The HayWired Scenario—Earthquake Early 

Warning Forecast and Potential Hazard 

Mitigation Actions

By Jennifer A. Strauss,Anne M. Wein,Jamie L. Jones, and Douglas D. Given

Chapter W of

The HayWired Earthquake Scenario—Societal Consequences

Edited by Shane T. Detweiler and Anne M. Wein

Scientific Investigations Report 2017–5013–R–W

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

DAVID BERNHARDT, Secretary

U.S. Geological Survey

James F. Reilly II, Director

U.S. Geological Survey, Reston, Virginia: 2019

For more information on the USGS—the Federal source for science about the Earth, its natural and living 

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Although this information product, for the most part, is in the public domain, it also may contain copyrighted materials 

as noted in the text. Permission to reproduce copyrighted items must be secured from the copyright owner.

Suggested citation:

Strauss, J.A., Wein, A.M., Jones, J.L., and Given, D.D., 2019, The HayWired scenario—Earthquake early warning 

forecast and potential hazard mitigation actions, chap. W of Detweiler, S.T., and Wein, A.M., eds., The HayWired 

earthquake scenario—Societal consequences: U.S. Geological Survey Scientific Investigations Report 

2017–5013–R–W, 21 p., https://doi.org/10.3133/sir20175013V3.

ISSN 2328-0328 (online)
iii

Contents

Abstract...........................................................................................................................................................1

Introduction.....................................................................................................................................................1

ShakeAlert Time Estimation for the HayWired Scenario ........................................................................2

ShakeAlert Can Prompt Automated Controls ............................................................................................5

Elevator Systems...................................................................................................................................7

Transportation Systems .......................................................................................................................8

ShakeAlert Can Prompt Protective Actions ............................................................................................10

Hospitals and Injuries.........................................................................................................................10

Drop, Cover, and Hold On ...................................................................................................................12

ShakeAlert and Aftershocks ......................................................................................................................12

Actions Discussed Elsewhere in the Literature .....................................................................................17

Conclusion.....................................................................................................................................................18

Acknowledgments.......................................................................................................................................18

References....................................................................................................................................................18

Figures

1. Map of the San Francisco Bay region, California, showing contours of earthquake

early warning time estimates relative to secondary wave arrival for the hypothetical

moment-magnitude-7.0 mainshock of the HayWired earthquake scenario on the

Hayward Fault ...............................................................................................................................4

2. Map of the San Francisco Bay region, California, showing ShakeAlert earthquake

early warning time estimates overlain with population density information for the

hypothetical moment-magnitude-7.0 mainshock of the HayWired earthquake

scenario on the Hayward Fault ..................................................................................................6

3. Maps of the San Francisco Bay region California, showing U.S. Geological Survey

ShakeCast shaking damage estimate for the Bay Area Rapid Transit system at the

time of the hypothetical April 18, 2018, moment-magnitude-7.0 mainshock of the

HayWired earthquake scenario on the Hayward Fault ..........................................................9

4. Schematic illustration of Bay Area Rapid Transit train locations along the systems

tracks at the time of the hypothetical moment-magnitude-7.0 mainshock of the

HayWired earthquake scenario on the Hayward Fault in the San Francisco Bay

region, California. ........................................................................................................................10

5. Map of the San Francisco Bay region, California, showing the location of criticalcare facilities and the number of beds that they can accommodate, overlain with

earthquake early warning time estimates for the hypothetical moment-magnitude7.0 mainshock of the HayWired earthquake scenario on the Hayward Fault ..................11

6. U.S. Geological Survey ShakeMap of the San Francisco Bay region, California,

for the moment-magnitude-5.6 Fairfield aftershock of the hypothetical HayWired

scenario earthquake sequence on the Hayward Fault on April 29, 2018, at

11:13 p.m.......................................................................................................................................13
iv

 7. U.S. Geological Survey ShakeMap of the San Francisco Bay region, California, for

Tables

1. Estimates for earthquake early warning times, relative to secondary-wave arrival, 

 and peak shaking intensities at select locations for the hypothetical momentmagnitude-7.0 mainshock of the HayWired earthquake scenario.......................................3

2. Number of elevators and percentage of riders in the San Francisco Bay region, 

California, that could use ShakeAlert to remain at a floor and (or) stop at the next 

floor to avoid entrapment of passengers in transit during power outage or damage at 

the site during the hypothetical moment-magnitude-7.0 mainshock of the HayWired 

earthquake scenario. ...................................................................................................................8
The HayWired Earthquake Scenario—Societal Consequences

Edited by Shane T. Detweiler and Anne M. Wein

Scientific Investigations Report 2017–5013–R–W

[Also see https://doi.org/10.3133/sir20175013 ]

Chapter W

The HayWired Scenario—Earthquake Early Warning 

Forecast and Potential Hazard Mitigation Actions

By Jennifer A. Strauss,1 Anne M. Wein,2 Jamie L. Jones,2 and Douglas D. Given2

Abstract

The HayWired scenario is a hypothetical earthquake 

sequence that begins with a moment magnitude (Mw) 7.0 

earthquake (mainshock) occurring on April 18, 2018, at 

4:18 p.m. on the Hayward Fault in the east bay part of the 

San Francisco Bay region, California. In the mainshock, the 

Hayward Fault ruptures along 86 kilometers (km)—from 

beneath San Pablo Bay southeast to the City of Fremont—

rattling the greater San Francisco Bay region during the 

30 seconds of sustained shaking. Using this scenario, the 

impacts of earthquake early warning (EEW) information 

and triggered automated controls are explored. EEW is the 

rapid detection of earthquakes, real-time assessment of the 

shaking hazard, and notification of people before the seismic 

waves that cause shaking arrive at their location. To assess 

the utility and efficacy of EEW for a significant earthquake 

in the San Francisco Bay region, alert times were calculated 

for the mainshock of the HayWired scenario. EEW alert times 

throughout the bay region were estimated for the mainshock 

based on expected performance of the ShakeAlert system, 

then mapped against shaking intensities, and used to envision 

plausible responses and mitigation actions. Less than 15 km 

from the epicenter (for example, in the cities of Oakland 

and Berkeley), strong shaking would arrive before the alert. 

However, outside of this “no-warning zone,” alerts could 

have widespread positive effects in the densely built urban 

environment. The most notable benefit for individuals is the 

possible reduction in injuries resulting from people having 

more time to take the self-protective “drop, cover, and hold 

on” (DCHO) actions. We summarize an initial estimate of the 

potential benefit of ShakeAlert and DCHO in the HayWired 

scenario, as well as assessments of elevator, transit, and 

hospital responses to highlight how prevention of cascading 

failures of lifeline infrastructure systems (such as highways, 

rail systems, telecommunications, and electric grids) is 

important for resiliency during and after the rupture. The 

HayWired scenario invites us to take a step back and assess 

both the built environment’s possible response to disasters 

of this scale and our own preparedness in a situation where 

we might not be able to rely on the communication and other 

systems of our interconnected, “wired” world.

Introduction

The HayWired scenario is a hypothetical yet scientifically 

realistic depiction of an earthquake sequence that begins 

with a moment magnitude (Mw) 7.0 earthquake (mainshock) 

occurring on Wednesday April 18, 2018, at 4:18 p.m. on the 

Hayward Fault in the east bay part of the San Francisco Bay 

region, California. The mainshock begins beneath the City 

of Oakland and ruptures 86 kilometers (km) of the fault—

north to beneath San Pablo Bay and southeast to the City of 

Fremont. During the approximately 30 seconds of sustained 

shaking, people and structures throughout much of the greater 

San Francisco Bay region are rattled, and the fault in some 

places is offset by more than 2 meters (m), soils liquefy, and 

landslides occur. Afternoon rush hour in the bay region is in 

full swing by 4:00 p.m., and many people would be taking an 

elevator, sitting on a train, or on roads and bridges on their 

way home from work. Others would still be in their offices, 

at after-school activities, running errands, or at home. Family 

members could be in very different locations in the bay region 

during their afternoon commute times. This scenario allows 

readers to envision the physical, infrastructural, and societal 

consequences of the rupture.

Chapters in U.S. Geological Survey (USGS) Scientific 

Investigations Report (SIR) 2017–5013–A–H (v. 1) outlined 

the science behind the models used in the HayWired scenario 

and the implications to the ground, such as fault rupture, 

shaking intensities, landslides, and zones of liquefaction (areas 

where soils become liquid-like during shaking). Chapters 

in SIR 2017–5013–I–Q (v. 2) assessed ordinary building 

performance (Seligson and others, 2018), building code 

performance (Porter, 2018a), and tall-building performance 

(Almufti and others, 2018). Building codes are said to 

support “life safety,” but there is a common misconception 

that this means buildings will also be habitable and useable 

1

University of California at Berkeley, Seismology Lab.

2

U.S. Geological Survey.
2 The HayWired Earthquake Scenario—Societal Consequences

in the aftermath of a design-level earthquake (Porter, 2018a). 

The reality is that many people and businesses will likely 

be displaced (Applied Technology Council, 2012; Johnson 

and others, in prep. [planned to be published as part of this 

volume]). Building codes aim to preserve the lives of those 

inside them, but perhaps we can do better than that in the 

future (Porter, 2016). New engineering designs and risk 

mitigation measures put in place now can increase resiliency 

and recovery. 

