1. 19 August 2005 5 Th EM-DAT Technical Advisory Group Meeting Creation of a hazard index : Overview of the Hotspots methodology Piet Buys pbuys@worldbank.org

2. 19 August 2005 5 Th EM-DAT Technical Advisory Group Meeting Project Objectives Identification of natural disaster risk hotspots at sub-national scalesIdentification of natural disaster risk hotspots at sub-national scales Initial focus:Initial focus:  Drought, floods, tropical cyclones, earthquakes, volcanoes, landslides Where do they occur?Where do they occur? Where might damage be most severe (mortality and economic)Where might damage be most severe (mortality and economic)

3. 19 August 2005 5 Th EM-DAT Technical Advisory Group Meeting Project Objectives Prioritization for local vulnerability assessments and risk reduction in highest-risk areasPrioritization for local vulnerability assessments and risk reduction in highest-risk areas Support Bank efforts to engage clients in hazard management activities (Turkey Earthquake Insurance, CAS,...)Support Bank efforts to engage clients in hazard management activities (Turkey Earthquake Insurance, CAS,...)

4. 19 August 2005 5 Th EM-DAT Technical Advisory Group Meeting Ingredients for Disaster Hotspots Identification Hazard information / event probabilities at a given location, including probable magnitude, duration, timing Elements at risk people, infrastructure and economic activities/assets that would be affected if the hazard occurred Vulnerability of the elements at risk how damaged they would be, if they experienced a hazard event of some level

5. 19 August 2005 5 Th EM-DAT Technical Advisory Group Meeting Global Hazard Data HazardHazardousness Parameter PeriodResolutionSource(s) StormsFrequency by wind strength 1980- 2000 30”UNEP/GRID-Geneva PreView, DECRG processing DroughtPrecipitation less than 75% of median for a 3 + - month period (WASP) 1980- 2000 2.5°IRI Climate Data Library FloodsCounts of extreme flood events 1985- 2003* 1°1°Dartmouth Flood Obs. World Atlas of Large Flood Events EarthquakeExpected PGA (10% prob. of exceedance in 50 years) n/asampled at 1’Global Seismic Hazard Program Freq. of earthquakes > 4.5 on Richter Scale 1976- 2002 sampled at 2.5’ Smithsonian Institution VolcanoesCounts of volcanic activity79-2000Sampled at 2.5’ UNEP/GRID-Geneva and NGDC LandslidesEstimated annual prob. of landslide or avalanche n/a30”Norwegian Geotechnical Institute

6. 19 August 2005 5 Th EM-DAT Technical Advisory Group Meeting Global Data on Elements at Risk ExposureParameterPeriodResolutionSource(s) LandLand area20002.5”GPW Version 3 (beta) PopulationPopulation counts / density20002.5”GPW Version 3 (beta) Economic Activity National / subnational GDP20002.5”World Bank DECRG Agricultural Activity National agricultural GDP allocated to agricultural land area 20002.5”IFPRI Road DensityLength of major roads and railroads c. 19932.5”VMAP(0)

7. 19 August 2005 5 Th EM-DAT Technical Advisory Group Meeting Global Data on elements at risk Focused on two in this studyFocused on two in this study  Population / mortality (shown below)  GDP per unit area / economic losses (not shown)

8. 19 August 2005 5 Th EM-DAT Technical Advisory Group Meeting Global Data on Vulnerability of the Elements at Risk Vulnerability estimates guided by past eventsVulnerability estimates guided by past events EM-DAT has records of mortality, persons affected and direct economic damageEM-DAT has records of mortality, persons affected and direct economic damage  http://www.em-dat.net/ http://www.em-dat.net/ epidemiological approach based on mortality rate (extension to economic loss is straightforward)epidemiological approach based on mortality rate (extension to economic loss is straightforward)

9. 19 August 2005 5 Th EM-DAT Technical Advisory Group Meeting Mortality rates compute mortality rates using EM-DAT cumulative number of persons killed by a given hazard and divide by the total population in the area exposed to that hazardcompute mortality rates using EM-DAT cumulative number of persons killed by a given hazard and divide by the total population in the area exposed to that hazard e.g. globally, for storms :e.g. globally, for storms :  240,000+ fatalities between 1981 and 2000  1,312 million people in exposed area in 2000  16.6 fatalities per 100,000 population (note time periods) we can apply this rate to the population grid in areas exposed to the hazard to produce an estimate of expected fatalities over a 20 year periodwe can apply this rate to the population grid in areas exposed to the hazard to produce an estimate of expected fatalities over a 20 year period

10. 19 August 2005 5 Th EM-DAT Technical Advisory Group Meeting but: mortality is not distributed uniformlybut: mortality is not distributed uniformly e.g., earthquake of a given magnitude does more damage in India than in Japan social, economic and physical factors that reduce vulnerability:social, economic and physical factors that reduce vulnerability: building codes, emergency response, education, topography, geology many of these are related to the wealth of a countrymany of these are related to the wealth of a country Country data in EM-DAT is noisyCountry data in EM-DAT is noisy Geographic variations in mortality

11. 19 August 2005 5 Th EM-DAT Technical Advisory Group Meeting => use regionally specific mortality rates=> use regionally specific mortality rates WB regions classified into four income groups WB regions classified into four income groups geographically and hazard specific mortality rates provide a better estimate of potential vulnerabilitygeographically and hazard specific mortality rates provide a better estimate of potential vulnerability Geographic disaggregation

12. 19 August 2005 5 Th EM-DAT Technical Advisory Group Meeting Geographic disaggregation World Bank regions by income group

