Abstract:Abstract:The resilience of critical infrastructure (CI) to extreme weather events (EWE) is one of the most demanding challenges for all stakeholders in modern society. Although partial risk reduction is feasible through the introduction and implementation of various risk mitigation measures (RMM), decision-makers at all decision-making levels are pressured to find ways to cope with the impending extreme weather and to have a thorough understanding of the EWE impacts on CI. This paper discusses how the value of… Show more
“…33 These indicators for “COVID-19 Mitigation” were characterized by risk mitigations in the context of disasters (proportionate, adequate, self-containment, global impact) and were modified as self-reported questions. 34 Examples: “I feel relief with the degree of technology measures on COVID-19,” “enough efforts rendered on fighting the pandemic,” “I agree to some good policies applied during the pandemic,” “there are available possibilities to contain the virus,” and “the community compliance measures for the pandemic.” With items scored using 5-point Likert scale from strongly disagree 1 to strongly agree 5 aimed to assess COVID-19 risk mitigation (outcome variable) based on the technology of health apps.…”
Background Technological innovations gained momentum and supported COVID-19 intelligence surveillance among high-risk populations globally. We examined technology surveillance using mobile thermometer detectors (MTDs), knowledge of App, and self-efficacy as a means of sensing body temperature as a measure of COVID-19 risk mitigation. In a cross-sectional survey, we explored COVID-19 risk mitigation, mobile temperature detectable by network syndromic surveillance mobility, detachable from clinicians, and laboratory diagnoses to elucidate the magnitude of community monitoring. Materials and Methods In a cross-sectional survey, we create in-depth comprehension of risk mitigation, mobile temperature Thermometer detector, and other variables for surveillance and monitoring among 850 university students and healthcare workers. An applied structural equation model was adopted for analysis with Amos v.24. We established that mobile usability knowledge of APP could effectively aid in COVID-19 intelligence risk mitigation. Moreover, both self-efficacy and mobile temperature positively strengthened data visualization for public health decision-making. Results The algorithms utilize a validated point-of-center test to ascertain the HealthCode scanning system for a positive or negative COVID-19 notification. The MTD is an alternative personal self-testing procedure used to verify temperature rates based on previous SARS-CoV-2 and future mobility digital health. Personal self-care of MTD mobility and knowledge of mHealth apps can specifically manage COVID-19 mitigation in high or low terrestrial areas. We found mobile usability, mobile self-efficacy, and app knowledge were statistically significant to COVID-19 mitigation. Additionally, interaction strengthened the positive relationship between self-efficacy and COVID-19. Data aggregation is entrusted with government database agencies, using natural language processing and machine learning mechanisms to validate and analyze. Conclusion The study shows that temperature thermometer detectors, mobile usability, and knowledge of App enhanced COVID-19 risk mitigation in a high or low-risk environment. The standardizing dataset is necessary to ensure privacy and security preservation of data ethics.
“…33 These indicators for “COVID-19 Mitigation” were characterized by risk mitigations in the context of disasters (proportionate, adequate, self-containment, global impact) and were modified as self-reported questions. 34 Examples: “I feel relief with the degree of technology measures on COVID-19,” “enough efforts rendered on fighting the pandemic,” “I agree to some good policies applied during the pandemic,” “there are available possibilities to contain the virus,” and “the community compliance measures for the pandemic.” With items scored using 5-point Likert scale from strongly disagree 1 to strongly agree 5 aimed to assess COVID-19 risk mitigation (outcome variable) based on the technology of health apps.…”
Background Technological innovations gained momentum and supported COVID-19 intelligence surveillance among high-risk populations globally. We examined technology surveillance using mobile thermometer detectors (MTDs), knowledge of App, and self-efficacy as a means of sensing body temperature as a measure of COVID-19 risk mitigation. In a cross-sectional survey, we explored COVID-19 risk mitigation, mobile temperature detectable by network syndromic surveillance mobility, detachable from clinicians, and laboratory diagnoses to elucidate the magnitude of community monitoring. Materials and Methods In a cross-sectional survey, we create in-depth comprehension of risk mitigation, mobile temperature Thermometer detector, and other variables for surveillance and monitoring among 850 university students and healthcare workers. An applied structural equation model was adopted for analysis with Amos v.24. We established that mobile usability knowledge of APP could effectively aid in COVID-19 intelligence risk mitigation. Moreover, both self-efficacy and mobile temperature positively strengthened data visualization for public health decision-making. Results The algorithms utilize a validated point-of-center test to ascertain the HealthCode scanning system for a positive or negative COVID-19 notification. The MTD is an alternative personal self-testing procedure used to verify temperature rates based on previous SARS-CoV-2 and future mobility digital health. Personal self-care of MTD mobility and knowledge of mHealth apps can specifically manage COVID-19 mitigation in high or low terrestrial areas. We found mobile usability, mobile self-efficacy, and app knowledge were statistically significant to COVID-19 mitigation. Additionally, interaction strengthened the positive relationship between self-efficacy and COVID-19. Data aggregation is entrusted with government database agencies, using natural language processing and machine learning mechanisms to validate and analyze. Conclusion The study shows that temperature thermometer detectors, mobile usability, and knowledge of App enhanced COVID-19 risk mitigation in a high or low-risk environment. The standardizing dataset is necessary to ensure privacy and security preservation of data ethics.
