2.3.1 Weather-related disaster damage is increasing exponentiallyAcross the 21 countries and states (see Box 2.4), disaster occurrence and loss was down significantly in 2009. Given that most extensive risk is weather-related, its manifestations are closely related to climate variability, associated for example with the El Niño Southern Oscillation. As such it can be expected that both the number of events and losses increased again in 2010. Looking at the longer-term picture, the past 20 years have seen a significant increase in the number of local areas reporting losses, the number of houses damaged, the number of people affected and the damage to health and educational facilities associated with extensive disasters (Figure 2.24). This reinforces the view that the rapid increases in both population and GDP exposure described in Section 2.2 have not been addressed by commensurate reductions in vulnerability.
Extensive risk is also rising in relative terms. The number of houses damaged relative to population growth in all 21 countries and states has increased by approximately 600 percent since the early 1990s (Figure 2.25). The enormous difference between this increase and the increasing economic loss to major hazards, described in Section 2.2, reflects how extensive disaster loss is largely unaccounted for, disguising a transfer of risk within countries to low-income households and communities.
2.3.2 Extensive risk is expanding geographicallySpatially, the expansion of extensive risk mirrors urban and regional development and hence increasing population and asset exposure. Across all 21 countries and states, the number of local administrative areas reporting disaster losses has increased more or less continuously over the past 20 years (Figure 2.26). In Mozambique, for example, more local administrative areas reported losses more often between 1999 and 2009, than between 1989 and 1999 (Figure 2.27).
2.3.3 Mortality is still rising in the countries with the weakest risk governance capacitiesThese global trends in risk vary widely from country to country, indicating that risk accumulation processes that mirror development are as heterogeneous as development itself. However, confirming again the findings of Section 2.2, countries with stronger risk governance capacities appear better able to reduce mortality than to reduce the numbers of houses damaged and people affected (Table 2.7). The increase in extensive mortality risk reported in countries like Bolivia, Mozambique, Nepal and Yemen reflect low levels of development. In contrast, mortality risk in Chile and Costa Rica is falling while the rate of housing damage is rising. The heterogeneous nature of risk is further illustrated in Box 2.6, which explains that even in the world’s largest economy, the United States of America, there are major differences in risk governance capacities among wealthier and poorer states and counties.
2.3.4 Revisiting the underlying risk driversImproved reporting of disaster impacts and losses makes it difficult to determine with precision the cause of any increase in reports of disaster impacts and losses over time, even in the last 20 years. In the case of national disaster databases, there is certainly evidence of improved reporting in some countries such as Costa Rica and Sri Lanka, where new official data sources began to contribute to the datasets during the GAR11 analysis period. Nevertheless, improved reporting alone does not appear to explain the increase in damaged housing, for example, across the 21 countries and states used in the GAR11 analysis.
New case study evidence supports GAR09’s finding that increasing extensive risk is closely related to the challenges low- and middleincome countries face in addressing underlying risk drivers and reducing vulnerability. Risk is increasing most rapidly in small- and medium-sized urban centres with relatively weak capacities for managing urban growth (Table 2.8). Compounding this, landslide and flood risk at the local level is closely associated with poverty, and overall risk is magnified by deforestation and the destruction of coastal ecosystems.
2.4 Impacts on children and internal displacement
Children make up a large proportion of those who are most vulnerable to disasters, and they are affected particularly severely when they occur. Disasters can also contribute heavily to internal displacement, even when mortality is relatively low.
The mechanisms through which disaster losses contribute to poverty were explored in depth in GAR09 (UNISDR, 2009
). This year’s report expands on the different and specific disaster impacts that affect child welfare and development.
Click here to go to GAR09 page.
Children are affected particularly severely by disasters and constitute an extremely large percentage of those who are most vulnerable (Bartlett, 2008
). This is supported by a number of studies on how disasters affect children’s medium-term development (Baez and Santos, 2007
; López-Calva and Ortiz-Juárez, 2009
; Rodriguez-Oreggia et al., 2010
). For example, destroyed or damaged schools together with the loss of household assets and livelihoods can force children out of school, and infant malnutrition caused by loss of food supplies may cause stunting and lead to poor educational achievement and greater propensity to disease.
