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Published November 2020 | Published
Journal Article Open

Developing post-alert messaging for ShakeAlert, the earthquake early warning system for the west coast of the United States of America

Abstract

As ShakeAlert, the earthquake early warning system for the West Coast of the U.S., begins its transition to operational public alerting, we explore how post-alert messaging might represent system performance. Planned post-alert messaging can provide timely, crucial information to both emergency managers and ShakeAlert operators as well as calibrate expectations among various publics or public user groups and inform their responses to future alerts. There is a concern among the scientists and emergency managers that false alerts may negatively impact trust in the system, so quickly disseminated post-alert messages are necessary. For a new early warning system, such as ShakeAlert, this is particularly relevant given that the potentially affected population is likely to be unfamiliar with this system. We address this concern in six steps: (1) assessment of ShakeAlert performance to date, (2) characterization of human behavior and response to earthquake alerts, (3) presentation of a decision tree for issuing post-alert messages, (4) design of a critical set of post-alert messaging scenarios, (5) elaboration of these scenarios with message templates for a variety of communication channels and (6) development of a typology of earthquake alerts. We further explore methods for monitoring and evaluating ShakeAlert post-alert messaging, for continuous improvement to the system.

Additional Information

© 2020 Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Received 9 September 2019, Revised 28 May 2020, Accepted 5 June 2020, Available online 27 June 2020. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. We thank our USGS internal reviewers, Dr. Anne Wein and Dr. Elizabeth Cochran, for their insights which greatly improved this article. We also thank Dr. Andrea Llenos, Dr. Stephen Hickman, and Shane Detwiler at the USGS for further contributions to this article. We also thank our external reviewers for their contributions to this work. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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August 20, 2023
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