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"We lost 31 of those (street) cars. To rebuild those cars cost us $1.2 million
per car. That's not a capital cost you can replace very easily."
--Justin Augustine, CEO of the New Orleans Regional Transit Authority,
January 2011 on losses to the New Orleans
transportation system after Hurricane Katrina
3
Making the Case for Resilience Investments:
The Scope of the Challenge
INTRODUCTION
The potential benefits of being resilient to hazards and disasters make
abundant sense. Few would oppose taking action to reduce the loss of life or
property damage. However, increasing the resilience of a community requires
large-scale investments of money, human resources, and time. Once risk has
been identified and assessed, what actions are sufficient to address the risk?
How resilient does the community need to be? How do investments in
improving resilience compete with other community investment priorities? What
are the benefits? Who pays now? Who pays later?
The available data portraying past disasters show that the scale and
scope of disaster losses1 are enormous and that significant investment is required
to mitigate the losses of human life, risks to human health, and economic and
social costs. Investments are required for a wide spectrum of community needs
such as planning, organizing, training, and equipping first responders to large
infrastructure projects. Owners of community assets are primarily responsible
for their own resilience investments, yet community leaders from both the public
and private sectors recognize that community assets are interconnected and
interdependent and that holistic planning, programming, investing, and
execution create common and interrelated resilience benefits for the community.
Realizing the maximum benefits requires close collaboration among public- and
private-sector leaders aided by a shared approach and commitment to
investment.
1
Unless otherwise noted, economic losses refer to property damage or crop losses (or both, if
noted).
67
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68 DISASTER RESILIENCE: A NATIONAL IMPERATIVE
As stewards of community assets the potential benefits of being
resilient to hazards and disasters are attractive from governmental, economic,
social, and environmental points of view. Although consensus generally exists
on the goals for strengthening resilience, making the case for investing in
resilience programs, in individual initiatives or projects, and in strengthening
weak infrastructure is very challenging, especially in the context of demand for
competing resources. Particularly during times of economic hardship, competing
demand for many societally relevant resources (education, health, and social
services) can be a major barrier to making progress in building resilience in
communities. As a prerequisite for making the case, advocates are required to
demonstrate that the potential benefits of being resilient to hazards and disasters
make conceptual sense. However, such efforts also have to show clearly that
community investments in resilience will yield significant and measurable short-
and long-term benefits that balance or exceed the costs. This kind of cost-benefit
analysis is critical for sustained commitment to increasing resilience, given the
rising level of competition for scarce resources at local, state, and federal levels
(Rose et al., 2007).
Furthermore, increasing resilience is tied in important ways to
economic recovery after a disaster. Specifically, resilience measures can
encourage efficient use of existing resources, and thereby lead to as rapid a
recovery as possible. Some factors that have been shown to have achieved these
ends include rapid business relocation (because of the existence of excess office
space), use of inventories and stockpiles, and substitution of inputs or suppliers
(Rose and Blomberg, 2010).
One approach that communities can use as they embark on a process of
improving resilience is to develop multiyear plans or programs that include
compelling initiatives or projects. These projects may include improving weak
or underfunded community infrastructure such as schools, clinics, and hospitals,
and the services which constitute any community. Involving and empowering
individuals and families in developing these programs are important because of
the ultimate need for individuals to take a share of responsibility in building
resilience. Beyond the essential cost-benefit analysis, the value of each initiative
or project also rests on the basis of its life-safety, economic, social, public
health, and environmental significance. This kind of valuation can assist
community leaders with prioritizing investments, decision making, and
developing a schedule for implementing their resilience-building strategies.
Resilience investments challenge traditional approaches to "cost-
benefit" analysis because communities have many different kinds of assets
which are valued differently. Communities have very-high-value assets that are
"essential" to keep operating--for example, hospitals, power plants, water and
sewage plants, and transportation and communication networks--that usually
have a tangible dollar value attached to them, and the costs of disruptions in
these services can usually be directly calculated. The social, cultural, and
environmental assets of a community also have high "value" but the value is
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MAKING THE CASE FOR RESILIENCE INVESTMENT 69
described in cultural and life-quality terms and is more difficult to quantify in
financial terms. Such assets include museums, natural landscapes or areas,
protected environmental zones, historical buildings, and a health infrastructure
that supports prevention and health maintenance throughout the population.
Thus the total value of a community's assets--both the high-value structural
assets and those with high social, cultural, and/or environmental value--
necessitates qualitative and quantitative inputs into a decision-making
framework for disaster resilience. Such decision making is going to be difficult
for community leaders as they try to address the value of multiple community
assets in economic, social, cultural, and environmental terms. Access to reliable
data is vital in order to support these kinds of decisions. This chapter identifies
the data needed and an approach for valuing assets, planning, programming, and
investment decision making for resilience. Specifically, the chapter addresses
(1) the challenge of decision making for community leaders in developing their
priorities in the context of their risk management findings and conclusions (see
also Chapter 2); and (2) the scale and scope of the threat and potential losses
from disasters. The ways in which communities might be able to develop or
adapt measures of their progress toward resilience are developed in Chapter 4.
