Extensive risk

Chapter 4

4.1

Extensive risk refers to the risk layer of high-fre-quency, low-severity losses. In general, this lay-er is not captured by global risk modelling, nor are the losses reported internationally. One key feature of the GAR (UNISDR, 2009a, 2011a, 2013a) has been to highlight the contingent liabilities associated with this risk layer, which tend to be absorbed by low-income households and com-munities, small businesses, and local and nation-al governments, and which are a criticnation-al factor in poverty (UNISDR, 2009a).

Extensive risk manifests as large numbers of recurrent, small-scale, low-severity disasters which are mainly associated with flash floods, landslides, urban flooding, storms, fires and oth-er localized events. In addition, damage from electrical storms and lightning is increasingly contributing to loss from extensive risk due to wildfires.¹

Extensive disaster risk is magnified by drivers such as badly planned and managed urban devel-opment, environmental degradation, poverty and inequality, vulnerable rural livelihoods and weak governance. This risk layer is characteristic of informal urban settlements and low-income rural areas (UNISDR, 2009a).

Unlike intensive risk, extensive risk is more closely associated with inequality and poverty than with earthquake fault lines and cyclone tracks. In many cases, the hazard, exposure and vulner-ability are simultaneously configured through the underlying risk drivers. This also makes extensive risk an important poverty attribute.

In cities, for example, poverty forces low-income households to occupy areas of low land value that may be exposed to floods, landslides and other hazards (Wamsler, 2014). Informal settlements are usually characterized by highly vulnerable housing and a deficit of risk-reducing infrastruc-ture such as drainage (Mitlin and Satterthwaite, 2013). At the same time, speculative urban devel-opment, which can lead to the paving of green areas in rapidly expanding cities and subsid-ence due to the over-extraction of groundwater, may also increase the frequency and severity of urban flooding (UNISDR, 2013a). Unlike intensive risk, extensive risk is less closely associated with earthquake fault lines and cyclone tracks than with inequality and poverty. In many cases, the hazard, exposure and vulnerability are simulta-neously constructed by the underlying risk driv-ers. For example, all of Panama’s municipal areas report extensive disaster losses even though the country lies south of the Caribbean hurricane belt and earthquakes are infrequent.

Given that extensive and intensive risk simply refer to different risk layers, any quantitative threshold between them is arbitrary. The GAR has used a statistically determined loss thresh-old (Box 4.1) within which a minimum number of disasters accumulate the maximum possi-ble mortality and economic damage (UNISDR, 2011a, Annex II), though it would be equally val-id to determine a threshold on the basis of return periods.

At the time when the HFA was adopted, the mortality, physical damage and economic loss from extensive risk had not been accounted for in national or international reports, except in a number of Latin American countries.² As a result,

Box 4.1 Intensive vs extensive risk: two different footprints

Figure 4.1 The different footprints of extensive vs intensive disaster loss in Indonesia, 1990-2013

(Source: UNISDR with data from Indonesian national loss database.)

The variables used to define the threshold between intensive and extensive disaster losses are mortality and housing destruction. Statistically, the threshold is fixed at:

Mortality: less than 30 people killed (extensive); 30 or more killed (intensive); or

Housing destruction: less than 600 houses destroyed (extensive); 600 or more houses destroyed (intensive).

This threshold has proved robust even as the universe of national disaster databases continues to grow.

As the case of Indonesia shows, extensive and intensive disasters have very different footprints (Figure 4.1).

Box 4.2 Understanding loss and risk from the bottom up: national loss accounting

Figure 4.2 Increase in number of national loss databases featured in Global Assessment Reports

To uncover extensive risks, an increasing number of countries around the world are adopting a simple and well-defined methodology to report, analyse and display disaster occurrence and losses at the local level through a standard definition of hazards, impacts and other indicators.³ Because the loss data is captured at the level of local administrative units, this makes it possible to record losses associated with huge numbers of small extensive disasters that are not internationally reported and thus do not appear in other disaster databases.

In a pattern that resembles the growth of computer processing power, the number of countries systemati-cally collecting disaster loss data has roughly doubled every two years since these efforts began in Latin America in the 1990s.

