Disaster Indicators their Capacity and Applicability Finance Essay

The influence of natural and artificial disasters has been displayed in most societies throughout the world. As the human population continues to expand and societies become more complex, the significance of disaster prevention and mitigation has advanced to unprecedented heights. Former and recent methodologies employed to alleviate and avoid disasters are varied and complex; unfortunately, the aspiration of a composite index that provides a comprehensive picture of the societal impact of disasters has remained elusive. Disasters of similar cause and magnitude frequently occur; nonetheless, despite the similarity between disasters, the results are commonly different. Without a unique set of indicators that are universally quantifiable, predicting the societal impact of a disaster remains ambiguous and relatively unattainable. By comparison and analysis, the purpose of this paper is to propose evidence-based indicators which are comprehensive in capacity, yet specific in applicability; a strategy that will potentially enhance the ability of policy makers and emergency specialists to more accurately prevent and relieve the consequences of disasters.

Disaster Indicators: Capacity and Applicability

The World Health Organization (WHO) defines disasters as "a serious disruption of the functioning of a community or a society causing widespread human, material, economic or environmental losses which exceed the ability of the affected community or society to cope using its own resources" (World Health Organization, 2010). Historically, there are several illustrations of disasters; many of which provide significant support for the WHO's current characterization.

Throughout human history, natural and man-made disasters have influenced colonies, societies, families, and individuals. For instance, Dr. David Crossley, a Professor of Geophysics at Saint Louis University, suggested;

Considerable evidence exists for a major global paleoclimate event that happened around 3000B.C. It appears to have affected sea-level changes, vegetation and much surface chemistry. Likewise, the event in 1737 that may have killed some 300,000 people around Calcutta, India, is now ascribed to a typhoon (the Asian equivalent of a hurricane) combined with massive flooding. Originally thought to be an earthquake, this is unlikely from a tectonics point of view - the major Himalayan seismicity is well to the north. This could be the most catastrophic atmospheric event ever recorded in terms of casualties (Crossley, D., 2005).

Certainly, instances more recent are extremely prevalent; the name Katrina has forever embedded itself in America's book of devastation. Rebecca Solnit reported, "In August 2005, 90,000 square miles of the Gulf Coast were devastated; more than 1,800 people died; 182,000 homes were severely damaged in New Orleans alone, where 80 percent of the city was flooded. Hundreds of thousands went into an exile from which some will never return" (2010). Similarly, reports suggest that the earthquake that struck the Haitian capital of Port-au-Prince on January 12, 2010 affected over 3 million people, destroyed more than 200,000 homes, and killed over 230,000 people.

Correspondingly, man-made disasters have similarly become a reality; a threat that appears to be universal and devastatingly dangerous. Author Bruce Hoffman undertook a comprehensive survey of 109 existing definitions. As a result, he proposes that terrorism is:

ineluctably political in aims and motives; violent - or . . . threatens violence; designed to have far-reaching psychological repercussions beyond the immediate victim or target; conducted either by an organization with an identifiable chain of command or conspiratorial cell structure . . . or by individuals or a small collection of individuals directly influenced, motivated, or inspired by the ideological aims or example of some existent terrorist movement and/or its leaders; and, perpetrated by a subnational group or state entity (Hoffman, B., 2006).

With unyielding force, natural and man-made disasters have significantly altered human history. The data and descriptions of these disasters are seemingly infinite. Current analysis and examination provides some material related to disaster prevention and mitigation. However, to properly distinguish essential information, and eventually implement the conclusions, careful scrutiny of past and present societies, both successful and unsuccessful, may prove helpful.

Traditionally, societies that have maintained balance and equality within agriculture, industry, government, and the economy have distinguished themselves from those who have not. Unfortunately, the relationship between each of these societal areas is complicated and often convoluted. Nonetheless, the impact of disasters is generally gauged by the overall equilibrium of each of these capacities following an incident (Jahan, S. 2003).

