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Requirements: Identify the question you decide to answer at the top of your post. Prompt responses should answer the question

Requirements: Identify the question you decide to answer at the top of your post. Prompt responses should answer the question and elaborate in a meaningful way using 2 of the weekly class readings (250 words of original content). Do not quote the readings, paraphrase and cite them using APA style in text citations. You can only use ONE multimedia source for your minimum 2 sources each week. The readings must be from the current week. The more sources you use, the more convincing your argument. Include a reference list in APA style at the end of your post, does not count towards minimum word content. 


Select ONE of the following:

1) Analyze the 4 types of vulnerabilities present in this case before the event. what could have been done better? What is the biggest lesson learned from the Mount Pinatubo Eruption? Note: Review Coppola reading on vulnerability (week 2): no need to define each type of vulnerability, it is common knowledge now, Coppola does not count for the 2 minimum sources. 

2) Describe the issues with the local/ indigenous community in this case. How can governments better communicate with indigenous groups living in at risk locations?

Introduction to International Disaster Management

Third Edition

Damon P. Coppola




Butterworth-Heinemann is an imprint of Elsevier

150 Introduction to International Disaster Management. Copyright © 2015 Elsevier Inc. All rights reserved.




Citizens collectively face risks from a range of large-scale hazards. Risk is the interaction of hazard consequences

and likelihood. Using this formula, hazards are compared and ranked, allowing disaster managers to determine

the most effective and appropriate treatment options. The goal of risk analysis is a standard measurement of likeli-

hood and consequence, whether quantitative or qualitative. Consequence describes hazard effects on humans, built

structures, and the environment. Losses may be direct or indirect, and tangible or intangible. Hazard likelihood and

consequences can change considerably over time. These trends can be incremental or extreme, and can occur sud-

denly or over centuries. Risk evaluation is conducted to determine the relative seriousness of risks, and to compare

and prioritize them. Disaster managers must decide what risks to treat, what risks to prevent at all costs, and what

risks to disregard. These decisions are based on risk acceptability. The personal factors that dictate risk acceptabil-

ity are guided by risk perception. Vulnerability is a measure of the propensity of an object, area, individual, group,

community, country, or other entity to incur the consequences of a hazard, and is the result of physical, social,

economic, and environmental factors.

Key Terms: consequence; direct and indirect losses; likelihood; qualitative risk analysis; quantitative risk analysis;

risk; risk evaluation; risk matrix; risk perception; tangible and intangible losses; vulnerability.

INTRODUCTION Risk is an unavoidable part of life, affecting all people without exception, irrespective of geographic or

socioeconomic limits. Each choice we make as individuals and as a society involves specific, often

unknown, factors of risk, and full risk avoidance is generally impossible.

On the individual level, each person is primarily responsible for managing the risks he or she faces

as he or she sees fit. For some risks, management may be obligatory, as with automobile speed limits

and seatbelt usage. For other personal risks, such as those associated with many recreational sports,

individuals are free to decide the degree to which they will reduce their risk exposure, such as by wear-

ing a helmet or other protective clothing. Similarly, the risk of disease affects humans as individuals,

and as such is generally managed by individuals. By employing risk reduction techniques for each life

hazard, individuals effectively reduce their vulnerability to those hazard risks.

As a society or a nation, citizens collectively face risks from a range of large-scale hazards. Although

these hazards usually result in fewer total injuries and fatalities over the course of each year than indi-

vidually faced hazards, they are considered much more significant because they have the potential to

result in many deaths, injuries, or damages in a single event or series of events. In fact, some of these

hazards are so great that, if they occurred, they would result in such devastation that the capacity of

local response mechanisms would be overwhelmed. This, by definition, is a disaster. For these


large-scale hazards, many of which are identified in chapter 2, vulnerability is most effectively reduced

by disaster risk management efforts collectively, as a society. For most of these hazards, it is the govern-

ment’s responsibility to manage, or at least guide the management of, disaster risk reduction measures.

And when these hazards do result in disaster, it is likewise the responsibility of governments to respond

to them and aid in the recovery that follows.

TWO COMPONENTS OF RISK Chapter 1 defines risk as the interaction of a hazard’s consequences with its probability or likelihood.

This definition and similar derivatives are used in virtually all technical documents associated with risk

management. Clearly defining the meaning of “risk” is important, because the term often carries mark-

edly different meanings for different people (Jardine and Hrudey 1997). One of the simplest and most

common definitions of risk, preferred by many risk managers, is displayed by the equation stating that

risk is the likelihood of an event occurring multiplied by the consequence of that event, were it to occur:

Risk = Likelihood × Consequence (Ansell and Wharton 1992).


