Essay
student2006
Journal-of-Emergency-Management.zipJEM.pdf
Journal of
EMERGENCY MANAGEMENT
JE M
Emergency Planning and Response Risk Management Disaster Recovery
Business Continuity
®
Volume 9 • Number 4 July/August 2011 ISSN 1543-5865
470 Boston Post Road
Weston, MA 02493
781-899-2702 n Fax: 781-899-4900
Web site:
www.emergencymanagementjournal.com
eJournal:
ejournal.emergencymanagementjournal.com
E-mail:
Title_Title.qxd 8/10/2011 10:20 AM Page 1
J E M
Subscription�Rates�(Rates in US dollars): Individual: US $203; Canada $234; Foreign $308 Institutions:�US $278; Canada $328; Foreign $421 Libraries:�US $287; Canada $335; Foreign $432 Student�Rate: US $79.50; Canada $126.50; Foreign $181.50 Single�issues: US $50; Canada $60; Foreign $70
Subscription� Information:� On-line, visit our website at www.emergencymanagement journal.com. By mail, submit your complete name, address, and zip code, attention: Journal of Emergency Management, Subscription Department, 470 Boston Post Road, Weston, MA 02493. Please enclose check, purchase order, or credit card number and expiration date with author- ization signature. Student Rate requires photocopy of current student ID along with payment. Subscribers notifying the publication of an address change must submit an old mailing label and their new address, including zip code. No claims for copies lost in the mail may be allowed unless they are received within 90 days of the date of issue. Claims for issues lost as a result of insufficient notice of change of address will not be honored.
Manuscript�Submittal/Author�Information�(See�Call�for�manuscripts)
Quotations�and�Reprints:�Quotations from Journal of Emergency Management may be used for purposes of review without applying for permission as long as the extract does not exceed 200 words of text, and appropriate credit is given to the Journal. Authorization to photocopy items for internal use of specific clients is granted by Weston Medical Publishing, LLC, provided the appropriate fee is paid directly to: Copyright Clearance Center (CCC), 222 Rosewood Drive, Danvers, MA 01923, USA, 978-750-8400. CCC should also be contacted prior to photocopying items for educational classroom use. Multiple reprints of material published in Journal of Emergency Management can be obtained by filling out the reprint order form in the publication, by calling 781-899-2702, or visit our Web site at www.emergencymanagementjournal.com.
Trademarks�and�Copyrights:�Journal of Emergency Management is a registered trademark of Weston Medical Publishing, LLC. All materials are ©2011 by Weston Medical Publishing, LLC. All rights reserved.
Postal�Information:�Postmaster: Send address changes and form 3579 to: Journal of Emergency Management, 470 Boston Post Road, Weston, MA 02493.
Disclaimer: The publisher and editors are not responsible for any opinions expressed by the authors for articles published in Journal of Emergency Management.
Copyright 2011. Quotation is not permitted except as above. Duplicating an entire issue for sharing with others, by any means, is illegal. Photocopying of individual items for internal use is permitted for registrants with the Copyright Clearance Center, 222 Rosewood Drive, Danvers, MA 01923. For details, call 978-750-8400 or visit www.copyright.com. For elec- tronic or hard copy reprints visit our website www.emergencymanagementjournal.com or www.emergencyjournal.com.
12234 2/09/11 Rev w
Published bimonthly by Weston Medical Publishing, LLC 470 Boston Post Rd., Weston, MA 02493 • 781-899-2702, Fax: 781-899-4900
E-mail: [email protected] • Web site: www.emergencyjournal.com or www.emergencymanagementjournal.com
ISSN 1543-5865
Publisher Richard A. DeVito, Jr.
Publisher�Emeritus Richard A. DeVito, Sr.
President�Emeritus Eileen F. DeVito
Editorial�Coordinator Deborah Rines [email protected]
Peer-Review�Manager Holly Messerschmidt [email protected]
Advertising�Program�Manager Kelly Miller M. J. Mrvica Associates [email protected] 2�W.�Taunton�Avenue Berlin�NJ�08009 Phone:�856-768-9360
Sales�&�Marketing�Director George A. Marks, Jr. [email protected]
Subscription�Manager Brenda DeVito [email protected]
12234 8/10/2011 10:27 AM Page 1
J E M EDITORIA L BOAR DBarbara Audley, DPAWestern Washington University,
Bellingham, Washington
Paul Barnes, PhD Senior Lecturer, School of
Management; Deputy Director,
Information Security Institute,
Queensland University of Technology,
Brisbane, Australia
Richard A. Bissell, PhD Associate Professor, University of
Maryland–Baltimore County,
Baltimore, Maryland
B. Wayne Blanchard, PhD, CEM Higher Education Project
Manager, Emergency Management
Institute, Federal Emergency
Management Agency
(FEMA), Department
of Home land Security,
Emmitsburg, Maryland
Hilda J. Blanco, PhD Professor and Chair, University of
Washington, Seattle, Washington
Paul A. Bott, EdD Professor and Chair, Professional
Studies Department, California
State University–Long Beach,
Long Beach, California
H. Stefan Bracha, MD National Center for
Posttraumatic Stress
Disorder-Pacific Island Division,
Department of Veterans Affairs,
Spark M. Matsunaga Medical Center,
Honolulu, Hawaii
Michael W. Brand, PhD Assistant Professor of Research,
University of Oklahoma
Health Sciences Center,
College of Public Health,
Oklahoma City, Oklahoma
Anthony E. Brown, PhD, MPA Associate Professor and Coordinator,
Oklahoma State University,
Stillwater, Oklahoma
Lucien G. Canton, CEM, CPP, CBCP Emergency Management Consultant,
San Francisco, California
Stephen Stuart Carter, MS Academic Director, Emergency
Management, Fire Science, and
Homeland Security, Department of
Business and Professional Programs,
University of Maryland University
College, Adelphi, Maryland
Steven J. Charvat, CEM Emergency Management Director,
University of Washington, Office
of Emergency Management,
Seattle, Washington
John B. Copenhaver Chairman and CEO,
Contingency Management Group,
Alpharetta, Georgia
Russel J. Decker, MS, CEM Director, Allen County Office of
Homeland Security & Emergency
Management, Lima, Ohio
Daniel E. Della-Giustina, PhD Professor, Industrial and Manage -
ment Systems Engineering, Safety &
Environmental Management Program,
College of Engineering and Mineral
Resources, West Virginia University,
Morgantown, West Virginia
Raymond V. DeMichiei, BA, EMT-P Deputy Director; WMD Coordinator,
City of Pittsburgh, Office of the
Mayor, Emergency Management
Agency, Pittsburgh, Pennsylvania
Amy K. Donahue, PhD Associate Professor and Department
Head, Department of Public Policy,
University of Connecticut, West
Hartford, Connecticut
Thomas Drabek, PhD John Evans Professor, Emeritus,
Department of Sociology and
Criminology, University of Denver,
Denver, Colorado
Martin Gill, PhD
Director, Perpetuity Research and
Consultancy International, and
Professor of Criminology, University
of Leicester, United Kingdom
Roger E. Glick, MS, MBA Director, Emergency Management
and Safety, Carilion Medical Center,
Carilion Clinic, Roanoke, Virginia
12235 3/1/11 Rev aa
William L. Waugh, Jr., PhD
Editor-in-Chief
Professor, Public Administration and Urban Studies/Political Science
Andrew Young School of Policy Studies
Georgia State University, Atlanta, Georgia
12235_12235.qxd 8/10/2011 10:26 AM Page 1
Kay C. Goss, CEM Senior Principal and Director of
Emergency Management, SRA
International, Arlington, Virginia
Tee L. Guidotti, MD, MPH, DABT HSE and Sustainability Advisor,
Medical Advisory Services,
Rockville, Maryland
Wallace G. “Bo” Harris, PhD, SPHR Professor and Program Coordinator,
Emergency Services Management/
Disaster Science, School of Continuing
Studies, University of Richmond,
Richmond, Virginia
Jeffery A. Hartle, MS, CFPS, MIFireE, Vice President, Skillful Means, Inc., Knob Noster, Missouri
George A. Heake, Jr. Disaster Management and Response
Coordinator, Institute on Disabilities
(UCEDD), Temple University,
Philadelphia, Pennsylvania
Vincent E. Henry, CPP, PhD Professor and Director, Homeland
Security Management Institute,
