A Review of the Technical and Socio-Organizational Components of Earthquake Early Warning Systems - Velazquez, Omar; Pescaroli, Gianluca; Cremen, Gemma; Galasso, Carmine (Frontiers in Earth Science, 2020)
Every year, natural hazards affect millions of people around the world, causing significant economic and life losses. The rapid progress of technology and advances in understanding of the highly complex physical phenomena related to various natural hazards have promoted the development of new disaster-mitigation tools, such as earthquake early warning (EEW) systems. However, there is a general lack of integration between the multi- and cross-disciplinary elements of EEW, limiting its effectiveness and applications for end users. This paper reviews the current state-of-the-art in EEW, exploring both the technical components (i.e., seismological and engineering) as well as the socio-organisational components (i.e., social science, policy, and management) of EEW systems. This includes a discussion of specific evidence from case studies of Italy, California, Japan and Mexico, where EEW systems have reached varying levels of maturity. Our aim is to highlight necessary improvements for increasing the effectiveness of the technical aspects of EEW in terms of their implications on operational, political/legal, social, behavioural and organisational drivers. Our analysis suggests open areas for research, associated with: 1) the information that needs to be included in EEW alerts to implement successful mitigation actions at both individual and organisational levels; 2) the need for response training to the community by official bodies, such as civil protection; 3) existing gaps in the attribution of accountability and development of liability policies involving EEW implementation; 4) the potential for EEW to increase seismic resilience of critical infrastructure and lifelines; 5) the need for strong organisational links with first responders and official EEW bodies; and 6) the lack of engineering-related (i.e., risk and resilience) metrics currently used to support decision making related to the triggering of alerts by various end users.