CHALLENGE OF RESILIENCE DECISION MAKING FOR
COMMUNITY LEADERS
High-value assets of a community are those for which continued
operation is essential and urgent for the entire community (e.g., water and power
utilities, fuel systems, transportation facilities and systems, communication
systems, first responder operations centers, and hospitals). These interdependent,
high-value assets drive the need for holistic thinking, risk management (Chapter
2), priority setting, and investment timing.
Although substantial investments in some communities are made for
contingency preparations to secure essential community services and operations
during disasters, the scale of a disaster can nonetheless overwhelm the capacity
of the system and its operators to cope, leading to a failure in one or more parts
of the system as occurred, for example, with essential utilities in coastal
Louisiana during and after hurricane Katrina (NRC, 2011). Proven techniques
such as systemwide analyses and scenario planning offer insights for decision
makers to see resilience improvement needs and weigh their investment
priorities.
Other high-value assets of a community may include its economic
foundation (e.g., local industry or business), and its social, cultural,
environmental, and educational assets. These may include traditional ethnic
neighborhoods, religious centers, parks and preserves, wildlife habitats, art
centers and architectural icons, town squares, and schools or other educational
institutions. These assets are held dear and are highly valued as distinguishing
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70 DISASTER RESILIENCE: A NATIONAL IMPERATIVE
attributes by the community. Although it is difficult to measure their value in
purely monetary terms, their loss may significantly degrade the total ambiance
or qualify of life of a community. Although such losses may at first be
devastating, the investment priority judgments of community leaders will
consider the promise and possibilities embedded in the ingenuity and self-
reliance of citizens (see Box 3.1).
Establishing ownership of a community's assets is also important.
Asset owners in a community will vary and include those from public utilities,
local businesses and industries, faith-based communities, governmental and
nongovernmental organizations, and individual citizens. Owners are primarily
responsible for their property and for making appropriate steps including
investments in mitigation measures--structural and nonstructural (see Chapter
2)--to prepare and plan for hazards and risks. Community resilience planning
and investment programming set goals, strategies, and metrics for the
community and guide owners in how best to prioritize and time their
investments. However, resilience is also the outcome of interconnected systems
(Chapter 1). Decisions about the prioritization and the level of investment
require consideration of both quantitative data and qualitative value assessments
BOX 3.1
Decentralization of Community Assets: One Means to Forge a Greater
Sense of Community Resilience
Prior to Hurricane Katrina, the public school system in New Orleans
was centralized, and the schools were operated largely through a unified school
district and primarily served one community function--to educate the city's
children. With the destruction of many essential functions including the schools
and school system in New Orleans as a result of Katrina, some members of the
private sector, nonprofit organizations, and local citizens revisited together the
"value" of their schools in the context of the larger neighborhood communities
that the schools serve. What emerged was a design for new schools that
encompassed a "systems" approach where schools were designed and built to
serve multiple community purposes--with facilities to support cultural and
social events and community health through fitness centers in gymnasiums.
Investments in hardening the school structures to withstand the hazards present
in the area have focused not only on protecting students in the event of a
disaster, but also on having the schools capable of serving as centers for shelter
of the neighborhood community in case of a crisis. These planned investments
by the "owners" and stakeholders of this educational community asset--
essentially a blend of private, nonprofit, and community members--have
increased the scope of the asset as well as its overall community value.
Source: NRC (2011); Steven Bingler, personal communication, January 20, 2011.
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MAKING THE CASE FOR RESILIENCE INVESTMENT 71
the community is key in this regard. The next section examines the urgency of
the need to consider the scale and scope of disasters and disaster losses as a
means to motivate community efforts to identify and prioritize the full extent of
a community's assets.
THE SCALE AND SCOPE OF DISASTERS AND DISASTER LOSSES--
AN URGENT PROBLEM
The Economic Value of Mitigation
Understanding the benefits of investing in one or more mitigation
strategies in one place may provide some level of guidance that similar measures
implemented elsewhere may yield a certain, or potentially greater, level of
benefit. One of the landmark studies on the economic value of disaster
mitigation is the work of the Multihazard Mitigation Council (2005), a public
private partnership established to reduce the economic and social costs of
natural hazards. The study, based on cost-benefit analysis, examined future
savings from hazard mitigation related to earthquakes, wind, and floods using
two approaches: (1) a purposive sample of communities with mitigation grants
funded by the Federal Emergency Management Agency (FEMA) to determine
losses avoided through reductions in direct property damage, business
interruptions, nonmarket damages, human losses, and costs of emergency
response; (2) estimates of future savings from FEMA mitigation expenditures
that use a statistically representative sample of FEMA-funded mitigation grants
and that was then generalized to all FEMA mitigation grants (Multihazard
Mitigation Council, 2005). HAZUS-MH was used to estimate direct property
damage from earthquake, flooding, and hurricane wind. The mitigation
approaches included both physical measures (elevating or relocating structures,
strengthening structures against earthquake or wind hazards) and processes
(such as building codes, policies, education). The study results concluded that
mitigation saves money with benefits that greatly exceed the costs: for every $1
spent on pre-event mitigation, $4 was saved in post-event damages (see also
Chapter 1). In another study that examined physical mitigation measures, Sutter
et al. (2009) found that wind-resistant construction costing less than $500
additional per typical single-family home could mitigate future wind damage in
tornado-prone regions by 30 percent. Research conducted by the Institute for
Business and Home Safety has also demonstrated the economic value of
relatively simple and inexpensive home fortification through significant
reduction in structural damage and economic losses from strong weather events
(Box 3.2).
