Estimating economic loss from cascading infrastructure failure: a perspective on modelling interdependency (original) (raw)
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Infrastructures are needed for maintaining functionality and stability of society, while being put under substantial stresses from natural or man-made shocks. Since avoiding shock is impossible, increased focus is given to infrastructure resilience, which denotes the ability to recover and operate under new stable regimes. This paper addresses the problem of estimating, quantifying and planning for economic resilience of interdependent infrastructures, where interconnectedness adds to problem complexity. The risk-based economic input–output model enterprise, a useful tool for measuring the cascading effects of interdependent failures, is employed to introduce a framework for economic resilience estimation. We propose static and dynamic measures for resilience that confirm to well-known resilience concepts of robustness, rapidity, redundancy, and resourcefulness. The quantitative metrics proposed here (static resilience metric, time averaged level of operability, maximum loss of functionality, time to recovery) guide a preparedness decision making framework to promote interdependent economic resilience estimation. Using the metrics we introduce new multi-dimensional resilience functions that allow multiple resource allocation scenarios. Through an example problem we demonstrate the usefulness of these functions in guiding resource planning for building resilience.
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The functioning of communities and industries depends on the infrastructure network. Daily activities (such as production, shipping, supply chain, etc., for industries and commuting to work, business, schooling, etc., for communities) are performed efficiently with the help of the infrastructure network. It is vital for the infrastructure to function efficiently at all times. However, during disasters, either manmade or natural, the functioning or serviceability of the infrastructure could be severely affected. This in turn has an impact on the activities/services of communities and industries. These activities and services contribute socially and economically. When their functioning is affected and usually reduced in the case of disasters, their social and economic contribution is reduced. This reduction can be assessed as social and economic impact on communities and industries due to reduction in serviceability of the infrastructure network. This paper presents a framework that establishes a relationship between the services and activities of communities and industries and infrastructure. The paper also provides a unique approach to assess social and economic impacts due to serviceability reduction of infrastructure after floods. The framework is a step towards providing valuable information for decision making during the quick recovery phase after disaster.
The functionality of modern cities relies heavily on interdependent infrastructure systems such as those for water, power, and transportation. Disruptions often propagate within and across physical infrastructure networks and result in catastrophic consequences. The reaction of communities to disasters (e.g., seeking alternative resource sources) may further transfer and aggravate the burden on surviving infrastructures, which may facilitate cascading secondary disruptions. Hence, a holistic analysis framework that integrates infrastructure interdepen-dencies and human community behaviors is needed to evaluate a city's vulnerability to disruptions and to assess the impact of a disaster. To this end, we develop a game-theoretical equilibrium model in a multilayer infrastructure network to systematically investigate the mutual influence between the infrastructures and the communities. Two types of infrastructure failure patterns are formulated to capture general network interdependencies; network equilibrium is extended into infrastructure and community systems to address redistribution of demand for life-supporting resources; the societal impact of disasters is estimated based on communities' resource demand loss, cost increase, as well as total infrastructure failures. A real-world case study based on Maiduguri, Nigeria, is implemented to demonstrate the proposed model and algorithm , and to reveal insights.