Utilization of Crowdsourced Felt Reports to Distinguish High‐Impact from Low‐Impact Earthquakes Globally within Minutes of an Event

Abstract

Rapid assessment of an earthquake’s impact on the affected society is a crucial step in the early phase of disaster management, navigating the need for further emergency response measures. We demonstrate that felt reports collected via the LastQuake service of the European Mediterranean Seismological Center can be utilized to rapidly estimate the probability of a felt earthquake being high impact rather than low impact on a global scale. Our data‐driven, transparent, and reproducible method utilizing Bayes’ theorem and kernel density estimation provides results within 10 min for 393 felt events in 2021. Although a separation of high‐ and low‐impact events remains challenging, the correct and unambiguous assessment of a large portion of low‐impact events is a key strength of our approach. We consider our method as an inexpensive addition to the pool of earthquake impact assessment tools, one that is fully independent of seismic data and can be utilized in many populated areas on the planet. Although practical deployment of our method remains an open task, we demonstrate the potential to improve disaster management in regions that currently lack expensive seismic instrumentation.