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.
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Health Policy Plan
January 2025
University of Cape Town, Health Systems and Policy Division and London School of Hygiene and Tropical Medicine, Falmouth Road, Observatory, Cape Town 7925, South Africa.
Understanding health systems as comprising interacting elements of hardware and software acknowledges health systems as complex adaptive systems (CAS). Hardware represents the concrete components of systems, whereas software represents the elements which influence actions and underpin relationships, such as processes, values and norms As a specific call for research on health system software was made in 2011, we conducted a qualitative scoping review considering how and for what purpose the concept has been used since then. Our overall purpose was to synthesise current knowledge and generate lessons about how to deepen research on, and understanding of, health system software.
View Article and Find Full Text PDFIntroduction: Research has consistently shown that the prevalence of burnout symptoms (such as emotional and physical exhaustion, cynicism, or lack of interest in schoolwork, the sense of incompetence, or the feeling that you cannot be effective) in medical students is greater than the prevalence in the general population. Students with preexisting anxiety, depression, mood disorder or other psychological distress are more vulnerable to burnout. It is estimated that at least half of U.
View Article and Find Full Text PDFJ Environ Manage
January 2025
School of Environment, Tsinghua University, Beijing, 100084, China; Jiangsu Collaborative Innovation Center of Technology and Material of Water Treatment, Suzhou University of Science and Technology, Suzhou, 215009, China. Electronic address:
Urban flooding poses a significant risk to cities worldwide, exacerbated by increasing urbanization and climate change. Effective flood risk management requires comprehensive assessments considering the complex interaction of social, economic, and environmental factors. This study developed an innovative Urban Flood Risk Index (FRI) to quantify and assess flood risk at the sub-catchment level, providing a tool for evidence-based planning and resilient infrastructure development.
View Article and Find Full Text PDFRev Gaucha Enferm
January 2025
Universidade Estadual de Maringá. Programa de Pós-Graduação em Enfermagem. Departamento de Enfermagem. Maringá, Paraná, Brasil.
Objective: To analyze the association between sociodemographic characteristics, level of perceived stress and resilience with family functioning of immigrants in Brazil.
Method: Cross-sectional study with 122 immigrants living in a municipality in southern Brazil. Data collected in 2021, using questions for characterization, Family Cohesion and Adaptability, Resilience and Perceived Stress Assessment Scale.
Chaos
January 2025
Classe di Scienze, Scuola Normale Superiore, Piazza dei Cavalieri 7, 56126 Pisa, Italy.
Modeling how a shock propagates in a temporal network and how the system relaxes back to equilibrium is challenging but important in many applications, such as financial systemic risk. Most studies, so far, have focused on shocks hitting a link of the network, while often it is the node and its propensity to be connected that are affected by a shock. Using the configuration model-a specific exponential random graph model-as a starting point, we propose a vector autoregressive (VAR) framework to analytically compute the Impulse Response Function (IRF) of a network metric conditional to a shock on a node.
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