CHAPTER 8

# MYTHS AND REALITIES OF

# HOUSEHOLD DISASTER RESPONSE

Expectations about people's behavior during disaster impacts shapes the
way that emergency managers plan for community emergency response. This
chapter examines the prevailing myths and misconceptions about people's
behavior in disasters and contrasts these with the findings of research
on how people actually respond in emergencies. In particular, this
chapter emphasizes the relationship between households and the community
emergency response organization in connection with the population
protection function---especially warning and the implementation of
protective actions such as evacuation and sheltering in-place.

**Introduction**

Even people who have never been in a disaster hold definite beliefs
about how others typically respond when disaster strikes. Unfortunately,
disaster researchers have been forced to label many of these beliefs as
*disaster myths* because five decades of research have found little
support for their validity. Some disaster myths have a grain of truth
but are overgeneralized. That is, people assume them to be true for all
(or at least most) victims but, in fact, the myths only apply to a very
small minority. Other disaster myths have no validity whatsoever. A
common theme among these disaster myths is that disaster victims are so
psychologically fragile as to be incapable of taking care of themselves,
whereas others are so predatory that they will take advantage of any
disruption in social control (e.g., police surveillance) to prey upon
others. Thus, according to these myths, local authorities must cope with
widespread panic, disaster shock, and looting. The logical consequence
of these myths is that external authorities must intervene as powerful
rescuers to take care of the helpless victims.

The rather bleak and depressing view of human nature that these disaster
myths express is propagated by the mass media---sometimes in movies,
other times in (second- or third-hand) hearsay passed on by reporters,
and occasionally by disaster victims themselves (Drabek, 1997; Fischer,
1998). These disaster myths can create problems if they distort the
assumptions upon which emergency preparedness and response are based.
Local emergency responders have limited resources, so they must base
their actions on victims' actual needs rather than mistaken conceptions
of those needs. Some risk area residents do indeed require a substantial
amount of assistance, but most households will be largely
self-sufficient. Most disaster victims are psychologically resilient and
engage in socially integrative---rather than destructive---responses. As
the following sections indicate, many people stricken by community-wide
disasters take considerable personal initiative and improvise adaptive
responses to unfamiliar circumstances. Disasters frequently produce a
convergence of volunteers who provide support (behavioral, material, and
emotional), as well as the emergence of organized groups. If emergency
managers understand how many households can take care of
themselves---and, better yet, identify which parts of the community are
most likely to be self-sufficient---then the emergency response
organization can focus its efforts on those who are truly needy.

This chapter examines what is known about people's responses to natural
and technological disasters, and also extrapolates from that information
to infer what might be reasonably expected in connection with terrorist
incidents. As noted in Chapter 5, natural disasters and accidental
technological accidents vary with respect to the threats they pose to
society. Consequently, they can vary in their psychological impact on
citizens and the demands they place on emergency response organizations.
Terrorist incidents do not differ in the nature of the threats to
society; the same types of materials, energy, and information could be
involved in an accidental incident as in a deliberate incident. What is
likely to be different about terrorist incidents is their greater
frequency compared to accidental incidents and the deliberate selection
of hazard agents (radiation, for example) that generate higher and more
acute levels of fear than others (Slovic, et al., 1980). Indeed, an
often noted finding from studies of the reactor accident at Three Mile
Island is that, when facing a perceived radiation threat, local
residents expressed higher levels of concern, warning compliance, and
spontaneous evacuation than were anticipated by authorities (Lindell &
Perry, 1992). Thus, examining data on human response to similar hazard
agents can provide meaningful guides both to household response and
organizational response needs in terrorist incidents---even those that
have not previously been experienced.

**Myths of Household Response to Disasters**

According to widespread belief (and common depictions in the media),
disaster victims typically act irrationally. They flee in panic, wander
aimlessly in shock, or comply docilely with the recommendations of
authorities. Following impact, they are incapable of protecting
themselves or others, let alone protect their property from further
damage. Thus, they need assistance from governmental agencies or NGOs
such as the American Red Cross. The widespread breakdown of the social
order leads to looting in evacuated areas and an increase in the rates
for other crimes, as well. Consequently, martial law must be declared to
restore order in the impact area. Moreover, concerned citizens must
travel to the impact area to donate blood, food, and clothing. Indeed,
decades of movies, novels, and press coverage of disasters emphasize the
general theme that a few "exceptional" individuals lead the masses of
frightened and passive victims to safety (Wenger, 1980). Thus,
conventional wisdom holds that victims typically respond to disasters
with shock, passivity, or panic (Drabek, 1997; Perry, 1983).

Social scientific studies have repeatedly demonstrated that none of
these responses represents the reaction of the majority of disaster
victims (Quarantelli, 1954; Quarantelli & Dynes, 1972; Wenger, Faupel &
James, 1980; Goltz, Russell & Bourque, 1992; Johnson, Feinberg &
Johnston, 1994). Indeed, most people do not develop shock reactions,
panic flight occurs only rarely, and people tend to act in what they
believe is their best interest, *given their limited understanding of
the situation*. As Chapter 4 indicated, most people respond
constructively to environmental threats by seeking information and
progressing through a reasonably logical sequence of steps in
determining how to cope with a threatening event. Moreover, behavior in
the emergency response phase is generally prosocial as well as rational.
After a disaster strikes, uninjured victims are often the first to
search for survivors, care for those who are injured, and assist others
in protecting property from further damage. When they seek assistance,
victims are more likely to contact informal sources such as friends,
relatives, and local groups rather than governmental agencies or even
such quasi-official sources as the Red Cross. Antisocial behaviors such
as looting are relatively rare, while crime rates tend to *decline*
following disaster impact. People tend to converge on disaster scenes to
offer help and even many of those who are geographically distant send
money and supplies. The picture that emerges of disaster victims is one
of responsible activism, self-reliance, community support, and
adaptation the situation as best they understand it, using whatever
resources are available. Victims are typically supported in their
efforts by official organizations and resources, but also by
contributions from other people not directly affected by the event.

The myths of irrational and antisocial behavior in disaster are not just
erroneous; they can hamper the effectiveness of emergency planning by
misdirecting the allocation of resources and the dissemination of
information (Tierney, et al., 2001). For example, expectations of panic
often become the justification for giving the public incomplete
information about an environmental threat or withholding it altogether.
This response to the myth of panic is particularly troubling because
people have been shown repeatedly to be more reluctant to comply with
recommended protective actions when they are provided with vague or
incomplete information in warning messages. The misconception that
accurate information will cause panic sometimes leads officials to
release information that actually *decreases* the likelihood of
compliance. Consequently, an important part of the emergency planning
process involves review not only of physical or biological science
literature on the hazards to which a community is exposed, but also of
the behavioral science literature describing the response patterns of
affected populations. The behavioral record is very clear with respect
to three commonly held beliefs about disaster victims'
reactions---disaster shock, panic flight, and socially integrative
responses.

### Disaster Shock

Following disasters, there have been documented reports of a condition
characterized by a state of shock associated with docility, disoriented
thinking, and sometimes a general insensitivity to cues in the immediate
environment. Wallace (1957) described the shock behavior that
characterized surviving victims whose friends and family members were
killed in the context of assaults on American Indian settlements.
Menninger (1952) reported on transient "apathy, confusion and disbelief"
among some flood victims. Particularly in the literature of clinical and
community psychology, there have been many studies identifying cases
where disaster shock symptoms have appeared. Melick's (1985) review of
studies conducted between 1943 and 1983 yielded three important
conclusions. First, disaster shock appears most frequently in sudden
onset, low forewarning events involving widespread physical destruction,
traumatic injuries, or death (Fritz & Marks, 1954; Murphy, 1984; Melick,
1985). Second, when the symptoms do appear, a relatively small
proportion of the disaster stricken population is affected. In one of
the classic studies of the phenomenon, Fritz and Marks (1954) found 14%
of their random sample showed evidence of the early symptoms associated
with the disaster shock. Most of those who report any symptoms of
disaster shock report only mild ones. For example, Moore (1958) reported
that 17-30% of families exposed to the Waco tornado claimed at least one
member (usually a child) experienced "emotional upset". Taylor's (1977)
study of the Xenia, Ohio Tornado reported "trouble sleeping" was the
most common symptom, with a frequency of 27%. Third, the disaster shock
is transient in that it usually persists for a maximum of a few hours or
days, rarely being detected outside the immediate postimpact period.
This is not to say that psychological consequences vanish after
disasters. Depending upon the nature and severity of the event and
specific characteristics of the victim, studies have concluded that
situational anxiety, phobia, and depression (among other diagnosable
psychopathology) with a presumed disaster etiology can persist for years
(Gleser, et al., 1981). However, these disorders are psychological
conditions that are clearly distinct from disaster shock.

