors of expertise can influence the ranking of the identified risk management measures, highlighting the value of investigating the preferences or priorities of different SH groups within the definition of adaptation plans.

Balancing climate resilience and adaptation for Caribbean Small Island Developing States (SIDS): Building institutional capacity.

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 2023;00:1-19. © 2023 SETAC.

The worsening divergence of biotechnology: the importance of risk culture.

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.

Establishing a regional interdisciplinary resilience center: a bottom-up approach.

Both natural and manmade disasters have severely impacted the region of Southeast Texas over the past few decades, and this has negatively affected the socio-economic well-being of the region. The state of Texas has suffered 200-250 billion dollars in damages from natural and manmade disasters since 2010. Given the region's strategic importance to the nation's energy and security, developing resilience knowledge and multi-disaster resilience research focused on issues pertaining to the region is needed. This paper describes the structure and process of building a center for multi-disaster resilience at a regional public university. By utilizing a bottom-up approach, the Center's mission and design are broadly democratized through the participation of a variety of scholars and various stakeholders with whom they interact. Resilience needs specific to the Southeast Texas region are examined, as is the relationship between resilience and the academic disciplines of the stakeholders involved. The issues of resilience in the region are discussed as well as the future steps for the Center's continued growth and development for the study of resilience.

Finding shortest and nearly shortest path nodes in large substantially incomplete networks by hyperbolic mapping.

Dynamic processes on networks, be it information transfer in the Internet, contagious spreading in a social network, or neural signaling, take place along shortest or nearly shortest paths. Computing shortest paths is a straightforward task when the network of interest is fully known, and there are a plethora of computational algorithms for this purpose. Unfortunately, our maps of most large networks are substantially incomplete due to either the highly dynamic nature of networks, or high cost of network measurements, or both, rendering traditional path finding methods inefficient. We find that shortest paths in large real networks, such as the network of protein-protein interactions and the Internet at the autonomous system level, are not random but are organized according to latent-geometric rules. If nodes of these networks are mapped to points in latent hyperbolic spaces, shortest paths in them align along geodesic curves connecting endpoint nodes. We find that this alignment is sufficiently strong to allow for the identification of shortest path nodes even in the case of substantially incomplete networks, where numbers of missing links exceed those of observable links. We demonstrate the utility of latent-geometric path finding in problems of cellular pathway reconstruction and communication security.

Framework for multirisk climate scenarios across system receptors with application to the Metropolitan City of Venice.

Climate change influences the frequency of extreme events that affect both human and natural systems. It requires systemic climate change adaptation to address the complexity of risks across multiple domains and tackle the uncertainties of future scenarios. This paper introduces a multirisk analysis of climate hazard, exposure, vulnerability, and risk severity, specifically designed to hotspot geographic locations and prioritize system receptors that are affected by climate-related extremes. The analysis is demonstrated for the Metropolitan City of Venice. Representative scenarios (RCP4.5 and RCP8.5) of climate threats (i.e., storm surges, pluvial flood, heat waves, and drought) are selected and represented by projections of Regional Climate Models for a 30-year period (2021-2050). A sample of results is as follows. First, an increase in the risk is largely due to drought, pluvial flood, and storm surge, depending on the areas of interest, with the overall situation worsening under the RCP8.5 scenario. Second, particular locations have colocated vulnerable receptors at higher risk, concentrated in the urban centers (e.g., housing, railways, roads) and along the coast (e.g., beaches, wetlands, primary sector). Third, risk communication of potential environmental and socio-economic losses via the multirisk maps is useful to stakeholders and public administration. Fourth, the multirisk maps recommend priorities for future investigation and risk management, such as collection of sensor data, elaboration of mitigations, and adaptation plans at hotspot locations.

Multimorbidity resilience and health behaviors among older adults: A longitudinal study using the Canadian Longitudinal Study on Aging.

