Modeling critical infrastructure resilience under compounding threats: A systematic literature review

Multiple threat events may disrupt critical infrastructure functioning, thereby inhibiting the provision of essential goods and services to affected communities. It is currently unclear how modeling approaches have assessed critical infrastructure resilience when facing compounding (i.e., the COVID-...

詳細記述

書誌詳細
出版年:Progress in Disaster Science
主要な著者: Emily M. Wells, Mariel Boden, Ilana Tseytlin, Igor Linkov
フォーマット: 論文
言語:英語
出版事項: Elsevier 2022-10-01
主題:
オンライン・アクセス:http://www.sciencedirect.com/science/article/pii/S259006172200031X
その他の書誌記述
要約:Multiple threat events may disrupt critical infrastructure functioning, thereby inhibiting the provision of essential goods and services to affected communities. It is currently unclear how modeling approaches have assessed critical infrastructure resilience when facing compounding (i.e., the COVID-19 pandemic co-occurring with natural hazards) or cascading (i.e., landslides following wildland fires) threats. For both, connection across multiple domains of critical infrastructure are of crucial importance and modeling risk and resilience associated with complex threats has been proposed as a way forward in assessing and managing systemic risk and resilience. A systematic review is conducted to understand how critical infrastructure resilience was assessed in network science literature published between 2010 and 2021. The literature was classified based on phases of resilience (preparation, absorption, recovery, and adaptation) and system domains (physical, information, cognitive, social). Results indicate that literature has focused on absorption of compounding and cascading threats by critical infrastructure, particularly within the physical and information domains. Results also identified a potential gap in network science models' incorporation of the resilience phases of preparation and adaption, signifying a potential opportunity for network science methodologies to integrate all four phases into models of critical infrastructure resilience.
ISSN:2590-0617