Respectively, one study proposes the resulting societal impact of two earthquakes of similar magnitude, one that occurred in a developing country, Pakistan, and another that occurred in a developed country, Japan. The study explains the two countries' populations at the time of the earthquakes were comparable: 167 million for Pakistan and 125 million for Japan. The earthquake intensities were also comparable: 7.6 magnitude for Pakistan and 7.2 magnitude for Japan (Gardoni, P., Murphy, C., 2010). Despite these similarities, however, the resulting damages were considerably different. The index provided indicates that Pakistan had approximately 14 times more fatalities than Japan, 2 times more individuals injured and 11 times more individuals left homeless.

Country

Pakistan

Japan

Event

Phenomenon

Earthquake

Earthquake

Magnitude

7.6

7.2

Date

2005

1995

Characteristics of the Country

GDP (x 106)

91,080

4,428,530

Population

167,121,000

125,568,000

Consequences of the event

Killed

73,338

5,297

Injured

69,142

34,492

Homeless

2,800,000

251,301

Cost (x 106)

5,000

100,000

Cost/GDP

0.05490

0.02258(Gardoni, P, Murphy. C., 2010)

As governments and countries collaborate to more efficiently counter and prepare for situations comparable to those listed, it has become apparent that the development of an index or instrument that can quantitatively predict or suggest the impact of a disaster would prove to be invaluable. The ability to calculate the possible repercussions of any natural or man-made disaster before its occurrence could facilitate stronger economic resilience, more stable governmental control, and most importantly, possibly save thousands of lives. In the above study, the researchers observed:

In terms of costs, Japan had direct economic losses that amounted to 20 times more than the direct economic losses in Pakistan. However, when factoring in the relative wealth of the two countries, it becomes clear that the economic impact (cost/GDP) on Pakistan was more than twice the economic impact on Japan. Creating a greater difficulty for mitigation efforts (Gardoni, P., Murphy, C., 2010).

Consequently, many organizations, governments, and scientists have generated theories and suggestions for disaster indexes that may potentially meet these demands. In general, the current proposed theories agree the well-being of individuals "be defined and gauged in terms of individual capabilities; Capabilities refer to the effective freedom of individuals to achieve valuable functionings, or doings and beings" (Anand, S.,& Sen, A. 2000). Examples of functionings include being healthy, adequately nourished, adequately sheltered, mobile and educated. Capabilities thus describe the genuine opportunities open to a person (Sen, A, 1999). In essence, the societal impact is simplified and reduced to individuals rather than larger-scale groups. Likewise, an index is required that provides quantitative analysis and results opposed to qualitative observations will certainly facilitate decision and policy-makers' ability to provide sound judgment in terms of prevention, response, and mitigation (Gardoni, P, Murphy, C., 2010).

One such index is the Human Development Index (HDI). In 1990, the United Nations Development Program (UNDP) introduced the HDI to measure human development of countries. Despite a few modifications that were introduced after its inception, "the basic framework has remained the same. It is a composite index of normalized achievements in three different dimensions: economic prosperity, level of knowledge and skill, and quality of health" (Finch, C., Emrich, C., & Cutter, S., 2010). The HDI characterizes each of these dimensions by specific indicators. First, economic prosperity is measured by taking the logarithm of the Gross Domestic Product per-capita and adequately adjusted to the purchasing power disparities. Next, the level of knowledge and skill is measured "by a weighted average of two attributes: the adult literacy rate, and the combined gross enrolment ratio for primary, secondary and tertiary schools" (Finch, C., Emrich, C., & Cutter, S., 2010). Last, the quality of life is measured by the life expectancy rate.

Together, these three indicators provide a cumulative score that is ranked against other countries or societies (Eisenman, D., Cordasco, K., Asch, S., Golden, J., & Glik, D., 2007). As previously observed, the HDI provides an instrument to measure certain individual attributes hypothesized to be most indicative of development.