“Likelihood” can be given as a probability or a frequency, whichever is appropriate for the analysis

under consideration. There are multiple variants to how probability and frequency are displayed, but

these all typically refer to the same absolute value. “Frequency” communicates the number of times an

event will or is expected to occur within an established sample size over a specific period of time. Quite

literally, it tells how frequently an event occurs. For instance, the frequency of auto accident deaths in

the United States equates to approximately one death per 81 million miles driven (Dubner and Levitt


In contrast to frequency, “probability” refers to single-event scenarios. Its value is expressed as a

number between zero and one, with zero signifying a zero chance of occurrence and one signifying

certain occurrence. Using the auto accident example, in which the frequency of death is one per 81

million miles driven, we can say that the probability of a random person in the United States dying in

a car accident equals 0.000001 if he or she was to drive 81 miles.

When disaster risk managers use a standardized method of calculating risk utilizing this formula

across all identified hazards, comparison and ranking by severity is possible. If hazard risks are instead

analyzed and described using different methods and/or terms of reference for each hazard, or even for

groups of hazards, comparison and ranking becomes very difficult when prioritizing how limited

resources will be dedicated to risk reduction efforts.

This ranking of risks, or “risk evaluation,” is what allows disaster risk managers to determine which

treatment options, whether mitigation or preparedness, or both, are the most effective, most appropri-

ate, and will provide the most benefit per unit of cost. Not all hazard risks are equally serious, and risk

analysis is what enables an informed decision-making process.

Without exception, governments have limited funds available to manage the hazard risks they face.

While reducing the risk of one hazard may be less expensive or more easily implemented than reducing

the risk of another, cost and ease alone may not be valid reasons to choose a treatment option. Hazards

that have the potential to inflict great consequences (in terms of lives lost or injured, or property


damaged or destroyed) and/or occur with great frequency pose the greatest overall threat. Considering

budgetary limits, disaster risk managers should generally treat those hazard risks that pose the greatest

threat first. Fiscal realities often drive this analytic approach, resulting in situations in which certain

hazard risks in the community’s overall risk profile are mitigated, while others are not addressed to any

degree at all.

The goal of risk analysis is therefore to establish a standard, comparable measurement of the likeli-

hood and consequence factors for each hazard identified. The different mechanisms through which

values are derived for a hazard’s likelihood and consequences fall into two general categories of analy-

sis: quantitative analysis and qualitative analysis. Quantitative analysis draws upon mathematical and/

or statistical data to achieve numerical descriptions of risk. Qualitative analysis also relies upon math-

ematical and/or statistical data, but instead uses defined terms (words) to describe and categorize the

hazard risk likelihood and consequence value outcomes. And while quantitative analyses provide spe-

cific data points (e.g., dollars, probability, frequency, or number of injuries/fatalities), qualitative analy-

ses consider ranges of possible values for which each qualifier is assigned. It is often cost- and

time-prohibitive, and often not necessary, to determine the exact quantitative measures for the likeli-

hood and consequence factors of a hazard’s risk. Qualitative measures are much easier to determine and

typically require less time, money, and, most important, expertise, to conduct. For this reason, it is the

most commonly encountered method of assessment in practice. The following section provides a gen-

eral explanation of how these two types of measurements apply to the likelihood and consequence

components of risk.

Quantitative Representation of Likelihood As previously stated, likelihood can be derived as either a frequency or a probability. A quantitative

system of measurement exists for each. For frequency, this number indicates the number of times a

hazard is expected to result in an actual event over a chosen time frame. For example, a particular area

might experience flooding four times per year, one time per decade, ten times each month, and so on as

calculated. Probability considers the same base data, but expresses the outcome as a measure that lies

between 0 and 1 or as a percentage value that falls between 0 percent and 100 percent. In both cases,

this represents the chance of occurrence. For example, if an area has experienced four flood events in

the past 200 years where floodwaters reached 20 feet above the base flood elevation, then this severity

of flooding has a one-in-fifty chance of occurring in any given year, or a probability of 2 percent, or

0.02, each year. This is also considered to be a 50-year flood. An event that is expected to occur two

times in the next three years has a 0.66 probability each year, or a 66 percent chance of occurrence, and

is much more probable than the 50-year event.