A DHS National Transportation Security
Center of Excellence, Long Island
University, Southampton, New York
Peter J. Hotez, MD, FAAP, PhD
Professor of Microbiology,
Tropical Medi cine, Global Health
and In ter na tional Affairs; Chair,
Depart ment of Micro biology
and Tropical Medicine, George
Washington University Medical
Center,Washington, DC
Robert D. Jaffin, MBA Program Manager, American Public
University, Charles Town, West Virginia
E. Lynn Jenkins, PhD
Senior Scientist, Office of Research and
Technology Transfer, National Institute
for Occupational Safety and Health,
Centers for Disease Control and
Pre vention, Morgantown, West Virginia
Andrea Jennings-Sanders, DrPh, RN
Associate Professor, Cleveland
University School of Nursing,
Cleveland, Ohio
Paul D. Kim, MD
Director of Planning and National
Security Service, Office of Security
and Preparedness, Department of
Veterans Affairs, Albany, New York
Daniel J. Klenow, PhD
Professor and Head, Department of
Emergency Management, North Dakota
State University, Fargo, North Dakota
Gunnar J. Kuepper
Chief of Operations, Emergency
& Disaster Management, Inc.,
Los Angeles, California
John Roderick Lindsay, MCP
Assistant Professor and Chair,
Department of Applied Disaster
and Emergency Studies,
Brandon University, Brandon,
Manitoba, Canada
Valerie Lucus-McEwen, CEM, CBCP Emergency & Business Continuity
Manager, University of California,
Davis, Davis, California
David A. McEntire, PhD Associate Professor, University of
North Texas, Denton, Texas
Robert K. McLellan, MD, MPH
Occupational Medicine, Dartmouth
Hitchcock Medical Center,
Lebanon, New Hampshire
Edith F. Neumann, PhD
Professor; President, TUI Institute
of Learning, Touro University
International, Cypress, California
William C. Nicholson, JD
Department of Criminal Justice,
North Carolina Central University,
Durham, North Carolina
Corinne Peek-Asa, MPH, PhD
Associate Professor, UCLA
School of Public Health,
Department of Epidem iology,
Los Angeles, California
Danny M. Peterson, PhD Professor of Practice, Arizona State
University, Mesa, Arizona
Scot Phelps, JD, MPH, Paramedic, CEM/CBCP/MEP Professor, Emergency Management
Academy, New York City, New York
John C. Pine, EdD Director, Disaster Science,
Louisiana State University,
Baton Rouge, Louisiana
Randy Rapp, DMgt, PE
Associate Professor, College of
Technology, Purdue University,
West Lafayette, Indiana
Richard Reed, MSW
Management Analyst, Emergency
Preparedness Coordinator, Department
of Veterans Affairs, Washington, DC
Havidan Rodriguez, PhD Director, Disaster Research
Center, University of Delaware,
Newark, Delaware
Phillip D. Schertzing, PhD Director, Global Community Security
Institute, Michigan State University,
East Lansing, Michigan
Robert O. Schneider, PhD Associate Vice Chancellor International
Programs, University of North Carolina
at Pembroke, Pembroke, North Carolina
Robert M. Schwartz, PhD
Associate Professor of Emergency
Management, Department of Public
Service Technology, The University
of Akron, Akron, Ohio
Joseph J. Schwerha, MD, MPH
Professor, Department of Occupational
and Environmental Health, University
of Pittsburgh, Graduate School of Public
Health, Pittsburgh, Pennsylvania
Robert Shesser, MD, MPH, FACP
Professor and Chair, Department of
Emergency Medicine; Director, Ronald
Reagan Institute of Emer gency Medi -
cine, George Washington University
Medical Center, Washington, DC
Gary Leonard Simon, MD, PhD
Professor of Medicine (Infectious
Diseases), Biochemistry, and Molecular
Biology, George Washington University
Medical Center, Washington, DC
Neil Simon, MA
President, Incident Mitigation LLC,
Southfield, Michigan
Susan M. Smith, EdD, MSPH Associate Professor, Department of
Applied Health Sciences, Indiana
University, Bloomington, Indiana
Richard T. Sylves, PhD
Professor, Political Science
Department, University of Delaware,
Newark, Delaware
J. R. Thomas
Associate Vice President, Domestic
Emergency Management Unit, Save
the Children, Columbus, Ohio
Derin Ural, PhD
Professor and Vice President,
Istanbul Technical University,
Maslak, Istanbul, Turkey
Steven Weinstein, MT (ASCP), MPH, CIC, Environmental, Health & Safety
Specialist, Abbott Laboratories, MediSense
Products, Bedford, Massachusetts
Mitchell Yudasz, Jr., PhD
Emergency Management Director,
Monroe County Emergency Management
Division, Monroe, Michigan
12235_12235.qxd 8/10/2011 10:26 AM Page 2
JE M CONTENTSEDITORIAL� Playgrounds helping to heal traumatized children .....................11David B. Jones, EdD, CTRS
FEATURE ARTICLES � Emergency management 2.0: Integrating social media
in emergency communications .......................................................13 R. Sabra Jafarzadeh, JD
� Cost and benefits of a typical county’s emergency response program ............................................................................19 Lillian R. Butterworth, MS Steve Riedel, BS J. Eric Dietz, PhD, PE
� Impact of a multidisciplinary disaster response exercise..............35 David J. Cook, PhD Niaman Nazir, MBBS, MPH Marta Skalacki, BA Carole Dale Grube, MA Won S. Choi, PhD, MPH
� Disaster preparedness and educational attainment ......................45 Lauren A. Menard, EdD Robert O. Slater, PhD Jim Flaitz, PhD
� Radiological dispersal events within urban environments: A general method of measuring the economic impacts..................53 Antoine N. Munfakh, MS David A. Smith, PhD Daniel T. Holt, PhD Leonard J. Kloft, PhD Eric J. Unger, PhD Jeremy M. Slagley, PhD
� A spatially accurate incident reporting system during the 2010 Gulf of Mexico oil spill disaster .........................................69 Joshua D. Kent, PhD Roy K. Dokka, PhD
Emergency concerns cross borders— whether you are down the street or across the world. Today, being connected is more important than ever. IAEM brings together emergency managers and disaster response professionals from all levels of government, as well as the military, the private sector, and volunteer organizations around the world.
Joining IAEM brings you benefits that connect you with: • A large, network of experts offering solutions, guidance
and assistance.
• Job opportunities on our extensive online listing. • A unified voice on policies and legislation. • Information updates via email and our monthly newsletter. • Professional tools and discussion groups on www.iaem.com. • Certified Emergency Manager® and Associate Emergency
Manager programs.
• Scholarship program.
Now more than ever, IAEM is for you…
Join IAEM Today!
KEYNOTE SPEAKER
W. Craig Fugate Administrator of the Federal Emergency
Management Agency
Amanda Ripley Author, The Unthinkable: Who Survives When Disaster Strikes—and Why
Jason Ryan Dorsey, The Gen Y Guy® Crossing the Generational Divide: Leveraging the Power of Generations™ for Your Strategic Advantage
Gordon Graham Ignoring Problems Lying In Wait: The Ultimate High Stakes Gamble
®
Power of Generations™ for Your Strategic Advantage
Jason Ryan Dorsey, The Gen Y Guy Crossing the Generational Divide: Leveraging the Power of Generations™ for Your Strategic Advantage
Jason Ryan Dorsey, The Gen Y Guy®
Power of Generations™ for Your Strategic Advantage
Who Should Attend?
Save the Date! NOVEMBER 11-18, 2011
www.EMEX.org
www.IAEM.com
You don’t want to miss this great opportunity to network and exchange ideas with more than 2,500 others in the emergency management and homeland security fields. Attendees will benefit from educational forums on current industry trends and tools, as well as professional training.
While you’re here, plan to visit EMEX 2011— the showcase for leading technolgies, products and services in emergency management.
www.www.IAEM.com.com Join us in Clark County, NV for the 2011 IAEM-USA Annual Conference and EMEX.
FEATURED SESSIONS INCLUDE:
Emergency concerns cross borders— whether you are down the street or
Get Connected. Be a part of the organization that represents Emergency Managers in local communities, and around the globe.
