Hostname: page-component-586b7cd67f-t7czq Total loading time: 0 Render date: 2024-11-21T19:38:43.328Z Has data issue: false hasContentIssue false

Are We Ready for Mass Fatality Incidents? Preparedness of the US Mass Fatality Infrastructure

Published online by Cambridge University Press:  28 December 2015

Jacqueline A. Merrill
Affiliation:
Department of Nursing in Biomedical Informatics, Columbia University Medical Center, New York, New York
Mark Orr
Affiliation:
Social and Decision Analytics Laboratory, Virginia Polytechnic Institute and State University-National Capital Region, Arlington, Virginia
Daniel Y. Chen
Affiliation:
Social and Decision Analytics Laboratory, Virginia Polytechnic Institute and State University-National Capital Region, Arlington, Virginia
Qi Zhi
Affiliation:
Phillip R. Lee Institute for Health Policy Studies, School of Medicine, University of California, San Francisco
Robyn R. Gershon*
Affiliation:
Phillip R. Lee Institute for Health Policy Studies and Department of Epidemiology and Biostatistics, School of Medicine, University of California, San Francisco.
*
Correspondence and reprint requests to Robyn R. Gershon, DrPH, MHS, Phillip R. Lee Institute for Health Policy Studies and Department of Epidemiology and Biostatistics, School of Medicine, University of California, San Francisco, 3333 California Street, Suite 280, San Francisco, CA 94118 (e-mail: robyn.gershon@ucsf.edu).

Abstract

Objective

To assess the preparedness of the US mass fatality infrastructure, we developed and tested metrics for 3 components of preparedness: organizational, operational, and resource sharing networks.

Methods

In 2014, data were collected from 5 response sectors: medical examiners and coroners, the death care industry, health departments, faith-based organizations, and offices of emergency management. Scores were calculated within and across sectors and a weighted score was developed for the infrastructure.

Results

A total of 879 respondents reported highly variable organizational capabilities: 15% had responded to a mass fatality incident (MFI); 42% reported staff trained for an MFI, but only 27% for an MFI involving hazardous contaminants. Respondents estimated that 75% of their staff would be willing and able to respond, but only 53% if contaminants were involved. Most perceived their organization as somewhat prepared, but 13% indicated “not at all.” Operational capability scores ranged from 33% (death care industry) to 77% (offices of emergency management). Network capability analysis found that only 42% of possible reciprocal relationships between resource-sharing partners were present. The cross-sector composite score was 51%; that is, half the key capabilities for preparedness were in place.

Conclusions

The sectors in the US mass fatality infrastructure report suboptimal capability to respond. National leadership is needed to ensure sector-specific and infrastructure-wide preparedness for a large-scale MFI. (Disaster Med Public Health Preparedness. 2016;10:87–97)

Type
Original Research
Copyright
Copyright © Society for Disaster Medicine and Public Health, Inc. 2015 

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.)