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72 DISASTER RESILIENCE: A NATIONAL IMPERATIVE
BOX 3.2
For the Want of a Ring-Shank Nail, the Roof Was Lost:
Research Supports Inexpensive Ways to Fortify a Home against Natural
Hazards
Steps toward resilience need not be expensive. During a wind, water,
or fire event, the roof is often involved, and "once the roof cover is
compromised, all sorts of bad things can happen to the structure" (J. Rochman,
personal communication, January 20, 2011). Research conducted by the Institute
for Business and Home Safety (IBHS) has demonstrated that using ring-shank
nails with full round heads instead of smooth-shank nails or staples to hold
siding and roofing materials on a home contributes to significantly more
resilient structures when the homes are subjected to strong weather events such
as hurricanes and wind storms. IBHS has a stronger, safer construction standard
for new homes, known as FORTIFIED for Safer Living®, which goes above
building codes (where they exist) with risk-specific guidance for homeowners,
architects, and builders.
A simple and inexpensive change to improve the resilience of a roof--
whether first put on a new building or during reroofing--is to use a minimum of
2-inch ring-shank nails instead of smooth-shank nails or staples to secure the
roof decking. In a series of full-scale tests at the IBHS Research Center, two
virtually identical two-story, 1,300-ft2 homes (one built to standard building
codes as they exist in the center of the country and one built to FORTIFIED
standards for new construction) were subjected to hurricane-strength wind
speeds. Unlike the conventionally constructed house, the FORTIFIED house had
ring-shank nails securing the roof and met other FORTIFIED requirements, such
as using metal strapping to hold load-path elements together. The cost of the
extra FORTIFIED modifications totaled only about $3,000. After subjecting
both houses to sustained wind and gusts that peaked at 96 miles per hour,
professional insurance adjustors examined both homes and estimated that the
cost of exterior repairs to the conventionally built home was ~2.5 to 8 times
higher than the home built to the IBHS FORTIFIED standard.
FORTIFIED program value was clearly demonstrated in a real-world
situation on the Bolivar Peninsula of Texas during Hurricane Ike. Thirteen
FORTIFIED homes stood directly in the path of Ike's eye wall, which included
110-mph winds and an 18-ft to 20-ft storm surge. Ten FORTIFIED homes
remained standing with minimal damage, while all other homes for miles around
were totally destroyed. The three FORTIFIED homes that were destroyed were
lost due to impacts from surrounding homes that were knocked off their
foundations and became moving piles of debris.
Research by the committee at a local home supply store revealed the
cost of 2,500 2-inch ring-shank nails with full round heads was $38.
Approximately 6,000 nails are required to attach the roof sheeting for a 2,000-ft2
house, another 6,000 nails with plastic or metal caps to anchor the
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MAKING THE CASE FOR RESILIENCE INVESTMENT 73
underlayment, and about 12,000 nails to attach the shingles (ca. 6 nails per
shingle).
Sources: http://www.disastersafety.org/content/data/file/FORTIFIED-vs-Conventional.pdf;
http://www.disastersafety.org/fortified; J. Rochman, personal communication, January 20, 2011.
Patterns of Disaster Losses to Guide Resilience Investments
Examining historic patterns of disaster losses provides some sense of
the magnitude of the need to become more disaster resilient. In addition, the
geographic patterns of disaster losses--human fatalities, property losses, and
crop losses--illustrate where the impacts are the greatest, and where there could
be challenges in responding to and recovering from disasters. Geographic
patterns of losses, when compared with available data on housing, population
growth, income level, and types of natural hazards, allow understanding of some
of the driving factors of exposure and vulnerability to hazards and disasters (see
also Chapter 2), and can lead more readily to appropriate paths to increase
resilience. This kind of analysis also reveals gaps in our knowledge of natural,
built, and socioeconomic systems--including their interrelationships--and is
useful in prioritizing research needs. The following sections review disaster
losses in terms of U.S. and global tendencies; geographic variation in economic
losses, human losses, and patterns of exposure; and population growth. Each
section draws upon available data and also presents evidence for gaps in data
collection, analysis, and availability.