Clark County, NV, USA | Rio All-Suites Hotel
FOR EMERGENCY MANAGERS
● Emergency Managers
● Homeland Security Officials
● First Response Coordinators
● Contingency Planners
● Private Industry Risk Managers
● Operations Personnel
● Contract Services Providers
● Emergency/Disaster Management Students
IAEM_JEMsAd_FPg_crops-bleedF.pdf 8/17/11 9:52:42 AM
Journal of Emergency Management Higher Education Directory is a trademark of and ©2011 Weston Medical Publishing, LLC. All rights reserved.
Higher Education Directory Volume�9,�Number�4J
E M
TM
EMERGENCY
MANAGEMENT
CALU ������ ������
California University of Pennsylvania Building Character. Building Careers.
www.calu.edu/go A proud member of the Pennsylvania State System of Higher Education.
BACHELOR OF SCIENCE OR MASTER OF SCIENCE IN
Legal Studies 1 0 0 % O N L I N E D E G R E E
The 100% online curriculum provides students with a strong foundation in criminal, family, real estate, administrative and business law. It also includes a set of competencies in legal research and writing, litigation, estates and trusts, bankruptcy, ethics and constitutional law.
To learn more about the 100% online BS and MS in Legal Studies: Law & Public Policy, Homeland Security and Criminal Justice tracks, and other unique online opportunities, visit Cal U’s website at www.calu.edu/go or call 724-597-7400.
• LAW & PUBLIC POLICY TRACK • HOMELAND SECURITY TRACK • CRIMINAL JUSTICE TRACK
University in the country for online degree programs.* *www.guidetoonlineschools.com
#1
12575 8/15/2011 7:06 AM Page 1
Attention
Emergency Management Students
Enhance your education
with a student subscription to the
Journal of Emergency Management Benefit from the latest research in Emergency Management!
The Journal of Emergency Management is written, edited and peer reviewed by
an internationally recognized team of EM experts that include top professionals from
the leading public, private and academic sectors. They provide perspective and
analysis on the latest research and studies. The journal provides you with the most
thorough, relevant and useful source of information on emergency management.
Read About The Most Pressing Issues In Your Field!
Published bi-monthly, every issue of the Journal of Emergency Management is
packed with invaluable information and insight. Topics include:
- Emergency planning and response
- Disaster recovery and business continuity planning
- Emergency preparedness and response legislation
- Risk management
- Emergency management today, tomorrow and in the future
- Severe weather, flood and hurricane studies
- Emergency communications
- Continuity of operations and infrastructure protection
- Preparation and evacuation for the disabled
- Cross-training in emergency management
Enhance Your Education, Subscribe Today...Includes Online Access!
To start your student subscription to the Journal of Emergency Management,
send a copy of your current student ID along with your name, complete address,
email and payment of $79.50* to: Journal of Emergency Management Student
Program, 470 Boston Post Road, Weston, MA 02493. Or visit our website, select an
individual subscription and complete the order with coupon code JEMST2011 at
checkout. (*Student rates outside US are slightly higher due to the increased postage costs.)
www.emergencymanagementjournal.com
Scan this QR barcode
to order JEM
at the student rate
Use Coupon Code
JEMST2011 at checkout
for student rate
12575 8/15/2011 7:07 AM Page 2
� LIVES DEPEND ON MY LEADERSHIP. AMU teaches what I use in the fi eld.”
Shannondor Marquez | Graduate, School of Public Safety and Health
AMU is proud of our graduates’ success. A retired Sr. Chief Petty Offi cer,
Shannondor combines education with 28 years of experience to help lead
emergency operations at Naval Medical Center Portsmouth. Like 40% of our
graduates, Shannondor chose AMU to pursue his master’s based on academic
quality and the caliber of its faculty.
Learn More at www.PublicSafetyatAMU.com/JEM
Art & Humanities | Business | Education | Management | Public Safety & Health | Science & Technology | Security & Global Studies
What’s This? AMU-QR.com
12575 8/15/2011 7:07 AM Page 3
GENERAL INFORMATION
SCOPE
Journal of Emergency Management (JEM)
is a vehicle for academics and practitioners
to share field research. In addition to scien-
tific studies and program descriptions, we
will consider letters to the editor, guest edi-
torials, and book reviews. Individuals desir-
ing to contribute should not hesitate to make
inquiries, even if they are unfamiliar with
procedures for writing and submitting man-
uscripts. Our goal is to provide original, rel-
evant, and timely information from diverse
sources; to publish with absolute integrity;
and to serve as effectively as possible the needs
of those involved in emergency manage-
ment. If your research will help us achieve
these goals, we would like to hear from you.
MANUSCRIPT SUBMISSION
Manuscripts submitted for consideration
must not have been previously published
(other than as an abstract) and must not be
under consideration for publication else-
where. JEM encourages the online submis-
sion of materials to be considered for publi-
cation. Online submission (with in struc tions)
is available at http://jem.allentrack2.net.
Those without access to online submission
may submit manuscripts to the editor.
Manuscripts submitted by mail must include
one hard copy and a copy on computer disk.
Each mailed submission must include one
full set of original figures as well as figures
on diskette or CD (if possible).
PERMISSIONS
Submission of a manuscript to JEM is taken
as evidence that no portion of the text or fig-
ures has been published or submitted for
publication elsewhere, unless information
regarding previous publication is explicitly
cited and copyright permission obtained (fax
or mail to JEM editorial office—see above)
at the time of manuscript submission.
Permission should be obtained for both print
and online publication.
MANUSCRIPT PUBLICATION
Publication of material in JEM should not be
interpreted as an endorsement of the materi-
al contained therein. Authors are responsible
for the accuracy of references and statistical
computations. The author(s) acknowledge that
the publisher reserves the right to charge
authors for excessive revisions made to their
galley proofs. Authors are responsible for all
excessive revision charges associated with
their article. Publication may be withheld if
authors fail to fulfill these financial obligations.
REPRINTS
Single reprints may be purchased online at
www.emergencymanagementjournal.com;
click on the "Abstracts" link and select year
of publication to view all abstracts and pur-
chase your selection. Reprints in quantities of
100 or more may be ordered from JEM, 470
Boston Post Road, Weston, MA 02493; tele-
phone: (781) 899-2702; fax: (781) 899-
4900.
AUTHOR RESPONSIBILITY
The corresponding author is responsible for
ensuring that all individuals named as co-
authors have made a major contribution to
the manuscript. Authorship credit should be
based on significant contributions to all of
the following: 1) conception and design, or
acquisition of data, or analysis and interpre-
tation of data; 2) drafting of the manuscript
or critical revision of the manuscript for
important intellectual content; and 3) final
approval of the submitted manuscript. Each
author must declare his or her contribution
to the manuscript on the copyright transfer
form from the JEM editorial office.
FINANCIAL DISCLOSURE/CONFLICT
OF INTEREST
Authors are required to disclose, in a cover
letter accompanying their manuscript, any
relevant conflict of interest, including direct
or indirect financial interests they may have
in the materials or subject matter dealt with
in the manuscript. This information will be
held in confidence by the editor during the
review process but, at the discretion of the
editor, may be included in publication of an
accepted manuscript.
PATIENT ANONYMITY
The author is responsible for ensuring the
protection of a patient's anonymity. A signed
consent form must accompany any figure
including recognizable individuals. Shading
of the eyes is not an acceptable means of
rendering an individual unrecognizable. If
an author chooses to use his/her own institu-
tional patient permission form, it must
include permission to use photographs for
all types of publication including but not
limited to print, visual, electronic, or broad-
cast media. Consent forms should be mailed
or faxed to the JEM editorial office.
REFERENCES
References are organized in AMA format;
that is, they are to be cited numerically in the
text and in consecutive order, including the
first three authors followed by et al., and listed
at the end of the article in the following format:
Journal articles— 1. Mudd P, Smith JG,
Allen AZ, et al.: High ideals and hard cases:
The evolution of opioid therapy for cancer
pain. Hastings Cent Rep. 1982; 12(2): 11-14.
Books— 1. Bayles SP (ed.): Nutritional
Supplements and Interactions with Analgesics.
Boston: GK Hall & Co., 1978.
Book chapters— 1. Martin RJ, Post SG:
Introducing alternative prescribing strategies.
In Smith J, Howard RP, Donaldson P (eds.):
The Oncology Management Handbook.