USGS and a coalition of State and university partners 

are developing and testing an earthquake early warning 

(EEW) system called ShakeAlert (https://www.shakealert.org) 

to provide a few seconds of earthquake early warning to 

reduce risk and increase resiliency, not just for utilities and 

infrastructure, but also for people and organizations. The 

ShakeAlert system continues to evolve, and pilot groups, 

technology enablers, licensed operators, and stakeholders 

in the transportation, utility, healthcare, education, and 

emergency management sectors have been engaged in 

developing hazard-mitigation best practices and strategies in 

response to alerts of shaking. In the spirit of HayWired’s focus 

on interconnectivity, and the authors’ work with ShakeAlert 

stakeholders, this chapter is meant to outline possibilities 

for uses and benefits of the ShakeAlert system based on data 

researched for the scenario and priority focus areas from 

stakeholders. It is not intended as a rigorous cost-benefit 

assessment; the numbers of affected people or systems 

discussed should not be taken as absolutes. The discussion in 

this chapter is best used as a planning tool to probe the extent 

of what is possible for ShakeAlert.

We live in a “wired,” interconnected world. When the 

first thorough cost-benefit study of the impacts of EEW was 

done in California (Holden and others, 1989), automated 

controls were not an accepted part of daily life. Now, we 

cannot imagine a world without machines helping with 

ordinary, daily tasks. In 1989, planning for the unknown was 

often a part of life, and distribution of goods and services was 

handled differently. For example, before the constant presence 

of cell phones, many families had a plan of where to meet 

if, say, people went to different stores in a mall. Emergencyresponse groups historically had access to warehouses of 

supplies in case of dire need. Now, businesses rely on justin-time delivery to fill stores, and on-site inventories have 

been reduced. An earthquake can temporarily interfere with 

our constant interconnectedness, so having a plan in place 

before an earthquake strikes is even more crucial in today’s 

world. The hypothetical ShakeAlert responses discussed in 

this chapter do not cover the full range of what is possible 

but instead give a rational flavor of what we could expect 

to unfold during an earthquake like the HayWired scenario 

mainshock and provide a framework to engender discussion 

on new strategies and responses. (For other resources, also see 

Allen and others, 2009; Fujinawa and Noda, 2013; Gasparini 

and others, 2007; Goltz and Flores, 1997; Heaton and others, 

1985; Strauss and Allen, 2016.)

ShakeAlert Time Estimation for the 

HayWired Scenario

EEW provides an alert that an earthquake has occurred 

and may forecast the final magnitude and severity of shaking 

at a location. EEW has been deployed in at least eight 

countries—China, Japan, Mexico, Romania, Switzerland, 

Taiwan, and Turkey (National Research Council, 2011) and 

the United States, South Korea and Israel. Mexico began 

providing limited public alerts to certain cities within the 

country in 1993. Japan’s nationwide system has provided 

alerts for the safety of the general public since 2007. Taiwan 

implemented nationwide public alerting in 2016.

EEW has been in active development in the United 

States since 2006 (Allen, 2011; Burkett and others, 2014), 

in a collaborative group including the USGS, the California 

Institute of Technology, the University of California at 

Berkeley, the University of Oregon, and the University of 

Washington. This public EEW system is called ShakeAlert 

and operates on the West Coast of the United States. The 

ShakeAlert group also works with State, public, and private 

partners to assess dissemination, resiliency and hazard 

mitigation, and implementation strategies that can make use of 

the advanced warnings that EEW can provide.

The ShakeAlert system, as currently designed, will 

generate public alerts (in the future) for earthquakes greater 

than magnitude (M) 4.5 and will deliver alerts to regions 

estimated to experience expected Modified Mercalli Intensities 

(MMI) greater than or equal to II (that is, felt shaking). The

estimated regions are octagonal contours and thus provide an

average intensity estimate for the area, so actual felt shaking

could vary on a more local scale. Technical users, which could

include transportation and utility sectors, could receive more

detailed and lower magnitude threshold alerts, as well as alerts

for lower magnitude earthquakes. California public alerting

was activated just prior to publication of this chapter. Public

alert dissemination began earlier in the Los Angeles region

through the use of a cell phone application, and will be tested

in California by the end of 2019.

The ShakeAlert system uses a network approach, 

where the first seismic wave (the primary, or P-wave), which 

radiates from the earthquake hypocenter at speeds of 

5–8 kilometers per second (km/s), is detected by nearby 

seismic sensors. Seismic sensors relay information about the 

P-wave to data centers, where algorithms compute the

probable earthquake location and magnitude, and estimate the

shaking intensities that will result. This information is used to

generate an EEW alert for the impacted region that is sent to

people and devices electronically. The goal is to distribute the

alerts before the slower moving (3–5 km/s), yet generally

stronger and more damaging, secondary wave (or S-wave) and

following series of surface waves arrive at a given location.

Because electronic communication travels much more rapidly

than seismic energy, advanced warning can be possible even
Chapter W. Earthquake Early Warning Forecast and Potential Hazard Mitigation Actions 3

in regions where critical infrastructure and population centers 

are located close to the rupturing fault (as is the case in the 

HayWired scenario).

ShakeAlert (Cochran and others, 2017; Given and others, 

2018; Kohler and others, 2017) relies on an array of sensors 

throughout the West Coast that relay information back to a 

central site for analysis and alert distribution. The amount 

of warning provided depends on many factors, including the 

time it takes for the fault rupture to grow (large ruptures can 

take several to tens of seconds to grow), the shaking intensity 

threshold used to issue an alert, how often alerts are updated, 

time to detect the growing rupture, and time to distribute an 

alert to an end user or to engage an automated control, as 

well as the user’s distance from the earthquake hypocenter. 

The amount of shaking a user experiences is related to their 

distance from the part of the fault that ruptures and site 

conditions at their location, whereas the amount of warning a 

user receives is based on their distance from the epicenter.

It is important to note that these local variations in 

shaking intensity can be large, and estimated shaking 

intensities can have large uncertainties. In general, P-waves 

induce vertical shaking, which has minimal impact on the built 

environment, because buildings are constructed to withstand 

the vertical force of gravity and less so for lateral motions 

from S-waves. However, that does not mean that high shaking 

intensities will only be experienced during the S-wave and 

later phases of an earthquake. The reader is encouraged to 

keep this in mind, as the estimated ShakeAlert warning times 

below are in reference to S-wave arrival.

It is estimated that ShakeAlert would issue its first alert 

5.1 seconds (s) after the HayWired scenario mainshock begins 

(for details, see appendix 2 of Porter and Jones, 2018). This 

estimate is based on the system’s performance during the 

Mw4.0 Piedmont, California, earthquake on August 17, 2015. 

The Piedmont earthquake epicenter lies only 6 km from the 

epicenter of the HayWired scenario mainshock, and thus it is 

a reasonable proxy for our purposes here because the initial 

alert latency should be comparable. Initial alert latency (the 

alert time minus earthquake origin time) depends on the 

local seismic station density and the speed with which data is 

delivered to ShakeAlert processing centers. The station density 

has remained relatively constant in this region but upgrades 

to sensors and telemetry have improved data delivery since 

2015. In the future, ShakeAlert will also continue to refine 

the algorithms to improve alert speeds. Full station buildout 

is complete in the bay region as of this writing. Buildout for 

the State of California is funded and expected to be completed 

in the coming years. The full West Coast of the United States 

will be built out sometime after that. Once all stations are 

contributing to the system, alert speeds will improve in areas 

where coverage is currently lacking. 

The time between an EEW alert and the S-wave arrival 

at a particular location is what we call the EEW time. 

Different alert distribution methods used by various pilot 

implementations, such as public announcement systems, 

cellular applications, or radio communications, will increase 

latencies and result in shorter EEW times for end users. For the 

HayWired scenario mainshock, the distance traveled by 

S-waves during the 5.1 s after the earthquake begins and the 

modeled distribution of the alert is approximately 15 km from 

the epicenter. This region defines a “no-warning zone,” where 

S-wave shaking would arrive before or at the time of the

published ShakeAlert. At distances greater than 15 km, a user

of an EEW system could receive an alert before the arrival of

S-waves. It should be noted that for large ruptures, the initial

shaking intensity estimates are likely to be low and increase as

a fault continues to rupture. Automated responses, outlined

below, should take this into account when setting thresholds

(Minson and others, 2018).

Table 1 catalogs the warning times and shaking 

intensities that ShakeAlert could provide for major cities 

affected by the Mw7.0 HayWired mainshock using the

assumptions outlined above and described in appendix 2 ofPorter

and Jones (2018) (fig. 1). Nearby regions situated about 0–65 km 

Table 1. Estimates for earthquake early warning times, relative to secondary-wave (S-wave) arrival, and peak shaking intensities at 

select locations for the hypothetical moment-magnitude-7.0 mainshock of the HayWired earthquake scenario in the San Francisco Bay 

region, California.