U.S. and Global Patterns in Economic Losses
Because local and national patterns in disaster losses occur within a
larger global context, a useful way to assess the current state of resilience in the
United States is to examine the magnitude of global events and losses. As
estimated by Munich RE (2012), the costliest year on record for natural disasters
around the world (based on preliminary global data for the year) was 2011, with
more than $380 billion in losses (of which only $105 billion was insured),
exceeding the previous record set in 2005. The earthquakes in New Zealand, the
March earthquake and tsunami in Japan, and flooding in Australia and Thailand
all contributed to these new levels of loss. The Japanese earthquake and tsunami
combined were the most costly events globally in 2011. In the United States,
estimated losses were $64 billion, of which $35.8 billion were insured losses
(Munich RE, 2012). The snows of February, severe storms in April and May
which brought many tornadoes, the extensive flooding in the Midwest and Great
Plains, wildfires in Texas and the Southwest, and Hurricane Irene impacting
much of the U.S. East Coast all contributed to the total (see also Figure 1.1).
Establishing the tendencies in economic losses provides the baseline
against which we can monitor losses avoided due to improved resilience. Data
that have been collected in a consistent manner are essential for measuring
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74 DISASTER RESILIENCE: A NATIONAL IMPERATIVE
losses in absolute terms over time or in different locations, or simply attempting
to monitor loss history for a single location. Existing global loss databases are
useful for certain kinds of analyses, but require improvement in measurements,
accuracy, and consistency. For example, there is an ongoing debate in the
literature over whether losses from natural disasters are actually increasing over
time (Figure 3.1), or whether the data reflect large, recent singular extreme
events (e.g., the Tohoku earthquake and tsunami), changes in asset values,
changes in reporting, changes in housing stock, improved awareness, or some
combination of these. When national losses are normalized for population and
wealth, upward patterns in normalized losses appear to become less significant
(Pielke and Landsea, 1998; Brooks and Doswell, 2001; Miller et al., 2008);
however, other evidence suggests that even with normalization for population
and wealth, losses are increasing significantly, especially in the United States
(Gall et al., 2012) (Figure 3.2). Improvements in disaster-data collection will
help clarify these fundamental tendencies.
FI
GURE 3.1 Natural hazard losses worldwide 1980-2011. Source: Munich RE (2012).
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MAKING THE CASE FOR RESILIENCE INVESTMENT 75
FIGURE 3.2 Trends in per-capita property and crop losses (adjusted to $2010) from natural
hazards, 1960-2010. According to Gall et al. (2012), per-capita losses appear to be escalating in the
United States, even when normalized by population, and have more than tripled per person since the
1960s. Source: S. Cutter; compiled from SHELDUS.
Another issue in analyzing loss data is that not all losses are counted
and valued (Box 3.3). In the case of Munich RE, the NatCatSERVICE database
provides property losses (total and insured) and insured business interruption
losses, estimated from known insured losses. Because of the differences in loss
estimation techniques, thresholds for inclusion in the database (large versus
small events; insured versus uninsured losses), and data availability (public
versus proprietary), natural-hazard loss databases are rarely comparable with
one another. For example, comparisons among four publicly accessible
databases show different total dollar loss estimates for the United States in 2010
attributed to weather perils such as winter storms, hurricanes, tornadoes, and
flooding (Table 3.1). In the health arena, some losses of life and health may
occur days or months after the disaster and thus may go uncounted.
Geographic Variation in Economic Losses
Long-term disaster loss data for specific geographic regions provide a
baseline from which to measure improvements in resilience. The success of
measures to reduce disaster risk and impacts are difficult to evaluate without this
baseline information. A number of federal agencies compile separate data on
disaster losses and costs including the National Oceanic and Atmospheric
Administration (NOAA), FEMA, the U.S. Geological Survey (USGS), and the
Department of Agriculture. These data serve quite specific and useful purposes,
but in aggregate are incomplete, often incompatible with one another, have
limited economic impact information, and are less useful for mapping the
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76 DISASTER RESILIENCE: A NATIONAL IMPERATIVE
BOX 3.3
Which Economic Losses Are Counted?
Losses from natural hazards are normally divided into two major
categories--direct losses and indirect losses. Economic losses are
classified as stock losses (property damage) and flow losses (business
interruption). There are direct and indirect versions of each. For
example, direct property damage occurs from the seismic shaking
from an earthquake whereas indirect property damage can occur from
fires due to the rupture of a natural gas pipeline caused by the
earthquake. Direct flow losses occur to those businesses in the
affected area that had to shut down temporarily. Indirect flow losses
refer to the disruption in the supply chain for other businesses as a
result of the shutdown (a ripple effect caused by the
interconnectedness of many supply chains regionally and globally).