Madison, WI: Clearwater Press, 1998, pp.
310-334.
Web sites— Health Care Financing
Administration: HCFA Statistics at a glance.
Available at: www.hcfa/gov/stats/stahili.htm.
Accessed December 27, 2002.
12832 2/14/08 Rev. c
470 Boston Post Road, Weston, MA 02493 • 781-899-2702 • Fax: 781-899-4900
E-mail: [email protected] • Web site: www.emergencymanagementjournal.com
Online manuscript submission (with instructions) http://jem.allentrack2.net
Call for manuscripts
12832_12832.qxd 8/10/2011 10:24 AM Page 1
Journal of Emergency Management
Vol. 9, No. 4, July/August 2011 11
The devastation caused by the January 12th
2010, Port au Prince Earthquake has been over-
whelming. The news reports and photos streaming
from Haiti have left many with feelings of helpless-
ness and despair. Since the quake the plight of the
people of Haiti, the poorest county in the Western
Hemisphere, has greatly worsened. The earthquake
killed an estimated 200,000 Haitians and left tens of
thousands of children orphaned. As well, many chil-
dren have been seriously injured or traumatized from
the earthquake. An estimated 2 million children have
been affected by the earthquake, many at high risk
for post-traumatic stress disorder.1
The war in Afghanistan, which began in 2001,
has also had a disastrous affect on the Afghan people,
especially the children. While there is no single offi-
cial figure for the overall number of civilians killed,
the United Nations’ Assistance Mission in
Afghanistan (UNAMA), reported that 2,118 Afghan
civilians were killed in 2008, the highest number
since the initial 2001 invasion.2 As well, according to
the Afghan Opinion Survey, 96 percent of the Afghan
population has been affected by the war. Especially
impacted by the war have been the Afghan children.
Bhutta, Deuraj and Khan3 reported that in addition
to many injuries due to landmines and artillery, 80
percent of Afghan children revealed some psychologi-
cal scar of war, specifically girls who have suffered
under the oppressive Taliban regime and boys who
fear being kidnapped and conscripted into battle.
While the above situations are vastly different,
one major commonality is present, children in either
country have not had the opportunity to experience
childhood or “just be a kid.” One of the major casual-
ties of disaster, both natural and human made, is a
disruption in a child’s ability to experience play.
Deprived of this important aspect of living, the child’s
brain becomes vulnerable to overwhelming traumat-
ic stress. Thus, childhood traumatic experiences pre-
vent children from seeking what they need to heal
their trauma. This catch-22 situation eventually
leads to autoimmune disorders and physical dis-
eases.4 One important way to counteract the above is
to “design environments for traumatized children
that encourage silliness, laughter, expression of all
types and childhood enjoyment.”5
Since 2004 the International Childhood
Enrichment Program has sought to provide opportu-
nities for Afghan and Haitian children to be “kids.”
The International Childhood Enrichment Program
(ICEP) is a non-profit organization that has been
building safe playgrounds in Afghanistan and Haiti.
The organization hires local laborers to coordinate,
build and install low-cost playgrounds in secure,
accessible places such as schools, orphanages and
health clinics. Since its inception in 2004/2005 ICEP
has constructed seven playgrounds in Afghanistan
and eight in Haiti. ICEP’s US operation is done only
though volunteers and it has essentially no overhead.
In 2005 ICEP instituted Children Enriching
JEMEditorial
Playgrounds helping to heal traumatized children
David B. Jones, EdD, CTRS
DOI:10.5055/jem.2011.0062
Jones_editorial 8/10/2011 10:22 AM Page 11
Journal of Emergency Management
Vol. 9, No. 4, July/August 2011 12
Children. Through this program school children in
the United States have raised money through various
fund-raising activities to develop a playground for a
particular school in Afghanistan or Haiti. As part of
this effort students in the US learn about the history,
language and culture of the host country. They also
correspond with the school children in Afghanistan or
Haiti to find out about their everyday life. This pro-
gram has proven highly successful. Students from
several different local schools in Maine raised money
for the construction of playgrounds in Haiti.
During the 2010 Summer ICEP, in conjunction
with the Maine National Guard, two playgrounds
were constructed at Dand Wa Patan, Afghanistan.
Recently in Haiti, the priests at Bethlehem Orphanage
in Cap-Haitien approached ICEP to see if it would help
build an accessible playground for the children who
reside at the orphanage. Since the earthquake,
the orphanage has been inundated by children from
Port-au-Prince, making the need for a playground
even more important for the children’s recovery.
Childhood development experts recognize the
importance of play for all children. Through play,
children gain vital social, emotional, and physical
skills, contributing to their overall healthy develop-
ment. For traumatized children, play also allows
them to heal.
David B. Jones, EdD, CTRS, Department of Recreation and Leisure
Studies, University of Southern Maine, Portland, Maine. E-mail:
RefeRences
1. Save the Children: Haiti earthquake response. 2010. Available at
www.savethechildren.net/alliance/what_we_do/emergencies/haiti/
index.html. Accessed January 21, 2011.
2. United Nations Assistance Mission in Afghanistan: Afghan civil-
ian death toll jumps 31 percent due to insurgent attacks. 2010.
Available at http://unama.unmissions.org. Accessed January 21,
2011.
3. Bhutta ZA, Dewraj HL, Khan A: Children of war: The real
causalities of the Afghan conflict. British Medicine Journal. 2002;
324(7333): 349-352.
4. Felitti VJ, Anda RF, Nordenberg D, et al.: The relationship of
adult health status to childhood abuse and household dysfunction.
American Journal of Preventive Medicine. 1998; 14: 245-258.
5. Ziegler D: Childhood play is affected by traumatic experience.
Available at http://www.jaspermountain.org/childlike_play_
traumatic_experience.pdf . Accessed March 19, 2011.
Jones_editorial 8/10/2011 10:22 AM Page 12
Journal of Emergency Management Vol. 9, No. 4, July/August, 2011
13
ABSTRACT
Social media services have changed the way we communicate and analyze information. Through social media services, individuals can exchange infor- mation with large groups of people in real time. Furthermore, web-enabled cellular devices have made social media services accessible to significant portions of the population at all times. Moreover, because mobile infrastructure is more resilient than other modes of communication, it is the likely mode of com- munication during an emergency or disaster. As such, local emergency management agencies should incor- porate social media tools into their communication plans to effectively communicate with the public and to obtain an enhanced level of situational awareness during an emergency or disaster. Many local emer- gency management agencies are unaware of the bene- fits of using social media tools and have false notions about the liabilities associated with social media dis- course. By educating themselves about social media services, local emergency management agencies will find that social media services are an accessible resource that should be integrated within their exist- ing communication plans.
Key words: social media, mobile device, communi- cations, Facebook, Twitter, cellular device, Web 2.0
Social media has changed the way information is communicated and analyzed. Through social media services, individuals can exchange information with large groups of people in real time. Local emergency management agencies should incorporate these tools into their communication plans to effectively commu- nicate with the public and to obtain a better level of situational awareness to aid response and recovery
efforts. Many local emergency management agencies are unaware of the benefits of using social media tools. By educating themselves about social media services, local emergency management agencies will learn that social media services are an accessible resource that should be integrated within their exist- ing communication plans.
WHAT IS SOCIAL MEDIA?
Social media refers to web-based and mobile tech- nologies, which are built on a Web 2.0 platform.1,2 The Web 2.0 platform is not characterized by technologi- cal specifications, but rather, how software developers and end-users use the Word Wide Web. Web 2.0-based applications facilitate participatory information shar- ing, interoperability, user-centered design, and collab- oration. As such, the Web 2.0 platform allows the World Wide Web to serve as a medium for dialog, as opposed to passive consumption of content. Examples of social media include popular sites, such as Facebook, Twitter, YouTube, Flickr, and Blogger. Facebook is a social networking service that allows users to create a profile, to add other users as friends, and to post content and to exchange information.3
Twitter is a microblogging service that enables users to post and receive messages of up to 140 characters in length.4 YouTube is a video hosting service, where users upload, share, and view videos.5 Flickr is an image and video hosting service that is used prima- rily for personal photographs and videos.6 Blogger is a blog publishing service that allows users to post time stamped entries.7 These social media services can facilitate quick and efficient dissemination of information to large groups of people by emergency managers.