In general, the impact of natural and technological disasters is not
associated with substantial increases in mental health problems in the
affected population. Indeed, following the 1978 floods in Rochester,
Minnesota, Ollendick and Hoffman (1982) reported one third of their
sample of victims claimed they were able to function *better* after
their disaster experience. Consequently, emergency managers should
expect disasters to produce a significant number of minor psychological
consequences but very few major psychological consequences in the
aftermath of disaster. Singer (1982, p. 248) succinctly summarizes
empirical findings with the following generalization:

> Reports of actual experiences reveal that most persons respond in an
> adaptive, responsible manner. Those who show manifestly inappropriate
> responses tend to be in a distinct minority. At the same time, most
> people do show some signs of emotional disturbance as an immediate
> response to a disaster, and these tend to appear in characteristic
> phases or stages.

Disasters of any kind constitute significant life events for victims.
Reactions sometimes documented after natural and technological disasters
include sleep disruptions, anxiety, nausea, vomiting, bedwetting, and
irritability (Houts, et al., 1988). In a very few cases, serious
psychological consequences such as extended grief reactions, depression,
and psychoses ensue (Erikson, 1976). Such conditions are most likely to
follow disasters that fit a profile of being sudden, lacking warning,
creating physical destruction and death, and lacking apparent "rational"
explanation. However, these conditions are most commonly found in people
who have chronic psychological problems, making it difficult to directly
attribute them to any particular disaster incident. Thus, certain types
of disaster experiences could aggravate preexisting conditions that were
not diagnosed prior to the disaster.

For the most part, people presenting disaster shock symptoms seem to be
able to develop functional coping mechanisms for these disorders with
minimal (if any) intervention by mental health professionals (Gist,
Lubin & Redburn, 1999). What is important for emergency managers to
understand is that such short-term stress reactions do not interfere
with disaster victims' abilities to act responsibly on their own or to
follow instructions from emergency response officials. Isolated cases of
immobilizing shock are reported among some people in some disasters, but
such reactions are very rare and certainly cannot be described as
typical of the population as a whole (Wert, 1979). In summary, disaster
shock is a topic of significant theoretical interest to disaster
researchers and of practical relevance to mental health professionals,
but emergency managers should be aware that this reaction occurs so
infrequently that it will not impede emergency response and disaster
recovery operations.

### Panic

Perhaps the most stubborn myth about human response to disasters is the
idea that panic is a major problem in emergency management. In general,
"panic can be defined as an *acute fear reaction* marked by a loss of
self-control which is followed by *nonsocial* and *nonrational* flight
behavior" (Quarantelli, 1954, p. 272, emphasis added). Although such
panic flight is a staple of horror books and movies, it is a rare
response to natural or technological disasters. It is important to also
emphasize that the experience of fear is not the same as panic. People's
fear of disaster impacts motivates them to take actions that will avoid
those impacts. Thus, it is an overwhelming level of fear---panic---that
causes people to take actions that are either nonrational (e.g., moving
into areas of greater danger) or nonsocial (e.g., deliberately impeding
others' self-protective actions).

The pervasive myth of panic flight in response to disasters is
perpetuated by a set of erroneous inferences from the available
information people have about disasters. First, people tend to think
that panic is common because victims often label their immediate
reaction to the situation as one of "panic" when interviewed in the news
media. Careful scrutiny of these victims\' statements ("When I saw the
funnel cloud, I panicked") indicates they are referring *only* to the
first of Quarantelli\'s conditions---the acute fear reaction. Subsequent
statements from the victim describing rational protective responses
("\...so, I grabbed the baby out of the upstairs bedroom and ran down to
the basement just before the house collapsed") are often ignored. A
second reason why panic is thought to be common is that observers
misinterpret the state of mind of disaster victims who took unsuccessful
actions. For example, a news story might assert that the victims of a
motel fire found dead in a hall storage closet got there because they
"panicked". A more plausible explanation is that in crawling through the
zero visibility heavy smoke, the victims reasonably---but
erroneously---concluded that the first unlocked door they encountered in
this unfamiliar hallway was the door to the stairwell. Once they
realized their mistake, it might have seemed safer to remain in the
closet (fire safety instructions typically recommend sheltering in
rooms) or their exit may have been blocked by the sure peril of
advancing flames. In short, the fact that an error of judgment has
produced fatal consequences does not provide *prima facie* evidence of
panic.

Indeed, even when disaster victims are successful in avoiding death,
observers often interpret any attempt to flee the hazard as evidence of
panic. Yet, in light of Quarantelli\'s definition of panic, it is
difficult to see why anyone would assume that it is anything other than
*rational* to want to put distance between oneself and a
life-threatening event such as a fire, or to move quickly to leave the
vicinity of crumbling buildings in an earthquake or terrorist bombing.
In such cases, those affected are assessing a threat in the environment
and coping with it (and their fear as well) by taking an immediate
protective action.

Of course, some examples of panic flight cannot be explained away as
observer errors. While it is indeed very rare, panic flight does occur
under certain circumstances. In research dating back to the early 1950s,
analysis of situations in which panic flight took place indicates
several conditions must occur, probably simultaneously, in order to
evoke mass panic flight (Fritz, 1957; Quarantelli, 1981b; Drabek, 1986).
These are: (1) a perception of immediate and extreme danger; (2) the
existence of a limited number of escape routes; (3) a perception that
the escape routes are closing, necessitating immediate escape; and (4) a
lack of communication about the situation. It is important to recognize
that these conditions are defined in terms of an individual\'s
perceptions or beliefs; thus, the conditions are based on *what* *those
at risk believe to be true at the time*, not upon *what others know
after the fact*. It is also important to note the distinction between
the occurrence of an event and the potential for dangerous consequences
resulting from that event. In this connection, Quarantelli (1954, p.
274) has observed:

> Coal miners entombed by a collapsed tunnel who recognize they will
> have sufficient air until rescuers can dig through to them do not
> panic. \[Panic occurs in reaction\] to the immediate dangerous
> consequences of possible entrapment rather than to being trapped as
> such.

In summary, panic has sometimes been documented in response to both
natural and technological disasters, but it is not a common reaction to
any type of disaster. When panic flight is observed, it seems to involve
a relatively small proportion of the people exposed to the threat and
does not usually persist for any period of time. Emergency managers
should know that panic does not always materialize even in cases where
conditions support its emergence. For example, Johnson (1988) reported
that evacuation was orderly and altruistic responses were common during
the 1977 Beverly Hills Supper Club fire in Kentucky (where 160 patrons
died). Similar findings have been reported in other fires (Canter,
Breaux & Sime, 1980; Keating, Loftus & Manber, 1983; Johnson, et al.,
1994). Furthermore, Aguirre, Wenger, and Vigo (1998) reported the
evacuation of the World Trade Center in 1993 was tense but orderly, with
no reports of panic. Although some observers might think victims of the
2001 World Trade Center attack who jumped to their deaths were driven by
panic, this does not seem to be the case. The fact that 99% of those
below the impact floors evacuated successfully suggests those who jumped
chose to die quickly on impact rather than slowly and painfully in the
raging fire (National Institute for Standards and Technology, 2005).

### Socially Integrative Responses

Since Fritz and Mathewson (1958) coined the term *therapeutic
community*, it has been known that disasters often produce a shift in
values and norms that results in socially integrative responses. Wenger
(1972) has documented the virtual termination of socializing and social
participation (e.g., clubs), curtailment of nonessential activities
associated with production-distribution-consumption (e.g., luxury
goods), and decline in social control problems (e.g., minor traffic
offenses, domestic disputes) following disasters. At the same time,
there is usually an increase of mutual support functions among victims
and others in stricken communities (Wilmer, 1958; Fritz, 1961; Boileau,
et al., 1979). The appearance of these conditions or behaviors produces
what Barton (1969) has called the *altruistic community* and what others
refer to as the *therapeutic community response* (Fritz, 1968;
Midlarsky, 1968). The previous section mentioned that disaster victims
often initiate such urgently needed activities as search and rescue and
emergency first aid rather than passively await intervention by official
emergency response teams. It is also known that people in the disaster
impact area engage in helping behaviors directed at victims. Thus, at
least in the immediate post-impact period, the experience of disaster
has integrative effects upon the "community of sufferers" and in the
short run promotes cohesion among victims, as well as between victims
and those in unaffected areas of the community.