Other primary losses include the costs of repair and placement of
structures, the cost of debris removal, loss of jobs, loss of rental
income, and evacuation costs. Secondary losses such as those
associated with decreased tax revenues, decline in property values,
loss of attractiveness of tourist destinations, psychological trauma,
and the damage to natural systems are not taken into account in loss
tallies, yet these hidden costs may directly influence the affected
community's ability to manage disaster risk.
SOURCES: Heinz Center (1999), Rose (2004), Multihazard Mitigation Council
(2005), NRC (2006a); Gall et al. (2009).
geographic distribution and impact of such losses at the local (community to
state) scale. Currently, no comprehensive federal database or national archive
for disaster loss data exists (Mileti, 1999; NRC, 1999; Cutter, 2001). The
SHELDUS® (Spatial Hazard Event and Loss Database for the United States),
compiled from existing federal data sources, is the closest approximation to a
U.S. national inventory of direct disaster losses from natural hazards, but it also
underestimates the total value of losses because indirect losses and business
interruption are not included, for example. Such indirect losses can be
substantial (see Box 3.4).
SHELDUS information can be used to examine patterns losses from
natural hazards within the United States over the last 50 years. Figure 3.3 shows
that these losses tend to be concentrated in a few regions and within a few states.
The overall patterns highlight losses on the hurricane coast along the Gulf of
Mexico extending from Texas to Florida and up the Atlantic Coast to the
Carolinas. When normalized to losses per square mile (Figure 3.3b) the largest
cumulative losses are concentrated in California, western Washington, the Gulf
Coast and Florida, the Carolinas, the Northeast, and in the upper Midwest.
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MAKING THE CASE FOR RESILIENCE INVESTMENT 77
Table 3.1 Losses from Selected Weather-Related Hazards in the United States
for 2010.
Databasea Loss ($ Billion) Deaths
Munich RE 13.6 197
NCDC Billion Dollar Events 6.8 46
SHELDUS 8.8 266
EM-DAT 9.15 90
a
Munich RE = NatCatSERVICE (which includes total property loss, known insured property losses,
and estimated insured business interruption losses; NCDC Billion Dollar Events
(http://www.ncdc.noaa.gov/oa/reports/billionz.html#narrative) reported total property and crop loss;
SHELDUS = Spatial Hazard Events and Loss Database for the United States, maintained by the
Hazards and Vulnerability Research Institute at the University of South Carolina
(http://www.sheldus.org), reported total property and crop loss; EM-DAT = Emergency Events
Database, maintained by the Centre for Research on the Epidemiology of Disasters, CRED
(http://www.emdat.be), estimated property and crop loss, loss of revenues). See Gall et al. 2009 for
more details on the databases.
BOX 3.4
Spatial Hazard Event and Loss Database for the United States
(SHELDUS®)
SHELDUS is a county-level database for U.S. states of loss-causing
natural hazards that spans the period from 1960 to the present. The database
is maintained by the University of South Carolina's Hazards & Vulnerability
Research Institute. It reports only direct losses as defined by the federal source
data it uses (e.g., National Climatic Data Center's Storm Data; U.S.
Geological Survey Open File Reports), and does not include Puerto Rico,
Guam, or other U.S. territories. The historic Storm Data (1960-1995) used
logarithmic categories for losses; for example, an event with a loss category 5
represents losses of $50,000-$500,000 in that database. SHELDUS uses the
lower-bound value (e.g., $50,000), and as a result, the database is conservative
and provides the minimum value of losses over the specified time period.
Thus, losses are expected to be higher than those reported in the database, but
how much higher is presently unknown.
The database is available online (http:www.sheldus.org), can be queried by
individual hazard, by geography (state and county), by time period, by
presidential disaster declarations number, by major named disasters (e.g.,
Hurricane Katrina, Blizzard of 1967), and by GLIDE number (an international
standard numeric to enable linkages across databases). The database provides
property losses (recorded in period dollars); crop losses (recorded in period
dollars); injuries; fatalities; county, state, and federal Information Processing
Standard codes; and beginning and ending dates for when the information was
recorded. Losses can be converted to current dollars or standardized to any
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80 DISASTER RESILIENCE: A NATIONAL IMPERATIVE
Given that the past 50 years may not be a good indicator of future
patterns in hazard losses, either for weather-related events likely to be impacted
by climate change or for hazards with long return periods such as earthquakes,
other probabilistic models can be used to predict the potential distribution or
impact of future losses for the nation. FEMA's natural hazard loss estimation
model, HAZUS, enables users to project losses for a community or region based
on inputs about a specific event that is defined by the user. Alternatively,
HAZUS can provide probabilistic loss estimates nationwide when the USGS
probabilistic seismic source model is input. An example of the output of such
modeling is the annualized earthquake losses by county for the United States
(FEMA, 2008) (Figure 3.4).