Emergency management 2.0: Integrating social media in emergency communications
R. Sabra Jafarzadeh, JD
JEM
DOI:10.5055/jem.2011.0063
HOW HAS SOCIAL MEDIA CHANGED THE WAY WE GATHER
AND ANALYZE INFORMATION?
Social media services are swiftly becoming one of the most widely used personal and professional communications tools. A study released by the Pew Research Center’s Internet and American Life Project in July of 2011 found that, “the number of those using social networking sites has nearly doubled since 2008 and the population of [social networking site] users has gotten older.”8 The study revealed that in 2010, 49 percent of American adults used at least one social networking site. This marked a significant increase from 2008, when only 26 percent of American adults used one or more social networking sites. The average age of those individuals who used social networking sites also increased from 33 to 38 years between 2008 and 2010. Cellular devices with wireless Internet capabilities, and notably smartphones, have made social media services more accessible.9 Another study by the Internet and American Life Project found that 59 percent of American adults accessed the Internet wirelessly in 2010. The study also indicated that the use of nonvoice data applications had increased among mobile users. For example, in 2010, 23 percent of mobile users accessed social networking sites through their wireless device. In addition, the study showed that 54 percent of individuals who owned cel- lular devices used them to send images and video and that 15 percent used their phone to post photos or video to social media sites.
The increase in social media services is due, in part, to the fact that it has become one of the fastest methods for obtaining information. For example, when an earthquake hit China in 2008, Robert Scoble, an American with a large Twitter following, reported the event on Twitter an hour before CNN broke the story. He learned about the earthquake from several friends living in China who were posting accounts of the earth- quake on Twitter as the event unfolded.10 Because social media services rely on users to publish content, information can be reported in real time by individu- als who are experiencing an incident first hand. This is particularly true for individuals who access social media services through their mobile phones and can provide photo and video documentation to support
their accounts.11 This method of reporting is more efficient and often more accurate than information provided by journalists who are deployed to the site of an incident by television or radio news agencies after an incident or event occurs.
Social media services’ user driven approach has changed the manner in which readers determine the accuracy and reliability of information. The large vol- ume of individuals contributing information through social media services allows readers to rely on the col- lective intelligence theory to decipher whether infor- mation is correct.12,13 Under this theory, information which contradicts the majority of posted content is likely to be inaccurate. Furthermore, because social media services are interactive, misinformation will be corrected through subsequent postings by either the original author or other users.10 For instance, just hours after a tornado hit Alabama in April 2011, dis- placing thousands of residents, Facebook users cre- ated the Group “Alabama 2011 Lost or Missing.”14 The Group allowed individuals to post photos and identi- fying information regarding missing people and to solicit information useful for locating the missing per- son. On May 6, 2011, a photograph and home address for William Joseph Shulte was posted to the Facebook Group. Shortly thereafter, an individual responded to the post, stating that they had reviewed aerial video from the location surrounding Shulte’s home on YouTube and that the home had not sustained struc- tural damage. Within a minute, the user who had requested information regarding Shulte had responded, explaining that they had already driven to Shulte’s residence and that there was in fact structural dam- age to the property.
SHOULD MANAGEMENT AGENCIES ENTER THE SOCIAL
MEDIA DISCOURSE?
As the aforementioned examples illustrate, the public is already using social media services to com- municate vital information and to facilitate response and recovery efforts during emergencies and disas- ters. Emergency management agencies should develop social media strategies that will allow them to take advantage of this exchange of information. The admin- istrator for Federal Emergency Management Agency
Journal of Emergency Management Vol. 9, No. 4, July/August, 2011
14
(FEMA), Craig Fugate, has challenged government and private sector partners to share nonsensitive dis- aster-related information, such as evacuation routes and shelter locations, with the public through social media.15 Fugate argues that this sharing of informa- tion is the single most important resource available during emergency or disaster response. Department of Homeland Security Deputy Secretary Jane Hull Lute concurs, stating that during emergency or disaster response, information should be treated as “a commod- ity as important as the more traditional and tangible commodities such as food, water and shelter.”16 By entering the conversation taking place through social media channels, emergency management agencies can educate the public about ways to prepare for emergen- cies and disasters. In addition, participating in discus- sions that occur via social media services will provide emergency management agencies with important information that will enhance the effectiveness of their response and recovery efforts. Emergency man- agement agencies should develop social media strate- gies before an emergency or disaster to allot time for the public to learn about their social media presence and the resources that are available to them through these channels.10 Furthermore, it will allow emergency management agencies to forge relationships with pri- vate partners that will be useful during emergency and disaster response.
Emergency management agencies can expand the reach of their emergency or disaster alerts and notifica- tions through social media services. For example, resi- dents of Johnson County, KS can use Twitter to register to receive emergency alerts on their cellular tele- phones.17 This allows Johnson County’s emergency management agency to notify residents who cannot be reached through the reverse 911 system because they do not have access to a landline. As such, social media services enable emergency management agencies to provide many individuals with the tools necessary to help prepare themselves and others for an emergency or disaster. Experts have found that people become increasingly social during emergencies and disasters and find access to relevant information highly comfort- ing.18 Amanda Ripley, author of When Disaster Strikes—and Why, found that when advised to evacuate
in advance of a hurricane, “the average individual checks with four to five sources, such as a news anchor, a neighbor, a spouse and a website, before deciding whether to pack up and go.”18
In addition, using social media services helps emer- gency management agencies to communicate their emergency and disaster response and recovery efforts to the public in real time; this facilitates more efficient communication with news media.18 Emergency man- agement agencies who use social media services receive fewer calls from the media during disasters and can respond more quickly to the inquiries they do receive. Efficient communication with the media is critical dur- ing emergencies and disasters, when resources are lim- ited, because the time spent addressing media inquiries can be directed to addressing other needs.
Social media services, and the individuals who use them, also serve as a vital response and recovery tool.10 Mobile infrastructure is more resilient and more quickly restored than physical infrastructure after an emergency or disaster.15 For example, social media communications through cellular devices occurred either immediately or within 48 hours after both the 2010 earthquake in Haiti and the 2011 earthquake in Japan.19 During these incidents, affected individuals used social media services avail- able through their mobile telephones to summon assistance and to communicate pertinent information to responders.
Individuals who use social media services during emergencies and disasters enhance the situational awareness of responders by providing them with a stream of real-time information and ensuring that responders and the public are working from a com- mon operating picture.10,15 Social media services are well suited to facilitate quick and specific information sharing that is vital to saving lives and ensuring that limited resources are deployed effectively and effi- ciently during an emergency or disaster. Social media allows affected individuals to relay key data points, such as location, status, and needs, to responders. Through a process referred to as crowdsourcing, this information can be aggregated to assist in developing response priorities.20 For example, in the aftermath of the 2010 earthquake in Haiti, a group of volunteers
Journal of Emergency Management Vol. 9, No. 4, July/August, 2011
15
gathered information that was communicated through social media regarding trapped individuals, medical emergencies, and the need for commodities, such as food, water, and shelter. Using Ushahidi, an open- source crisis mapping software, this information was plotted to maps that were updated in real time and made available to anyone with access to the World Wide Web. Responders used these maps to determine how, when, and where to direct resources.
WHY HAVE LOCAL EMERGENCY MANAGEMENT AGENCIES
BEEN HESITANT TO ADOPT SOCIAL MEDIA STRATEGIES?
FEMA uses a number of social media services geared toward fostering communication between itself and the public.15 Facebook users can receive information regarding current incidents, as well as preparedness tips in text, image, and video formats. FEMA also uses Twitter to provide the public with situational updates and preparedness information, including an account that is specifically dedicated to servicing communities affected by Hurricanes Katrina and Rita. The information presented through Facebook and Twitter is made available to users in both English and Spanish. In addition, the public can checkout FEMA-produced videos on YouTube to learn more about the response and recovery efforts, as well as, how to prepare a disaster kit and how to apply for assistance after a disaster. In early 2010, FEMA also launched a mobile Web site where disaster survivors can apply for assistance through their smartphones.
