Hostname: page-component-78c5997874-s2hrs Total loading time: 0 Render date: 2024-11-04T19:14:37.207Z Has data issue: false hasContentIssue false
  • English
  • Français

Disaster Metrics: Evaluation of de Boer's Disaster Severity Scale (DSS) Applied to Earthquakes

Published online by Cambridge University Press:  29 December 2014

Jamil D. Bayram ,
Shawki Zuabi ,
Caitlin M. McCord ,
Raphael A.G. Sherak ,
Edberdt B. Hsu  and
Gabor D. Kelen
Jamil D. Bayram*
Affiliation:
Department of Emergency Medicine, Johns Hopkins School of Medicine, Baltimore, MarylandUSA
Shawki Zuabi
Affiliation:
Orange Coast Memorial Medical Center, Department of Emergency Medicine, Orange County, CaliforniaUSA
Caitlin M. McCord
Affiliation:
Department of Emergency Medicine, Johns Hopkins School of Medicine, Baltimore, MarylandUSA
Raphael A.G. Sherak
Affiliation:
Hampshire College, Amherst, MassachusettsUSA
Edberdt B. Hsu
Affiliation:
Department of Emergency Medicine, Johns Hopkins School of Medicine, Baltimore, MarylandUSA
Gabor D. Kelen
Affiliation:
Department of Emergency Medicine, Johns Hopkins School of Medicine, Baltimore, MarylandUSA
*
Correspondence: Jamil D. Bayram, MD, MPH, EMDM, MEd Johns Hopkins School of Medicine 5801 Smith Avenue Davis Building, Suite 3220 Baltimore, Maryland 21209 USA E-mail [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Introduction

Quantitative measurement of the medical severity following multiple-casualty events (MCEs) is an important goal in disaster medicine. In 1990, de Boer proposed a 13-point, 7-parameter scale called the Disaster Severity Scale (DSS). Parameters include cause, duration, radius, number of casualties, nature of injuries, rescue time, and effect on surrounding community.

Hypothesis

This study aimed to examine the reliability and dimensionality (number of salient themes) of de Boer's DSS scale through its application to 144 discrete earthquake events.

Methods

A search for earthquake events was conducted via National Oceanic and Atmospheric Administration (NOAA) and US Geological Survey (USGS) databases. Two experts in the field of disaster medicine independently reviewed and assigned scores for parameters that had no data readily available (nature of injuries, rescue time, and effect on surrounding community), and differences were reconciled via consensus. Principle Component Analysis was performed using SPSS Statistics for Windows Version 22.0 (IBM Corp; Armonk, New York USA) to evaluate the reliability and dimensionality of the DSS.

Results

A total of 144 individual earthquakes from 2003 through 2013 were identified and scored. Of 13 points possible, the mean score was 6.04, the mode = 5, minimum = 4, maximum = 11, and standard deviation = 2.23. Three parameters in the DSS had zero variance (ie, the parameter received the same score in all 144 earthquakes). Because of the zero contribution to variance, these three parameters (cause, duration, and radius) were removed to run the statistical analysis. Cronbach's alpha score, a coefficient of internal consistency, for the remaining four parameters was found to be robust at 0.89. Principle Component Analysis showed uni-dimensional characteristics with only one component having an eigenvalue greater than one at 3.17. The 4-parameter DSS, however, suffered from restriction of scoring range on both parameter and scale levels.

Conclusion

Jan de Boer's DSS in its 7-parameter format fails to hold statistically in a dataset of 144 earthquakes subjected to analysis. A modified 4-parameter scale was found to quantitatively assess medical severity more directly, but remains flawed due to range restriction on both individual parameter and scale levels. Further research is needed in the field of disaster metrics to develop a scale that is reliable in its complete set of parameters, capable of better fine discrimination, and uni-dimensional in measurement of the medical severity of MCEs.

BayramJD, ZuabiS, McCordCM, SherakRAG, HsuEB, KelenGD. Disaster Metrics: Evaluation of de Boer's Disaster Severity Scale (DSS) Applied to Earthquakes. Prehosp Disaster Med. 2015;30(1):1-6.