References

1. Terbush, JW, Huckaby, GC, Luke, M. Civil-military integration for mass-fatality events. In: Gursky EA, Fierro MF, eds. Death in Large Numbers: the Science, Policy, and Management of Mass Fatality Events. Chicago, IL: American Medical Association; 2012.Google Scholar
2. Centers for Disease Control and Prevention. A Framework for Improving Cross-Sector Coordination for Emergency Preparedness and Response. http://www.cdc.gov/phlp/docs/CDC_BJA_Framework.pdf. Published July 2008. Accessed November 19, 2015.Google Scholar
3. Abbott, D. Disaster public health considerations. Prehosp Disaster Med. 2000;15(4):158-166.Google Scholar
4. Kapucu, N, Van Wart, M. The Evolving Role of the Public Sector in Managing Catastrophic Disasters: Lessons Learned. Administration & Society. 2006;38(3):279-308.Google Scholar
5. Federal Emergency Management Agency. National Response Framework. https://www.fema.gov/national-response-framework. Accessed November 19, 2015.Google Scholar
6. Gursky, E. A working group consensus statement on mass-fatality planning for pandemics and disasters. Journal of Homeland Security. July 2007.Google Scholar
7. Federal Emergency Management Agency. National Preparedness Report. http://www.fema.gov/national-preparedness-report. Accessed November 19, 2015.Google Scholar
8. SurveyMonkey Inc https://www.surveymonkey.com/. Accessed July 7, 2015.Google Scholar
9. R: A Language and Environment for Statistical Computing. [computer program]. Vienna, Austria: R Foundation for Statistical Computing; 2010.Google Scholar
10. Carley, KM. ORA: A Toolkit for Dynamic Network Analysis and Visualization. In: Alhajj R, Rokne J, eds. Encyclopedia of Social Network Analysis and Mining. New York, NY: Springer; 2014; http://dx.doi.org/10.1007/978-1-4614-6170-8_309.Google Scholar
11. Wasserman, S, Faust, K. Social Network Analysis: Methods and Applications. Vol 8. New York, NY: Cambridge University Press; 1994; http://dx.doi.org/10.1017/CBO9780511815478.Google Scholar
12. National Disaster Interfaiths Network. http://www.n-din.org/. Accessed July 7, 2015.Google Scholar
13. Gershon, RR, Magda, LA, Riley, HE, Merrill, JA. Mass fatality preparedness in the death care sector. J Occup Environ Med. 2011;53(10):1179-1186.Google Scholar
14. Merrill, JA, Carley, KM, Orr, MG, et al. Patterns of interaction among local public health officials and the adoption of recommended practices. Front Public Health Serv Syst Res. 2012;1(1):6.Google Scholar
15. Chaffee, M. Willingness of health care personnel to work in a disaster: an integrative review of the literature. Disaster Med Public Health Prep. 2009;3(1):42-56. http://dx.doi.org/10.1097/DMP.0b013e31818e8934.Google Scholar
16. Gershon, RR, Magda, LA, Qureshi, KA, et al. Factors associated with the ability and willingness of essential workers to report to duty during a pandemic. J Occup Environ Med. 2010;52(10):995-1003.CrossRefGoogle ScholarPubMed
17. Qureshi, K, Gershon, RR, Sherman, MF, et al. Health care workers’ ability and willingness to report to duty during catastrophic disasters. J Urban Health. 2005;82(3):378-388. http://dx.doi.org/10.1093/jurban/jti086.Google Scholar
18. Fierro, MF. Mass murder in a university setting: analysis of the medical examiner’s response. Disaster Med Public Health Prep. 2007;1(1 suppl):S25-S30. http://dx.doi.org/10.1097/DMP.0b013e31814cf374.Google Scholar
19. Santa Clara County Public Health Department Advanced Practice Center. Managing Mass Fatalities: A Toolkit for Planning. https://www.sccgov.org/sites/sccphd/en-us/HealthProviders/BePrepared/Pages/Managing-Mass-Fatalities.aspx. Published May 2008. Accessed November 19, 2015.Google Scholar
20. Floría, LM, Gracia-Lázaro, C, Gómez-Gardeñes, J, et al. Social network reciprocity as a phase transition in evolutionary cooperation. Physical Review E. 2009;79(2):026106. http://dx.doi.org/10.1103/PhysRevE.79.026106.Google Scholar
21. Simo, G, Bies, AL. The role of nonprofits in disaster response: an expanded model of cross‐sector collaboration. Public Adm Rev. 2007;67(s1):125-142. http://dx.doi.org/10.1111/j.1540-6210.2007.00821.x.Google Scholar
22. Haythornthwaite, C. Social network analysis: an approach and technique for the study of information exchange. Libr Inf Sci Res. 1996;18(4):323-342. http://dx.doi.org/10.1016/S0740-8188(96)90003-1.Google Scholar
23. Hossain, L, Kuti, M. Disaster response preparedness coordination through social networks. Disasters. 2010;34(3):755-786. http://dx.doi.org/10.1111/j.1467-7717.2010.01168.x.Google Scholar
24. Hawe, P, Webster, C, Shiell, A. A glossary of terms for navigating the field of social network analysis. J Epidemiol Community Health. 2004;58(12):971-975. http://dx.doi.org/10.1136/jech.2003.014530.Google Scholar
25. Mohammadfam, I, Bastani, S, Esaghi, M, et al. Evaluation of coordination of emergency response team through the social network analysis. Case study: oil and gas refinery. Saf Health Work. 2015;6(1):30-34.Google Scholar
26. Kenis, P, Knoke, D. How organizational field networks shape interorganizational tie-formation rates. Acad Manage Rev. 2002;27(2):275-293.Google Scholar
27. United States Census Bureau. USA Counties. 1969-2007. http://censtats.census.gov/usa/usainfo.shtml. Accessed May 4, 2015.Google Scholar
28. Woody, AC, Boyer, DA. Mass Fatality Management: Local & Regional Planning. Presented at: Texas Emergency Management Conference; March 2013; Texas.Google Scholar
29. Waugh, WL, Streib, G. Collaboration and leadership for effective emergency management. Public Adm Rev. 2006;66(s1):131-140. http://dx.doi.org/10.1111/j.1540-6210.2006.00673.x.Google Scholar
30. Partnership for Public Service. Annual Report. Washington, DC: Partnership for Public Service; 2008.Google Scholar
31. Federal Emergency Management Agency. National Training and Education (NTE). FEMA website. https://training.fema.gov/. Accessed July 15, 2015.Google Scholar
32. Frank DePaolo. Regional catastrophic mass fatality management response system. Presented at: International Mass Fatality Management Conference; April 25-27, 2012; New York, NY.Google Scholar
33. Walsh, L, Subbarao, I, Gebbie, K, et al. Core competencies for disaster medicine and public health. Disaster Med Public Health Prep. 2012;6(1):44-52. http://dx.doi.org/10.1001/dmp.2012.4.Google Scholar
34. US Department of Health and Human Services. Emergency Support Function #8 - Public Health and Medical Services Annex. http://www.fema.gov/media-library-data/20130726-1914-25045-3446/final_esf_8_public_health_medical_20130501.pdf. Accessed July 7, 2015.Google Scholar