As previously mentioned, FEMA has encouraged local emergency management agencies to push toward integrating social media initiatives within their emergency and disaster outreach and response plans. A number of local emergency management agencies have responded to FEMA’s call.17 Johnson County, KS, used Facebook to launch its “The 5,000 Prepared Citizens” campaign which sought to have 1 percent of the jurisdiction’s population pledge that they want to be prepared for emergencies and disas- ters. After experiencing significant flooding in 2009, the City of Moorhead, MN, incorporated the use of Facebook and Twitter into its flood emergency plan. Residents can sign up to join the jurisdiction’s Facebook and Twitter pages where they will receive real-time
flood information and updates. Both Fort Bend County, TX, and the City of Alexandria, VA, used Facebook and Twitter as part of their H1N1 response. Each jurisdiction relayed information and updates regarding symptoms, clinic operations, and vaccina- tions using these social media channels.
Despite these examples, a significant number of local emergency management agencies have shied away from incorporating social media services into their communication and response plans. A survey con- ducted by the Fels Institute of Government of University of Pennsylvania found that “as many as a third of cities recognized for their leadership in the areas of e-Government ... had not yet implemented any major social media technology.”21 This was the case despite the fact that the same group “ranked the importance of social media to their overall communica- tions strategy as 3.7 out of 5.” Furthermore, nearly all of those interviewed believed that the importance of social media would only increase in the coming years.
The hesitance of local emergency management agencies to incorporate social media tools into their outreach and emergency response plans is primarily attributed to four factors: skepticism regarding their usefulness, resource limitations, public relations, and legal concerns.21 However, these issues are largely overstated. The prevailing notion among emergency management agencies has often been that providing the public with too much information will create panic during an emergency or disaster.18 As previ- ously stated, this is simply not the case.10 Providing the public with accurate information instills confi- dence in their decision-making ability during an emergency or disaster and saves lives by facilitating a quicker and smarter response. This helps to estab- lish public trust and encourages the public to work with emergency management agencies during an emergency or disaster. In addition, using social media services helps emergency management agencies to provide important information to the public and allows these agencies to keep their finger on the pulse of conversations that will inevitably occur through social media channels during an emergency or disas- ter. As a result, emergency management agencies will be in a better position to respond to rumors and to
Journal of Emergency Management Vol. 9, No. 4, July/August, 2011
16
clarify misinformation. Furthermore, emergency management agencies can use existing tools to meas- ure the flow of traffic that their social media accounts receive and to determine which social media tools are most effective.
Emergency management agencies have also expressed concern regarding the interoperability of social media services and the difficulty associated with organizing information gleaned through these mediums.10 Indeed, systems for collecting and analyz- ing information obtained through social media need to be refined. However, solutions do exist and have been deployed during emergencies and disasters. For instance, “Tweak the Tweet” was developed in the aftermath of the earthquake in Haiti to leverage infor- mation communicated via Twitter. The system, which was created by a group of volunteers, enabled the automated extraction of data from Twitter through a syntax that indexed Twitter messages using their Hashtag. The Hashtag feature of Twitter allows users to include their message in a group by incorporating a predesignated label.
Emergency management agencies that have used social media initiatives reveal that they are less time intensive and more user friendly than initially antic- ipated.17 Many emergency management agencies use volunteers and interns to manage their social media networks. They also limit the need to create content by using materials developed by larger agencies such as the American Red Cross, National Weather Service, and FEMA. Also, during large-scale emergen- cies and disasters, FEMA has helped local emergency management agencies to manage and to enhance their social media capabilities.22 For instance, FEMA assisted the Alabama Emergency Management Agency launch a Facebook Page soon after the tornado in May 2011.
Local emergency management agencies are also concerned about the potential political and legal ram- ifications of their social media presence.21,23 Much of this fear relates back to a lack of understanding regarding the range in degree of participation allotted by social media services. Emergency management agencies can develop social media programs ranging from providing informational material to a selected
group of individuals to using it as a forum for public dialog. Emergency management agencies can quell much of their distress regarding overexposure by beginning with initiatives that call for little or no public interaction and gradually integrating more interactive programs once they feel comfortable with the social media tools.
Moreover, emergency management agencies should ensure that they are operating with a strong social media policy in place.24,25 A well-written social media policy will address several key factors geared toward minimizing adverse public relations or legal situations. Such a policy would outline those individu- als who are authorized to access and manage the emergency management agency’s social media accounts. The policy would also articulate what constitutes accept- able use of the social media accounts and how employ- ees are expected to conduct themselves while communi- cating through these channels. For example, emergency management agencies operating in jurisdictions with sunshine laws, which restrict communications between public officials, may want to incorporate this restriction into their social media policy.21 In addition, such a policy would lay out procedures for retaining and safeguard- ing the information exchanged through social media services. This is important because emergency man- agement agencies may be subject to open records laws, which require that government communications be made available to the public on demand. Because most social media services do not archive communications made on their site, emergency management agencies that are subject to such regulations will have to develop their own system for storing social media com- munications. Furthermore, a good social media policy would clarify the level of privacy and confidentiality that will be attributed to information volunteered to emergency management agencies through social media. For example, during the earthquake in Haiti, volunteers plotted reports of orphans on a map they made available to the public.10 After receiving reports of kidnappings, the group transferred the map to a pri- vate database that was only made available to respon- ders. Finally, a well-written social media policy would lay out disclaimers that should be published along with social media content to manage public expectations of
Journal of Emergency Management Vol. 9, No. 4, July/August, 2011
17
their communications with emergency management agencies through social media. A survey conducted by the American Red Cross revealed that 74 percent of respondents would expect a response within an hour of requesting help via social media channels. However, managing public expectations regarding their social media interactions with emergency man- agement agencies will go a long way in resolving any unrealistic expectations.
In conclusion, local emergency management agen- cies should make an effort to learn about social media services and how they can be incorporated into their communication plans. By doing so, local emergency management agencies will come to learn that social media tools are a valuable and accessible tool. This will enable local emergency management agencies to real- ize their coordinating function by keeping their finger on the pulse of preparedness, response, and recovery efforts that are being discussed via social media.
R. Sabra Jafarzadeh, JD, Law & Policy Analyst, University of Maryland,
Center for Health & Homeland Security, Baltimore, Maryland.