[MMI, Modified Mercalli Intensity]

City Latitude 

(north)

Longitude 

(west)

Distance from 

epicenter, in miles

Distance from 

epicenter, in kilometers 

Warning time, 

in seconds

Shaking intensity, 

MMI

Oakland 37.80 122.27 5 8 0.0 VIII

Berkeley 37.87 122.27 7 11 0.0 IX

Hayward 37.67 122.08 11 17 0.7 IX

San Francisco 37.78 122.42 13 21 1.8 VII

San Mateo 37.55 122.31 19 30 4.3 VII

Fremont 37.55 122.99 21 33 5.2 IX

Vallejo 38.11 122.24 21 35 5.8 VII

Redwood City 37.48 122.24 23 36 6.0 VII

San Rafael 37.97 122.53 23 36 6.0 VII

Livermore 37.68 122.77 24 39 6.9 VIII

San Jose 37.34 121.89 36 58 12.4 VIII
4 The HayWired Earthquake Scenario—Societal Consequences

SONOMA

NAPA

SANTA CLARA

SANTA CRUZ

SAN MATEO

SAN JOAQUIN

STANISLAUS

MERCED

SAN

BENITO

MONTEREY

MARIN

SOLANO

CONTRA COSTA

SACRAMENTO

San Jose

San Francisco

Oakland

Alameda

Stockton

Fremont

Modesto

Hayward

Livermore

0 seconds

5 seconds

1 0 seco nds

2 0 s eco nd s

2 5 s econ ds

0 seconds

5 seconds

1 0 seco nds

2 0 s eco nd s

2 5 s econ ds

–123° –122° –121°

38°

37°

0 10 20 KILOMETERS

Hydrology from U.S. Geological Survey National Hydrography Dataset, 2016 0 10 20 MILES

Boundary data from U.S. Census Bureau TIGER data, 2016

North American Datum of 1983 UTM 10N projection

Central meridian, 123° W., latitude of origin, 0.0° N.

EXPLANATION

Modified Mercalli Intensity

X+ (extreme)

IX (violent)

VIII (severe)

VII (very strong)

VI (strong)

V (moderate)

IV (light)

III (weak)

Warning time, 

in seconds

0

25

CALIFORNIA

Area

of map

Pacific Ocean

Figure 1. Map of the San Francisco Bay region, California, showing contours of earthquake early warning time estimates relative to secondary 

wave (S-wave) arrival for the hypothetical moment-magnitude-7.0 mainshock of the HayWired earthquake scenario on the Hayward Fault 

overlain on the instrumental intensity map for mainshock (intensity map modified from Aagaard and others, 2017a).
Chapter W. Earthquake Early Warning Forecast and Potential Hazard Mitigation Actions 5

from the epicenter could receive advanced warnings ranging 

from 0 to 12.4  s and experience shaking intensities from VII 

to IX on the MMI scale. The MMI scale describes the very 

strong shaking level (MMI VII) as when people have difficulty 

standing during shaking. The next level up, severe shaking 

(MMI VIII), would not only prevent people from standing but 

could overturn heavy furniture, cause chimneys to collapse, 

and cause structural damage.

Discounting local site effects and amplification in basins 

and areas of liquefaction, which can locally increase shaking 

intensities, more intense shaking is usually experienced closer 

to the section of the fault that ruptures and falls off as a 

function of distance (Aagaard and others, 2017a). Inversely, 

greater early warning times are possible for locations farther 

from the epicenter of an earthquake. For large events (M7.0 

and above), heavy shaking can be experienced far from the 

epicenter, because the rupture continues along the fault for 

some distance. Porter and Jones (2018, see appendix 2) 

suggest that MMI II or greater shaking would be felt as far as 

250 km away from the epicenter of the HayWired mainshock. 

In such a case, people downstream of the event can receive 

larger warning times and still feel shaking.

For the HayWired scenario mainshock, many highly 

populated areas, such as San Jose, have warning times of more 

than 12 s and ground shaking intensities of MMI VIII (fig. 2), 

whereas San Francisco, which is closer to the epicenter, would 

only receive 1.8 s of warning time and experience lower 

shaking of MMI VII. People and businesses in Fremont could 

receive 5 s of warning of violent shaking. Further afield, 

people in the Central Valley could receive as much as 42 s of 

warning preceding severe shaking. 

The HayWired mainshock rupture could be considered 

a worst-case scenario for the eastern part of the San 

Francisco Bay region, because the epicenter is right in the 

heart of an urban area, and the no-warning zone covers many 

affected people. Residents, businesses, and emergency 

responders in Oakland and Berkeley, less than 15 km from the 

epicenter, would be in this no-warning zone. That is, the 

S-wave would arrive before the warning did. The alert would 

not come in time for people in those cities to take advanced 

protective actions.

However, even in the no-warning zone, people who had 

been trained on how to use ShakeAlert warnings could have 

their minds and bodies “prompted” to remember their training 

to “drop, cover, and hold on” when an earthquake occurs, even 

if the warning came at the same time as or after the shaking. 

This is based on exemplification theory that tells us that:

The use of exemplifying imagery, mostly as a 

complement to informative text, has emerged as 

a powerful means of creating risk consciousness 

and of motivating protective and corrective action 

(Zillmann, 2006).

The developers of ShakeAlert are working with social 

scientists to ensure that alerts can make use of this body of 

research to benefit the recipient by linking a situation with 

a response. This is why training in advance, like the annual 

ShakeOut drills (see https://www.shakeout.org), is important. 

Of course, ShakeAlert warnings will not help with longer 

term decisions of constructing and retrofitting buildings for 

desired performance, nor can they prevent all impacts from 

heavy ground shaking. A few seconds of EEW is not enough 

time to take actions such as getting an earthquake kit together, 

contacting loved ones and deciding on a meeting place, 

securing heavy objects in a room, or stopping traffic over 

bridges. However, what a few seconds of EEW can do is 

allow people and organizations to implement mitigation and 

protective actions that were decided upon and put in place in 

advance of an earthquake. EEW is also a reminder that alerts 

and actions go hand in hand with preparedness (Allen and 

others, 2017). The process of planning strategies and actions 

for ShakeAlert can prompt people and organizations to also 

look at other protective actions in their environment that can 

be enacted well in advance of an earthquake. ShakeAlert is 

one tool in the resiliency toolbox, but one that requires prior 

planning to reach full potential. It should also be noted that the 

population affected by the no-warning zone for the HayWired 

scenario mainshock can, of course, benefit from warnings 

generated by earthquakes that occur in other parts of the San 

Francisco Bay region.

ShakeAlert Can Prompt Automated 

Controls

Automated controls are a key component for responding 

to the short warning times offered by ShakeAlert in the San 

Francisco Bay region. Automated responses eliminate the 

loss of precious time that a human would require to enact a 

process (such as opening fire station bay doors or slowing and 

stopping trains) that can aid in preventing cascading system 

failures. Cascading failures in this context are small failures 

that stack up together to have big impacts. Here, we outline 

some of the automated controls that ShakeAlert pilot users 

are working on, as well as those that were able to be directly 

investigated based on data provided as part of research for the 

HayWired scenario.

Many automated controls involve physical hardware 

and protocols to put specific equipment or systems into a safe 

mode. This is the case for elevator, door, and machinery type 

controls. There is also another approach that some groups 

are exploring to enable structural controls. These “smart civil 

structures” would be able to adapt building characteristics in 

real-time to more adequately brace a building for imminent 

earthquake shaking (Housner and Masri, 2000). A proof of 

concept using an EEW trigger to enact semiactive structural 

control capabilities was performed for a bridge in Southern 

California and shown to be effective at “reducing the response 

of the benchmark highway bridge for a wide variety of 

earthquake records” (Maddaloni and others, 2013). The 

analysis of structural controls is an interesting topic for further 

research but has not been integrated with EEW in the United 

States and is thus outside the scope of this chapter.
6 The HayWired Earthquake Scenario—Societal Consequences

"

"

"

"

"

"

" "

"

"

SOLANO

SONOMA

NAPA

SANTA CLARA

SANTA CRUZ

SAN MATEO

SAN JOAQUIN

STANISLAUS

MERCED

SAN

BENITO

MARIN

CONTRA COSTA

MONTEREY

SACRAMENTO

San Jose

San Francisco

Oakland

Alameda

Stockton

Fremont

Modesto

Hayward

Livermore

0 seconds

5 seconds

1 0 seco nds

2 0 s eco nd s

2 5 s econ ds

0 seconds

5 seconds

1 0 seco nds

2 0 s eco nd s

2 5 s econ ds

EXPLANATION

Warning time, 

in seconds

0

25

100,102–203,949

Block group density—Residents per 

sqare kilometer

49,532–100,101

24,905–49,531

12,913–24,904

7,073–12,912

4,230–7,072

< 2,845

2,845–4,229

0 10 20 KILOMETERS

0 10 20 MILES Hydrology from U.S. Geological Survey National Hydrography Dataset, 2016

Boundary data from U.S. Census Bureau TIGER data, 2016

North American Datum of 1983 UTM 10N projection

Central meridian, 123° W., latitude of origin, 0.0° N.

–123° –122° –121°

38°

37°

CALIFORNIA

Area

of map

Pacific Ocean

Figure 2. Map of the San Francisco Bay region, California, showing ShakeAlert (https://www.shakealert.org) earthquake early warning 

time estimates overlain with population density information for the hypothetical moment-magnitude-7.0 mainshock of the HayWired 

earthquake scenario on the Hayward Fault (also see fig. 2 in Porter and Jones, 2018). The geographically dispersed population 

experiences many different warning times in this scenario event.
Chapter W. Earthquake Early Warning Forecast and Potential Hazard Mitigation Actions 7

Elevator Systems

Automated controls added to building elevator systems can 

prevent passengers from becoming trapped when an elevator 

car and its counterweight become misaligned during heavy 

earthquake shaking (in the absence of structural controls). 

