The U.S. Geological Survey-managed ShakeAlert (R) earthquake early warning system is the first public alerting system in the United States to provide rapid mass notification when an earthquake is detected. Although public alert delivery via mobile phones began in California in 2019 followed by Oregon and Washington in 2021, little is known about what might drive widespread implementation in at-risk institutional settings such as schools. For example, there has been limited research on how to best integrate earthquake early warning into existing emergency plans, alert systems, and drills to keep school children and personnel safe in an earthquake. To address this gap, in the spring of 2022, every school district superintendent in Alaska, California, Oregon, and Washington was sent a 15-min online survey. The survey assessed superintendent knowledge of ShakeAlert, preferences for alert messaging, and perceived opportunities and barriers to incorporating the system in schools. The results showed that superintendents had low awareness of ShakeAlert but held positive perceptions of the system's potential to enable life-saving protective actions. A major barrier to adoption included the perceived financial cost of implementing and maintaining the system. There were some statistically significant differences in state responses, and future research could investigate the specific needs of each state based on school district size and composition, hazard exposure, and earthquake experience. Together these findings can help inform targeted strategies to increase ShakeAlert adoption in schools and ultimately improve the safety of school children and staff during earthquakes.

ShakeAlert, the earthquake early warning (EEW) system for the West Coast of the United States, attempts to provides crucial warnings before strong shaking occurs. However, because the alerts are triggered only when an earthquake is already in progress, and the alert latencies and delivery times are platform dependent, the time between these warnings and the arrival of shaking is variable. The ShakeAlert system uses, among other public alerting platforms like a mobile phone operating system, smartphone apps, and the Federal Emergency Man-agement Agency Integrated Public Alert & Warning System (IPAWS). IPAWS sends Wireless Emergency Alerts (WEAs) informing people via their smartphones and other mobile devices about various events, such as natural hazards, child abductions, or public health information about COVID-19. However, little is known about the IPAWS delivery latencies. Given that people may have only a few seconds of notice after they receive an alert to take a protective action before they feel earthquake shaking, quantifying latencies is critical to understanding whether the IPAWS system is useful for EEW. In this study, we developed new methods to test the IPAWS dis-tribution system's performance, both with devices in a controlled environment and as well as with a 2019 community-based feedback form, in Oakland and San Diego County, California, respectively. The controlled environment test used mobile phones (including smart and non-smart phones) and associated devices to determine alert receipt times; the community research form had participants self-report their receipt times. By triangulating the data between the controlled test environment and the community research, we determined the latency statistics as well as whether the geofence (the geographic area where the alert was intended to be sent) held broadly. We found that the latencies were similar between the two tests despite the large differences in population sizes. WEA messages were received within a median time frame of 6-12 s, and the geofence held with only a few exceptions. We use this latency to assess how the system would have performed in two large earthquakes, the 1989 M6.9 Loma Prieta and 2019 M7.1 Ridgecrest earthquakes, which both occurred near our WEA test locations. Our analysis revealed that had IPAWS been available during those earthquakes, particularly Loma Prieta, it would have provided crucial seconds of notice that damaging shaking was imminent in some locations relatively far from the epicenter. Further, we find affordable non-smart phones can receive WEAs as fast as smartphones. Finally, our new method can be used for latency and geospatial testing going forward for IPAWS and other similar alerting systems.

In October 2019, California became the first state in the United States to fully activate a public earthquake early warning system-ShakeAlert (R)-managed by the U.S. Geological Survey. The system was subsequently rolled out in March 2021 in Oregon and May 2021 in Washington. Earthquake early warning (EEW) systems can provide seconds of notice to people and technological systems that shaking is imminent, but their effectiveness depends on recipients' expectations and actions as well as technical performance. To better understand these dependencies, we surveyed representative samples of adults in California (N= 1219), Oregon (N= 1020), and Washington (N = 1037) in February 2021. Most respondents had experienced earthquakes, but few had lived through violent shaking; most had not followed protective action guidance to Drop, Cover, and Hold On (DCHO) in earthquakes; and most reported no personal or social harm from prior earthquakes. Nevertheless, expectations and perceived usefulness of EEW were high, and higher still for those who expected alerts to be accurate and easy to use, expressed tolerance of missed and erroneous warnings, and expected to be affected by a damaging earthquake in their lifetime. Results suggest opportunities to better align public preferences and expectations with ShakeAlert operations. For example, some respondents preferred lower alerting thresholds than those proposed by government and scientists. Moreover, reported tolerance of warning errors was widespread, but respondents wanted explanations quickly, suggesting a need to further develop post-alert messaging. Findings from this study should be informative for future research on the co-evolution of experiences and expectations with EEW systems.

Earthquake early warning (EEW) systems are becoming increasingly available or are in development throughout the world. As these systems develop, it is important to provide evidence-based recommendations for protective action so people know how to protect themselves when they receive an alert. However, many factors need to be considered when developing contextually relevant and appropriate recommendations. We have reviewed earthquake injury reports, protective action and communication theories, and behavioral research to determine what factors can guide inquiry and decision making when developing protective action guidelines. Factors that emerge from relevant literature include: (1) social, cultural, and environmental context, such as which people are present, what their social roles are, and in what type of building they are located when an earthquake happens, (2) demographic and experiential variables, such as gender and age as well as previous history with earthquakes; and (3) magnitude and intensity that influence the duration and impacts of the earthquake itself. Although we examine data from around the world, we focus largely on evidence-based recommendations for the U.S. system, ShakeAlert, because it provides a timely case study for understanding how people receive and respond to EEW messages. In addition to synthesizing relevant literature, we recommend pathways forward for this interdisciplinary research community that explores EEW and its application around the world. Consistency in collecting and reporting injury data globally may assist in aligning this fragmented literature to develop a richer understanding of how demographic, cultural, seismic, engineering, and technological issues can be addressed to reduce human suffering due to earthquakes.

