Data from: Disaster recovery – evidence from 100 natural disasters
Data files
Jan 09, 2026 version files 808.18 KB
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100_Disasters.xlsx
136.11 KB
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CRS_Disaster_Recovery_DB2.csv
670.82 KB
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README.md
1.25 KB
Abstract
This paper examines the factors that affect the recovery process following 100 major natural disasters. The study aimed to measure the speed and quality of recovery and to begin to answer the question of why some places recover faster and better than others. This worldwide study, conducted over a 15-year period, covers four natural hazards: major floods, storms, earthquakes, and tsunamis.
The following files are available for download:
- 100_Disasters.xlsx
- CRS_Disaster_Recovery_DB2.csv
100_Disasters.xlsx
This file has nine worksheets.
Data_030520
This is the data file with all fields as of 3 May 2020
Metrc_Definitions
Defines all the fields used in the data file
Metric_Codes
Coding of all fields
Countries
Economic type, based on World Bank data, and Economist Democracy Index
World Bank World Development Indicators http://wdi.worldbank.org/table/4.2
Economic type based on the proportion of Agricultural, Service and Industry GDP
Manual-AI Comparison
Speed of societal recovery, defined by time in years for ≥90% residents to return to permanent accommodation. Manual estimates produced by the research team from field study and desk work compared with AI estimates by ChatGPT based on an internet search of over 2000 references
CRS_Disaster_Recovery_DB2.csv
This file had one worksheet. This is a bibliography of 756 references used in the study, exported from Zotero
Methodology abstract
A number of indicators were considered to measure the speed of recovery, based on a “return to normality”.[i] Measures of the quality of recovery were based on the concept of “building back better” and a change in resilience.[ii] The speed of recovery was measured separately for ‘economy’ and ‘society’, based on the time taken in months to return to ‘normal’ to comply with the conditions listed below. The quality of recovery was measured in terms of changes in economic growth, safety and amenity. Improvements in these factors result in improved resilience, while a deterioration results in impaired recovery. They are each measured on a five-point scale: from 1, much worse to 5, much better.
Dependent variables - Factors measuring speed and quality of recovery
| Speed (months) | Quality (scale 1-5) | |
|---|---|---|
| Economy | Livelihoods ≥90% back in work; Economy ≥90% businesses back in operation; Services ≥90% telecoms, water, power restored | Economic growth |
| Society | Access fully restored; Temporary shelter completely cleared; Permanent housing ≥90% rehoused; Schooling ≥90% children in full-time school | Safety; Amenity |
Independent variables - Factors that might affect speed and quality of recovery
The independent variables that we imagined might affect the speed and quality of recovery include both "givens", including antecedent factors and the hazard load, and manageable factors, that include resourcing, organisation and management. (Table 4)
| Givens | Manageable Factors |
|---|---|
| ANTECEDENTS | RESOURCING |
| Economy Type (event year) | Self vs external finance |
| Income Group (2018) | Government aid |
| GDP Growth (event year) | Non-Governmental aid |
| GDP per Capita (event year) | Insured loss |
| GNI per Capita (event year) | Insurance penetration |
| IHDI Value (2017) | Speed of funding delivery |
| Gini Coefficient (2018) | Adequacy of funding |
| Corrupt. Index (2018) | ORGANISATION |
| Non-Life Insurance Penetration (event year) | State of Democracy |
| LOAD | Disaster Management Authority |
| Damage Severity (% damage buildings, infrastructure) | Preparedness |
| Economic Loss | Public Participation |
| Fatalities | MANAGEMENT |
| Displaced | Scientific basis of decision making |
| Affected Population | Decision Quality |
| Experience of previous disasters |
Data collection
Various data collection methods were used in a complementary way to provide both quantifiable and qualitative data.
Remote sensing (6 cases)
Interviews (15 cases)
Workshops (5 cases)
Surveys (7 cases)
EM-DAT international database (103 cases)
A cautionary note
In interpreting the information from published sources a number of measures relied on the subjective judgement of the author. Specifically this applies to the assessment of the speed and quality of recovery, in those cases where definitive information was unavailable, and to an assessment of the quality of decision making by the authorities responsible for disaster management.
The sources for each of the variables tabled in Appendix. Confidence level given for estimates of speed and quality and resourcing.
[i] Quarantelli, E.L. (1999), "What Is a Disaster: Perspectives on the Question", Disaster Prevention and Management, Vol. 8 No. 5, pp. 370-452. Routledge
[ii] Kim K., Olshansky R. B., (2014) The theory and practice of building back better. Journal of the American Planning Association 80 (4), 289-292