Elevator systems with active response systems based on either 

EEW systems or threshold-crossing protocols for ground 

shaking held 16,700 occupants during the Mw 9.0 2011 Tohoku 

earthquake in Japan (Layne, 2011). All of these elevators were 

in the affected region and experienced shaking at a high enough 

level to cause the systems to trigger. Using such a system, 

elevators in the United States could be configured to send 

elevator cars to the ground floor or stop at the nearest floor and 

hold the doors open during a strong earthquake.

Currently, there are limitations on using EEW for elevator 

systems, because not all buildings are modern enough to permit 

retrofits with ShakeAlert EEW technology, and regulations 

affecting how ShakeAlert warnings can be transmitted to 

elevators would need to be modified. ShakeAlert pilot users 

have indicated that California regulations do not permit internet 

services to initiate an elevator stop. Recently, Pacific Gas 

and Electric Company installed on-site EEW in some of their 

elevators, which does not use the internet to initiate the stop as 

a workaround (BusinessWire, 2017). If State regulations were 

changed from a location-by-location strategy, this could result 

in a more realistic approach to building resiliency throughout 

the West Coast.

A detailed analysis of elevator entrapment owing to 

power outages can be found in Porter (2018b); we summarize 

the methodology and results here because we apply the same 

assumptions to show how ShakeAlert could reduce the risk of 

elevator entrapment in the region impacted by the HayWired 

scenario. Porter (2018b) assumed a national average of one 

elevator for every 334 people to estimate numbers of elevators. 

He removed an estimated proportion of elevators with 

emergency power and assumed 60 percent of the elevators are 

in use (for example, actually carrying people) at any instance 

during peak times, and of those elevators, 30 percent would 

be between floors when the HayWired mainshock occurred. 

On the basis of this approach, Porter (2018b) estimated 4,500 

elevators in transit would be interrupted by power outages with 

the potential to trap as many as 22,000 people. This number is 

an upper limit estimation in that it assumes a widespread power 

outage occurs that affects all 10 million people living in the 

San Francisco Bay region and neighboring counties. 

The following estimation of the number of people 

trapped in elevators represents ideal-world conditions where 

all elevators that could trap riders owing to shaking (that is, 

shaking that cuts power at the site or misaligns the elevator) 

have automated controls that do not add significant delay in 

response to a ShakeAlert. Also, we calculate percentages of 

elevators that could avoid entrapping riders where ShakeAlert 

conditions apply. Using the estimated ShakeAlert warning 

times for the HayWired mainshock that are a function of 

distance from the epicenter, we estimate the number of 

elevators in each warning-time band by invoking Porter’s

(2018b) assumption of one elevator for every 334 people. The

numbers of people in each ShakeAlert warning-time band

were calculated using population data (U.S. Census, 2016) and

warning-time contours in a geographic information system

(as shown in fig. 2). Similar to Porter (2018b), we removed

percentages of elevators with emergency power, those not

in use by riders, and those that would be at floors when the

ShakeAlert is received.

We assume that given at least some ShakeAlert warning,

elevators equipped with automated controls could be held at

a floor and (or) stopped at the next floor with open doors for

easy egress. For example, if elevators receive 2 s of warning

of shaking that would trap riders, then those elevators that

would have left a floor or would reach a floor in less than 2 s

could be held before leaving a floor or stopped at the next floor,

respectively. Hydraulic elevators, which according to Otis are 

“used extensively in buildings up to five or six stories high,”

have transit speeds of 150 feet per minute, requiring 3.2 s to get 

between floors (Otis, n.d.). Rounding the transit time to 4 s and 

assuming transit times are uniformly distributed at any one 

time, then elevators with approximately 1 s of warning (in the 

1–2 s warning band) would allow one-quarter of riders to be 

held at a floor and one-quarter of riders to be stopped at the 

next floor. Similarly, half of riders might be held at a floor and 

the other half could be stopped at the next floor with about 2 s 

of warning (2–3 s warning band). If elevators can only 

be held or stopped, then three-quarters of riders might avoid

entrapment with about 3 s of warning (3–4 s warning band).

Beyond 4 s of warning, all riders would receive a warning

in time to remain at a floor or stop at the next floor to avoid

getting trapped.

With a ShakeAlert warning capable of only keeping

elevators at a floor, about 9 percent of all riders receiving

less than 2 s of warning could avoid entrapment (0 percent of

elevator occupants in the area with less than 1 s of warning and

25 percent of elevator occupants in the area with 1 to 2 s of

warning). About 40 percent of all riders receiving as much as

5 s of warning could avoid entrapment. This translates to about 

1,600 elevators carrying about 8,000 riders and illustrates how 

a few seconds of warning could make a difference for elevator 

riders because elevators only take seconds to travel between 

floors. The hypothetical upper bound for ShakeAlert helping to 

avoid elevator entrapment in the HayWired scenario is 81 percent of elevator riders. If a ShakeAlert warning is able to stop 

elevators at the next floor, the results are the same because 

elevator transit is distributed uniformly. If a ShakeAlert warning can both hold departing elevators and stop elevators when 

they arrive at the next floor, then the numbers double for the 

first 1 s and 2 s of warning and cap at 87 percent of avoided 

entrapments or an upper bound of 19,600 riders in elevators in 

the region. See table 2 for the details of estimates of avoided 

entrapments. Elevators within the no-warning zone, within 

the 1-s warning zone, or in transit beyond the warning time 

could still benefit from existing mechanical earthquake sensor 

controls that are non-EEW-related.
8 The HayWired Earthquake Scenario—Societal Consequences

Table 2. Number of elevators and percentage of riders in the San Francisco Bay region, California, that could use ShakeAlert to 

remain at a floor and (or) stop at the next floor to avoid entrapment of passengers in transit during power outage or damage at the site 

during the hypothetical moment-magnitude-7.0 mainshock of the HayWired earthquake scenario.

[Number of elevators is estimated using 2010 U.S. Census Bureau population data (U.S. Census Bureau, 2016) in the warning time areas. %, percent]

ShakeAlert warning-time bands

Estimate of the 

number of elevators 

in transit in warningtime band

Percent of riders avoiding 

entrapment with ShakeAlert 

capability to only hold elevators at a 

floor or only stop at the next floor

Percent of riders avoiding 

entrapment with ShakeAlert 

capabilities to both hold 

elevators at a floor and stop at 

the next floor

None 355 0 0

Less than 1 second 461 0 0

Less than 2 seconds 712 9 18

Less than 3 seconds 968 20 39

Less than 4 seconds 1,400 30 51

Less than 5 seconds 1,600 40 58

All warning-time bands in region, including 

areas receiving ≥5 seconds warning

4,500 81 87

Fewer people trapped in elevators would reduce the 

burden on 9-1-1 systems, which in turn could lessen the 

effects of cascading system and infrastructure failures. For 

example, in 2009, California experienced a 9-1-1 overload 

problem, which caused 26 percent of all wireless calls into 

the system to be “abandoned” (9-1-1 Industry Alliance, 2011). 

An example of how 9-1-1 overloads can lead to cascading 

failures involved a motorcycle accident on July 4, 2011, in 

Wichita, Kansas. Witnesses were unable to reach 9-1-1 to 

report the accident owing to the sheer volume of calls about 

fireworks clogging the lines (Finger, 2011). Paramedics were 

only reached after one witness bypassed 9-1-1 and directly 

contacted his father, who was an off-duty police officer. 

In light of this ongoing nationwide concern, California 

Governor’s Office of Emergency Services created the Routing 

on Empirical Data (RED) project, to use locations from 

wireless devices to help reduce the number of busy signals—

“shaving time and saving lives” (California Governor’s Office 

of Emergency Services, 2014). This method involves “using 

historical empirical call data [to] determine the most efficient 

routing for wireless 9-1-1 calls” (California Governor’s 

Office of Emergency Services, 2014).

Although the number of calls to 9-1-1 reporting trapped 

high-rise elevator occupants is not likely to ever reach the 

upper limit value of 3,900 calls represented by the number of 

elevators that could be held at a floor using ShakeAlert—in 

the HayWired scenario (87 percent of 4,500 elevators)— 

removing even some of these calls from the queue can have 

an impact on the volume of calls routed by 9-1-1 call centers.

Fire following earthquake is a major cause of 

postearthquake destruction (Scawthorn, 2018), so 

ShakeAlert’s ability to reduce 9-1-1 calls from low-level 

injuries through drop, cover, and hold on (outlined later in 

this chapter) and by stopping elevators (and the use of other 

automated controls) in combination with the RED project, 

may enable more calls, like those for fire, to get through.

Transportation Systems

Bay Area Rapid Transit (BART) trains are a crucial 

transportation system for the San Francisco Bay region. 

BART has invested in structural retrofits, an earthquake safety 

program, and in using the ShakeAlert system to limit system 

vulnerabilities in the case of an earthquake. BART is a crucial 

lifeline in the San Francisco Bay area, and these actions work 

together to increase resiliency for the train network.

In the HayWired scenario, trains arriving and departing 

from the Fruitvale, Coliseum, San Leandro, Bay Fair, 

Hayward, and South Hayward stations intersect locations 

of high estimated shaking damage and areas with low to 

moderate liquefaction and (or) landslide probability (fig.3). 

BART works with the ShakeAlert team and has implemented 

ShakeAlert warnings and their own local sensors, to slow and 

(or) stop the trains.