Qualitative Representation of Likelihood Likelihood can also be expressed using qualitative measurement, applying words to describe the chance

of occurrence. Each word or phrase represents a pre-established range of possibilities. For instance, the

likelihood of a particular hazard resulting in an emergency or disaster event might be described as fol-

lows using a qualitative system of likelihood:

• Certain: >99 percent chance of occurring in a given year (one or more occurrences per year)

• Likely: 50–99 percent chance of occurring in a given year (one occurrence every one to two



• Possible: 5–49 percent chance of occurring in a given year (one occurrence every two to twenty


• Unlikely: 2–5 percent chance of occurring in a given year (one occurrence every twenty to fifty


• Rare: 1–2 percent chance of occurring in a given year (one occurrence every fifty to one hundred


• Extremely rare: <1 percent chance of occurring in a given year (one occurrence every one hun-

dred or more years)

Note that this is just one of a limitless range of qualitative terms and values that can be used to

describe the likelihood component of risk. As long as all hazards are compared using the same range of

qualitative values, the actual determination of likelihood ranges attached to each term does not neces-

sarily matter. (See exhibit 3.1.)


In brief, different people fear different hazards for many different reasons. These differences in perception can be based

on experience with previous instances of disasters, specific characteristics of the hazard, or many other combinations of

reasons. Even the word risk has different meanings to different people, ranging from “danger” to “adventure.”

Planners, or members of disaster risk management teams, are likely to draw from diverse backgrounds and may even be

from different parts of the country or the world. Each will have a unique perception of risk (regardless of whether they are able

to recognize these differences). Such differences can be subtle, but they make a major difference in the risk analysis process.

Quantitative methods of assessing risk use exact measurements and are therefore not very susceptible to the effects of

risk perception. A 50 percent likelihood of occurrence is the same to everyone, regardless of their convictions. Unfortu-

nately, there rarely exists sufficient information to make definitive calculations of a hazard’s likelihood and consequence.

The exact numeric form of measurement achieved through quantitative measurements is incomparable. The value of

qualitative assessments, however, lies in their ability to accommodate for an absence of exact figures and their ease of use.

Unfortunately, risk perception causes different people to view the terms used in qualitative systems of measurement

differently. For this reason, qualitative assessments of risk must be based on quantitative ranges of possibilities or clear

definitions. For example, imagine a qualitative system for measuring the consequences of earthquakes in a particular city

in terms of lives lost and people injured. Now imagine that the disaster management team’s options are “None,” “Minor,”

“Moderate,” “Major,” or “Catastrophic.” One person on the team could consider 10 lives lost as minor. However, another

team member considers the same number of fatalities to be catastrophic. It depends on the perception of risk that each has

developed over time.

This confusion is significantly alleviated when detailed definitions are used to determine the assignation of

consequence measurements for each hazard. Imagine the same scenario, using the following qualitative system of


1. None. No injuries or fatalities.

2. Minor. Small number of injuries but no fatalities. First aid treatment required.

3. Moderate. Medical treatment needed but no fatalities. Some hospitalisation.

4. Major. Extensive injuries, significant hospitalisation. . . . Fatalities.

5. Catastrophic. Large number of severe injuries. Extended and large numbers requiring hospitalisation. . . . Significant

fatalities. (EMA 2000)

This system of qualitative measurement, with defined terms, makes it more likely that people of different backgrounds

or beliefs would choose the same characterization for the same magnitude of event. Were this system to include ranges

of values, such as “1–20 fatalities” for “Major,” and “more than 20 fatalities” for “Catastrophic,” the confusion could be

alleviated even more.



The consequence component of risk describes the effects of the risk on humans, built structures, and

the environment. There are generally three factors examined when determining the consequences of a


1. Deaths/fatalities (human)

2. Injuries (human)

3. Damages (cost, reported in currency, generally US dollars for international comparison)

Further distinctions have been made to distinguish between damages and losses, as is the case with

the World Bank’s Damage and Loss Assessment (DALA) methodology (see chapter 6). In this case,

damages are defined as the destruction of physical assets, while losses are defined as foregone produc-

tion or income. And while damages occur immediately and can be rebuilt, losses occur over a longer

period of time and may not be recoverable.

Although attempts have been made to convert all three of these consequence factors into monetary

amounts to derive a single number to quantify the consequences of a disaster, doing so has proved

controversial (how can one place a value on life?) and complex (is a young life worth more than an old

life? by how much?). As such, it is often most appropriate and convenient to maintain a distinction

between these three factors when detailing an event’s impact.

Categories of consequence can be further divided, and often are, to better understand their influence

within social and economic contexts. Two of the most common distinctions are direct and indirect

effects (damages/losses), and tangible and intangible effects (damages/losses).