Recent studies conducted in Bolivia, Indonesia, Mexico, Mozambique, Nepal, the Philippines and Viet Nam provide evidence of how extensive disasters negatively affect children’s education, health and access to services such as water and sanitation, though it was difficult to establish significant relationships between intensive disasters and child welfare (Tarazona and Gallegos, 2010
; Seballos and Tanner, 2011
Click here to view this GAR paper.
). Given the importance of primary education for human and long-term economic development, these findings should serve as a warning to governments.
Click here to view this GAR paper.
In areas in Bolivia that experienced the greatest incidence of extensive disasters, the gender gap in primary education achievement widened, pre-school enrolment rates decreased and dropout rates increased. Equivalent areas in Nepal and Viet Nam saw, respectively, reduced primary enrolment rates and a drop in the total number of children in primary education. Extensive disasters also led to an increased incidence of diarrhoea in children under five years of age in Bolivia, an increased proportion of malnourished children under three in Nepal, an increased infant mortality rate in Viet Nam, and an increase in the incidence of babies born with low birth weight in Mozambique. This study also found evidence of negative impacts in terms of access to water and sanitation in Mexico and Viet Nam. These impacts indicate a need for greater consideration of children’s vulnerability (Box 2.7).
Box 2.7 Child-centred approaches to dealing with climate stresses and extreme events
A number of estimates suggest that at least 66.5 million children are affected by disasters annually (Penrose and Takaki, 2006
; Bartlett, 2008
; Costello, 2009
; Sanchez et al., 2009
). Addressing high child mortality rates as well as the significant psychological impacts of disasters on children requires new approaches that recognize the role of children as agents of change. On the one hand, these approaches should include child-sensitive policy and programming, where existing social protection, school feeding programmes and structural strengthening of school buildings all contribute to child welfare. On the other hand, they extend to participatory DRM policy and programming in which children and young people are actively engaged in decision-making and accountability processes. These usually have the benefit of improving communication and integrated planning within communities, and increasingly serve to promote effective preparation and prevention.
Engaging children in DRM remains constrained by lack of finance, skills and knowledge. This hampers both the processes and delivery of risk management and the engagement of children in planning and decision-making. Also, perceptions of children as passive, subordinate and unable to participate hinder them from actively voicing their risk perceptions, needs and potential.
There are examples of how an enabling policy environment can help change this. In the Philippines, the Strategic National Action Plan and the Local Government Code provide a policy environment in which decentralization of disaster risk management responsibilities opens up opportunities for child-centred initiatives. Sangguniang Kabataan are youth councils that are directly involved in decision-making at village level and are represented at municipal, provincial and national levels. However, it is political will and local capacities above and beyond these supporting policies that facilitate child-centred participatory DRM. With external support and guidance, youth groups have made good progress in changing attitudes and providing opportunities for participatory DRM.
Disasters also contribute to internal displacement (Box 2.8). Hazards such as floods, although causing relatively low mortality, destroy many houses and hence cause considerable displacement. Between 1970 and 2009 in Colombia, for example, 24 of the country’s 35 disaster loss reports detailed floods that killed fewer than 10 people but destroyed more than 500 houses. In total, around 26,500 houses were destroyed, potentially displacing more than 130,000 people. In the Indian state of Orissa, 265 floods with similar low mortality rates destroyed more than half a million houses.
Box 2.8 Floods and internal displacement in Tumaco, Colombia
On 16 February 2009, the Mira and Telembí rivers in Nariño, Colombia, flooded four municipalities on the Pacific Coast: Tumaco, Barbacoas, Roberto Payán and Magüí Payán. Two people were killed, with a further 20 reported missing, but 1,125 houses as well as schools, health centres, and roads were destroyed. The government declared a municipal emergency on 23 February in Tumaco, but there was no international appeal for relief.
Based on the number of houses destroyed, there were an estimated 5,625 displaced people. However, the actual number recorded by the authorities was more than 25,000, of whom 14,000 were forced into shelters, with the remainder staying with friends and families.
One reason for the discrepancy may be that people whose houses were damaged (but not destroyed) were nevertheless displaced during the peak of the flood. Around 1,400 houses were damaged by the floods, likely generating another 8,000 displaced people. In addition, the number of displaced may include those who evacuated during the floods as a preventive measure, and who most likely returned after a few days or weeks. The number of destroyed houses is therefore more likely to be a better indicator for long-term displacement than for short-term displacement during emergencies.