*Convergence*. The therapeutic community response is related to
convergence behavior, which is always a challenge for local emergency
managers, and accompanies virtually all disasters. Convergence takes
place when a stricken community becomes the focus of an aid-giving
effort on the part of surrounding communities and individuals, larger
political entities (counties, states and the federal government), and
private organizations. This aid takes the form of spontaneously
volunteered human and material resources. The positive impact of
convergence can be seen in the increase of local authorities\' resource
base for emergency management and also upon the morale of victims.
Victims interpret the presence of such help as evidence that others care
and that the catastrophe can be overcome.

Although the influx of people and materials can provide local emergency
managers with resources needed to respond effectively to the
agent-generated demands of the disaster, convergence can produce
unprecedented communication and response difficulties. For example,
Kartez and Lindell (1987) described a Louisiana air crash in which fire
departments from distant communities appeared at the crash site
unrequested. This created a serious strain on the local authorities'
ability to not only deal with the crash but also to handle the logistics
associated with additional responders. To complicate matters further,
unsolicited materials can also arrive unannounced early in the incident
and continue to arrive for days or weeks thereafter. Thus, emergency
managers need to be aware of the convergence of volunteers and
unsolicited contributions of resources. When convergence processes
inundate them with unanticipated people and materials, a potential asset
becomes a liability. This makes it essential to develop donations
management procedures such as SUMA (Supply Management) which was
developed by the Pan American Health Organization (PAHO) to facilitate
the integration of volunteers into the response force; the management
and care of volunteer labor; and the logistics of receiving, storing,
and deploying material and equipment.

*Resources*. A second aspect of the positive social response is the
generosity of nonvictims. This is related to, but distinct from, the
convergence response. We are referring here to the volunteering of
direct help to victims in the form of needed clothing, food, and
lodging. Perhaps the earliest documentation of this type of response is
found in Prince's (1920, p. 137) study of an explosion in Halifax, Nova
Scotia.

> The idea spread of taking the refugees into such private homes as had
> fared less badly. It became the thing to do. The thing to do is social
> pressure. It may be unwilled and unintended but it is inexorable. It
> worked effectively upon all who had an unused room.

Since the time Prince conducted his study, further research has been
conducted on the extent to which community members not directly impacted
by the event support the victims (e.g., Midlarsky, 1968; Vallance &
D'Augelli, 1982). Such helping behavior directed at (and among) victims
may be seen as a normative response. What is important from the
standpoint of emergency management, however, is the positive social
climate created by such altruism.

The result of these psychological and social processes is a therapeutic
social system in which an unplanned outpouring of personal warmth and
direct help provides support to many victims in a time of considerable
sorrow and stress (Barton, 1969). This is not to say that these
naturally occurring social processes provide complete support for
victims or that they entirely mitigate the negative psychological
consequences of disaster impact. Both natural and technological
disasters are calamitous experiences for many victims. Terrorist events
also can be expected to elicit extreme outpourings of help to the
perceived blameless victims. The scale of giving following the 9/11
terrorist attacks stands as an extreme example. It is essential for
emergency managers to recognize disasters cause indirect positive
effects as well as the more direct, and certainly more widely known,
negative psychological impacts.

It is also important to appreciate the likely persistence of the
therapeutic community response over time. Early researchers saw the
therapeutic community as "an outpouring of altruistic feelings and
behavior beginning with mass rescue work and *carrying on for days,
weeks, possibly even months after the impact*" (Barton, 1969, p. 206,
emphasis added). Regrettably, research on the persistence of the
therapeutic community response has been insufficient to permit confident
acceptance of Barton\'s hypothesis of long-term persistence. As Dynes
and Quarantelli (1976; see also Quarantelli & Dynes, 1977) suggest, the
therapeutic community may not be a long lasting condition. Although
their work does not directly test Barton\'s proposition, they have found
that decreases in community conflict and the apparent increase in
community consensus following disasters are short-lived phenomena. While
the empirical record is too sparse to support specific time estimates,
some conflict regarding the distribution of contributed funds and
materials began to arise within six months following the 9/11 terrorist
attacks. There is agreement regarding the development of a therapeutic
community in the short-term aftermath and that it should be seen as
promoting positive psychological outcomes for disaster victims.
Emergency managers planning for the recovery period, however, are well
advised to remember that the duration of situational therapeutic norms
is limited.

**Other Misconceptions and Erroneous Assumptions**

Less prominent, but just as damaging, are some specific misconceptions
and erroneous assumptions that about households' emergency response.
Misconceptions are *explicit* beliefs that are relatively easy to
identify and correct. By contrast, erroneous assumptions are *implicit*
and, therefore, more difficult to correct. Whether these erroneous
beliefs are explicit or implicit, they produce a distorted image of the
processes by which risk area residents receive warnings, evaluate the
information, make decisions, and take action to protect themselves,
their loved ones, and their property. The most serious misconceptions
and erroneous assumptions about household response are discussed below.

*Population Segments*

One of the most common misconceptions is that there is an
undifferentiated "public" when, in fact, there are many population
segments that differ in their hazard knowledge, family roles, and
household resources. In particular, emergency mangers must distinguish
among residents, transients, and special facility populations because
these population segments differ in their willingness and ability to
evacuate (Drabek, 1996; Urbanik, 2000). Residents are those who live or
work in the risk area, whereas transients consist primarily of those who
stay in hotels/motels--- although day visitors can be a significant
concern in rapid onset disasters. However, day visitors are unlikely to
be a problem for hurricanes and other hazards with forewarning because
they are likely to leave very early. Special facilities include schools,
hospitals, nursing homes, and jails (for a more complete list, see Table
6-2). Special facility populations typically must be analyzed separately
because their patterns of warning and evacuation are very different from
those of residents and transients (Urbanik, 2000).

*Warnings*

It is commonly assumed that authorities are the first to warn risk area
residents and also that authorities provide almost all the information
about a disaster. However, as indicated by the Protective Action
Decision Model (recall the discussion in Chapter 4), people also rely
substantially on the news media, peers, and environmental cues to
determine if disaster impact is likely to affect them. People also
observe the behavior of others (peers evacuating and businesses closing)
to assess the need for protective actions such as evacuation. They also
seek to confirm warnings, regardless of the initial warning source, to
verify the information they have received, and to work out the logistics
of response (mode of transportation, route of travel, shelter
destination). Indeed, in a major disaster, the volume of calls into and
within the impact area can overload the available telephone circuits.

The process of warning dissemination generates a distribution of times
at which households first receive a warning. Figure 8-1 shows the
cumulative distribution of warning receipt over time of the type
reported by Rogers and Sorensen (1988). The curve is nonlinear so the
rate of warning receipt first increases and later decreases over time.
For example, 39% receive a warning in the first hour, another 47%
receive a warning in the second hour, only 12% receive a warning during
the third hour, and 1%. receive a warning in the fourth hour. The last
few people take a long time to receive a warning.

Whether people receive a warning and when they receive one has been the
subject of substantial research over the past five decades (Lindell &
Perry, 2004). Warning sources differ in their accessibility and these
differences can vary by community. For example, Lindell and Perry
reported that the majority of those at risk from the eruption of Mt. St.
Helens received their first warning from peers (see Table 8-1). In
Toutle (a town very close to the volcano), 58% of the population
received their first warning from peers, whereas in Woodland (which was
farther away), 47% received their first warning from this source. The
greatest differences between communities were associated with the news
media; 39% of the Woodland residents but only 6% of the Toutle residents
received their first warning from this source.