The BART system carries individual riders on more than 

127 million trips annually (2015 data; Bay Area Rapid Transit, 

2015). On Wednesdays at 4:18 p.m., there are on average 

10,482 persons in motion on 40 trains and 2,021 patrons on 6 

berthed trains (Kevin Copley, BART, written commun., 2015). 

Using timetables for each BART line passing through these 

six stations, we can construct a snapshot of train locations and 

directions along the track lines at 4:18 p.m. on a Wednesday 

afternoon (fig. 4) and envision how ShakeAlerts could impact 

the system. The following scenario is based on BART’s late 

2017 schedule.

Three trains (the Oakland International Airport and both 

Richmond line trains at Bay Fair) are berthed at the station 

platforms at 4:18 p.m. when the ShakeAlert alarm is received. 

Thus, approximately 1,011 passengers on the platforms and 

within the three trains would receive the command to hold 

position. Two trains on the Fremont-Daly City lines (both 

northbound and southbound) would be enroute between the 

South Hayward and Hayward stations at the time of the alarm. 
Chapter W. Earthquake Early Warning Forecast and Potential Hazard Mitigation Actions 9

Each train should receive 2 s of ShakeAlert warning in this 

scenario. BART receives alerts directly from ShakeAlert that 

do not pass through a third-party redistributor, so latency times 

are minimal from alert generation to alert receipt at BART. 

Two seconds is not enough time to slow and completely stop 

trains in motion; BART trains only can reduce speed 3 miles 

per hour per second. However, for the two trains in motion, 

which receive 2 s of warning before shaking, and the five trains

in transit through the affected area, which would not receive an 

early enough warning, the automated controls still protect the 

system by not requiring slower human interventions to make 

decisions to begin slowing or stopping the trains. The trains 

would automatically begin slowing as a result of either the 

networked ShakeAlert warning or BART’s own wayside track 

monitors. We should note that currently BART’s Oakland 

International Airport to Coliseum leg does not yet have the 

benefit of automated reaction.

Other transportation systems, such as metered entrances 

to highways and toll bridges, could benefit from ShakeAlert. 

There are thousands of commuters on the road during rush 

^_

Oakland ^_

Alameda

Berkeley Orinda

Piedmont

Emeryville

San Francisco

Oakland

Alameda

Berkeley

Piedmont

Emeryville

San Francisco

Moraga

Orinda

Hayward

Union City

San Leandro Dublin

San Ramon

A

C

C

B

B

C

C

0 4 8 KILOMETERS

0 4 8 MILES

0 1 2 KILOMETERS

0 1 2 MILES

Liquefaction/landslide probability

> 25%

5–25%

< 5%

EXPLANATION

BART station damage state

Retrofitted

Low

Low-moderate

Moderate

Moderate-high

High

CALIFORNIA

BART rail line

Area

of map

San Francisco Bay

N

Hydrology from U.S. Geological Survey National 

Hydrography Dataset, 2016

Boundary data from U.S. Census Bureau TIGER data, 2016

North American Datum of 1983 UTM 10N projection

Central meridian, 123° W., latitude of origin, 0.0° N.

Figure 3. Maps of the San Francisco Bay region California, showing U.S. Geological Survey ShakeCast (see https://earthquake.usgs.gov/

research/software/shakecast.php) shaking damage estimate for the Bay Area Rapid Transit (BART) system at the time of the hypothetical 

April 18, 2018, moment-magnitude-7.0 mainshock of the HayWired earthquake scenario on the Hayward Fault. A, Map showing the entire 

BART system; B, map showing BART stations near the mainshock epicenter (star) that are forecast to sustain moderate-high shaking 

damage, and C, map showing BART stations further south of the mainshock epicenter that are forecast to sustain moderate-high to high 

shaking damage.
10 The HayWired Earthquake Scenario—Societal Consequences

hour in the San Francisco Bay region, with many crossing 

over the Richmond Bridge, Golden Gate Bridge, San 

Francisco-Oakland Bay Bridge, San Mateo-Hayward Bridge, 

Dumbarton Bridge, and other smaller spans to return home. 

During the Mw 6.9 1989 Loma Prieta earthquake, more 

than 80 bridges in the region sustained minor damage, 10 

required temporary supports, and 10 were closed owing to 

major structural damage—including most notably, the San 

Francisco-Oakland Bay Bridge, whose upper level collapsed, 

causing one fatality. The Cypress Viaduct in the east bay 

catastrophically collapsed owing to amplified shaking of the 

underlying soft soils and was the locus of the vast majority 

of fatalities for the earthquake (Yashinsky, 1998). Today, the 

Bay Bridge has been retrofitted and a new eastern span has 

been put in place. The Cypress Viaduct was demolished, and 

a new connector between I–880 and I–80 was built nearby. 

Bridges in the region should now be safer to cross during 

heavy shaking, owing to the retrofitting and relocation, but 

halting traffic at freeway entrance metering lights and bridge 

toll booths in response to a ShakeAlert warning could lessen 

the number of cars entering these areas during peak shaking 

and further reduce potential risk.

ShakeAlert Can Prompt Protective 

Actions

Hospitals and Injuries

Hospitals play a crucial role for society after an 

earthquake—responding not only to patients currently in their 

care, but also triaging incoming patients with injuries resulting 

from shaking. Horiuchi (2009) researched EEW capabilities in 

a hospital setting in Japan and found that within the hospital, 

EEW can play a role in securing patients during surgery to 

prevent errors, protecting equipment so it may be useable after 

shaking, and protecting staff so that they may be physically 

able to carry on their duties. Horiuchi (2009) found possible 

protective applications for EEW such as securing radiation 

sources (turning off X-rays) and detaching tubing that could 

become forcibly removed during shaking. Each hospital will 

need to identify their own best practices for EEW based on 

their own facility and seismic risk.

In discussions with hospital groups in the San Francisco 

Bay region, one theme that is often brought up is the impact 

that ShakeAlert could have on reducing a large influx of 

patients in the aftermath of an earthquake. As was seen when 

Hurricane Katrina struck the Gulf Coast in 2005, medical 

personnel were overwhelmed by the number of patients coming 

in and could only triage and provide basic first aid, leaving 

many critical patients unassisted owing to lack of supplies 

and resources (Franco and others, 2006). Reducing the sheer 

number of people who need to be triaged, in an earthquake’s 

aftermath, could speed the triage process and allow hospitals to 

more nimbly respond to any severe trauma cases.

Lake Merritt

Fruitvale

Coliseum

San Leandro

Bay Fair

Hayward

South Hayward

Union City

Depart 4:17 p.m.

Arrive 4:20 p.m.

No EEW Depart 4:16 p.m.

Arrive 4:20 p.m.

No EEW

Warm Springs/South Fremont-Daly City

Oakland 

International 

Airport

4:18 p.m. EEW

Train held at 

station

4:18 p.m. EEW

Train held at 

station

Depart 4:15 p.m.

Arrive 4:23 p.m.

No EEW

Depart 4:15 p.m.

Arrive 4:19 p.m.

No EEW

Oakland Airport-Coliseum

Depart 4:17 p.m.

Arrive 4:20 p.m.

No EEW

Dublin/Pleasanton-Daly City

Depart 4:16 p.m.

Arrive 4:20 p.m.

Depart 4:16 p.m. 2-second EEW

Arrive 4:20 p.m.

2-second EEW

Warm Springs/South Fremont-Richmond

EXPLANATION

4:18 p.m. EEW

Train held at 

station

Figure 4. Schematic illustration of Bay Area Rapid Transit (BART) train 

locations along the systems tracks at the time of the hypothetical momentmagnitude-7.0 mainshock of the HayWired earthquake scenario on the 

Hayward Fault in the San Francisco Bay region, California. Colored arrows 

represent the train direction of motion in the area of interest and yellow 

boxes indicate trains that receive earthquake early warning (EEW).

For the HayWired mainshock, this could be especially 

crucial in the east bay, where critical-care facilities are 

concentrated in a few city centers (fig. 5). This is in contrast 

to the San Francisco Peninsula side of the bay, from San 

Francisco to San Jose. There, warning times are larger, 

shaking is lower, and critical-care facilities are more evenly 

distributed geographically. If the roads and bridges are 

passable, facilities along the peninsula could perhaps help 

by providing extra medical services to east bay residents. 

However, roads and bridges may be difficult to navigate 

after a powerful earthquake on the Hayward Fault, so east 

bay residents could have difficulty reaching these other 

hospitals on their own. This could put stress on ambulances 

and other first responders. ShakeAlert could be used to reduce 

the number of injuries in an earthquake like the HayWired 

mainshock (see next section) and thus may be a helpful tool to 

reduce the demands on medical services.

Two hospitals in the Los Angeles region were running 

pilots of the ShakeAlert system during the 2019 Ridgecrest 

earthquake sequence. Alerts were received but no actions 

were taken at the facilities, even though people there 

experienced shaking, because the shaking at those locations 

did not reach pre-set thresholds for action. The hospitals are 

now considering lowering the thresholds, since people in the 
Chapter W. Earthquake Early Warning Forecast and Potential Hazard Mitigation Actions 11

SONOMA

NAPA

SANTA CLARA

SANTA CRUZ

SAN MATEO

SAN JOAQUIN

STANISLAUS

MERCED

SAN

BENITO

MONTEREY

MARIN

SOLANO

CONTRA COSTA

SACRAMENTO

San Jose

San Francisco

Oakland

Alameda

Stockton

Fremont

Modesto

Hayward

Livermore

0 seconds

5 seconds

1 0 seco nds

2 0 s eco nd s

2 5 s econ ds

0 seconds

5 seconds

1 0 seco nds

2 0 s eco nd s

2 5 s econ ds

–123° –122° –121°

38°

37°

Hydrology from U.S. Geological Survey National Hydrography Dataset, 2016

Boundary data from U.S. Census Bureau TIGER data, 2016

North American Datum of 1983 UTM 10N projection

Central meridian, 123° W., latitude of origin, 0.0° N.