REFERENCES 1. Bruns A, Bahnisch M: Social Media: Tools for User-Generated Content. Vol. 1: State of the Art. NSW, Australia: Smart Services CRC Pty Ltd, 2009. 2. Sharma P: Core characteristics of Web 2.0 services. TechPlut. Available at http://www.techpluto.com/web-20-services/. Accessed June 20, 2011. 3. Facebook: Available at http://facebook.com. Accessed June 20, 2011. 4. Twitter: Available at http://twitter.com. Accessed June 20, 2011. 5. YouTube: Available at http://youtube.com. Accessed June 20, 2011. 6. Flickr: Available at http://flicker.com. Accessed June 20, 2011. 7. Blogger: Available at http://blogger.com. Accessed June 20, 2011. 8. Hampton K, Goulet, LS, Rainie L, et al.: Social Networking Sites and Our Lives. Pew Internet and American Life Project. Washington, DC: Pew Research Center, 2011. 9. Smith A: Mobile Access 2010. Pew Internet and American Life Project. Washington, DC: Pew Research Center, 2010. 10. American Red Cross: White paper: The case for integrating crisis response with social media. August 2010. Available at http://www. scribd.com/doc/35737608/White-Paper-The-Case-for-Integrating- Crisis-Response-With-Social-Media. Accessed June 20, 2011. 11. Chipchase J: On our mobile phones [video file]. TED. October 2007. Available at http://www.ted.com/talks/jan_chipchase_on_our_ mobile_phones.html. Accessed June 20, 2011. 12. Caloh L, Spurr J, Schneider S, et al.: Tools to use: Existing mod- els and best practices. Paper presented at the Social Networking for Emergency Management and Public Safety Workshop, Seattle,
WA, August 2010. Available at http://www.au.af.mil/au/awc/ awcgate/pnl/social_ networking.pdf. Accessed June 20, 2011. 13. Suroweicki J: When social media became news [video file]. TED. November 2008. Available at http://www.ted.com/talks/lang/eng/ james_surowiecki_on_the_turning_point_for_social_media.html. Accessed June 20, 2011. 14. Facebook: Alabama 2011 tornado lost or missing. Available at http://www.facebook.com/pages/Alabama-2011-Tornado-Lost-or- Missing/183171718402002. Accessed June 20, 2011. 15. Fugate C: Administrator, Federal Emergency Management Agency. Written Testimony Before Senate Committee of Homeland Security and Government Affairs, Subcommittee on Disaster Recovery and Intergovernmental Affairs: “Understanding the Power of Social Media as a Communication Tool in the Aftermath of Disasters.” May 2011. Available at http://www.dhs.gov/ynews/ testimony/testimony_1304533264361.shtm. Accessed June 20, 2011. 16. Woodbury G: To tweet, or not to tweet: That is the question for public safety leaders in the 21st century. Paper presented at the Social Networking for Emergency Management and Public Safety Workshop, Seattle, WA, August 2010. Available at http://www.au.af. mil/au/awc/awcgate/pnl/social_networking.pdf. Accessed June 20, 2011. 17. Chavez C, Repas MA, Stefaniak T, et al.: A new way to commu- nicate with residents: Local government use of social media to pre- pare for emergencies. ICMA Report. Washington, DC: International City/County Management Association, 2010. 18. Currie D: Expert round table on social media and risk commu- nication during times of crisis: Strategic challenges and opportuni- ties. Booz Allen Hamilton Special Report. 2009. Available at http://www.boozallen.com/media/file/Risk_Communications_Times_ of_Crisis.pdf. Accessed June 20, 2011. 19. idisaster 2.0. Social media and emergency management: Top 10 questions. June 6, 2011. Available at http://idisaster.wordpress.com. Accessed June 20, 2011. 20. Heinzelman J, Waters C: Crowdsourcing crisis information in disaster affected Haiti. Special Report. United States Institute of Peace. October 2010. Available at http://www.usip.org/files/ resources/SR252%20-%20Crowdsourcing%20Crisis%20Information% 20in%20Disaster-Affected%20Haiti.pdf. Accessed June 20, 2011. 21. Kingsley C: Making the Most of Social Media: 7 Lessons from Successful Cities. University of Pennsylvania, Fels Institute of Government, September 2009. Available at https://www.fels. upenn.edu/sites/www.fels.upenn.edu/files/PP3_SocialMedia.pdf. Accessed June 20, 2011. 22. Gary J: Alabama tornados: Twitter, Facebook, other social media make a big mark in disaster response, relief. The Birmingham News. May 31, 2011. Available at http://blog.al.com/spotnews/2011/ 05/alabama_tornadoes_twitter_face.html. Accessed June 20, 2011. 23. McShea K: Privacy Impact Assessment for the Use of Social Networking Interactions and Applications Communications/ Outreach/Public Dialogue. Washington, DC: US Department of Homeland Security, September 16, 2010. 24. Hrdinová J, Helbig N, Peters CS: Designing social medical pol- icy for government: Eight essential elements. University at Albany, Center for Technology in Government. May 12, 2010. Available at http://www.ctg.albany.edu/publications/guides/social_media_policy/ social_media_policy.pdf. Accessed June 20, 2011. 25. Stevens L: The C.O.P.P.S. Social Media Method™ for Cops. ConnectedCOPS.net. March 3, 2010. Available at http://connectedcops. net/?p=1634. Accessed June 20, 2011.
Journal of Emergency Management Vol. 9, No. 4, July/August, 2011
18
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
19
ABSTRACT
Threats from natural disasters and terrorist attacks are real and are occurring ever closer to home. The State Homeland Security Program authorizes annual grants to supplement state and local response capabilities. Although county-level emergency man- agement agencies have received grants to enhance response capabilities, analysis tools to strategically manage these new capabilities are still not in place. Through a combination of research, qualitative, and quantitative analysis, this study provides a broad view of the resource-based relationships between a typi- cal Midwest county emergency management agency and its neighboring district counties, as well as other coun- ties and districts within the state. A capabilities assess- ment and a life cycle cost analysis are also presented to demonstrate ways of valuing response equipment and the future costs associated with replacement, mainte- nance, and training.
Key words: homeland security, emergency man- agement, sustainment, life cycle cost
INTRODUCTION
Hurricane Katrina exposed a number of break- downs in the staffing, training, and organizational structure of the Federal Emergency Management Agency (FEMA), which resulted in preparedness and response efforts that were uncoordinated and ulti- mately led to FEMA’s inability to respond effectively to a widespread disaster.1 The 9/11 Act, passed in 2007, contained provisions to strengthen national prepared- ness by encouraging the development of regional capa- bilities. Regional capabilities, especially at the local
level, are important because they provide the first response in disaster situations, while state and federal aid may take up to several days or weeks.2 Among other things, the 9/11 law stipulates the threshold amounts allocated to states out of the funds from the State Homeland Security Program (SHSP). The SHSP is one of the five subprograms of the Homeland Security Grant Program (HSGP). The HSGP is a core assistance program that provides funds to align capabilities at the state and local level with the homeland security strate- gies and initiatives put forth in the State’s Preparedness Report. The SHSP allocates funding to states based on the optimum amount of funds that will achieve the most effectiveness while staying within the bounds of risk methodology of the United States Department of Homeland Security (DHS). The intent of this is to close the gap between the state preparedness and response capabilities and that of the Federal Government.3
With this increased focus on local resources, the need exists to ensure that regional capabilities, partic- ularly at the county level, not only respond to the immediate locale but also strengthen neighboring areas. Equipment purchased for this preparedness effort must be supported throughout its life cycle; oth- erwise it will lose effectiveness and not function when needed. A general-use sustainment tool can be used to accurately reflect the year-to-year financial obliga- tions not funded by the SHSP grant and approximate the total cost once the equipment is acquired.
Tippecanoe County is fairly typical of many Midwest locations: a more populated central county, with a variety of manufacturing companies and agrarian groups, as
Cost and benefits of a typical county’s emergency response program
Lillian R. Butterworth, MS Steve Riedel, BS
J. Eric Dietz, PhD, PE
JEM
DOI:10.5055/jem.2011.0064
well as a major university, surrounded by smaller pop- ulation centers and rural areas. Tippecanoe County is geographically central to the other counties and acts as the financial agent for the region. The Tippecanoe County Emergency Management Agency (TEMA) is a typical county-wide service that responds to and pro- vides care for Tippecanoe county residents harmed by natural and man-made disasters. They are also respon- sible for maintaining and activating the Emergency Warning System Siren for their county. In a broad sense, TEMA plays a support role within the region by providing emergency response expertise in public safety and preparedness. However, given the limited hazardous materials (hazmat) response capabilities of the surrounding counties, TEMA takes the lead in haz- mat response and incident management.4
The SHSP grants and various other grants from fed- eral agencies (such as FEMA) have provided TEMA the financial resources to purchase equipment that previ- ously was difficult to obtain (M. Kirby, written communi- cation, February 22, 2010). Maintenance contracts or warranties of equipment that are already funded by a state or local authority cannot be purchased or renewed with SHSP grant funds. In addition, the grant does not cover routine upkeep such as inspections, replacement, maintenance, and training. The SHSP funds are intended to supplement TEMA’s ability to purchase new systems as well as extended warranties on those sys- tems, thereby ensuring continued use of the system under the warranty contract.5 As these grants are made possible through taxpayer’s dollars, it is important to maximize the amount of use from the equipment pur- chased since future grants are not guaranteed and the amounts are subject to variation due to multiple politi- cal and economic factors making sustainment of these capabilities problematic.
TEMA solicited this study to gain a broader view of all available resources and capabilities in Indiana DHS (IDHS) District 4. Without a clear understanding of every county’s resources, county EMA directors are cur- rently inhibited from providing appropriate support and ensuring that they respond to emergencies at the district level. In 2003, TEMA purchased a second Haz-Mat Response Trailer (Haz-Mat Trailer #2) with Homeland Security grant funds; however, TEMA does not use a
standard method of estimating the future maintenance, training, and replacement costs for this trailer and equip- ment. As a result, TEMA is not properly accounting for these future costs when determining their budget.
The primary purpose of this study is to broadly assess the benefits and costs of TEMA’s response assets and how these assets enhance TEMA’s capabil- ities. Moreover, what effect would the absence of such capabilities have on the surrounding counties who rely on TEMA for certain resources? Benefits are the specific capabilities that TEMA can perform as a result of the equipment and resources it possesses. A resource-based relationship between TEMA and its neighbor counties will be identified. The secondary purpose of this study is to analyze the inventory items of Haz-Mat Trailer #2 to determine the future costs associated with the maintenance, training, and replacement of these items. Although these costs are not typically covered by the grant, they are nonethe- less vital to the sustainment of TEMA’s response capabilities because the sustainment of this equip- ment directly affects the condition of the equipment and the ability to respond when needed. The valua- tion method presented in this study will provide a tool to plan for these future costs.