Objective: There has been a growing interest in examining why some individuals adapt and bounce back from multimorbidity (resilience) better than others. This paper investigates the positive role of protective health behaviors on multimorbidity resilience (MR) among older adults focusing on older persons with two or more concurrent chronic conditions, and separately for three multimorbidity chronic illness clusters. Methods: Using Baseline and Follow-up One data from the Comprehensive Cohort of the Canadian Longitudinal Study on Aging, we studied 10,628 participants aged 65 years and older who reported two or more of 27 chronic conditions, and three multimorbidity clusters: Cardiovascular/metabolic, Musculoskeletal, and Mental health. Associations between health behaviors and MR were evaluated using Linear Mixed Models, adjusting for socio-demographic, social/environmental, and illness context social determinants of health. Results: Among older adults with two or more illnesses, smoking, satisfaction with sleep, appetite, and skipping meals were associated with MR in the expected direction. Also, obesity (compared to normal weight) and skipping meals showed longitudinal interaction effects with survey wave. Most of the results were replicated for the physical multimorbidity clusters (Cardiovascular/metabolic and Musculoskeletal) compared to the full 2+ multimorbidity analyses; however, for the Mental health cluster, only satisfaction with sleep was supported as a lifestyle predictor of MR. Discussion: Several modifiable health behaviors identified in the broader health and aging literature are important in affecting levels of multimorbidity resilience in older age. These factors are important strength-based areas to target. Additionally, several social determinants of health are also supported and parallel research on multimorbidity risk. The effects of lifestyle factors for resilience among older adults is dependent on the type of multimorbidity measured. We conclude that the results have significant public health, program intervention, and clinical implications for healthy aging among persons coping with multimorbidity.

Defining and analyzing health system resilience in rural jurisdictions.

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.

A Unified Model of Resilience and Aging: Applications to COVID-19.

Drawing on multidisciplinary research focusing on a spectrum ranging from individual experience to structural system-level risk response and resilience, this article develops a rationale for a Unified Model of Resilience and Aging (UMRA). In response to a broad range of adversities associated with aging, it details the ways in which some individuals are able to bounce back better than others, or adapt better than expected, termed resilience. However, resilience and aging theoretical models have developed out of different disciplinary developments, ranging from individual levels to structural level complex systems, including several gerontological theoretical models addressing adaptation to life course and aging processes. The article reviews and synthesizes prior conceptual and theoretical work, and their empirical groundings, in order to develop an integrated resilience model with wide applications to aging-related problems including chronic illness, mental health, widowhood, poverty, caregiving burden, etc. The article focuses specifically on COVID-19 pandemic risk, response and resilience in order to specify applications of the UMRA, and to suggest avenues for future research and testing of theoretical axioms.

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States.

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.

Mainstreaming resilience analytics: 10 years after the Fukushima disaster.

Multiple events over the last decade, including the ongoing COVID-19 pandemic, demonstrate a global lack of preparedness for low probability but high consequence events. Following the evaluation of the Fukushima Daiichi nuclear disaster, these authors called for a change from a risk-oriented approach to a resilience-focused framework for managing such disruptions. Over the past five years, the field of resilience analytics has conceptualized further resilience frameworks within the context of infrastructure development; however, the practice of resilience planning is still lagging behind the theories developed in the literature. In this article, we consider the lessons learned from the Fukushima nuclear accident through the lens of newly developed resilience analytics and the ongoing COVID-19-related challenges. Integr Environ Assess Manag 2022;18:1551-1554. © 2022 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Adaptation, Transformation and Resilience in Healthcare Comment on "Government Actions and Their Relation to Resilience in Healthcare During the COVID-19 Pandemic in New South Wales, Australia and Ontario, Canada".