In part, the extent to which any source provides the first warning---and
the rate at which the entire population is warned---depends on the
communication channels each source uses. Lindell and Perry (1992)
summarized the available warning mechanisms as face-to-face, route alert
(loudspeaker broadcast from a moving vehicle), siren, commercial radio
and television, tone alert radio (which only broadcasts a warning within
the home after receiving a special tone from the National Weather
Service), telephones, and newspapers. These warning mechanisms differ
with respect to their precision of dissemination, penetration of normal
activities, message specificity, susceptibility to message distortion,
rate of dissemination over time, receiver requirements, sender
requirements, and feedback (verification of receipt). Sources using
channels that have more rapid dissemination rates will produce steeper
warning curves. However, commercial radio and television cannot provide
warnings unless they are turned on, which limits their effectiveness
when people are asleep or outdoors. Conversely, sirens have limited
penetration into homes when people are engaged in noisy activities or
are asleep. Thus, the effectiveness of a given warning mechanism varies
with the types of activities in which people are engaged. Across a broad
range of situations, tone alert radio has been consistently effective in
providing rapid warning dissemination.

[**Figure 8-1**. Cumulative Distribution of Household Warning Receipt
over Time.]{.underline}

> ![](media/image1.wmf)

Source: Lindell, et al. 2002)

For hazard agents lacking environmental cues such as sights (smoke),
sounds (explosions), or smells (chemical odors), people must rely on
social sources of information---authorities, news media, and peers.
Thus, the time it takes each household to receive a warning from
authorities depends upon the warning mechanisms the authorities use. For
example, warnings disseminated by route alert depend on the number of
vehicles dispatched and the speed at which they travel. By contrast,
warnings disseminated by tone alert radio depend upon who owns these
devices.

**[Table 8-1]{.underline}**. Source of First Eruption Warning, by
Community.

  ------------------ ------------- ------------- ------------- ------------
                     Toutle                      Woodland      

                     Number        Percent       Number        Percent

  Saw environmental  27            30            12            14
  cues                                                         

  Authorities        6             6             0             0

  News media         6             6             34            39

  Peers              51            58            41            47
  ------------------ ------------- ------------- ------------- ------------

Source: Lindell and Perry (1992)

The time it takes each household to receive a warning from the news
media depends upon whether people have turned on their televisions or
radios and are attending to them. Although access to the news media
varies to some extent among households, it varies even more by time of
day---with the highest levels being reached during the day and early
evening (Lindell & Perry, 1992; Rogers & Sorensen, 1988).

The time it takes each household to receive a warning from peers depends
the extent to which people are integrated into social networks (Drabek &
Stephenson, 1971), which is correlated with a number of variables.
Specifically, social integration with both kinship groups (relatives)
and community groups (friends, neighbors, and coworkers) is negatively
correlated with age (Perry, 1985; Perry, et al., 1981), socioeconomic
status (Alvirez & Bean, 1976; Cohen & Kapsis, 1978), and ethnicity
(Bianchi & Farley, 1979; Staples & Mirande, 1980). The latter variable
introduces some complexities because minority households are more likely
to be extended families, to involve multigenerational depth, and to have
more than a single family in the same household. Thus, although ethnic
minorities are more integrated into kinship networks, there is a greater
probability that some family members may not be present, thereby slowing
later stages of the warning response until they can at least be
accounted for.

There is substantial variation across communities in the relative
importance of different warning sources to different ethnic groups.
Perry and Mushkatel (1986) found that Hispanics in three communities
were consistently more likely to receive their first warning from peers.
However, the role of the news media as a warning source for this ethnic
group varied among communities. Differences across communities were even
more striking for African-Americans. In one community, African-Americans
received their first warning from authorities. However, in another
community, almost no African-Americans received their first warning from
this source. There were also differences across communities for Whites.
In one community, the majority of Whites received their first warning
from the news media. However, in another community, peers were the most
common source of first warning.

*Personal risk assessment and response*. Consistent with common
assumptions, people do rely on authorities for information about what
protective actions to take and when to take them. However, they also
rely on the news media, peers, environmental cues, and their own
preexisting beliefs about appropriate protective actions. For example,
Perry and Greene (1983) reported the four most important reasons for
evacuating in the Mt. St. Helens eruption were environmental cues
(29.1%), authorities' evacuation recommendations (26.6%), relatives'
evacuation recommendations (20.3%), and observations of neighbors
leaving (12.7%). Contrary to most people's assumptions, personal
experience has no consistent effect on evacuation (Baker, 1991). In
particular, there is no evidence that false alarms depress the
likelihood of future evacuation (Dow & Cutter, 1998). However, false
alarms do cause decreased confidence in official warning sources
compared to the news media and peers. Thus, authorities should explain
that forecasts and warnings cannot be made with complete certainty.
Indeed, Sorensen (2000, p. 121) concluded "\[t\]he likelihood of people
responding to a warning is not diminished by what has come to be labeled
the 'cry wolf' syndrome *if the basis for the false alarm is
understood*" (emphasis added).

For the most part, demographic variables have limited value in
explaining people's warning responses. After an exhaustive review of
research, Quarantelli (1980, p. 43) stated "studies dealing with
demographic characteristics and evacuation are simply not conclusive."
Baker's (1991) review of hurricane evacuation studies reached a similar
conclusion. This means that source and message characteristics are the
most important determinants of household warning response.

*Evacuation trip generation.* Evacuation trip generation refers to the
number and location of vehicles evacuating from a risk area. People
often assume all vehicles in a risk area will evacuate, but this is not
the case. Lindell and Prater (2005) have shown how the number can
actually be estimated using procedures developed by traffic engineers
and disaster researchers. There are three parameters affecting trip
generation that emergency managers can estimate from US Census data for
their jurisdictions. These are the size and distribution of the resident
population, the number of persons per residential household, and the
size and distribution of the transit dependent resident population. In
addition, data from two variables can be collected from the Local
Visitors' Bureau. These are the size and distribution of the transient
population and the number of evacuating vehicles per transient
household. Finally, there are four variables that must be estimated from
behavioral research. These are the number of evacuating vehicles per
residential household, the number of evacuating trailers per residential
household, the percentage of residents' protective action recommendation
(PAR) compliance/spontaneous evacuation, and the percentage of
transients' PAR compliance/spontaneous evacuation.

Emergency mangers need to recognize that the resident population is
nonuniformly distributed within risk areas, but they can estimate
population size and distribution with Geographical Information Systems.
For example, they can overlay risk area boundaries onto census block
group boundaries and use this information to compute each risk area's
residential population (Lindell, et al., 2002b). In addition, emergency
managers should recognize that risk area residents are also nonuniformly
distributed in time (Alam & Goulias, 1999; Barrett, Ran & Pilai, 2000;
Urbanik, 2000). That is, structures are completely occupied at some
times, partially occupied at others, and sometimes completely empty.
Over 90% of the population is indoors at home from 10:00 p.m. to 6:00
a.m., but only about one-third is there from 10:00a.m. to 3:00 p.m.
(Klepeis, et al., 2001). This implies that evacuations initiated during
daytime hours should incorporate a time component for travel from work
to home (for adults) or school to home (for children when school is in
session). Such diurnal variation is especially important for the
evacuation of areas around nuclear and chemical facilities that can have
incidents with very short forewarning (Hobeika, Kim & Beckwith, 1994;
Urbanik, 2000). However, the ample forewarning of a hurricane leads
families to stay home in anticipation of an evacuation (Lindell, Lu &
Prater, 2005). In such incidents, emergency managers will generally have
little need to adjust for diurnal variation in household activity.

There is a tendency for most people to assume that all households have
their own private vehicles, but emergency managers should also recognize
the transit dependent segment of the resident population (Urbanik,
2000). The transit dependent segment can be as much as 15% or more of
the population in some coastal counties exposed to hurricanes and,
contrary to most people's assumptions, this level of transit dependence
can be found in both rural and urban counties. Also contrary to most
people's assumptions, much of the transit dependent population evacuates
with peers (Lindell, et al., 2005). Thus, the number of buses needed to
evacuate the transit dependent is likely to be smaller than expected.
However, some emergency managers fail to recognize that the time
required to mobilize buses, pick up evacuees at designated staging
areas, and travel out of the risk area might be greater than the time
required to evacuate households in cars. This is especially likely if
the transit dependent must share a limited number of buses with special
facilities.