Keywords

disaster metricsDisaster Severity Scaleearthquakesmeasurementmultiple-casualty events
Type
Original Research
Information
Prehospital and Disaster Medicine , Volume 30 , Issue 1 , February 2015 , pp. 22 - 27
Copyright
Copyright © World Association for Disaster and Emergency Medicine 2014 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

Conflicts of interest/funding: none

References

1. Debacker, M. Evidence-based Disaster Medicine? Proceedings from the Second Mediterranean Emergency Medicine Congress in Sitges, Spain. Track D- The Disaster Medicine Track (EMDM). September 16, 2003.Google Scholar
2. Sundnes, KO. Task Force for Quality Control of Disaster Medicine (TFQCDM). Health disaster management: guidelines for evaluation and research in the Utstein style: executive summary. Prehosp Disaster Med. 1999;17(3):43-52.Google Scholar
3. Sundnes, KO. Disaster medical response research: a template in the Utstein style. Prehosp Disaster Med. 1996;11(2):11,16-24.Google Scholar
4. Bayram, JD, Zuabi, S, Subbarao, I. Disaster metrics: quantitative benchmarking of trauma-related hospital surge capacity in multiple casualty events. Disaster Med Public Health Prep. 2011;5(2):117-124.CrossRefGoogle ScholarPubMed
5. “Report of proceedings of the International Conference on Disaster Medicine held in Cape Town, August 1979.” In: MacMahan AJ, Jooste P, (eds). Disaster Medicine. Cape Town, South Africa: Balkema; 1980.Google Scholar
6. Rutherford, WH, de Boer, J. The definition and classification of disasters. Injury. 1983;15(1):10-12.CrossRefGoogle ScholarPubMed
7. de Boer, J. Definition and classification of disasters: introduction of a disaster severity scale. J Emerg Med. 1990;8(5):591-595.CrossRefGoogle ScholarPubMed
8. de Boer, J. Order in chaos: modelling medical management in disasters. Eur J Emerg Med. 1999;6(2):141-148.CrossRefGoogle ScholarPubMed
9. Ferro, G. Assessment of major and minor events that occurred in Italy during the last century using a disaster severity scale score. Prehosp Disaster Med. 2005;20(5):316-323.CrossRefGoogle ScholarPubMed
10. Significant Earthquake Database. National Oceanic and Atmospheric Administration (NOAA). http://www.ngdc.noaa.gov/nndc/struts/form?t=101650&s=1&d=1. Accessed March 26, 2014.Google Scholar
11. “Did You Feel It” Database. US Geological Survey (USGS). http://earthquake.usgs.gov/earthquakes/dyfi/. Accessed March 26, 2014.Google Scholar
12. Shoaf, K, Nguyen, LH, Sareen, H, Bourque, L. Injuries as a result of California earthquakes in the past decade. Disasters. 1998;22(3):218-235.CrossRefGoogle ScholarPubMed
13. Alexander, D. Editorial: on the spatial pattern of casualties in earthquakes. Ann Epidemiol. 2000;10(1):1-4.CrossRefGoogle ScholarPubMed
14. Peek-Asa, C, Ramirez, M, Seligson, H, Shaof, K. Seismic, structural, and individual factors associated with earthquake related injury. Inj Prev. 2003;9(1):62-66.CrossRefGoogle ScholarPubMed
15. Cronbach, L. Coefficient alpha and the internal structure of tests. Psychometrika. 1951;16(3):297-334.CrossRefGoogle Scholar
16. Miller, M. Coefficient alpha: a basic introduction from the perspectives of classical test theory and structural equation modeling. Struct Equ Modeling. 1995;2(3):255-273.CrossRefGoogle Scholar
17. Cortina, J. What is coefficient alpha: an examination of theory and applications. J Apply Psychol. 1993;78(1):98-104.CrossRefGoogle Scholar
18. Takavol, M, Dennick, R. Making sense of Cronbach's alpha. Int J Med Educ. 2011;2:53-55.Google Scholar
19. Hyvarinen, A, Karhunen, J, Oja, E. Independent Component Analysis. New York, New York USA: Wiley; 2001.CrossRefGoogle ScholarPubMed
20. Kim, JO, Mueller, CW. Factor Analysis: Statistical Methods and Practical Issues. Thousand Oaks, California USA; Sage Publications: 1978.CrossRefGoogle Scholar
21. Kline, P. An Easy Guide to Factor Analysis. Thousand Oaks, California USA; Sage Publications: 1994.Google Scholar
22. Mulaik, SA. The Foundations of Factor Analysis. New York, New York USA; McGraw-Hill: 1972.Google Scholar
23. Nunnally, JC, Berstein, IH. Psychometric Theory, 3rd ed. New York, New York USA; McGraw-Hill: 1994.Google Scholar
24. Rummel, RJ. Applied Factor Analysis. Evanston, Illinois USA; Northwestern University Press: 1970.Google Scholar