GAR15 features data collected using the same methodology and parameters in 82 countries and 3 states (Tamil Nadu and Odisha in India, and Zanzibar in Tanzania).

Countries that have published data sets in the last two years, including: Comoros, Madagascar, Mauritius and Seychelles in the Indian Ocean; Morocco and Tunisia in North Africa; Niger, Senegal, Sierra Leone and Togo in West Africa; Barbados, Grenada, Saint Lucia, Saint Kitts and Nevis, Saint Vincent, and Trinidad and Tobago in the Caribbean; Cambodia, Pakistan and the State of Palestine in Asia; and Albania, Serbia, Spain and Turkey in Europe (Figure 4.2).

(Source: UNISDR with data from national loss databases.)

Table 4.1 National disaster loss data for 85 countries and states⁴

this risk layer remained largely invisible. However, since 2007, a sustained effort to assist countries in systematically recording local disaster losses (UNISDR, 2009a, 2011a, 2013a) has generated sys-tematic and comparable evidence regarding the scale of extensive risk from over 80 countries (Box 4.2). Given that 95 per cent of these databases have been built using a comparable approach and methodology, it is possible to analyse these local records at a global level of observation.

Table 4.1 shows that 99.1 per cent of the local-lev-el loss reports from these 85 countries and states are manifestations of extensive risk, with 96.4

per cent resulting from weather-related events.

The economic losses from extensive disasters account for more than 45 per cent of total accu-mulated loss.

Across these countries, extensive disasters are responsible for only 14 per cent of total disaster mortality. However, since 1990 extensive mortal-ity has increased almost fourfold in those coun-tries that have consistent data spanning that period (Figure 4.3), and the trend is statistically significant.

Figure 4.3 Extensive mortality, 1990-2013 (65 countries, 2 states)⁵

(Source: UNISDR with data from EM-DAT.)

Figure 4.4 Internationally reported global disaster mortality (events with fewer than 100 deaths)

Figure 4.5 Extensive disaster mortality relative to population (65 countries, 2 states)

A similar trend can be observed among small-er-scale disasters in global loss data sets (Fig-ure 4.4). There is a statistically significant trend towards increasing mortality in events with few-er than 100 deaths.

Extensive disaster mortality is also increasing rel-ative to population size (Figure 4.5).

While extensive risk is responsible for only a small percentage of mortality, it is associated with a far more significant proportion of morbidity and dis-placement (Figure 4.6), both of which feed direct-ly back into poverty.

Extensive risk critically erodes development assets. Reports show that the majori ty of damage

(Source: UNISDR with data from national loss databases.)

Figure 4.6 Proportion of injured and displaced people reported in extensive disasters (65 countries, 2 states)

Figure 4.7 Percentage of damage and loss from extensive and intensive disaster events (65 countries, 2 states)

and losses since 1990 have been associated with extensive disasters in those countries with con-sistent data sets (Figure 4.7).

This makes extensive risk a central concern for the low-income households and small business-es that depend on public infrastructure and for the local governments that provide it. These

reported losses all show statistically significant upward trends from 1990 onward (Figure 4.8). In part, these trends reflect improved reporting in some countries. However, upon closer analysis, this bias has only a low to moderate influence on the overall trends.⁶

(Source: UNISDR with data from national loss databases.)

Figure 4.8 Reported damage from extensive disasters to housing, education and health facilities, and agricultural production (65 countries, 2 states)

4.2

Losses from extensive disasters are responsible for most disaster morbidity and displacement, and represent an ongoing erosion of develop-ment assets. This presents a particular challenge to the achievement of development goals in ar-eas and regions that already experience social inequality and exclusion.

Extensive risk particularly challenges the achievement of development goals in areas and regions already characterized by social inequal-ity and exclusion. The deficit of infrastructure in these areas is already an underlying driv-er of vulndriv-erability and disastdriv-er risk and weak-ens resilience. The loss of this infrastructure in

disasters further aggravates the situation, gen-erating a vicious cycle. For example, a deficit of primary health facilities increases the vulnerabil-ity of low-income households that suffer flood-ing. Households with poor health are likely to be less resilient to disaster loss, and the damage or destruction of those facilities in disasters further compounds the problem.