427–724

261–426

141–260

16–140

EXPLANATION

Care facility beds available

725–1,700

0 10 20 KILOMETERS

0 10 20 MILES

CALIFORNIA

Area

of map

Warning time, 

in seconds

0

25

Pacific Ocean

Figure 5. Map of the San Francisco Bay region, California, showing the location of critical-care facilities and the number of beds that they can

accommodate (Doug Bausch, Federal Emergency Management Agency, written commun., 2014), overlain with earthquake early warning time 

estimates for the hypothetical moment-magnitude-7.0 mainshock of the HayWired earthquake scenario on the Hayward Fault.
12 The HayWired Earthquake Scenario—Societal Consequences

building felt the earthquake and expected an alert (Margaret 

Vinci, California Institute of Technology, oral commun., 2019). 

Before considering the impact to injuries, it is important to 

keep in mind that giving people information about what they 

are experiencing is considered useful and desired.

Looking at past events, we can obtain a better picture 

of the prevalence of injuries. After the 1989 Loma Prieta 

earthquake, it was determined that more than 50 percent 

of the nonfatal incidents were caused by falls and falling 

hazards (Shoaf and others, 1998). This includes those caused 

by collapses of chimneys and porches, which were the most 

common structural collapse hazards. In the Mw 6.2 2011 

Christchurch, New Zealand, earthquake, 70.4 percent of 

soft-tissue injuries were from trip or fall hazards (Lambie and 

others, 2017). Lambie and others (2017) used closed-circuit 

television footage to code responses during the earthquake 

and found that only a small number took self-protective 

actions—1.3 percent of people dropped and 26 percent held 

on to something. This is similar to the findings of Lindell 

and others (2016), where only 7.2 percent of people in 

Christchurch and 13.9 percent of people Hitachi, Japan, took 

cover during the 2011 Christchurch and Tohoku earthquakes, 

respectively. However, more than 30 percent of people froze 

in place (Lindell and others, 2016). Lindell also found that 

“lower levels of earthquake preparedness . . . produced higher 

levels of freezing in place.” Getting a warning out to people 

is important, but so is educating people on what to do if they 

receive such an alert.

Drop, Cover, and Hold On

Training and education are crucial for populations to 

perform the most effective self-protective actions during an 

earthquake. The messages received from ShakeAlert can serve 

to improve and increase performance of protective actions by 

communicating the proper response to take (Drabek, 1986; 

Mileti and Fitzpatrick, 1991; Mileti and Sorensen, 1990; 

Sorensen, 2000). “Drop, cover, and hold on” (DCHO) is the 

recommended action to take when shaking is felt (provided it 

is safe to do so). EEW serves to augment the efficacy of this 

self-protective action by providing the person with advanced 

notice to be aware of the coming situation, remember their 

training, and take action.

As part of the HayWired scenario, Porter and Jones 

(2018) conducted a survey of people to assess response times 

to DCHO after a simulated earthquake alert. The survey results 

indicated a median time to complete DCHO at 8.8 seconds. 

The Federal Emergency Management Agency’s Hazus-MH 

damage-estimation tool calculates 800 deaths and 18,000 

nonfatal injuries from building and structural damage caused 

by ground shaking and liquefaction hazards from the HayWired 

mainshock in the San Francisco Bay region. They combined 

these data with the ShakeAlert warning-time contours for 

the HayWired mainshock to assess the number of people that 

could conceivably complete DCHO before heavy shaking 

began (S-wave arrival). Porter and Jones (2018) found that 

the population of the bay region that lives in areas receiving

more than 8.8 seconds of EEW represents 8 percent of the

total nonfatally injured population, or about 1,500 people,

and they estimated that “The U.S. Government would value

mitigation measures to avoid that number of nonfatal injuries at

approximately $300 million (in 2015 [U.S. dollars]).”

One should note that this number only represents subjects

that fully completed DCHO before shaking began. Not every

person may be able to fully complete DCHO in the population

average time used for this study, but it is likely that DCHO

may not need to be fully completed before the arrival of heavy

shaking to have a benefit. As noted above, Lindell and others’

(2016) Christchurch and Tohoku earthquake studies indicated

that many injuries are trip and fall hazards. It therefore stands

to reason that the “drop” part of DCHO is the most important 

step to prevent fall and trip injuries. Further studies could 

assess the benefits of “drop” or “hold” and the time required 

to complete these actions. DCHO is thought to be an effective 

strategy even in the absence of EEW, and a ShakeAlert 

warning message augments this strategy by providing the 

cognitive link between imminent earthquake shaking and the 

prescribed action to take. ShakeAlert messages could help 

increase the probability that DCHO will be performed.

Effective training should not be overlooked. A survey on 

EEW responses, outlined by Nakayachi and others (2019),

suggests that “respondents seemed to place more value 

on mental preparation rather than reducing their chance 

of injury or death.” People want an alert, but more social 

science research needs to be done to improve the incidence 

of DCHO responses within the short time frames provided 

by EEW and to reduce the time spent milling, that is, seeking 

confirmation and deciding what to do (Wood and others, 

2017). This is supported by Nakayachi and others’ (2019) 

observation that “the connection between receiving an EEW 

and swiftly moving through key psychological processes to 

undertake quick, deliberate protective actions has not yet 

been established.”

ShakeAlert and Aftershocks

Aftershocks can occur following any earthquake. 

It should be noted that smaller aftershocks can vary in 

magnitude and can be more impactful than a mainshock in 

some areas, and a larger earthquake could also occur and 

become the new mainshock—as was the case in Japan in 2011, 

where a Mw 7.2 occurred offshore and was followed 2 days 

later by the Mw 9 Tohoku event. In the HayWired scenario, the 

Mw7.0 mainshock is the beginning of an earthquake sequence 

in the San Francisco Bay region with aftershocks large enough 

to cause or aggravate damage and complicate emergency 

response and recovery (Wein and others, 2017). 

Many aftershock sequences were generated by scientists 

for the Hayward fault rupture. We use a few earthquakes from 

the aftershock sequence selected for the HayWired scenario 

(Wein and others, 2017). The modeled HayWired aftershock 

sequence has 175 earthquakes of Mw

4 or larger that occur in 
Chapter W. Earthquake Early Warning Forecast and Potential Hazard Mitigation Actions 13

San Francisco

Sacramento

Stockton

Fremont

Santa Rosa

Vallejo

Vacaville

Roseville

Tracy

San Rafael

Lodi

Cloverdale

−− Earthquake Planning Scenario −−

ShakeMap for Ff558 Scenario

Scenario Date: Apr 30, 2018 06:13:00 AM UTC M 5.6 N38.19 W122.15 Depth: 11.1km

PLANNING SCENARIO ONLY −− Map Version 4 Processed 2016−12−27 09:03:29 PM UTC 

INSTRUMENTAL 

INTENSITY

PEAK VEL.(cm/s)

PEAK ACC.(%g)

POTENTIAL 

DAMAGE

PERCEIVED 

SHAKING

I II−III IV V VI VII VIII IX X+

<0.07 0.4 1.9 5.8 11 22 43 83 >160

<0.1 0.5 2.4 6.7 13 24 44 83 >156

none none none Very light Light Moderate Mod./Heavy Heavy Very Heavy

Not felt Weak Light Moderate Strong Very strong Severe Violent Extreme

Scale based on Wald and others, 1999

−123 ̊ −122 ̊ −121 ̊

37.5 ̊

38 ̊

38.5 ̊

39 ̊

0 50

km

Figure 7.

Figure 6. U.S. Geological Survey ShakeMap (see https://earthquake.usgs.gov/data/shakemap/) of the San Francisco 

Bay region, California, for the moment-magnitude-5.6 Fairfield aftershock of the hypothetical HayWired scenario 

earthquake sequence on the Hayward Fault on April 29, 2018, at 11:13 p.m. For details of the HayWired aftershock 

sequence see Wein and others (2017). km, kilometer; peak acc., peak acceleration; peak vel., peak velocity; %g, amount 

of ground acceleration caused by the earthquake, expressed in terms of the percentage of gravity’s acceleration at the 

Earth’s surface; cm/s, centimeter per second.
14 The HayWired Earthquake Scenario—Societal Consequences

the 2 years following the mainshock, the largest of which is 

a Mw 6.4 event. We examine three of the larger aftershocks in 

this sequence and how recovery and ShakeAlert could work 

together (figs. 6–8). The selected aftershocks were chosen 

based on size, area of impact, and time of day, as well as 

elapsed time after the mainshock to assess a broad range of 

situations where EEW could be notable.

