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|Title:||Assessing socioeconomic impacts of cascading infrastructure disruptions using the capability approach|
|Authors:||University of Illinois at Urbana-Champaign. Department of Civil and Environmental Engineering.|
United States. Office of the Assistant Secretary of the Army for Acquisition, Logistics, and Technology.
Wang, Yi (Victor)
Hurt, Tina M.
Hartman, Ellen R.
Myers, Natalie R. D.
Infrastructure (Economics) – Mathematical models Emergency management
Cities and towns
United States – Armed Forces – Stability operations Capability approach
Human-Infrastructure System Assessment (HISA)
|Publisher:||Construction Engineering Research Laboratory (U.S.)|
Engineer Research and Development Center (U.S.)
Abstract: U.S. Army doctrine requires that commanders understand, visualize, and describe the infrastructure component of the Joint Operating Environment to accomplish the Army’s missions of protecting, restoring, and developing infrastructure. 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 net-works and result in catastrophic consequences. The reaction of communities to disasters may further transfer and aggravate the burden and facilitate cascading secondary disruptions. Hence, a holistic analysis framework that integrates infrastructure interdependencies and community behaviors is needed to evaluate vulnerability to disruptions and to assess the impact of a disaster. The research for Human-Infrastructure System Assessment (HISA) for Military Operations adopts the Capability Approach (CA) to measure and predict the impact of potential infrastructural interdictions on the City of Maiduguri, Borno State, Nigeria. With the CA, 10 capabilities are identified to describe the well-being levels of Maiduguri. To quantify these 10 capabilities, 16 indicators were chosen to represent them. These indicator justifications provide the rationale for choosing the indicators for the corresponding capabilities and predictive modeling. Developing probabilistic predictive models of the indicators (or their indices) allows analysis of social well-being in relationship to cascading infrastructure failure.
|Rights:||Approved for public release; distribution is unlimited.|
|Appears in Collections:||Technical Report|
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|ERDC-CERL-TR-16-15-revised.pdf||8.05 MB||Adobe PDF|