Nationwide, the total modeled annualized loss of national building
stock from earthquakes is about $5.3 billion.2 If indirect business interruption
were taken into account the economic losses from earthquakes would be even
greater and more widely distributed. The map of total annualized earthquake
losses shown in Figure 3.4a demonstrates that nearly the entire nation is subject
to potential earthquake loss; however, the greatest risk exists along the West
Coast. Los Angeles County alone accounts for 25 percent of the entire nation's
annualized loss, which is not surprising considering the large number of active
faults in the region and the fact that the population of this single county is
greater than all but eight states in the country. California in total has about 66
percent of the nation's total annualized loss; the Pacific Northwest together with
California encompasses about 77 percent of the nation's annualized earthquake
loss.3 The map of normalized AEL (ratio of total loss to millions of dollars of
building inventory value) in Figure 3.4b highlights concentrated loss in regions
of high seismic hazard outside of the West Coast: the Wasatch Front in Utah
and extending north through the Rocky Mountains, as well as sites of historic
earthquakes in the central and eastern United States for which there is
geological evidence of repeated events over the past several thousand years
(New Madrid, Missouri region; Charleston, South Carolina; and along the Saint
Lawrence Seaway).
2
http://www.fema.gov/plan/prevent/hazus/hz_aelstudy.shtm.
3
http://www.fema.gov/plan/prevent/hazus/hz_aelstudy.shtm.
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MAKING THE CASE FOR RESILIENCE INVESTMENT 81
FIGURE 3.4 Annualized earthquake losses (AEL) derived from HAZUS using U.S. Geological
Survey probabilistic seismic hazard assessment as input. (a) AEL (total dollar value loss of all
structures included in the HAZUS exposure inventory); (b) normalized AEL (ratio of total loss to
millions of dollars of building inventory value (the value of all buildings in the study area). Source:
Federal Emergency Management Agency.
Human Losses and Loss-of-Life Data
Whereas national and global economic losses are growing annually, a
positive development is that human losses (deaths, injuries, displacements)
generally show the opposite tendency, especially in the developed world
(Goklany, 2009). In the United States, the number of fatalities due to disasters
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82 DISASTER RESILIENCE: A NATIONAL IMPERATIVE
has remained roughly steady between the 1990s and 2000s. In contrast, deaths
and numbers of people affected by disasters continue to grow in the developing
nations (IFRCRC, 2010); in fact, the number of people affected (those requiring
immediate assistance, those who are injured, or those made homeless from the
disaster) increased threefold during the first decade of the 21st century
(IFRCRC, 2010).
The declining number of deaths from natural disasters in the United
States and the rest of the developed world is mostly the result of improved
building codes and construction practices, improved awareness about disaster
risk, and more accurate forecasting and warning systems. Considerable
research on disaster mortality has been conducted, especially on specific perils
such as floods (Ashley and Ashley, 2008; Zahran et al., 2008), earthquakes
(Shoaf et al., 1998), and severe weather (Ashley, 2007). Well-established
research also exists on specific mortality-causing disasters such as Hurricane
Andrew (Combs et al., 1996), the Northridge earthquake (Peek-Asa et al.,
2000), the Chicago heat wave (Klinenberg, 2003), and Hurricane Katrina (Elder
et al., 2007; Jonkman et al., 2008). Despite those significant efforts, however,
research results on all-hazards mortality in terms of temporal and spatial
patterns are few (Borden and Cutter, 2008; Thacker et al., 2008) and do not
provide the quality and quantity of data necessary for understanding the overall
human losses.
As was the case with economic losses, loss-of-life data for disasters
can also be difficult to use and interpret (Box 3.5). NOAA and the Centers for
Disease Control (CDC) are the primary natural-disaster-fatality sources in the
federal government. Their data include direct and indirect fatalities related to a
disaster event. Death certificates are the source of the input data in CDC's
mortality databases. NOAA also records fatality statistics based on reports by
local National Weather Service offices and the news media and then
consolidates estimates into the monthly Storm Data. The CDC and NOAA
fatality databases differ in the classification of perils, which deaths are counted,
and the attribution of the death to a specific peril or place (Figure 3.5).
A further complication with mortality data is that most hazard-
mortality research uses raw counts of fatalities that are not adjusted to either
rates (deaths per population), densities (per unit area), or standardized mortality
ratios (accounting for the age/sex structure and size of the population). This lack
of refinement may present a very misleading indication of the nature of human
losses from natural disasters, especially when attempting to examine regional
variations. Moreover, the extreme variation in the scale of U.S. counties, both in
terms of population and area, makes interpretation of county-level maps, such
as those that illustrate this chapter, especially problematic. U.S. counties vary in
population from less than 100 to roughly 10 million, and in area from less than
2 square miles to more than 150,000 square miles. However, counties remain
the administrative unit for most hazard and risk management programs, and so
we opt to report data at this level of resolution.