“…Based on the INTACT project co-founded by the European Union, Räikkönen et al ( 2017 ) focus on Risk Management Measures (RMM). In particular, the study contributes to the value creation of RMM, which is crucial for decision-making and for the development of strategies to prevent or reduce the impacts of extreme weather events.…”
Modern societies are increasingly dependent on the proper functioning of critical infrastructures (CIs). CIs produce and distribute essential goods or services, as for power transmission systems, water treatment and distribution infrastructures, transportation systems, communication networks, nuclear power plants, and information technologies. Being resilient becomes a key property for CIs, which are constantly exposed to threats that can undermine safety, security, and business continuity. Nowadays, a variety of approaches exist in the context of CIs’ resilience research. This paper provides a state-of-the-art review on the approaches that have a complete qualitative dimension, or that can be used as entry points for semi-quantitative analyses. The study aims to uncover the usage of qualitative research methods through a systematic review based on PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). The paper identifies four principal dimensions of resilience referred to CIs (i.e., techno-centric, organisational, community, and urban) and discusses the related qualitative methods. Besides many studies being focused on energy and transportation systems, the literature review allows to observe that interviews and questionnaires are most frequently used to gather qualitative data, besides a high percentage of mixed-method research. The article aims to provide a synthesis of literature on qualitative methods used for resilience research in the domain of CIs, detailing lessons learned from such approaches to shed lights on best practices and identify possible future research directions.
“…Most infrastructures, due to long life cycles that extend decades into the future, will be more and more likely to experience vulnerabilities due to climate change, which is expected to increase the magnitude and frequency of extreme events such as heatwaves, forest fires, floods, violent storms, and strong winds. Risk management for uncertain events caused by climate change and strengthening the resilience of infrastructure systems are high priorities for technical experts and scholars (Balston et al, 2017;Räikkönen et al, 2017) and of interest to governments and the EU (e.g., US Department of Homeland Security, 2012; Karagiannis et al, 2019) and the Intergovernmental Panel on Climate Change (IPCC, 2018). The IPCC (2018) has anticipated the infrastructural impacts of extreme weather events to be manifold.…”
Section: Climate Changementioning
confidence: 99%
“…In all Nordic countries, remote areas have historically suffered from a high frequency of lengthy electrical power failures because of the vulnerability of overhead power lines to weather events, especially windstorms, which has created an active political debate over protecting these infrastructures (Heidenstrøm & Throne-Holst, 2020;Räikkönen et al, 2017;Rinkinen, 2013;Silvast, 2017). Examining extreme winter events and electricity distribution in Finland, one study concluded that relevant risk mitigation should not only be valued in monetary terms and investment analyses (cf.…”
Section: Infrastructures and Vulnerabilities Caused By Climate Change In The Nordic Countriesmentioning
confidence: 99%
“…Examining extreme winter events and electricity distribution in Finland, one study concluded that relevant risk mitigation should not only be valued in monetary terms and investment analyses (cf. Karagiannis et al, 2019), but also in more qualitative valuations concerning the importance of safety, security, and the recognition of infrastructure interdependencies (Räikkönen et al, 2017).…”
Section: Infrastructures and Vulnerabilities Caused By Climate Change In The Nordic Countriesmentioning
This research note reviews recent literature on the vulnerability of critical infrastructures caused by climate change with a focus on the Nordic countries. We integrate literature from three research areas: the role of critical infrastructures in the functioning of society, infrastructural vulnerabilities, and the long-term impacts of climate change. Focusing on climate change adaptation in the Nordic countries as a pivotal case, we discuss the mutually constitutive interrelationships between these three areas. The studies reviewed bring together social science and humanities research on infrastructure systems, their vulnerabilities, and climate change. By highlighting interdisciplinary perspectives on infrastructures, climate change, and societal security, this research note discusses a Nordic model of infrastructure provision and links the Nordic debate to a burgeoning European discussion on the role of the social sciences and humanities in addressing societal challenges related to climate change and the role of infrastructures in providing welfare.
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