Emergency managers should also estimate the size and distribution of the
transient population from local convention/visitor bureau data on the
number of hotel/motel rooms (Hobeika, et al., 1994; Lindell, et al.,
2002b). In addition, Hobeika, et al. (1994) considered the number of
campsites and their occupancy rate. It is extremely important to account
for seasonal variation in the transient population because, for example,
coastal areas tend to have high rates of tourist occupancy on holiday
weekends during the summer and much lower rates during the week after
Labor Day. Hobeika, et al. (1994) and Lindell, et al. (2002b) accounted
for variation in the size of this population segment by collecting data
on occupancy rates for hotel/motel rooms over time. However, these
occupancy rates are often reported by month rather than by week or day,
so analysts must still make assumptions about variation within month.

Some analysts have assumed that 70-80% of registered vehicles would be
used in a daytime evacuation and 90% would be used in a nighttime
evacuation (Southworth & Chin, 1987). These analysts also contended that
only 75% of registered vehicles would be used in rapidly developing
incidents. Unfortunately, there are no empirical data or theoretical
foundations for such assumptions. Instead, it is more logical to base
the estimated number of evacuating vehicles on the number of evacuating
households because fifty years of disaster research has identified the
household as the basic unit of evacuation. Indeed, households that are
separated when a warning is disseminated almost always attempt to
reunite before leaving the risk area (Drabek, 1986; Lindell & Perry,
1992; Tierney, et al., 2001). Data on the number of evacuating vehicles
per residential household (*EVHH~R~*) have been collected in a number of
household surveys. The *EVHH~R~* values vary substantially from county
to county, with a low of 1.10 and a high of 2.15 (Lindell, et al., 2005)
but the most probable range is about 1.2-1.5. Data on the number of
evacuating trailers per residential household (*ETHH~R~*) is an
important consideration in evacuations because many households in
coastal areas load boats onto trailers to take when they evacuate. These
trailers fill space on the highway, just as the cars towing them do, so
they should be included as vehicle equivalents in estimating traffic
demand. Lindell, et al. (2005) reported the number of evacuating
trailers taken in Hurricane Lili was *ETHH~R~* = 0.3, but values ranged
from 0.0 to 1.08 across the five counties.

Warning compliance refers to the percentage of those warned to evacuate
who actually do so. Spontaneous evacuation, also known as *evacuation
shadow*, refers to evacuation by those who are outside the risk area and
therefore not warned to evacuate. Many evacuation analysts have assumed
all persons advised to evacuate will do so and there would be no
spontaneous evacuation from areas not advised to evacuate. By contrast,
Lindell, et al. (2002a) used data, originally reported by Lindell, et
al. (2001), on expected evacuation rates as a function of residents'
risk areas and the Saffir-Simpson hurricane category of an approaching
storm. The evacuation percentages in the original data were subject to
sampling error, so the data can be smoothed statistically to yields the
percentages in Table 8-2 (Lindell & Prater, 2005).

Table 8-2 is consistent with the findings of previous research on
evacuations in showing risk area residents' evacuation expectations
differ significantly from the idealized pattern (100% evacuation in
areas advised to evacuate and 0% evacuation in areas not advised to
evacuate). These data are also consistent with previous evacuation
research, although no study other than Lindell, et al. (2002) broke down
compliance by risk area. Dow and Cutter (2002) reported 65% compliance
during Hurricane Floyd in South Carolina; Riad, Norris, and Ruback
(1999) found 42% compliance in Hurricanes Hugo and Andrew; and Prater,
et al. (2000) reported 34% compliance in Hurricane Bret. Lindell, et al.
(2005) reported that evacuation rates in Hurricane Lili ranged from 11.7
to 86.8% across five jurisdictions and these rates decayed as a function
of distance from the point of landfall. These findings are consistent
with Baker's (1991) report that evacuation compliance rates in 15
studies varied significantly from one storm to another at a given
location (47-68% in Galveston for three different storms) and from one
location to another in a given storm (33-97% in Hurricane Frederic).

Spontaneous evacuation has received increasing attention since Zeigler,
Brunn and Johnson (1981) called attention to this phenomenon, but
empirical data are sparse. Gladwin, Gladwin, and Peacock (2002) recently
confirmed the occurrence of spontaneous evacuation in hurricanes, which
Baker (1991) reported to range from 20--50% of residents in areas of
"low risk". Other than Lindell, et al. (2002a), warning compliance and
spontaneous rates have not been defined with enough precision to apply
to evacuation models. There appears to be no available data on the
percentage of transient households complying with an evacuation warning
or spontaneously evacuating, but the behavior of this population segment
is also likely to be a function of the hurricane's intensity and the
household's risk area. Based on information collected in interviews of
local Emergency Management Coordinators following Hurricane Bret
(Prater, et al., 2000) and in Drabek's (1996) interviews of hotel
managers, Lindell et al. (2002a) assumed tourists would produce 100%
compliance with a hurricane warning, regardless of their risk area.

**Table 8-2**. Percentages of Households Expecting to Evacuate from
Hurricanes.

+-----------+-----------+-----------+-----------+-----------+-----------+
| Risk      | Category  | Category  | Category  | Category  | Category  |
|           |           |           |           |           |           |
| Area      | One       | Two       | Three     | Four      | Five      |
+-----------+-----------+-----------+-----------+-----------+-----------+
| 1         | 45.9      | 63.7      | 87.8      | 98.2      | 100.0     |
+-----------+-----------+-----------+-----------+-----------+-----------+
| 2         | 35.9      | 53.7      | 77.8      | 88.2      | 91.4      |
+-----------+-----------+-----------+-----------+-----------+-----------+
| 3         | 31.1      | 48.9      | 73.0      | 83.4      | 86.6      |
+-----------+-----------+-----------+-----------+-----------+-----------+
| 4         | 28.2      | 46.0      | 70.1      | 80.5      | 83.7      |
+-----------+-----------+-----------+-----------+-----------+-----------+
| 5         | 26.5      | 44.3      | 68.4      | 78.8      | 82.0      |
+-----------+-----------+-----------+-----------+-----------+-----------+

Source: Lindell, et al. (2002)

*Departure timing*. Departure timing refers to the rate at which
evacuating vehicles enter the evacuation route system over time. It is
common for authorities to assume that people will leave immediately
after receiving a warning, but this is not the case. Instead, there are
two distinct population groups, residents and transients, whose
departure timing that must be estimated from behavioral research. For
each of these groups, it is important to estimate the percentage of
early (before an official warning) evacuating households and the
distribution of departure times for households leaving after an official
warning is issued.

There are few reports on the percentage of early evacuees, but data from
Lindell, et al. (2005) show the distribution of times when households
decided to evacuate from Hurricane Lili. Because of the storm's high
intensity (Category 4) and steady track, local authorities expected the
National Hurricane Center to announce a hurricane warning on Wednesday
morning 2 October. Accordingly, they announced on Tuesday evening that
they would initiate an evacuation on Wednesday morning. Figure 8-2 shows
almost two thirds of the households decided to evacuate before the
official warning and, moreover, there was a noticeable tendency for
people to make their decisions early in the morning so they would have
the maximum number of hours of daylight in which to evacuate.

There is a modest amount of empirical data on household departure time
distributions. Lindell and his colleagues (Lindell, et al., 1985;
Lindell & Perry, 1987, 1992) reported warning and preparation times from
four floods and the eruption of Mt. St. Helens and Sorensen and Rogers
(1989) reported warning and preparation time data from two hazardous
materials spills. These data can be used directly to estimate departure
times for these hazard agents and can also be used to construct
estimated departure time distributions for other hazard agents as well.
For example, Lindell, et al. (2002a) constructed synthetic departure
time distributions for hurricane evacuations by combining a warning time
and preparation time distributions from two different situations. To
approximate a rapid warning, such as might occur with a last minute
change in hurricane track (e.g., 1999 Hurricane Bret and 2004 Hurricane
Charley), they used data from the 1980 eruption of Mt. St. Helens
(Lindell & Perry, 1992). The use of these data is supported by a survey
conducted the month before the eruption, which indicated 34% of all
residents checked the news media for information about the volcano two
or three times per day and another 56% checked more than four times per
day (Greene, Perry & Lindell, 1981). This is a level of hazard
monitoring that seems to be quite comparable to the attentiveness of
those in hurricane risk areas during the days before landfall.

[**Figure 8-2.** Distribution of Evacuation Decision Times.]{.underline}

> ![](media/image2.wmf){width="5.125196850393701in"
> height="2.166535433070866in"}

Source: Lindell, et al. (2005).

