Characterizing Infrastructure Resilience in Disasters Using Dynamic Network Analysis of Consumers' Service Disruption Patterns

Abstract

This study proposes a network analysis framework for characterizing infrastructure resilience in the aftermath of disasters through the use of consumers' service disruption information. In the presented framework, the notion of "peers” is used to construct the network models of consumers experiencing service disruption in the aftermath of a disaster to understand the type and extent of infrastructure damages and specify disruption patterns. Data related to electricity disruption in Bhaktapur, Nepal, in the aftermath of the 2015 Gorkha Earthquake is used to construct the network models of consumers' networks at different points in time in the aftermath of the disaster. The created models are then used in network analysis for examining the network topological characteristics (such as clustering) and specifying the attributes of service disruption. The contribution of this paper lie in: (i) the development and validation of a novel network from disruption information, (ii) identify the extent of infrastructure disruption, type of damage, and recoverability from changes in network topology over time.