Rapid Public Information and Situational Awareness After the November 26, 2019, Albania Earthquake: Lessons Learned From the LastQuake System

Abstract

The use of LastQuake information system, its app, the associated Twitter account and to a lesser extent the EMSC’s websites have been analysed for the 7-days following the Nov. 26, 2019 M6.4 Albania destructive earthquake to evaluate what can be improved and how crowdsourcing of information and monitoring of both use and absence of use of the app can contribute to rapid situational awareness. The mainshock and its numerous felt aftershocks triggered a strong public desire for information which in turn led to rapid and massive adoption of the LastQuake app by up to 5% of the country’s population. The constant flow of new app users created a stress test of the app’s crowdsourcing features and led to errors in the association of felt reports with their appropriate earthquake. However these errors had no identifiable impact supporting the conclusion that the curation mechanisms currently in place are efficient. The rapid succession of felt aftershocks contributed to these errors by making information related to the mainshock difficult to access within hours of its occurrence, especially for new users who were not attuned to the app. This revealed that prioritization of information within the app layout is lacking and is an important requirement during these kinds of events. LastQuake has been shown to be a powerful tool for rapid situational awareness. The possibility of damage was detected within 8 min of the mainshock earthquake by a lack of LastQuake app activity close to the epicenter. This possibility was then gradually strengthened as new data became available and was finally confirmed by the reception of the first geo-located pictures of structural damage and building collapse within 60-70 min. Direct exchanges on Twitter were appreciated by eyewitnesses and were reported to reduce their anxiety. Questions mainly focused on the possible evolution of the seismicity. Attempts to debunk prediction claims were difficult and we report on how this could be eased and possibly made more efficient by the use of a clear concise, pre-prepared statement in the local language explaining the state of scientific knowledge and the difference between prediction, early warning or forecasts.