HDI RANK

COUNTRY

HDI VALUE

LIFE EXPECTANCY AT BIRTH

MEAN YEARS OF SCHOOLING

EXPECTED YEARS OF SCHOOLING

GNI per-capita

VERY HIGH HUMAN DEVELOPMENT

1

Norway

0.938

81.0

12.6

17.3

58,810

2

Australia

0.937

81.9

12.0

20.5

38,692

3

New Zealand

0.907

80.6

12.5

19.7

25,438

4

United States

0.902

79.6

12.4

15.7

47,094(United Nations Development Programme. 2010)

HDI RANK

COUNTRY

HDI VALUE

LIFE

EXPECTANCY AT BIRTH

MEAN YEARS OF SCHOOLING

EXPECTED YEARS OF SCHOOLING

GNI per-capita

VERY LOW HUMAN DEVELOPMENT

1

Central African Republic

0.315

47.7

3.5

6.3

758

2

Mali

0.309

49.2

1.4

8.0

1171

3

Burkina Faso

0.305

53.7

1.3

5.8

1215

4

Liberia

0.300

59.1

3.9

11.0

320(United Nations Development Programme. 2010)

It can be deduced that those countries or societies with excellent HDI scores should be most able to adapt to disasters. However, observational research suggests otherwise. Although the original HDI provides individual analysis, the index fails to account for societies that have interpersonal inequality. Researchers suggest, "lower inequality should, ethically, increase overall human development of a region" (Eisenman, D., Cordasco, K., Asch, S., Golden, J., & Glik, D. 2007). In 2010, UNDP implemented an inequality factor; however, due to the nature of the HDI quantifying such observations remains difficult and merely provides an indirect measurement function with specific indicators (Anand, S., & Sen, A., 2000). Implementing such an index in the calculation of actual or potential disaster impact remains problematic when assessing complete societal impact.

A similar disaster index, the Life Quality Index (LQI), has been proposed as a solution to measuring the societal impact of disasters. Unlike the UNDP's Human Development Index (HDI), the LQI is measured meticulously from the economics of human welfare. Similar to the HDI, the LQI elicits a system for ranking societies based on human development. However, more importantly and unlike the HDI researchers report:

The LQI can also serve as an objective function to be used in setting national or corporate goals for managing risk and to guide effective allocation of society's scarce resources for the mitigation of risks to life or health. The LQI is, essentially, a summary indicator providing a proposal of the net benefit to society for improving the overall public welfare by reducing risks to life in a cost-effective manner (Ditlevsen, O., & Friis-Hansen, P. 2007).

Despite these differences and proposed advantages over the HDI, the LQI remains an index to measure life expectancy and gross domestic product (GDP) per-capita; which, as defined, allows for errors and omissions in interpretation of indirect qualitative information. Both instruments provide essential material but, nonetheless, offer inadequate implementation and, therefore, appear to fall short of the necessary abilities of measuring or predicting disaster impact. Therefore, neither satisfies disaster index requirements.

As previously noted, a capability approach provides a stronger theoretical foundation for identifying and quantifying the societal impact of natural disasters on the basis of overall changes in individuals' capabilities- a technique employed by each of the indexes discussed previously (Jalali, R. 2002). Associate professors Paulo Gardoni and Colleen Murphy specifically stated:

Because the proposed capability approach is more comprehensive in dimensions of well-being affected by a natural disaster it considers and, hence, in the picture of the societal impact it provides, it allows for a more complete and more accurate policy- and decision-making process for disaster recovery and mitigation. In addition, implementing a capability approach to the societal impact of a disaster will facilitate an integrated and coordinated approach to public policy decision-making for both development and disaster recovery and mitigation. The need to take into consideration natural disasters in development assessment, projects and planning is widely recognized in development economics. Using capabilities to measure both development and the impact of disasters will encourage the inclusion of a component on the vulnerability of that society to disasters in the assessment of the development of a society. Further, the same data could be used for the assessment of both the vulnerability and development of a society, therefore optimizing the allocation of the resources available for the data collection (Gardoni, P, Murphy, C., 2010).