Direct effects, as described by Keith Smith in his book Environmental Hazards, are “the first

order consequences that occur immediately after an event, such as the deaths and economic loss

caused by the throwing down of buildings in an earthquake” (Smith 1992). Examples of direct

effects are

• Fatalities

• Injuries (“The prediction of injuries is often more valuable than the prediction of fatalities,

because the injured will require a commitment of medical and other resources for treatment.”

[UNDP 1994])

• Cost of repair or replacement of damaged or destroyed public and private structures (buildings,

schools, bridges, roads, etc.)

• Loss of possessions

• Relocation costs/temporary housing

• Loss of agriculture and livestock

• Loss of business inventory/facilities/equipment/information

• Loss of usable land

• Community response and cleanup costs incurred

• Loss of historical documents or records

Indirect effects, according to Smith (1992), “emerge later and may be more difficult to attribute to

the event.” Examples of indirect losses include:

• Loss of livelihoods/income potential

• Input/output losses of businesses


• Loss of community population

• Loss of community character

• Loss of critical services due to organization or business losses

• Reductions in business/personal spending (“ripple effects”)

• Loss of institutional/tacit knowledge

• Mental illness/psychosocial impacts

• Bereavement/emotional loss

Tangible effects “are those for which it is possible to assign monetary values” (Smith 1992). Gener-

ally, only tangible effects are included in the estimation of future events and the reporting of past

events. Examples of tangible effects include:

• Cost of building repair/replacement

• Response costs

• Loss of inventory or possessions

• Loss of wages

• Loss of tax revenue

• Loss of trained or technical staff

Intangible effects are those that “cannot be properly assessed in monetary terms” (Smith 1992). This

is the primary reason that human fatalities and human injuries are assessed as a separate category from

the cost measurement of consequence in disaster management. These effects are almost never included

in damage assessments or predictions. Examples of intangible effects include:

• Cultural impacts

• Stress

• Mental illness

• Loss of community character

• Poor morale

• Consequences of a damaged environment

• Increased health risks

• Sentimental value

• Environmental losses (aesthetic value)

Although it is extremely rare for benefits or positive effects to be included in the assessment of past

disasters or the prediction of future ones, they do arise in the aftermath of many disasters. Like losses,

gains can be categorized as direct or indirect, tangible or intangible. Examples of tangible, intangible,

direct, and indirect gains include:

• Decreases in future hazard risk by preventing rebuilding in hazard-prone areas

• New technologies used in reconstruction that result in an increase in quality of services

• Removal of old/unused/hazardous buildings

• Jobs created in reconstruction

• Greater public recognition of hazard risk

• Otherwise-unobtainable funds available for development or disaster risk reduction

• Environmental benefits (e.g., fertile soil from a volcano)

• Community cohesion


As with the likelihood component of risk, the consequences of risk can be described according to

quantitative or qualitative reporting methods. Quantitative representations of consequence vary accord-

ing to deaths/fatalities, injuries, and damages:

• Deaths/fatalities. The specific number of people who perished in a past event or who would be

expected to perish in a future event; for example, 55 people killed.

• Injuries. The specific number of people who were injured in a past event or who would be

expected to become injured in a future event. Can be expressed just as injuries, or divided into

mild and serious; for example, 530 people injured, 56 seriously.

• Damages. The assessed monetary amount of actual damages and/or losses incurred in a past event

or the amount of damages expected to occur in a future event. Occasionally, this number includes

insured losses as well; for example, $2 billion in damages, $980 million in insured losses. For past

disasters, damages may also be adjusted for inflation to enable a more meaningful comparison of

events that occurred many years apart.

Qualitative Representation of Consequence As with the qualitative representation of likelihood, words or phrases can be used to describe the effects

of a past disaster or the anticipated effects of a future one. These measurements can be assigned to

deaths, injuries, or costs (the qualitative measurements of fatalities and injuries are often combined).

The list of qualitative terms included in Exhibit 3.1 is one example.

Additional measures of consequence are possible, depending on the depth of analysis. These addi-

tional measures tend to require a great amount of resources, and are often not reported or cannot be

derived from historical information. Examples include:

• Emergency operations. Can be measured as a ratio of responders to victims, examining the

number of people who will be able to participate in disaster response (both official and unofficial

responders can be included) as a ratio of the number of people who will require assistance. This

ratio will differ significantly depending on the hazard. For example, following a single tornado

touchdown, there are usually many more responders than victims, but following a hurricane,

there are almost always many more victims than responders. This measure could include the first

responders from the community as well as the responders from the surrounding communities

with which mutual aid agreements have been made. Emergency operations also can measure the

mobilization costs and investment in preparedness capabilities. It can be difficult to measure the

stress and overwork of the first responders and their inability to carry out regular operations (fire

suppression, regular police work, regular medical work).