To estimate hurricane preparation times, Lindell, et al. (2002a)
analyzed data collected by Lindell, et al. (2001), who asked coastal
residents to report the length of time they expected to take in
preparing prepare to leave work, travel from work to home, gather
household members, pack travel items, install storm shutters, and secure
their home before evacuating from a hurricane. Later comparison of
expected preparation times with actual preparation times during
Hurricane Lili revealed statistically and practically significant
correlations (Kang, et al., in press).

Drabek's (1996) research suggests transients are warned at a faster rate
than residents and also prepare to evacuate more rapidly than residents,
but there are no quantitative data on the size of this difference.
Consequently, Lindell, et al. (2002a) derived warning and preparation
time distributions for this population segment from their data on
residents.

*Destination/route choice*. Finally, there are four parameters defining
evacuees' destination/route choice. These are evacuees' ultimate
evacuation destinations, their proximate destination/route choices, and
their utilization of the primary evacuation route system. The *ultimate
destination* is the place where an evacuating household intends to stay
until it is safe to return to their home. The ultimate evacuation
destination constrains the proximate destination/route choice because
there are few routes that can be taken out of a risk area to the
ultimate evacuation destination without significantly increasing travel
distance and time. *Proximate destination* choice (the point at which
the vehicle leaves the risk area) is closely related to route choice
(the selected route to the exit from the risk area). Some analysts have
assumed evacuees choose their routes dynamically when they encounter
traffic queues. For example, Sheffi, Mahmassani & Powell (1981)
contended drivers have a "myopic view" of alternative routes to their
proximate destination and theorized that drivers select the least
congested road they encounter at each intersection. However, reports
from recent hurricane evacuations (Dow & Cutter, 2002; Prater, et al.,
2000) show evacuees tend to take the most familiar routes inland
(especially interstate highways), thus overloading those routes and
ignoring unused capacity on alternate routes. It seems likely that some
evacuees persist in following predetermined routes whereas others
improvise in the face of adverse traffic conditions, but there is
insufficient data to determine the relative proportion of each type of
driver and the conditions affecting this proportion.

*Search and rescue*

The societal response to disasters, especially disasters having little
forewarning, can be understood in reference to zones defining impact and
response (Wallace, 1957). In Figure 8-3, the innermost circle is the
*total impact* zone where casualties and damage are the greatest.
Immediately adjacent to the total impact area is the *fringe impact*
zone, in which casualties and damage are significant but not
overwhelming. The next ring is the *resource filter* zone, through which
information passes from the inner (total impact and fringe) zones to the
outer (community aid and regional aid) zones and material resources pass
from the outer zones to the inner zones. The *community aid* zone is the
area from which assistance is drawn for minor disasters whereas the
*regional aid* zone is needed to support response and recovery from
major disasters.

[**Figure 8-3**. Disaster Impact Zones.]{.underline}

Source: Dynes (1970)

It has long been known that survivors in the impact area are usually the
first to respond to disaster impact by searching for those who are
trapped in building debris, extricating them, providing preliminary
treatment, and transporting them to hospitals. As time passes, there is
increasing involvement by those in the fringe impact area and other
zones (Dynes, 1970; Form & Nosow, 1958). These volunteers' search and
rescue efforts can be highly effective when the local building stock
comprises wood frame and unreinforced masonry structures. However,
collapsed buildings made of steel reinforced concrete require organized
teams with specialized equipment.

*Medical Transport*

It is commonly assumed that authorities transport injured disaster
victims in ambulances to the most appropriate hospitals. However,
according to Quarantelli (1983), many injured victims arrive at
hospitals in their own vehicles or those of peers or bystanders (46% of
casualties) rather than in ambulances (54% of casualties). Moreover, the
vast majority (75%) of victims are transported to the nearest hospital,
which is usually overloaded at the same time as other competent
facilities are sent few or no patients (Auf der Heide, 1994). Indeed, a
study of 14 disasters found an average of 67% of casualties were treated
in a single hospital even though the affected communities ranged from
3-105 hospitals (Golec & Gurney, 1977). Such findings call attention to
the need for emergency managers to work with their local EMS agencies to
establish procedures for transporting and allocating disaster casualties
among the available hospitals.

*Shelter Use*

People commonly assume the majority of evacuees stay in mass care
facilities while they are waiting to return to their homes but, in fact,
only a minority do so. Mileti, Sorensen and O'Brien (1992) reported the
average level of mass care shelter use in 23 well-documented evacuations
was 14.7% of the evacuating population. These researchers also found the
percentage of the evacuees using mass care facilities varied in the
range 5-20% across disasters (Mileti, et al., 1992). The use of mass
care facilities could be as low as 5% if evacuations are initiated early
in the morning with good weather and evacuation routes have effective
traffic management inside and outside the risk areas. Conversely, the
level of mass care demand is likely to be higher when the evacuation
zone has a high proportion of households from lower income strata or
ethnic minority groups. Other conditions causing mass care demand to
reach 20% or higher include darkness, bad weather, traffic congestion,
or other conditions impeding evacuees' ability to reach their intended
destinations.

In general, evacuees prefer to avoid mass care facilities if other
options are available. For example, the Lindell, et al. (2001) hurricane
planning analysis found the majority of the respondents to their survey
expect to stay with friends and relatives (46.3%), while the next most
popular accommodations are expected to be commercial hotels or motels
(32.9%). Another 4.3% of the respondents expect to stay in campers or
trailers, 3.2% expect to stay in second homes, and 9.8% indicated that
they don't know where they will stay or did not respond. Only 3.4%
expect to stay in public shelters. These findings are generally
consistent with the findings of previous evacuation research (e.g.,
Drabek, 1986; Lindell & Perry, 1992; Mileti, et al., 1975; Tierney, et
al., 2001).

*Emergency Responder Role Abandonment*

Another frequently expressed concern is that role conflicts will lead
emergency responders to abandon their professional duties in favor of
protecting their families. That is, when confronted with the dilemma of
protecting the public at large or their families in particular, they
resolve the conflict in favor of their families. Contrary to this myth,
Quarantelli's (1982b) careful examination of the Disaster Research
Center's studies of hundreds of emergencies indicates that there is no
evidence that role abandonment occurs. The explanation for the
nonoccurrence of role conflict is explained by the fact that emergency
responders typically develop family emergency plans and some emergency
response agencies develop family protection plans to prevent such
conflicts from arising. The performance of the New Orleans police in
Hurricane Katrina seem to be a well documented exception to the general
rule that emergency response personnel do not abandon their roles.
Future research will undoubtedly be conducted to explain why police
performance in this situation was so different all the previously
studied disasters.

In any event, it is important to recognize that conclusions about
emergency personnel role abandonment will not necessarily apply to
*emergency response auxiliaries* who are called upon to perform their
normal duties but aren't trained to perform them under emergency
conditions (Lindell, et al., 1985). For example, emergency managers
might plan for school bus drivers to evacuate transit dependent
households. However, they should not automatically assume that these
drivers will perform their duties under emergency conditions. Instead,
emergency managers should seek to have any emergency response
auxiliaries make an explicit commitment to perform their jobs in an
emergency and encourage them to make the same preparations as other
emergency responders. Identifying all of the emergency response
auxiliaries that are *implicitly* (rather than explicitly) designated in
an EOP can be a challenging task. The absence of staff members led to
deaths of nursing home residents in Hurricane Katrina and the absence of
baggage inspectors prevented people from flying out of Houston before
Hurricane Rita struck.

*Volunteers and Emergent Organizations*

A common theme in many of the previous sections is that volunteers are
extremely active in the emergency response and disaster recovery phases.
One of the consequences of the large number of volunteers performing
tasks such as search and rescue is a need to organize the efforts of
those who have not been trained to serve as part of the emergency
response organization. To be effective, volunteers must be organized
into groups that can perform tasks that are within the scope of their
abilities and can interact effectively with the rest of the emergency
response organization. Dynes's (1970) typology of disaster organizations
provides a useful way of understanding how to organize volunteers. As
Table 8-3 indicates, tasks can be characterized as normal
(organizational members perform them routinely) or novel (organizational
members perform them only in disasters). Similarly, organizational
structures can also be characterized as normal (organizational members
conform to their normal roles and authority relationships) or novel
(organizational members develop new roles and authority relationships).