The economic value of these social assets is sig-nificant. While the economic losses from intensive disasters are usually evaluated by governments or international organizations and insured losses are assessed by the insurance industry, the eco-nomic cost of extensive risk is largely unaccount-ed for and ultimately reabsorbunaccount-ed into poverty.

Estimates of the cost of those unreported disas-ters highlight a growing and largely unknown

economic loss since 1990 as well as an over-looked poverty factor.

In 2012, EM-DAT reported economic losses of US$157 billion, an estimate that is lower than those published by Swiss Re (US$186 billion), Munich Re (US$160 billion) and Aon (US$200 bil-lion). If the economic cost of assets lost in exten-sive disasters in 82 countries (Figure 4.9) is extrapolated globally, direct economic losses would be around 60 per cent higher than those internationally reported by EM DAT, implying a total of around US$250 billion for 2012.

This total loss represents 0.33 per cent of global GDP, 1.4 per cent of global capital investment and an annual loss of more than US$35 per capita.⁷ For those 1.4 billion people living below the pov-erty line with an income under US$1.25 per day,⁸ the loss is equivalent to almost 8 per cent of their annual income.

Figure 4.9 Economic losses reported internationally and additional losses reported nationally in 82 countries, 1990-2013

In particular, such losses represent a serious erosion of public investment in some of those countries with the least capacity to invest. For example, the average historical annual loss-es from disasters in Madagascar since 2001 are equivalent to around 75 per cent of annual aver-age public investment in the same period;⁹ in El Salvador, they amount to almost 60 per cent, and in Vanuatu they exceed 40 per cent.

Chapter 2 showed how countries have partial-ly succeeded in reducing mortality in inten-sive disasters through improvements in disaster management. In contrast, the increasing level of extensive risk shows how countries have not been able to address the underlying risk drivers.

Increasing risk at the local level is the necessary counterfactual to the success in reducing disas-ter mortality in some countries. It is in reducing losses in the social and economic assets of commu-nities where countries have gained the least trac-tion in the HFA.

Notes

1 A new analysis of national disaster loss data shows that be-tween 1980 and 2013, 41 countries reported a total of more than 6,000 events involving electrical storms which killed more than 8,700 people, injured around 4,500 people and destroyed almost 42,000 houses.

2 http://www.desenredando.org/public/libros/1999/edete/.

3 For more information on national loss databases and the data sets used in this report, see www.desinventar.net.

4 82 countries and 3 states (Odisha and Tamil Nadu, India, and Zanzibar, Tanzania) in total over varying time frames. For access to the loss databases and more details on the countries and states included, see www.desinventar.net.

5 The two states referred to in Figures 4.3, 4.5, 4.6 and 4.7 are Odi-sha and Tamil Nadu, India.

6 Only a very small group of countries show an increasing trend that can be associated with improved reporting, but the popula-tion of those countries (and the impact reported) is low in com-parison to the majority of countries with loss databases. The group with low reporting bias accounts for more than 95 per cent of the population represented (1.6 billion) and 74 per cent of all reports in the sample. Reports of mortality impacts show simi-larly stable patterns, and reports on other types of impacts show slightly higher trends which suggest that better reporting should be taken as one of the causes of the increase, but with a moderate to low influence. See Annex 2 for more details.

7 Gross Domestic Product (GDP) and Gross Fixed Capital Forma-tion (GFCF) of 2013.

8 Data from the World Bank Development Indicators: http://data.

worldbank.org/.

9 Public investment was calculated as an average of the annual percentage of public investment in relation to GDP from 2001 to 2011, based on data from the World Bank.

Increases in extensive risk threaten efforts to reduce poverty and to achieve the Sustainable Development Goals related to poverty and social development, and they highlight that under-standing and practising disaster risk reduction as disaster management has not been effective in avoiding risk generation and accumulation. This theme will be explored further in Parts II and III of this report.