The analysis assumes that the ShakeAlert system 

continues to function and alerts are received by the public 

and organizations after the HayWired mainshock. ShakeAlert 

has redundant servers in three locations throughout the West 

Coast to ensure that even if one location experiences loss 

owing to shaking, other locations will still be able to push out 

alerts. Alerts would also be provided using multiple pathways 

(cellular, broadcast, and internet methods), which provide 

redundancy to increase the chances that alerts will get out. 

Physical damage to stations, communication lapses, or other 

effects could slow down alert delivery and result in shorter 

EEW times.

The first aftershock we consider is centered in Solano 

County near Fairfield, a Mw 5.6 event occurring 12 days 

after the mainshock on April 29, 2018, at 11:13 p.m. (fig. 6). 

For this event, the maximum expected shaking intensity is 

MMI VII. The area of strong shaking in this event does not 

overlap with the area of strong shaking during the mainshock, 

so there is an expectation that critical infrastructure in this 

area was likely not heavily damaged in the mainshock. We 

can also surmise that at 11:13 p.m. most people are at home 

and not working or commuting, so injuries sustained are 

likely to be fewer. We specifically highlight this aftershock 

to show that aftershocks can occur at some distance from the 

mainshock, especially to encourage organizations that use 

the HayWired scenario to construct or test resiliency plans 

to include contingencies for ShakeAlerts from such events. 

This also serves to remind readers that the no-warning zone 

of the mainshock will not always be the same for subsequent 

aftershocks. The EEW system is designed to help people in 

a broad region, not just those near the epicenter, so lifelines, 

businesses, and people could take this into consideration 

with their planning. The HayWired scenario mainshock is 

not likely to be the exact location of the next actual major 

earthquake on the HayWard Fault, so the covered populations 

could vary greatly.

The second aftershock we consider here is a Mw 5.4 

event modeled to occur in Alameda County near Oakland 

on May 20, 2018, at 8:37 a.m. (fig. 7). At that time, 32 days 

would have passed since the mainshock. Infrastructure repairs 

would likely be ongoing in some areas because afterslip (fault 

movement after an earthquake) on the Hayward Fault of 

~0.5–1.5 m (see Aagaard and others, 2017b) could continue 

to shift pipelines, roads, and utility conduits as the ground 

continues to move over time.

Land on the margins of the east bay side of San Francisco 

Bay that was already compromised by the mainshock and 

other aftershocks would be impacted by the strong shaking of 

this aftershock. In the Oakland area, those people at or heading 

to work, who were able to return to work since the mainshock, 

would be especially impacted by the shaking, as 8:37 a.m. is 

in the middle of morning rush hour. However, owing to the 

location and the less widespread heavy shaking, ShakeAlert 

may not be as effective for this area. Most of the heavily 

impacted locations with ongoing road repairs and unstable 

debris might be in the no-warning zone and may not receive 

sufficient warning for actions to be taken. This emphasizes the 

importance of restricting entry to dangerous areas. Repairs that 

were completed in the early weeks after the mainshock may 

now have to be redone.

Several of the larger HayWired aftershocks cluster in 

Silicon Valley (in the southern part of the San Francisco Bay 

region), hitting the area multiple times in the 2 years following 

the mainshock. This is a situation where (1) people will be 

continually rattled (as in Fairfield) and (2) multiple damaging 

earthquakes will wreak havoc on the recovery efforts. A 

Mw 6.4 aftershock in Santa Clara County near Cupertino on 

October 1, 2018, at 12:33 a.m. (fig. 8) follows close on the 

heels of a Mw 6.0 aftershock near Mountain View (also in 

Santa Clara County) 4 hours earlier. Although many repairs 

may not be underway during the night, response to the 8:16 

p.m. Mw 6.0 event will have begun, and unstable debris and

any repair work will likely be heavily shaken. In the Mw 6.4

aftershock, strong and very strong shaking would be felt over

a large area of the south bay, so many people would receive a

ShakeAlert warning. First responders activated in response to

the earlier Mw 6.0 aftershock using ShakeAlert would know

that another larger aftershock was on its way and might be

more prepared to take self-protective actions. ShakeAlert

could also help prioritize response to the aftershock before

more detailed information is available.

The ShakeAlert warning could also help protect repair 

workers outside of the no-warning zone from unstable debris 

and other hazards caused by the Mw 6.0 aftershock. Bakun and 

others (1994) note that:

Structures damaged in strong shaking are weakened 

and susceptible to additional damage and possible 

failure in subsequent shaking from aftershocks. 

More than 20 magnitude 4 and larger Loma Prieta 

aftershocks occurred in the month following the 

mainshock, each large enough to be widely felt in 

San Francisco and Oakland. Weeks after the shock, 

crews were still working in and near damaged 

structures in the Marina district of San Francisco 

and at the collapsed Cypress Street section of 

the 1-880 freeway in Oakland. The certainty of 

aftershocks in the weeks following the Loma Prieta 

earthquake posed a constant threat to the rescue 

and reconstruction crews working near weakened 

structures. Clearly the few tens-of-seconds warning 

of incoming strong shaking achievable in an early 

warning system provides a means to reduce this risk.

The damage done by continual aftershocks is not just 

to the built environment. A longitudinal study assessed the 

mental-health impact of the continuing aftershocks following 

the Mw 7.1 2010 Canterbury, New Zealand, earthquake 
Chapter W. Earthquake Early Warning Forecast and Potential Hazard Mitigation Actions 15

San Jose

San Francisco

Stockton

Fremont

Vallejo

Vacaville

Tracy

San Rafael

Lodi

−− Earthquake Planning Scenario −−

ShakeMap for Ok542 Scenario

Scenario Date: May 20, 2018 03:37:00 PM UTC M 5.4 N37.76 W122.15 Depth: 8.4km

PLANNING SCENARIO ONLY −− Map Version 1 Processed 2016−12−27 08:25:18 PM UTC 

INSTRUMENTAL 

INTENSITY

PEAK VEL.(cm/s)

PEAK ACC.(%g)

POTENTIAL 

DAMAGE

PERCEIVED 

SHAKING

I II−III IV V VI VII VIII IX X+

<0.07 0.4 1.9 5.8 11 22 43 83 >160

<0.1 0.5 2.4 6.7 13 24 44 83 >156

none none none Very light Light Moderate Mod./Heavy Heavy Very Heavy

Not felt Weak Light Moderate Strong Very strong Severe Violent Extreme

Scale based on Wald and others, 1999

−123 ̊ −122 ̊ −121 ̊

37 ̊

37.5 ̊

38 ̊

38.5 ̊

0 50

km

Figure 8.

Figure 7. U.S. Geological Survey ShakeMap (see https://earthquake.usgs.gov/data/shakemap/) of the San 

Francisco Bay region, California, for the moment-magnitude-5.4 Oakland aftershock of the hypothetical HayWired 

scenario earthquake sequence on the Hayward Fault on May 20, 2018, at 8:37 a.m. For details of the HayWired 

aftershock sequence see Wein and others (2017). km, kilometer; peak acc., peak acceleration; peak vel., peak 

velocity; %g, amount of ground acceleration caused by the earhquake, expressed in terms of the percentage of 

gravity’s acceleration at the Earth’s surface; cm/s, centimeter per second.
16 The HayWired Earthquake Scenario—Societal Consequences

San Jose

San Francisco

Stockton

Fremont

Modesto

Salinas

San Rafael

Santa Cruz

−− Earthquake Planning Scenario −−

ShakeMap for Cu640 Scenario

Scenario Date: Oct 1, 2018 07:33:00 AM UTC M 6.4 N37.31 W122.06 Depth: 15.4km

PLANNING SCENARIO ONLY −− Map Version 2 Processed 2016−12−27 08:53:48 PM UTC 

INSTRUMENTAL 

INTENSITY

PEAK VEL.(cm/s)

PEAK ACC.(%g)

POTENTIAL 

DAMAGE

PERCEIVED 

SHAKING

I II−III IV V VI VII VIII IX X+

<0.07 0.4 1.9 5.8 11 22 43 83 >160

<0.1 0.5 2.4 6.7 13 24 44 83 >156

none none none Very light Light Moderate Mod./Heavy Heavy Very Heavy

Not felt Weak Light Moderate Strong Very strong Severe Violent Extreme

Scale based on Wald and others, 1999

−123 ̊ −122 ̊ −121 ̊

36.5 ̊

37 ̊

37.5 ̊

38 ̊

0 50

km

Figure 9.

Figure 8. U.S. Geological Survey ShakeMap (see https://earthquake.usgs.gov/data/shakemap/) of the San Francisco Bay 

region, California, for the moment-magnitude-6.4 Cupertino aftershock of the hypothetical HayWired scenario earthquake 

sequence on the Hayward Fault on October 1, 2018, at 12:33 a.m. For details of the HayWired aftershock sequence see Wein 

and others (2017). km, kilometer; peak acc., peak acceleration; peak vel., peak velocity; %g, amount of ground acceleration 

caused by the earthquake, expressed in terms of the percentage of gravity’s acceleration at the Earth’s surface; cm/s, 

centimeter per second.
Chapter W. Earthquake Early Warning Forecast and Potential Hazard Mitigation Actions 17

(Spittlehouse and others, 2014). The researchers found 

that there was an increased prevalence of major depressive 

disorder and bipolar disorder in the study cohort in the 

18 months after the earthquake. They also found “scores 

significantly lower than the population norms in the mental 

health, vitality, social functioning and role-emotional 

subscales” (Spittlehouse and others, 2014). ShakeAlert 

would not be able to prevent the psychological repercussions 

of major earthquakes, as described by Mooney and others 

(2011) after the 2010 Canterbury earthquake. Although there 

is evidence that more people opt to use EEW than not (Ohara 

and others, 2012), and the benefits include increasing their 

awareness and preparedness to take protective actions (Allen 

and others, 2017; Ohara and others, 2012), psychological 

benefits from using ShakeAlert (for a damaging earthquake or 

during an aftershock sequence) is an open research question.