Intensive disasters also lead to large-scale internal displacement. Pakistan’s 2010 floods have to date left an estimated 6 million people in need of shelter; India’s 2008 floods uprooted roughly 6 million people; Hurricane Katrina displaced more than half a million people in the United States of America; and Cyclone Nargis uprooted eight hundred thousand people in Myanmar and South Asia (IDMC, 2010
Click here to view this GAR paper.
Assuming a family size of five in the 21 countries and states included in the GAR11 analysis, the destruction of 5.9 million houses in intensive disasters between 1970 and 2009 would have displaced almost 30 million people. Although extensive disasters account for less than one-fifth (19 percent) of destroyed housing, this implies an additional 7.5 million displaced people, who are typically less visible than those displaced in intensive disasters subject to large-scale international humanitarian assistance.
19 Small urban centres are defined as those with populations of 10,000 to 19,999; medium urban centres 20,000 to 99,999; large urban centres 100,000 to 999,999 and megacities greater than 1 million.
GAR 2011 Contributing PapersCepeda, J., Smebye, H., Vangelsten, B., Nadim, F. and Muslim, D. 2010. Landslide risk in Indonesia. . Prepared by the International Centre for Geohazards, Norwegian Geotechnical Institute. [View]
Corrales Leal, W. 2010. Overcoming trade and development limitations associated to climate change and disaster risk. . [View]
ERN-AL, 2011. Probabilistic modelling of disaster risk at global level: Development of a methodology and implementation of case studies. Phase 1A: Colombia, Mexico, Nepal. Prepared by the Consortium Evaluación de Riesgos Naturales – América Latina. [View]
Freire, C. 2011. Extensive Risk of the Impact of Disasters. Prepared by Macroeconomic Policy and Development Division Economic and Social Commission for Asia and the Pacific (ESCAP)[View]
Gupta, M. 2011. Filling the governance ‘gap’ in disaster risk reduction. Background Paper prepared by the Asian Disaster Reduction and Response Network (ADRRN). [View]
Herold C.; Pedduzzi P., 2011. Testing the GAR risk methodology at the national level : the case of earthquakes in Indonesia. Prepared by the Global Change & Vulnerability Unit UNEP/GRID-Europe[View]
Hobbs, C. 2010. Current and future risks posed by unprotected radioactive waste sites in Central Asia. [View]
IDMC (Internal Displacement Monitoring Centre). 2010. Using disaster data to monitor disaster-induced displacement. . [View]
Kent, R. 2010a. Disaster risk reduction and changing dimensions and dynamics of future crisis drivers. [View]
Mansilla, E. 2010. Riesgo urbano y políticas públicas en America Latina: La irregularidad y el acceso al suelo. [View]
Moreno, A. and Cardona, O.D. 2011. Efectos de los desastres naturales sobre el crecimiento, el desempleo, la inflación y la distribución del ingreso: Una evaluación de los casos de Colombia y México. [View]
Nhu, O.L, Thuy N. T. T., Wilderspin, I. andd Coulier, M. 2011 A preliminary analysis of flood and storm disaster data in Viet Nam. UNDP CO, Hanoi, Viet Nam.[View]
O'Donnell, I. 2010. Addressing the grand challenges of disaster risk: A systems approach to disaster risk management. [View]
OSSO (Southwestern Seismological Observatory). 2011b. Análisis de manifestaciones de riesgo en America Latina: Patrones y tendencias de las manifestaciones intensivas y extensivas de riesgo. . [View]
OSSO (Southwestern Seismological Observatory). 2011a. Extensive risk analysis for the 2011a Global Assessment Report on Disaster Risk Reduction: Metodología para la identification de Umbrales. [View]
Serje, J. 2010a. Extensive and intensive risk in the USA: A comparative with developing economies. [View]
Serje, J. 2010b. Preliminary extensive risk analysis for the Global Assessment Report 2011. [View]
Sparks, S., 2011. Global Volcanic Risk. Bristol University, UK. [View]
Tarazona, M. and Gallegos, J. Children and disasters: Understanding differentiated risk and enabling child-centered agency. Brighton, UK: Children in a Changing Climate Research. [View]
Tonini, M., Vega Orozco, C., Charrière, M., and Tapia, R. 2010. Relation between disaster losses and environmental degradation in the Peruvian Amazon. Lausanne, Switzerland:Institute of Geomatics and Risk Analysis, University of Lausanne. [View]