13. 19 August 2005 5 Th EM-DAT Technical Advisory Group Meeting mortality rates will be higher in areas where severity measures are largermortality rates will be higher in areas where severity measures are larger some indication of how severely different areas are affected within exposed areasome indication of how severely different areas are affected within exposed area measures of severity: estimates of frequency or probability, frequency by wind strength, expected potential peak ground acceleration for earthquakesmeasures of severity: estimates of frequency or probability, frequency by wind strength, expected potential peak ground acceleration for earthquakes use severity as a weight to adjust mortality ratesuse severity as a weight to adjust mortality rates Incorporating hazard severity

14. 19 August 2005 5 Th EM-DAT Technical Advisory Group Meeting 1.mortality rate 2.weighted cell mortality 3.adjustment 4.multi-hazard w here: h = hazard, i = grid cell, j = region_wealth M = mortality (EM-DAT), P = population (GPW3), W = hazard severity weight In summary

15. 19 August 2005 5 Th EM-DAT Technical Advisory Group Meeting Hurricane Severity and Intensity

16. 19 August 2005 5 Th EM-DAT Technical Advisory Group Meeting Uniform Global Mortality Rate log of mortality

17. 19 August 2005 5 Th EM-DAT Technical Advisory Group Meeting Region Specific Mortality Rate log of mortality

18. 19 August 2005 5 Th EM-DAT Technical Advisory Group Meeting Region Specific Mortality Weighted by Hazard Severity log of mortality

19. 19 August 2005 5 Th EM-DAT Technical Advisory Group Meeting Global results although the model output presents an estimate of predicted cumulative mortality from all hazards over a twenty year period, we interpret it as a notional index (low  high)although the model output presents an estimate of predicted cumulative mortality from all hazards over a twenty year period, we interpret it as a notional index (low  high) hazard specific mortality-weighted indexeshazard specific mortality-weighted indexes combined, multi-hazard hotspots indexcombined, multi-hazard hotspots index the same methodology can be applied to economic losses (globally /proportion)the same methodology can be applied to economic losses (globally /proportion)

20. 19 August 2005 5 Th EM-DAT Technical Advisory Group Meeting Estimated Mortality rates highest mortality rates:highest mortality rates:  droughts: AFR low income  earthquakes: ECA low middle income  floods: LAC upper middle income  storms: SA low income  landslides: EAP upper middle income  volcanoes: LAC low middle income given the limited time period and quality of input data => relative risk levels / deciles:given the limited time period and quality of input data => relative risk levels / deciles:

21. 19 August 2005 5 Th EM-DAT Technical Advisory Group Meeting Drought mortality risk hotspots

22. 19 August 2005 5 Th EM-DAT Technical Advisory Group Meeting Identification of areas affected by multiple hazards

23. 19 August 2005 5 Th EM-DAT Technical Advisory Group Meeting All hazards mortality risk hotspots note Africa vs. Europe

24. 19 August 2005 5 Th EM-DAT Technical Advisory Group Meeting All hazards total economic loss risk hotspots note Africa vs. Europe

25. 19 August 2005 5 Th EM-DAT Technical Advisory Group Meeting All hazards Prop economic loss risk hotspots note Africa vs. Europe

26. 19 August 2005 5 Th EM-DAT Technical Advisory Group Meeting Conclusion impact-weighted multi-hazard hotspots index combines information on hazard extent, exposed elements and vulnerability (based on historic impacts)impact-weighted multi-hazard hotspots index combines information on hazard extent, exposed elements and vulnerability (based on historic impacts) Scope for refinementScope for refinement  Better weights / response function (feasible?)  narrower definition of exposed area (hazards maps)  better (more complete) damage estimates (EM-DAT)  better definition of exposed economic assets

27. 19 August 2005 5 Th EM-DAT Technical Advisory Group Meeting Thank you

28. 19 August 2005 5 Th EM-DAT Technical Advisory Group Meeting

29. 19 August 2005 5 Th EM-DAT Technical Advisory Group Meeting consider hazard severity as the dose and hazard impacts as the responseconsider hazard severity as the dose and hazard impacts as the response requires ability to link specific hazard events (e.g., hurricanes) to their impacts (fatalities, economic damage)requires ability to link specific hazard events (e.g., hurricanes) to their impacts (fatalities, economic damage) statistical estimation also yields measures of accuracystatistical estimation also yields measures of accuracy e.g., M h = β o + β 1 H h + β 2 X h + ε where M h = damage (mortality) from disaster event h H h = characteristics of the hazard leading to disaster X h = exposure and vulnerability characteristics of area affected β 1 = an estimate of severity weight We.g., M h = β o + β 1 H h + β 2 X h + ε where M h = damage (mortality) from disaster event h H h = characteristics of the hazard leading to disaster X h = exposure and vulnerability characteristics of area affected β 1 = an estimate of severity weight W Statistical determination of weights

30. 19 August 2005 5 Th EM-DAT Technical Advisory Group Meeting Statistical determination of weights hazard severity hazard impact “ dose-response function ” could be any shape or form “ dose-response function ” could be any shape or form

31. 19 August 2005 5 Th EM-DAT Technical Advisory Group Meeting fatalities 1981-2000 per 100,000 inhabitants in 2000 Estimated mortality rates

32. 19 August 2005 5 Th EM-DAT Technical Advisory Group Meeting this is an intuitive approach and relatively easy to implement (but: it builds on many years of diligent data development!)this is an intuitive approach and relatively easy to implement (but: it builds on many years of diligent data development!) main problem: weighting is ad hoc and deterministic – need to know:main problem: weighting is ad hoc and deterministic – need to know:  what should be the cutoff for exposed area?  at what level of severity does damage occur?  how does damage vary with changes in severity? Caveats

33. 19 August 2005 5 Th EM-DAT Technical Advisory Group Meeting Mask areas of low pop, non-ag 55 % of area, 99 % of population remains