Actions Discussed Elsewhere in the 

Literature

EEW is in use in several countries worldwide, including 

Japan and Mexico, and is a proven technology for hazard 

mitigation (Fujinawa and Noda, 2013; Lee and EspinosaAranda, 2003; Shimamura and others, 2001; Allen and 

Melgar, 2019). An exhaustive list of self-protective actions to 

take in response to EEW was not attempted for this chapter 

and only a few are highlighted, and automated controls in 

response to ShakeAlert warnings are still under development. 

To encourage discussion of ShakeAlert among those who 

may use the HayWired scenario to inform hazard mitigation 

strategies, several overviews of EEW in the literature are 

worth noting. However, not all EEW actions performed in 

other countries will be applicable or practical to enact in the 

United States.

Heaton and others (1985) pioneered the idea of using 

computer-based automated controls in conjunction with 

EEW to increase resiliency. This idea took hold, and now 

many EEW systems are in place worldwide that are aided 

by automated technology. A summary of these systems and 

EEW use cases can be found in Allen (2011). A more specific 

demonstration of capabilities for both the prototypic U.S. 

ShakeAlert system and the Japan Meteorological Agency’s 

approach to EEW are outlined by Burkett and others (2018), 

Fujinawa and Noda (2013), and Given and others (2014). 

Specific actions that can be taken to enhance the benefits of 

EEW include development of risk scenarios (for example, 

planned response protocols) in advance of an earthquake, 

such as described by Pittore and others (2014) and generaluse case studies that include recovery and economic benefits 

as described by Strauss and Allen (2016).

Transportation systems can use EEW alerts to hold trains 

at station platforms and slow and stop trains that are enroute 

to reduce the chance of derailment and allow patrons and 

workers at stations to take protective actions, as discussed for 

the BART system in this chapter. Edwards and others (2015) 

extend this discussion beyond the San Francisco Bay region 

to look at transportation systems in Japan as well. Bridge 

and tunnel metering lights could be turned on to reduce the 

number of entering cars. Airports could make use of EEW 

alerts both inside and outside of terminals—baggage handlers 

can protect themselves before items fall, moving baggage 

carousels can be stopped to prevent damage, and alerts 

to patrons inside terminals could allow them to take selfprotective actions.

Schools and hospitals both house vulnerable populations. 

EEW alerts in schools allow teachers and staff advanced 

warning to help their students to take DCHO actions and 

get to a safe space after shaking stops (Motosaka and 

Homma, 2009). Frequent drills help reinforce this training. 

In hospitals, surgeons can secure patients during surgery, 

delicate machinery like magnetic resonance imaging (MRI) 

machines can be put into a safe mode, and staff can take (as 

well as help patients take) self-protective action to ensure 

they are ready to respond once shaking ends (Horiuchi, 2009).

Fire following earthquake can be a large contributor to 

the postearthquake damage and is examined for the HayWired 

scenario by Scawthorn (2018). During the Northridge 

earthquake in 1994, many fire stations were seriously affected 

(Schneider, 1994). ShakeAlert triggers could be used to open 

firehouse doors before heavy shaking or loss of power occurs, 

enabling firefighters to exit with their equipment in a faster 

manner and more quickly respond to fires.

Work with ShakeAlert pilot groups in the water, gas, 

and electric distribution sectors, has shown that protecting 

both personnel and infrastructure with ShakeAlert will be 

a key to resiliency for a powerful earthquake. ShakeAlert 

warnings for utility workers in “cherry picker” lifts, out in 

the field, or in small tunnels are being assessed to ensure that 

these personnel are protected and services can get restored 

in a timely manner. Both water and gas systems could use 

ShakeAlert to trigger safety interlock systems for hazardous 

chemicals to reduce spills, fires, and explosions. Some groups 

are also exploring redirecting or securing certain sections of 

the utility grids.

Emergency responders help coordinate their disaster 

response and recovery efforts through incident command 

centers. Many in the San Francisco Bay region subscribe to 

the California Integrated Seismic Network Display to get 

accurate up-to-date information on earthquakes that have 

recently occurred. Groups in major cities and counties of the 

San Francisco Bay region are also piloting the ShakeAlert 

system through its UserDisplay (see https://www.shakealert.

org/eew-research/caltech/shakealert-user-display/), which 

provides information on local shaking intensity, epicenter 

location, and event magnitude. ShakeAlert provides 

situational awareness to emergency responders so that 

they can more quickly and safely mobilize their teams and 

choose the best plan of action. Knowing right away where 

an earthquake epicenter is located and which areas likely 

experienced the most significant shaking can help the incident 
18 The HayWired Earthquake Scenario—Societal Consequences

command team marshal resources to the correct areas for 

damage assessment and provide information on likely 

mutual aid from outside areas that were not as affected. The 

importance of this was seen in the Mw 6.0 2014 South Napa, 

California, earthquake, when many local first responders 

initially assumed that the epicenter was near San Francisco. 

Had they been using ShakeAlert at the time, they would have 

known right away that mutual aid was likely coming their 

way and to prepare for that fact.

Conclusion

The HayWired earthquake scenario presents a framework 

to envision ShakeAlert’s contribution to protecting local 

populations and infrastructure and reduce cascading failures 

in the aftermath of a major urban earthquake in the San 

Francisco Bay region. The most recent major earthquakes in 

this region—the Mw 6.0 2014 South Napa and Mw 6.9 1989 

Loma Prieta earthquakes—are often reference points for 

people when they imagine what a Hayward Fault event could 

look like. Unfortunately for planning purposes, the South 

Napa earthquake was much smaller than the Mw 7.0 mainshock 

modeled in the HayWired scenario, and the epicenter of the 

Loma Prieta earthquake, although of similar magnitude, was 

not directly under a densely built urban environment. Thus, 

“tabletop” exercises using the HayWired scenario can better 

support proper planning and forecasting of risk reduction 

benefits, including those derived from ShakeAlert.

In closing, we would like to outline some limitations 

of ShakeAlert and the assumptions we made, as well as 

areas for future analysis. ShakeAlert is a tool for improving 

resiliency; however, building retrofits, improvements to 

building codes, and lifeline coordination will continue to 

be crucially important, even when a full public ShakeAlert 

system is in place. Fire following earthquake is a major 

source of loss in the HayWired scenario. Therefore, end users 

who use ShakeAlert in their critical facilities might consider 

assessing whether automated controls can be put in place that 

use the alerts to reduce ignition sources. As mentioned earlier, 

current regulations in California prohibit internet-distributed 

ShakeAlert warnings to trigger switches on elevators to cause 

them to remain open at the nearest floor. Changes to these 

regulations would need to be undertaken to permit these 

automated controls to be put into practice.

The ShakeAlert system will also need to explore a 

varied landscape of alert redistribution methods to ensure 

broad coverage and uptake of the system. Working with 

groups such as the Alliance for Telecommunications Industry 

Solutions will likely be needed to develop longer term alert 

delivery solutions so that future technologies can better serve 

the end user. As part of the 2018 limited public rollout of 

ShakeAlert, pilot users and technology enablers are exploring 

the landscape of options. Any policies on alert distribution 

need to also consider that notifications should be equitable 

and cover a number of different groups, including those with 

access and functional needs, people without access to cellular 

networks, and technical users who require more detailed 

information. The public will need to be made aware that broad 

alert distribution channels may cause them to be alerted when 

they may not personally feel shaking at their location. More 

technical users will also need to be made aware that the design 

of automated controls need to take this into consideration 

and not be precisely dependent on strict shaking values. A 

full public ShakeAlert system can have many benefits for 

people, including the possibility to begin the drop, cover, and 

hold on recommended action before shaking onset. However, 

public use of ShakeAlert will require an ongoing education 

and training campaign to be effective. The U.S. Geological 

Survey’s Joint Committee for Communication, Education, and 

Outreach will need to work with State and local officials to 

develop a long-term strategy to engage the public. This will be 

especially necessary during times of low earthquake activity, 

so that preparedness remains fresh in the public’s memory.

The HayWired scenario provides the first glimpse of 

ShakeAlert’s role in resiliency and postearthquake recovery 

in the San Francisco Bay region. We envision a future where 

a broader landscape of automated responses and uses for 

ShakeAlert are identified and implemented. Organizations 

who use the information in this chapter should be aware that 

the solutions outlined here have not been fully developed or 

tested in the United States. Also, the epicenter for an actual 

large earthquake on the Hayward Fault may be in a different 

location with a different magnitude, so ShakeAlert times could 

geographically vary significantly from what is outlined here. 

Policymakers and end users would be best served by using this 

chapter about the potential immediate responses to ShakeAlert 

warnings in concert with longer term earthquake mitigation 

actions and planning.

Acknowledgments

We would like to thank Kevin Copley (Bay Area Rapid 

Transit) for help with the transportation section, Mary Lou 

Zoback (Build Change, Stanford University) for comments, 

and our reviewers for their suggestions.

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