A dynamic Bayesian network‐based emergency decision‐making framework highlighting emergency propagations: Illustrated using the Fukushima nuclear accidents and the Covid‐19 pandemic
Yinan Cai,Michael W. Golay +1 more
Reads0
Chats0
TLDR
In this paper , the authors developed a framework based upon dynamic Bayesian networks in order to simulate emergency scenarios and support corresponding decisions, highlighting the importance of emergency propagation, which is a critical factor often ignored by decisionmakers.Abstract:
When facing public emergencies, human societies need to make decisions rapidly in order to mitigate the problems. However, this process can be difficult due to complexity of the emergency scenarios and lack of systematic methods for analyzing them. In the work reported here, we develop a framework based upon dynamic Bayesian networks in order to simulate emergency scenarios and support corresponding decisions. In this framework, we highlight the importance of emergency propagation, which is a critical factor often ignored by decisionmakers. We illustrate that failure of considering emergency propagation can lead to suboptimal mitigation strategies. By incorporating this critical factor, our framework enables decisionmakers to identify optimal response strategies minimizing emergency impacts. Scenarios developed from two public emergencies: the 2011 Fukushima nuclear power plant accidents and the Covid‐19 pandemic, are utilized to illustrate the framework in this paper. Capabilities of the framework in supporting decision making in both events illustrate its generality and adaptability when dealing with complex real‐world situations. Our analysis results reveal many similarities between these two seemingly distinct events. This indicates that seemingly unrelated emergencies can share many common features beyond their idiosyncratic characteristics. Valuable mitigation insights can be obtained by analyzing a broad range of past emergencies systematically.read more
Citations
More filters
Journal ArticleDOI
A copula-based method of risk prediction for autonomous underwater gliders in dynamic environments.
TL;DR: In this paper , a Gaussian copula was employed to measure correlated dependencies among identified risk factors, and the dependence analysis and CBN inference were performed to assess the risk level of vehicle loss given various environmental observations.
Journal ArticleDOI
A dynamic emergency decision support model for emergencies in urban areas
Linghang Meng,Wuyi Cheng +1 more
TL;DR: In this paper , a dynamic emergency decision-support model considering the cascade effect is proposed, which divides the whole process of urban emergency development into several time slices, and each time slice describes a cascading process.
References
More filters
Journal ArticleDOI
Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV-2)
TL;DR: It is estimated that 86% of all infections were undocumented before the 23 January 2020 travel restrictions, which explains the rapid geographic spread of SARS-CoV-2 and indicates that containment of this virus will be particularly challenging.
Journal ArticleDOI
The reproductive number of COVID-19 is higher compared to SARS coronavirus.
TL;DR: The authors' review found the average R0 for 2019-nCoV to be 3.28, which exceeds WHO estimates of 1.4 to 2.5, and is higher than expected.
Journal ArticleDOI
Fair Allocation of Scarce Medical Resources in the Time of Covid-19.
Ezekiel J. Emanuel,Govind Persad,Ross E.G. Upshur,Beatriz Thomé,Michael Parker,Aaron Glickman,Cathy Zhang,Connor W. Boyle,Maxwell J. Smith,James P. Phillips +9 more
TL;DR: Allocating Scarce Medical Resources for Covid-19 The Covd-19 pandemic has already stressed health care systems throughout the world, requiring rationing of medical equipment and care.
Journal ArticleDOI
Risk assessment and risk management: Review of recent advances on their foundation
TL;DR: A review of advances in risk assessment and management, with a special focus on the fundamental ideas and thinking on which these advances are based, and reflects on where further development of the risk field is needed and should be encouraged.
Journal ArticleDOI
Overview on Bayesian networks applications for dependability, risk analysis and maintenance areas
TL;DR: A bibliographical review over the last decade is presented on the application of Bayesian networks to dependability, risk analysis and maintenance and an increasing trend of the literature related to these domains is shown.
Related Papers (5)
Challenges to probabilistic risk assessment of nuclear power plants
Elnara Nasimi,Hossam A. Gabbar +1 more