• Social disruption (people made homeless/displaced). This can be a difficult measure because,

unlike injuries or fatalities, people do not always report their status to municipal authorities

(injuries and deaths are reported by the hospitals), and baseline figures do not always exist. It is

also difficult to measure how many of those who are injured or displaced have alternative options

for shelter or care. Measuring damage to community morale, social contacts and cohesion, and

psychological distress can be very difficult, if not impossible.

• Disruption to economy. This can be measured in terms of either the number of working days

lost or the volume of production lost. The value of lost production is relatively easy to measure,

while the lost opportunities, lost competitiveness, and damage to reputation can be much more


difficult. The loss of livelihoods can be extremely difficult to measure, especially in farming

or fishing communities or communities centered around home-based production of crafts, for


• Environmental impact. This can be measured in terms of the clean-up costs and the costs to repair

and rehabilitate damaged areas. It is harder to measure in terms of the loss of aesthetics and public

enjoyment, the consequences of a poorer environment, newly introduced health risks, and the risk

of future disasters.

It does not matter what system is used for qualitative analysis, but the same qualitative analysis

system must be used for all hazards analyzed in order to compare risks. It may be necessary for disaster

managers to create a qualitative system of measurement tailored to the country or community where

they are working. Not all countries or communities are the same, and what amounts to a minor impact

in one could represent a catastrophe in another. Qualitative measures of consequence should therefore

accommodate these differences. For example, a town of 500 people would be severely affected by a

disaster that caused 10 deaths, while a city of 5 million may experience that many, or even more, deaths

just from car accidents in any given week.

Another benefit of creating an individualized system of qualitative analysis is the incorporation of

the alternative measures of consequence (ratio of responders to victims, people made homeless/dis-

placed). The more tailored a system of analysis is to the needs of the study area, the more meaningful

its outcome will be to the disaster risk management process.

Intensive, Extensive, and Emerging Risk Disaster risk managers are most often focused on addressing those hazards for which the likelihood of

occurrence is highest and the consequences are greatest. The risk for such hazards is considered to be

intensive. At the opposite end of the spectrum are those hazards for which frequency is high or very

high, yet the consequences are generally much less severe—perhaps isolated to an individual or a

neighborhood. Risk for hazards falling in this category are considered to be extensive. And while inten-

sive risk is most often associated with events that impact a large area, this does not mean that extensive

risk impacts only highly localized areas (though that is often the case.)

Events resulting from extensive risk are rarely if ever noteworthy or newsworthy, and often are not

tracked by centralized disaster information systems. Likewise, the required response may be nothing

beyond what is typical for the local emergency services to perform on any given day. It is the collective

sum of extensive risk that is significant, in that it can—and often does—exceed that of the major disas-

ter events incurred in any given year with regard to consequences. (See figure 3.1.) Extensive risk is

thus important to the disaster risk manager not in terms of preparing for response, but rather because it

is often true that the same mechanisms by which intensive risk is reduced hold true for extensive risk.

(See chapter 4 for mitigation options.)

The United Nations Office for Disaster Reduction (UNISDR) reports that 97 percent of extensive

risk is weather-related. It is interesting to note that extensive and intensive risks are relative terms, such

that two events of equal consequence in two separate locations might be considered extensive—or

routine—in a large city, yet intensive in a small village. And because of these distinctions between

localities or countries, differences between extensive and intensive risk should be thought of as a matter

of capacity.


The third special category, termed emerging risk, refers to hazards with traditionally low frequen-

cies of occurrencebut which are nonetheless increasing due to new patterns of exposure, increasing

frequencies, and changes in population vulnerability. Space weather is an example of an emerging risk.

In this instance, there is not an increase in the incidence of solar flares, but the impact they have on

modern technological systems, and the reverberations that has on contemporary social and economic

systems, are significant. The expansion of tropical diseases into areas farther and farther from the equa-

tor are presenting another form of emerging risk. The chukungunya virus, which, like Dengue Fever in

the 1980s, is moving quickly through the Caribbean, threatens many countries previously unaffected

because of wetter and warmer conditions that enable breeding of the mosquitos that carry the disease.

TRENDS Whether risks have existed for centuries or are just emerging, the likelihoods and consequences associ-

ated with them are rarely static. The number of events caused by a particular hazard might increase or

decrease over time, whether due to changing global climate patterns, changes in human activities, or