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Updated: Jun 27, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Ranking the risks from multiple hazards in a small community
Hua Li1, George E Apostolakis, Joseph Gifun
1Massachusetts Institute of Technology, Cambridge, MA 02139-4307, USA.
Abstract:
Natural hazards, human-induced accidents, and malicious acts have caused great losses and disruptions to society. After September 11, 2001, critical infrastructure protection has become a national focus in the United States and is likely to remain one for the foreseeable future. Damage to the infrastructures and assets could be mitigated through predisaster planning and actions. A systematic methodology was developed to assess and rank the risks from these multiple hazards in a community of 20,000 people. It is an interdisciplinary study that includes probabilistic risk assessment (PRA), decision analysis, and expert judgment. Scenarios are constructed to show how the initiating events evolve into undesirable consequences. A value tree, based on multi-attribute utility theory (MAUT), is used to capture the decisionmaker's preferences about the impacts on the infrastructures and other assets. The risks from random failures are ranked according to their expected performance index (PI), which is the product of frequency, probabilities, and consequences of a scenario. Risks from malicious acts are ranked according to their PI as the frequency of attack is not available. A deliberative process is used to capture the factors that could not be addressed in the analysis and to scrutinize the results. This methodology provides a framework for the development of a risk-informed decision strategy. Although this study uses the Massachusetts Institute of Technology campus as a case study of a real project, it is a general methodology that could be used by other similar communities and municipalities.
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