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FIGURE 3.5 Hazard fatalities 1979-2004 compared by perils. Earth movements refers to
earthquake-related fatalities and landslides. (a) Centers for Disease Control and Prevention (Thacker
et al., 2008) and (b) National Oceanic and Atmospheric Administration (Borden and Cutter, 2008).
CDC data are more likely to include urban and exposure deaths (heat and cold extremes), whereas
NOAA data are biased toward more rural events such as lightning. The comparison illustrates the
difficulty and inconsistency in data and recording the peril that contributed to the hazard fatality.
Source: S. Cutter; complied from SHELDUS.
BOX 3.5
Problems with Collecting and Interpreting Disaster Fatality Data
Tracking deaths is relatively straightforward because all deaths are
required by law to be reported. The difficulties with disaster fatality data are in
how to attribute the cause of the death to a particular disaster or peril. This
designation will vary depending on who is doing the reporting and recording on
the death certificate. Attribution of the cause of death and the conditions
contributing to it become highly subjective, and pronouncing physicians may
have difficulties completely identifying the contributing conditions. For
example, if a person has a heart attack while shoveling snow, the death may or
may not be recorded as a disaster death depending on how the paperwork is
completed. The cause of death would be a heart attack, but the contributors
would be physical exertion due to the snowstorm. A further complication
related to disaster fatality statistics is determining the location where the death
occurred. A death certificate contains a place to fill in the geographic location
of the initial injury (street, county, zip code, etc.). If left blank, the fatality is
georeferenced to the place of residence of the deceased, or is recorded as the
place where the death pronouncement was made (e.g., a hospital). For example,
if a tourist from Arkansas died in a wildfire while on vacation in Colorado, the
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84 DISASTER RESILIENCE: A NATIONAL IMPERATIVE
death could be recorded as a wildfire fatality in Arkansas (where the person
lived), but it could also be listed for Colorado (where he or she died), depending
on how the death certificate was completed. Finally, problems arise with the
timing of the death. Many suicides and deaths related to toxic exposures post-
Katrina were not recorded as related to Katrina. Deaths from toxic exposures
experienced by first responders to the 9/11/2001 destruction of the World Trade
Center towers in New York City are still occurring.
Patterns of Exposure and Population Growth
Population growth affects exposure to hazards for a variety of reasons.
Understanding these population patterns through time allows assessment of
some of the underlying socioeconomic or demographic changes that may
contribute to the vulnerability of communities to disasters. Population growth
or decline in a geographic location can also relate to infrastructure issues
pertinent to the particular hazards associated with that region. For example, the
new infrastructure needs (housing, roads, bridges) that growing communities
need may require decisions to be made regarding land use and development in
undeveloped areas. These undeveloped areas may include areas of natural
defenses whose integrity may be important as a mitigation measure against
existing natural hazards (see Chapter 2). The United States is experiencing a
major transformation in population development patterns, which began in the
1970s with the movement of population out of the northern Rust Belt states into
the south and southwest. This period saw a tremendous influx into coastal
counties where approximately 53 percent of the U.S. population now resides
and where about half of the nation's residential units are located (Crosset et al.,
2004). Over the period from 2000 to 2010, the migration to the coastal counties
has slowed somewhat (Figure 3.6) although growth in selected Florida counties
exceeded 50 percent. Depopulation is another aspect that is visible in Figure
3.6, with much of the Great Plains showing decreasing populations. Also
notable is the declining population in counties bordering the lower Mississippi
River from southern Illinois to southern Mississippi (Mackun and Wilson,
2011). Large population losses during the decade occurred in Orleans and St.
Bernard parishes in Louisiana (due to Hurricane Katrina), in Cameron Parish,
Louisiana (due to Hurricane Ike), and in Issaquena and Sharkey counties in
Mississippi due to poor economic conditions and a long history of population
decline from the counties.
The aging of the U.S. population is also important to consider. The
growing number of older adults who need more specialized care will require
greater knowledge, expertise, equipment, and supplies during a disaster,
particularly during an evacuation. This problem was very clearly evident in the
hours and days that followed Hurricane Katrina, where responders were not
prepared to handle the medical needs they encountered in older adults (NRC,
2011).
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MAKING THE CASE FOR RESILIENCE INVESTMENT 85
FIGURE 3.6 Changes in housing units from 2000 to 2010. Counties with a decline in housing units
are shown in purple; areas with increasing housing units are shown in dark green. Source: S.
Cutter/HVRI.
What is missing from this narrative is the overlay of the population
shifts and residential housing units with consistent national probabilistic hazard
maps (such as the USGS National Seismic Hazard Map and the FEMA flood
zone maps) and with accurate mapping of both structural and social
vulnerability. Although existing data allow discussion about increases and
decreases in exposure, conclusions remain difficult to make regarding the
effects on resilience of changes in populations in hazardous zones such as flood-
prone areas or seismically active regions. Consistent multihazard data for the
entire country calibrated from the local to the state level together with local- to
regional-scale vulnerability data are needed to create true national risk maps to
allow comparison of relative risks from different perils as different return
periods. Such information could provide the basis for community prioritization
of limited resources to expend on reducing risk and building resilience.