**[Table 8-3]{.underline}**. Types of Organized Behavior in Disasters.

  ---------------- ------------------ ------------------ ------------------
                                      Tasks              

                                      Normal             Novel

  Organizational   Normal             Established        Extending
  structures                                             

                   Novel              Expanding          Emergent
  ---------------- ------------------ ------------------ ------------------

Source: Dynes (1970)

This cross-classification produces four different types of disaster
response organizations.

*Established organizations* perform their normal tasks within normal
organizational structures, as when police direct evacuation traffic.
*Extending organizations* perform novel tasks within normal
organizational structures, as when crews from public works agencies or
private construction contractors dig through rubble to extricate trapped
victims. *Expanding organizations* perform their normal tasks within
novel organizational structures, as when Red Cross volunteers work under
the supervision of permanent staff to operate mass care centers.
Finally, *emergent organizations* perform novel tasks within novel
organizational structures, as when neighbors form a team to search for
and extricate trapped casualties after an earthquake. Drabek, et al.
(1980) extended this typology by noting that organizations of all four
types must often interact with each other in novel ways. They termed
such structures *emergent multiorganizational networks* (EMONs). EMONs
typically comprise a mixture of professional and volunteer personnel
from a variety of government agencies within local government, as well
as representatives from state and federal agencies, NGOs, and the
private sector. Because of their differences in organizational titles,
organizational structures, training, experience, and legal authority,
EMONs frequently experience severe difficulties in communicating with
each other and coordinating their responses to disasters. Indeed, as the
next two chapters will show, standardized systems have been designed to
coordinate the behavior of emergency response organizations. When all
emergency responders are trained according to the Incident Command
System or Incident Management System, they can focus their efforts on
saving lives and protecting property rather than on debating who is in
charge of the emergency response.

**Basic Principles of Household Behavior in Emergencies**

It is crucial for emergency managers to understand that people
confronted by a disaster tend to respond in ways that seem logical to
them given their limited information about the situation and the
constraints that limit their options. People generally act adaptively
and sometimes even heroically, as in the case of passengers in United
Airlines Flight 93 on September 11, 2001. Unlike the passengers on the
earlier hijacked flights, they understood the hijackers' goal. Thus,
they organized and attacked their hijackers, choosing to crash the
flight in a Pennsylvania field rather than allow it to be flown into a
building in Washington DC.

The first basic principle is that people threatened by disaster
generally have multiple sources of information, but none of these
sources is completely credible nor is any single source expected to have
all the information a household needs to protect itself. This frequently
produces confusing and conflicting information that people have
difficulty resolving because they don't know which source is correct.
For example, Figure 8-4 depicts ratings that residents of Longview and
Kelso, Washington, made in 1985 about the degree of hazard knowledge
held by themselves, their peers, the news media, and local, state, and
federal government. They were asked to make these judgments about hazard
knowledge separately for three hazard agents---a volcanic eruption of
Mt. St. Helens (about 40 miles east of their communities), a chlorine
release from a truck or train on nearby transportation routes, and a
release of radioactive materials from the Trojan nuclear power plant
(which was less than 10 miles away). The figure indicates most people
think they know more about hazards than their peers, but less than the
news media, local government, and state and federal government.
Moreover, the news media were judged to be significantly more
knowledgeable than self or peers but less knowledgeable than local,
state, or federal government. However, the differences in knowledge
ratings are smaller for the more familiar volcanic hazard than for
either of the two technological hazards. Interestingly, the knowledge
ratings were consistently higher for radiation hazard than for chlorine
hazard, quite possibly because federal licensing regulations required
the nuclear power plant to distribute emergency information brochures
annually. It is important to note that none of the sources was rated as
extremely knowledgeable about any of the hazards (i.e., ratings of 4 or
higher). Nor were any of the sources rated as severely lacking in
knowledge (i.e., ratings of 2 or lower). Thus, even though there were
significant differences among sources, each was credited with some
degree of knowledge. Therefore, conflicts in the information provided by
different sources would be difficult for people to resolve.

The second basic principle is that people generally experience
*fear*---not debilitating shock or panic. Fear is a normal human
reaction to extreme environmental conditions that arises when people
expect that they or their loved ones are personally threatened by forces
that are high in certainty ("it definitely will happen"), severity ("it
will be very bad"), immediacy ("it will be very soon"), and duration
("the effects will last a long time"). Fear rarely is so overwhelming
that it prevents people from responding, but does impair people's
ability to effectively reason through complex, unfamiliar problems. Fear
is especially high when people lack information about the personal
consequences of hazard exposure. Technological hazards and terrorist
events involving chemical, biological, or radiological agents inherently
involve unknown consequences. Many of these agents are undetectable by
normal human senses, so people cannot tell if they are being exposed. In
addition, some of these agents have long latencies---it takes many years
for symptoms to develop---and they result in conditions such as cancer
and birth defects that people dread (Slovic, et al., 1980).

######## [**Figure 8-4**. Judged Degree of Hazard Knowledge.]{.underline} 

![](media/image3.wmf)

Source: Lindell & Perry (1992).

Therefore, it is important for emergency managers to address people's
concerns directly. This is done most effectively through a strategy of
information dissemination. As Chapter 4 indicated, emergency managers
should not try to give people a university education on the topic.
Instead, they should provide clear, direct, and relevant information
about the hazard agent and its potential personal consequences. In
addition, people should also be told what the authorities are doing to
provide protection from the threat and what sources they can contact for
additional information. Contrary to popular fiction, the path to fear
reduction is through providing---not withholding--- information
(Quarantelli & Dynes, 1985).

The third basic principle is that people take action when they think
they are at risk. The initial response to a threatening situation might
be to seek additional information, but those who ultimately conclude
they are at risk will take protective action***.*** It is therefore
important that official warning messages include recommended protective
actions. If authorities do not provide recommended actions, people will
take action anyway---implementing the most appropriate actions they know
(or hear about from other sources such as the news media and peers) with
whatever resources are available to them. Figure 8-5 illustrates some of
the factors that people might consider if told they are threatened by
toxic chemical release (Lindell & Perry, 1992). First of all, it is
important to recognize that many people would not even think of
sheltering in-place and expedient respiratory protection unless these
were specifically mentioned in a warning message. Second, many people
would be uncertain how to implement sheltering in-place and expedient
respiratory protection even if told to do so. Third, Figure 8-5 makes it
clear that evacuation is highly attractive because it is believed to be
far more effective than either of the other two protective actions. It
is also attractive because it takes little more skill than sheltering
in-place or expedient respiratory protection. However, it requires more
time, effort, and money and is likely to experience more obstacles than
the other protective actions. The presence of advantages (being much
higher in positively valued traits such as efficacy) and disadvantages
(being much higher in negatively valued traits such as time, effort,
money, and obstacles) is likely to make people ambivalent about
evacuating. In addition, research has found people have additional
concerns about evacuation in connection with physically destructive
hazards such as hurricanes. For example, some evacuees from Hurricane
Lili were concerned that evacuation would expose their homes to looters
and to storm damage that they might be able to prevent if they remained
at home (Lindell, et al., 2005).

######## [**Figure 8-5**. Perceived Characteristics of Protective Actions for a Chemical Hazard.]{.underline} 

![](media/image4.wmf)

Source: Lindell & Perry (1992).

One of the logical implications of Figure 8-5 is that emergency managers
might consider some of these ratings to reflect misperceptions. For
example, they might believe sheltering in-place and expedient
respiratory protection are much more similar to evacuation in their
efficacy and much more different in terms of their time and effort
requirements. Alternatively, emergency managers might seek explanations
for why sheltering in-place and expedient respiratory protection
received such high ratings on obstacles. If the obstacles involve
knowledge about how to implement these actions, emergency managers could
increase the overall attractiveness of these protective actions by a
risk communication campaign.

In summary, a message not accompanied by guidance for protective action
fails to provide opportunities to reduce fear. In providing protective
action recommendations, it might also be necessary to briefly explain
why the action will be effective. Tell people *why* quarantine at home
will reduce their exposure to smallpox, or *why* climbing a canyon wall
will provide better protection from a flash flood better than driving
their cars out of the canyon, or *why* taking potassium iodide will
reduce radiation exposure damage. Such information accomplishes two
important functions. First, it gives people a rationale for complying
with official instructions; and second, it discourages people from
inventing other *apparently reasonable* alternative actions that might
or might not ultimately be protective.