As a step towards bridging the assessment of the vulnerability and development of a society, the authors of this paper have previously proposed how to evaluate hazard mitigation policies from a capability approach.

Although most indexes have similar mechanisms, generally incorporating life expectancy and GDP, a common flaw should be noted in each of the previous instruments; primarily, measuring or estimating disaster impact is difficult when specific indicators are individually based rather than collectively or societally based. Gardoni and Murphy observed such results and defined specific errors regarding previous disaster index strategies. Most notably, the GDP includes potential misrepresentation when it comes to societal development. In fact, the development of the capability approach to disaster analysis was, in essence, a result of partially deceiving information given by the GDP. For instance, the GDP is characterized as a calculated average of a region or area. However, the GDP does not indicate the value of every individual; if wealth and income are concentrated "in the hands of a small percentage of a population", then the possibility remains that, although the GDP may appear high, the standard of living of many individuals within a society might be very low (Nussbaum, M., 2000).

Likewise, previous disaster indexes have over-simplified the interpretation of "quality of life". The HDI and the LQI presume to identify indicators based on individual members of a society; when a more accurate approach, in terms of predicting disaster impact, would be indicators designed for a society made up of individuals.

A third disaster index, the Disaster Indicator Index (DII), appears to meet the demands of disaster measurement by employing a unique methodology. Consequently, analysis proves DII supplies indicators based on collective and societal concepts. As disaster indicators are not quantifiable, the DII proposes a technique to more accurately measure disaster results. The tables below provide the DII indicators based specifically on a capability group accompanied by the meaning of each capability.

Capability Group

Capability (being able toA¢â‚¬A¦)

Indicator

Longevity

A¢â‚¬A¦live to the normal end of life

No. of individuals killed

Physical and mental health

A¢â‚¬A¦avoid injuries

No. of individuals injured

A¢â‚¬A¦have adequate and permanent shelter

No. of individuals left homeless

A¢â‚¬A¦have adequate nourishment

Correlated

A¢â‚¬A¦live in a healthy environment

No. of individuals without access to water

Affiliation and mobility

A¢â‚¬A¦engage in forms of interaction with others

No. of individuals unemployed due to the disaster

A¢â‚¬A¦move freely from place to place

Correlated

Command over resource

A¢â‚¬A¦hold property

Direct economic classes ($)(Gardoni, P, Murphy. C., 2010)

Considering the DII, it is noteworthy that the previously described weaknesses present in the HDI and the LQI are absent. The DII accounts for limits in GDP and accounts for the impact influence of certain inequalities present within a society. Each of the four capabilities employed by the DII creates an umbrella category for several indicators necessary to measure or predict disaster impact. The previously described earthquakes in Pakistan and Japan have been analyzed by the DII and measured accordingly. The table below provides an impact ranking based on the four indicators and also includes data from the previous table. The likely conclusion of the inspection of the DII is positive when considering certain conditions. Nonetheless, the ability to generate quantifiable data based on qualitative evidence is still subjective and not concrete (Wei, J., Zhao, D., Wu, D., & Lv, S., 2009). With this in mind, the DII appears to provide the most up-to-date characterization of capabilities or necessary abilities of a society while eliminating flaws found in other indexes.

Country

Pakistan

Japan

Event

Phenomenon

Earthquake

Earthquake

Magnitude

7.6

7.2

Date

2005

1995

Characteristics of the Country

GDP (x 106)

91,080

4,428,530

Population

167,121,000

125,568,000

Consequences of the event

Killed

73,338

5,297

Injured

69,142

34,492

Homeless

2,800,000

251,301

Cost (x 106)

5,000

100,000

Cost/GDP

0.05490

0.02258

Indicators

I1

0.003

0.066

I2

0.117

0.110

I3

0.010

0.250

I4

0.021

0.112

DI

0.401

0.597

DII

0.154

0.208

(Gardoni, P, Murphy. C., 2010)

Upon examination of several indexing systems, several problematic issues remain at the forefront of efficient disaster management and preparation. Despite certain difficulties, such as, the limitation of data and its impact of indexes and indicators, there are more current up-to-date principles that will allow for the evolution of disaster mitigation and management, and the eventual development of an index that meets proposed expectations. These principles may be simplified to four individually necessary concepts.