KNOWLEDGE AND DATA NEEDS
The lack of standardization of data on hazardous conditions, disaster
losses, and impacts is a continuous challenge in the effort to understand and
managing risk and increase disaster resilience. Hazard and disaster informatics
is a relatively new scientific field, yet information derived from this area of
study is critical to the national resilience efforts. The CDC is beginning to
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86 DISASTER RESILIENCE: A NATIONAL IMPERATIVE
coordinate health and health-risk and emergency data from hospitals and health
departments, but medical professionals are a long way from having the ability to
access individual health records in an emergency, or recording losses of life and
health accurately following a disaster. A number of NRC reports recognize the
need addressing issues of hazard and disaster data collection, standardization,
management, archiving, and sharing (NRC, 2006b, 2007a,b,c). Whether such
principles are achieved through a nongovernmental panel looking at hazard and
disaster informatics (NRC, 2006a) or through the formal establishment of a
national loss inventory (Mileti, 1999; Cutter, 2001) or other mechanisms is open
for discussion. What is not debatable is the criticality of the need to solve the
disaster informatics issue.
SUMMARY AND RECOMMENDATION
The ability to measure and evaluate the assets of communities and to
understand the economic and human value of resilience is critical to improving
disaster resilience. The resources of a community involve more than the high-
value essential assets such as hospitals and utilities. They also include other
assets with high social, cultural, and environmental value, and so decision-
making models developed by communities have to involve both quantitative
and qualitative "valuation" of assets in order to prioritize resilience investments.
Presently, little guidance exists for communities to understand how to place
meaningful value on both their quantitative and qualitative assets.
In developing the case for enhancing resilience now and providing
motivation for community decision makers to understand their inventory of
assets and the ways in which they interact with one another, this chapter has
also outlined the historical spatial and temporal patterns of economic and
human disaster losses on communities in the United States. Although the data
available to assess economic and human losses nationally are conservative and
are neither comprehensive nor centrally archived for the nation, the historical
patterns of economic losses from hazards and disasters in the United States
appear to be increasing and will be expensive to absorb, if allowed to continue.
A positive sign--a declining tendency in human losses (fatalities) from disasters
in the United States and other developed countries--attests to the success of
some resilience-building measures. Improved building codes, improved
awareness, and more accurate forecasting and better warning systems are some
of the factors researchers think may contribute to fewer fatalities from disasters.
However, changing patterns of hazards as well as changes in
population and vulnerability affect economic and human loss patterns.
Attempts to improve resilience of individual communities and the nation require
more consistent hazard and risk assessments supported by consistent and
centrally available disaster loss data. Accurate loss and casualty data on past
disasters enable researchers to better constrain the factors controlling the
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MAKING THE CASE FOR RESILIENCE INVESTMENT 87
structural and social vulnerability of communities and also enable practitioners
to quantitatively calibrate risk/loss models and make more accurate predictions
of future losses. This lack of data compromises the ability of communities to
make informed decisions about resilience-building strategies. Importantly, the
need for resilience-building strategies continues even if historical patterns of
loss begin to improve.
Recommendation: A national resource of disaster-related data should be
established that documents injuries, loss of life, property loss, and impacts
on economic activity. Such a database will support efforts to develop more
quantitative risk models and better understand structural and social
vulnerability to disasters. To improve access to these data, the principle of
open access should be recognized in all relevant federal data management
policies. The data should be made accessible through an Internet portal
maintained either by a designated agency or by an independent entity such as a
university. The National Science and Technology Council (NSTC) would be an
appropriate entity to convene federal and state agencies, private actors,
nongovernmental organizations, and the research community to develop
strategies and policies in support of these data collection and maintenance goals.
Such a data inventory would reconcile and integrate the fragmented
federal datasets on disasters and losses; serve as a national data archive for
historic hazard events and loss data; assist in the development of better loss
metrics; and provide the evidentiary basis for potentially evaluating resilience
interventions. Federal agencies, private actors, and the research community
working in concert would improve post-event data collection and public access
to such data, would determine essential data, standards, and protocols to
employ, and determine which agencies are best positioned to collect and archive
specific data on the impacts of hazards. Such an approach helps to avoid
duplication of efforts. Likely federal actors include FEMA, NOAA, CDC,
USGS, the U.S. Forest Service, and the U.S. Army Corps of Engineers. Biennial
status reports coordinated by the NSTC on the nation's resilience could be
based in part on an analysis of these data, and could include priorities for future
data collection and dissemination. At the same time, data on resilience are also
lacking. Chapter 4 discusses specific ways in which resilience can be measured
and used as a basis for such status reports.
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88 DISASTER RESILIENCE: A NATIONAL IMPERATIVE
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