The fourth basic principle is that some of those at risk will comply
with authorities' recommendations, but their compliance is rarely
automatic. The level of compliance is contingent upon a variety of other
factors; it varies by information source, message content, and receiver
characteristics as well as situational characteristics such as threat
familiarity and apparent urgency for response (usually lead time until
impact). In cases such as seasonal floods, where risk area residents are
likely to be very familiar with the threat and its environmental cues,
compliance with protective action recommendations from authorities is
likely to be lower than with less familiar threats such as toxic
chemicals. When those at risk are familiar with threat agents, they are
more comfortable in their own ability to understand the danger, when and
where it will materialize, and what should be done about it.
Consequently their personal assessment of the situation might cause them
to reject official recommendations, or at least thoroughly examine the
basis for of such recommendations. Where threat familiarity is low, for
example with some hazardous materials or at the initial eruptive
activities of long quiet volcanoes, there is little or no personal
experience or knowledge of the threat. In such cases, people are more
likely to accept (in the response period) the assessment of authorities.
Also, people tend to comply more readily when the warning claims that
impact is imminent or the threat is visible, simply because there is no
time for reflection.

This is a research-based conclusion from the disaster literature, not
wishful thinking by emergency managers (Lindell & Perry, 1992). In times
of extreme stress, people look to government for guidance. When the
agent of destruction is unfamiliar or intangible, or when the
consequences appear overwhelming, people's expectations of protection
and help are especially pronounced. Thus, compliance tends to higher
with technological and terrorist threats. For example, national opinion
polling following the September 11^th^ attacks indicated substantial
increases in levels of trust in government. The combination of citizen
concern and a tendency to feel that taking action is important sets the
stage for attention to messages from emergency authorities and enhances
a positive attitude for compliance. As has been the case in other types
of disasters, people tend to return to their normal skeptical attitudes
toward government over time. Nonetheless, there is a window of
opportunity for emergency managers in the height of crisis and for some
time thereafter.

Particularly during the response phase, people appear to carefully
comply with directions from police and fire personnel and sometimes
other uniformed personnel. For example, in Phoenix, Arizona, during
March, 1999, women who were believed to have been exposed to anthrax
underwent nude decontamination by male hazardous materials technicians
in a decontamination shelter without roof covering while news
helicopters hovered above. One person mentioned concern with modesty,
but none of the victims hesitated to follow instructions. Since that
time, the Phoenix Metropolitan Medical Response System has acquired
enhanced decontamination shelters and the ability to deploy "all female"
decontamination teams. Nonetheless, the incident stands as an example of
citizen compliance with emergency instructions when the threat is
unfamiliar and time for action is limited.

The expectation of compliance also places a special responsibility upon
local authorities to manage emergencies responsibly. Namely, they must
have current, ongoing vulnerability assessment, detection, and
prediction systems for threats when technologically possible. They must
recognize the varying degree to which different population segments
trust them and plan accordingly. Finally, the plans they establish must
be capable of being executed. In the absence of adequate plans, people
will hold them responsible through the political process and the courts.

The fifth basic principle is that some of those whom authorities
consider not to be at risk will also comply with authorities' protective
action recommendations. Evacuation shadow (i.e., spontaneous evacuation)
has been reported in response to hazard agents as varied as nuclear
power plant accidents, toxic chemical releases, volcanic eruptions, and
hurricanes. Lindell and Perry (1983) concluded that approximately ten
times as many people evacuated during the nuclear power plant accident
at Three Mile Island as were designated in the governor's limited
evacuation advisory---only about 15,000 out of the approximately 150,000
that actually evacuated. An equally impressive example of spontaneous
evacuation occurred as Hurricane Rita approached the Texas coast during
2005. Approximately 1.8 million people evacuated from the
Houston/Galveston area even though analyses conducted for the state of
Texas three years earlier indicated that only about a 700,000 people
were in the risk area for a Category 5 hurricane. It is likely that the
level of spontaneous evacuation was affected substantially by the
devastating impact of Hurricane Katrina on New Orleans only three weeks
earlier. Moreover, the plight of the New Orleans evacuees was
particularly salient because Houston was the site of the largest mass
care operation for the Katrina evacuees and problems were being reported
every day in the news media. In any event, the Hurricane Rita evacuation
makes it absolutely clear that large scale spontaneous evacuation is not
limited to unfamiliar hazards such as radiation.

### Expectations Regarding Stress Effects 

Although the research record demonstrates that psychological
consequences rarely prevent people from responding adaptively in the
short-run, authorities must remember that the experience of any disaster
can have longer term consequences for a few of the victims (Perry,
1985). Emergency managers should work with mental health professionals
to anticipate disaster shock and traumatic responses---even
post-traumatic stress disorder (PTSD)---among some population segments.
Other difficulties can be manifest as depression and sometimes "survivor
syndrome". The research literature shows such long-term consequences are
more likely to arise among: (1) people who have witnessed death or
handled the dead; (2) people who have been exposed to large scale
property destruction; (3) people whose friends, relatives, or neighbors
have been seriously injured or lost their lives. However, people can
become depressed even if less severe conditions occur. As authorities
move from concern with emergency response to issues of recovery and
reconstruction, they should anticipate the need for referrals to crisis
counseling and other short-term therapeutic contact as a means of
reducing long-term negative consequences. Attention can also be given to
victims' needs for economic support, a sense of closure, and integrating
the disaster experience into a worldview that allows a transition to a
stable life (Perry & Lindell, 1978).

### Expectations for Health Consequences

One of the least studied phenomena following disasters is the tendency
of victims to develop physical health symptoms (Bourque, et al., 1993).
Studies dating back to Prince's (1920) research on the Halifax, Nova
Scotia, explosion indicated victims developed both psychological
responses and physical health responses. A handful of studies over the
decades have reported that, even in the apparent absence of
psychological symptoms, victims and nonvictims have developed physical
health problems following disasters that are not clearly related to the
disaster agent. Titchner (1988) reported disaster survivors one year
after the event reported statistically significantly higher levels of
health problems when compared to nonvictims. Taylor (1977) found tornado
victims showed higher levels of headache, nausea, and emergency room
visits. Logue, Hansen and Struening (1979) found higher levels of
emergency room visits following hurricane exposure, as well as
gastritis, constipation, bladder problems, and headache. Smith, Handmer
and Martin (1980) reported higher levels of heart disease symptoms among
flood victims, whereas Janerich, et al. (1981) found (also among flood
victims) higher levels of spontaneous abortions, leukemia, and lymphoma.
Although there is no compelling and direct link between natural
disasters and the types of non-impact related physical health problems
cited above, there is at least a time linkage between the disaster event
and the onset of symptoms. This condition leaves open the possibility of
either direct---but unknown---causality of physical health symptoms, or
an indirect---and unstudied---link through psychological processes
(Logue, Hansen & Struening, 1981a, 1981b). As Melick (1985, p. 196)
concluded "Uniformly victims have indicated poorer post disaster health"
but also noted that further studies are needed using better research
designs to better explain this phenomenon.

*Expectations About Adaptive Behavior*

According to Dynes's (1983) *emergent human resources* model, emergency
managers should assume that many risk area residents have
disaster-relevant competencies, just as local emergency response
organizations do. In addition, emergency managers should also rely on
households' existing patterns of social and task behavior rather than
expect them to learn new ones. Finally, emergency managers should also
utilize existing authority structures and communications channels
(Dynes, 1994). In particular, they need to understand what percentage of
the population can perform different emergency response actions and what
are the resources (communications devices, information,
vehicles/equipment) households need to respond effectively. Accordingly,
emergency managers need to avoid stereotyping all households as being
identical. Instead they must recognize the differences among households.
Moreover, emergency managers must avoid the error of *assumed
self-typicality*; they must recognize that many households are not
self-reliant nuclear families who have reliable cars, can (and will)
evacuate when they are advised to do so, and have credit cards to pay
for their evacuation expenses. Finally, emergency managers should
recognize the problems that can arise from the large number of people
who converge on the disaster scene to help. Such volunteers, together
with local residents may form emergent groups that lack formal elements
of organization and, thus, are difficult to work with (Stallings &
Quarantelli, 1985). Emergency managers can avoid the confusion arising
from convergence of massive amounts of human and material resources on
the disaster scene by devising special units to organize volunteers,
developing special locations and procedures for donations management,
and asking people to donate money to organizations such as the Red Cross
rather than sending food, clothing, and medicines.