First, global applicability is required and has recently become more possible with the development of more accurate data gathering and communication. Although, disaster indexes are best implemented on a micro-social level, the indicators must be recognizable on all levels. However, difficulties with funding and resources continue to be a limiting factor in relation to developing a comprehensive disaster index. Data collection requires significant time and resources if it is to be done accurately and extensively. Consequently, funding for such collection is often extremely scarce and of low importance to policy makers. Without an index that is globally applicable, the ability to counter or prevent disasters remains questionable; particularly because disasters of similar magnitudes occurring in different geographic areas often yield various results (Cavanaugh, J., Gelles, M., Reyes, G., Civiello, C., & Zahner, M., 2008).

Another necessary quality of a disaster index includes quality data. Similar to global applicability, quality data is often limited by resources and funding. It remains obvious, however, that in order to generate an instrument that incorporates all variables and occurrences the date used must be of high quality and accuracy- an attribute that is difficult to measure. Quality data, included with a third required concept, collectability will likely continue to be the most difficult aspect to overcome within disaster mitigation and prevention. Behind each number within a set of data is an individual or family. This consideration creates difficulties when proposing indicators that allow of the greatest collectability. Sociologically, it is difficult to place a number on humanity; nonetheless, it is necessary to assess disaster impact accurately.

The fourth characteristic or principle which is supported by evidence is proper communication disaster risk management. Ditlevsen and Friis-Hansen describe the importance or communication with disaster mitigation:

The concerns of different levels of government should be addressed in a meaningful way. For example, risk is very different at the local level (a community or small town) than it is at the national level. If risk is not presented and explained in a way that attracts stakeholders' attention, it will not be possible to make progress in reducing the impact of disasters. To date the system of indicators has been opened up to scrutiny and discussion by international advisors, academics, risk professionals and a limited number of national technical and professional staff, but too few policy makers as such. In the short term it would thus be very wise to organize a series of national dialogues where the derived indicator results and implications are presented to a selected number of national level policy and decision makers. This would allow a testing of relevance and pertinence and offer conclusions as regards future work on the program. It is very important to take into account the set of "next steps" that might be taken to improve the reliability and validity of the data collected and the analyses undertaken (Ditlevsen, O., & Friis-Hansen, P. 2007).

In the future, sustainability for the program and promoting its applicability at the decision maker level requires a significant amount of local, national, and international communication. Without complete communication, global applicability, quality and collectible data, are simply impossible.

In conclusion, the difficulty in achieving effective disaster risk management has been, in part, the result of the lack of a comprehensive conceptual framework of disaster risk that could facilitate a multidisciplinary evaluation and intervention. Most existing indices and evaluation techniques do not adequately express risk and are not based on a holistic approach that invites intervention. This is because of an inability to generate accurate and quality data. It is undeniably necessary to extrapolate information that proposes risk or threat in different ways. Disaster impact is comprehensive in nature and, thus, disaster management is complex (Rigg, J., Grundy-Warr, C., Law, L., & Tan-Mullins, M., 2008).

As a result, complexities in resource allocation, interstate and international communication, data collection appear to be the hurdles most challenging areas to understand. There has been significant progress made in disaster management and concepts, some through trial and error, have become increasingly important. The indexes described and analyzed above provide a partial framework for the future of disaster management and as more time and resources are spent responding to and learning from disasters, an eventual instrument will be developed that will save thousands in not millions of lives.

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