Adaptive capacity is a critical component of building resilience in healthcare (RiH). Adaptive capacity comprises the ability of a system to cope with and adapt to disturbances. However, "shocks," such as the current coronavirus disease 2019 (COVID-19) pandemic, can potentially exceed critical adaptation thresholds and lead to systemic collapse. To effectively manage healthcare systems during periods of crises, both adaptive and transformative changes are necessary. This commentary discusses adaptation and transformation as two complementary, integral components of resilience and applies them to healthcare. We treat resilience as an emergent property of complex systems that accounts for multiple, often disparately distinct regimes in which multiple processes (eg, adaptation, recovery) are subsumed and operate. We argue that Convergence Mental Health and other transdisciplinary paradigms such as Brain Capital and One Health can facilitate resilience planning and management in healthcare systems.

Assessment of the COVID-19 infection risk at a workplace through stochastic microexposure modeling.

BACKGROUND: The COVID-19 pandemic has a significant impact on economy. Decisions regarding the reopening of businesses should account for infection risks. OBJECTIVE: This paper describes a novel model for COVID-19 infection risks and policy evaluations. METHODS: The model combines the best principles of the agent-based, microexposure, and probabilistic modeling approaches. It takes into account specifics of a workplace, mask efficiency, and daily routines of employees, but does not require specific inter-agent rules for simulations. Likewise, it does not require knowledge of microscopic disease related parameters. Instead, the risk of infection is aggregated into the probability of infection, which depends on the duration and distance of every contact. The probability of infection at the end of a workday is found using rigorous probabilistic rules. Unlike previous models, this approach requires only a few reference data points for calibration, which are more easily collected via empirical studies. RESULTS: The application of the model is demonstrated for a typical office environment and for a real-world case. CONCLUSION: The proposed model allows for effective risk assessment and policy evaluation when there are large uncertainties about the disease, making it particularly suitable for COVID-19 risk assessments.

Prioritization of Resilience Initiatives for Climate-Related Disasters in the Metropolitan City of Venice.

Increases in the magnitude and frequency of climate and other disruptive factors are placing environmental, economic, and social stresses on coastal systems. This is further exacerbated by land use transformations, urbanization, over-tourism, sociopolitical tensions, technological innovations, among others. A scenario-informed multicriteria decision analysis (MCDA) was applied in the Metropolitan City of Venice integrating qualitative (i.e., local stakeholder preferences) and quantitative information (i.e., climate-change projections) with the aim of enhancing system resilience to multiple climate-related threats. As part of this analysis, different groups of local stakeholders (e.g., local authorities, civil protection agencies, SMEs, NGOs) were asked to identify critical functions that needs to be sustained. Various policy initiatives were considered to support these critical functions. The MCDA was used to rank the initiatives across several scenarios describing main climate threats (e.g., storm surges, floods, heatwaves, drought). We found that many climate change scenarios were considered to be disruptive to stakeholders and influence alternative ranking. The management alternatives acting on physical domain generally enhance resilience across just a few scenarios while cognitive and informative initiatives provided resilience enhancement across most scenarios considered. With uncertainty of multiple stressors along with projected climate variability, a portfolio of cognitive and physical initiatives is recommended to enhance resilience.

Governing biotechnology to provide safety and security and address ethical, legal, and social implications.

The field of biotechnology has produced a wide variety of materials and products which are rapidly entering the commercial marketplace. While many developments promise revolutionary benefits, some of them pose uncertain or largely untested risks and may spur debate, consternation, and outrage from individuals and groups who may be affected by their development and use. In this paper we show that the success of any advanced genetic development and usage requires that the creators establish technical soundness, ensure safety and security, and transparently represent the product's ethical, legal, and social implications (ELSI). We further identify how failures to address ELSI can manifest as significant roadblocks to product acceptance and adoption and advocate for use of the "safety-by-design" governance philosophy. This approach requires addressing risk and ELSI needs early and often in the technology development process to support innovation while providing security and safety for workers, the public, and the broader environment. This paper identifies and evaluates major ELSI challenges and perspectives to suggest a methodology for implementing safety-by-design in a manner consistent with local institutions and politics. We anticipate the need for safety-by-design approach to grow and permeate biotechnology governance structures as the field expands in scientific and technological complexity, increases in public attention and prominence, and further impacts human health and the environment.