..........................................................................................................................................................1 The ShakeAlert Earthquake Early Warning System .................................................................................1 Earthquake Hazards in the Pacific Northwest ..........................................................................................4 Hazard Deaggregation ..................................................................................................................................5 Definition of Warning Times .........................................................................................................................7 Warning Times for Shallow Crustal Events ...............................................................................................8 Warning Times for Deep Instraslab Earthquakes ...................................................................................10 Warning Times for Offshore M 7–9 Megathrust Earthquakes ..............................................................13 The Current ShakeAlert Production System ..................................................................................14 The Future ShakeAlert Production System ....................................................................................17 Implications for EEW Users in the Pacific Northwest ...........................................................................21 Effects on Protective Actions and the ShakeAlert Warning Message ......................................23 Conclusions...................................................................................................................................................24 References Cited..........................................................................................................................................25 Appendix 1.....................................................................................................................................................29

The ShakeAlert earthquake early warning system is designed to automatically identify and characterize the initiation and rupture evolution of large earthquakes, estimate the intensity of ground shaking that will result, and deliver alerts to people and systems that may experience shaking, prior to the occurrence of shaking at their location. It is configured to issue alerts to locations within the West Coast of the United States. In 2018, ShakeAlert 2.0 went live in a regional public test in the first phase of a general public rollout. The ShakeAlert system is now providing alerts to more than 60 institutional partners in the three states of the western United States where most of the nation's earthquake risk is concentrated: California, Oregon, and Washington. The ShakeAlert 2.0 product for public alerting is a message containing a polygon enclosing a region predicted to experience modified Mercalli intensity (MMI) threshold levels that depend on the delivery method. Wireless Emergency Alerts are delivered for M 5+ earthquakes with expected shaking of MMI >= IV. For cell phone apps, the thresholds are M 4.5+ and MMI >= III. A polygon format alert is the easiest description for selective rebroadcasting mechanisms (e.g., cell towers) and is a requirement for some mass notification systems such as the Federal Emergency Management Agency's Integrated Public Alert and Warning System. ShakeAlert 2.0 was tested using historic waveform data consisting of 60 M 3.5+ and 25 M 5.0+ earthquakes, in addition to other anomalous waveforms such as calibration signals. For the historic event test, the average M 5+ false alert and missed event rates for ShakeAlert 2.0 are 8% and 16%. The M 3.5+ false alert and missed event rates are 10% and 36.7%. Real-time performance metrics are also presented to assess how the system behaves in regions that are well-instrumented, sparsely instrumented, and for offshore earthquakes.

First posted October 2, 2018 For additional information, contact: Earthquake Science Center-Pasadena Field OfficeU.S. Geological Survey525 South Wilson Ave.Pasadena, CA 91106-3212 The U.S. Geological Survey (USGS), along with partner organizations, has developed an earthquake early warning (EEW) system called ShakeAlert for the highest risk areas of the United States: namely, California, Oregon, and Washington. The purpose of the system is to reduce the impact of earthquakes and save lives and property by providing alerts to institutional users and the public. Using networks of ground-motion sensors and sophisticated computer algorithms, ShakeAlert can detect an earthquake seconds after it begins, calculate its location and magnitude, and estimate the resulting intensity of shaking. Alerts can then be sent to people and systems that may experience damaging shaking, allowing them to take appropriate protective actions. Depending on the user’s distance from the earthquake, alerts may be delivered before, during, or after the arrival of strong shaking.ShakeAlert is built on the foundation of the sensor networks and data processing infrastructure of the USGS-led Advanced National Seismic System. However, these networks were not originally designed for EEW; old equip­ment needs to be updated and new stations must be added to construct EEW-capable networks. The ShakeAlert data-processing infrastructure includes redundant servers that are geographically distributed at monitoring centers in Seattle, Washington, as well as Menlo Park, Berkeley, and Pasadena in California. Three data-processing layers collect raw ground-motion data from field stations (data layer), analyze these data to estimate the area and intensity of the resulting shaking (production layer), and publish alert products as appropriate for end users (alert layer). The alert layer can support thousands of institutional users and alert redistributors, but the USGS does not have the mission, infrastructure, or expertise to perform public notifications and is therefore recruiting technology enablers from the private sector. Additionally, ShakeAlert will coordinate with both public and private partners to accomplish consistent and ongoing public communication, education, and outreach.The estimated cost of completing the ShakeAlert infrastructure and sensor networks is \$39.4 million and has an estimated annual operation and maintenance cost of \$28.6 million per year. Building a highly reliable data telemetry infrastructure would cost another \$20.5 million and operating this telemetry system would add \$49.8 million per year; however, these costs could be reduced if project partners provide bandwidth on existing systems.