A multi-attribute method for ranking the risks from multiple hazards in a small community

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 pre-disaster planning and actions. A systematic method has been developed to assess and rank the risks from these multiple hazards in a small community of 20,000 people. It is an interdisciplinary study that includes probabilistic risk assessment, 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, is used to capture the decision maker's preferences about the impacts on the infrastructures and other assets. The risks from random failures are ranked according to their Expected Performance Index values, which is the product of frequency, probability, and consequence of a scenario. Risks from malicious acts are ranked according to their Performance Index values 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 method provides a framework for the development of a risk-informed decision strategy. Although this study uses the Massachusetts Institute of Technology campus as a test-bed, it is a general methodology that could be used by other similar communities and municipalities.