METHODS
Part I: Capabilities dependency of surrounding counties
This study was undertaken to determine the level of codependency within IDHS District 4 counties. District 4 encompasses the counties of Benton, Carroll, Cass, Clinton, Fountain, Montgomery, Tippecanoe, Warren, and White. Working through the District 4 office, contact points for all county EMA directors were provided. This led to several meeting with county directors to discuss their respective county’s response capabilities and resources, their comprehensive inventory list of resources, and any mutual aid agreements currently in place. Institutional Review Board’s approval was not required for this project.
In general, outside of their respective county EMA allocations, TEMA would very likely provide mutual aid and assistance to the other District 4 counties. If
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
20
an emergency situation occurred in which one or more of these counties needed more specialized equipment, TEMA would be positioned to provide some of the most rapid response. Otherwise, the counties would need to plan for outside response that might be slow to arrive when needed. While some assets could be pro- vided from private contractors to provide necessary services and equipment, the cost would be high. The common belief among the various District 4 county EMA directors was that TEMA capabilities define their district’s response capabilities.
To determine the nominal time for aid to reach Tippecanoe County from other major areas with res- ponse capabilities, a hypothetical situation in which TEMA required resources from other well-equipped IDHS Districts (such as Districts 3 and 7) was consid- ered. The purpose was to determine the mutual aid relationship between districts, assuming that the amount of time it would take for TEMA to obtain any kind of resource from another district depends on the following factors: the distance between the two loca- tions, prevailing weather and visibility, the type, or more importantly, the weight of the equipment being transported, and the presence of road blockages caused by the emergency situation.
By using Google Maps, an approximate travel time was established to Tippecanoe County (District 4) from its closest neighboring districts able to pro- vide assistance: Districts 3, 5, and 7. District 3, based in Ft. Wayne, IN (Allen County), is approximately 120 miles away and has a 2.5-hour response time. District 5, based in Indianapolis (Marion County), is approxi- mately 65 miles away and has a response time of 1 hour. District 7, based in Terre Haute (Vigo County), is approximately 95 miles away and has a response time of 2 hours.6 These response times are typical for more populated counties in the continental United States that support rural neighbors and can serve as a guide to many other regions.
Part II: Determining the value of TEMA’s response equipment
The TEMA director provided an inventory list that was analyzed according to the capabilities that the equipment would provide in a disaster. To measure the
value of this emergency response equipment, it was cat- egorized into four primary groups: warehouse, trans- port, vehicle, and tool, each of which provides a different functional capability. This categorized data were inputted into a functional capability matrix, as illus- trated in Table A1. The warehouse provides TEMA with the capability to store equipment. The transport group, which includes the trailers and forklifts, provides TEMA with the capability to move large amounts of people, machinery, and equipment. The vehicle group, which includes all the trucks and cars, provides TEMA with the capability of transporting a few people and a small amount of equipment at a faster rate. The tool group encompasses the remaining items and provides TEMA with the capability to provide power, establish a commu- nications network, offer support to a neighbor county, and engage in a special activity such as hazmat response or decontamination. These subcategories are designated as “pow” for power, “comm” for communica- tion, and “supp” for support. Hazmat and decon are self-explanatory. With each piece categorized according to its capabilities and group, a visual representation can be made, ranging from “Hi” to “Low.”
To determine the value of this equipment for both natural and man-made disaster response, the most likely events to affect the region and state were iden- tified. In the last 10 years, the most common natural disasters to hit Indiana were winter storms, bliz- zards, flash floods, and tornados. The man-made dis- asters identified were radiation attack, biological attack, bombing or explosion, and chemical attack. Table A2 shows the disaster utilization matrix. At the top, this matrix lists the disasters identified. On the left axis, the matrix lists all the items in TEMA’s equipment inventory. The items were assessed for their usefulness in each of the disasters, and received a “yes” if it was determined that it would be useful in a particular disaster and a “no” if it would not be use- ful. All the “yes” responses are indicated in shades of blue, whereas the “no” responses are indicated in red. The matrix is mostly blue, indicating that the major- ity of the equipment would be useful in most disasters.
A point system was used to quantify the “yes” and “no” responses as shown in Figure A1, which is
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
21
indicated in the key to right. As natural disasters are more prevalent, a “yes” in a natural disaster received two points, whereas a “yes” in a man-made disaster received one point. A “no” received zero points. The point basis of 0, 1, and 2 was used to simplify the addition. In contrast to natural disasters, not as much equipment would be valuable in the face of man-made disasters, because within these four categories, more “no” responses appeared. However, because of the nature of man-made attacks, it is more difficult to be prepared for them, as they lack the forewarning that usually precedes natural disasters. Each equipment item scored points with a range of 2 to 12. The results are shown in Figure A1, and can be arranged in value from largest to smallest, to show what equipment is most likely to be used in the most frequently encoun- tered response missions.
LIFE CYCLE COSTS OF HAZ-MAT TRAILER #2
The life cycle costs of the equipment contained in Haz-Mat Trailer #2 was determined by measuring the value of each item based on the general account- ing principles of present and future value. Haz-Mat Trailer #2 was used to perform this analysis because of its relatively new equipment and its contribution to the overall inventory. However, original purchase price for individual pieces of equipment was not avail- able, and a current market value was determined by the use of Internet price data.
Determining life cycle costs The life cycle cost matrix is used for this analysis,
as shown in Table A3. The first column entitled “expected life” is an estimate of how long the item would last assuming that it is used in the manner for which it was intended. A time period of 10 years was used as the maximum life of an item, and the valua- tion was based on this time period.
The “MRL” column specifies what action should be taken with regard to the maintenance of the item. If an item was determined to last longer than 10 years, then the item was assigned an “L” for “last indefinitely” in the MRL column. An “M” means that the item will need “maintenance” during its specified expected life. This may or may not incur a cost; however, it was assumed
that any item identified as requiring maintenance dur- ing its expected life will incur a certain cost. An “R” means that the item will need to be “replaced” at the end of its expected life at the price in the corresponding replacement year. Several items have both an L and an M. This means that the item will last indefinitely if the required maintenance is performed. The next column entitled “training” specifies which items will require the user to be trained in the operation of that item. Identification of individual costs for training was beyond the scope of this project; however, it was assumed that 15 percent of the items in the Haz-Mat Trailer #2 would require some kind of training. The designations of M, R, and L are necessary to further identify what costs for the line item will be incurred in the future. For exam- ple, if it has been determined that an item has an expected life of 2 years, then that item will need to be replaced every 2 years and the cost of maintaining that item over the next 10 years is the sum of its future costs every other year until 2020. The next column entitled “original value” gives the current market price of the line items. TEMA’s original purchasing data were unavail- able, and therefore, future costs are not based on the prices at which the items were originally purchased. Instead, they are based on current prices found online of same or comparable items.
Determining future values All future values were calculated using a 3 percent
rate of inflation for a period of 10 years, from 2010 to 2020. The 3 percent inflation rate is not based on any historical scientific evidence of price inflation, but was chosen solely based on the authors’ general knowledge of finance and macroeconomics. At the bottom of each “Year” column is a total cost. This total cost is the esti- mated expense paid each year in replacement costs. It is important to note that the total costs at the end of each column are not the sums of all the costs in the col- umn. Only the costs that have been specified to be incurred in that particular year have been tallied at the bottom.
Table A3 shows a summary of the costs associated with this equipment. There are three categories of costs: replacement, maintenance, and training. Inspection costs and other infrequent or miscellaneous costs are
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
22
assumed to be included in maintenance costs. As stated earlier, replacement costs are based on the present mar- ket value adjusted for 3 percent inflation. Replacement costs fall into two categories: items that must be replaced each year and items that do not need to be replaced each year. The total costs for items that will be replaced each year, such as consumables, are called “annual replacement costs.” The total costs for items that will only be replaced in certain years are called “year-specific replacement costs.” The total of these two costs equal the “total yearly maintenance cost.” For example, all the items that were identified as having an expected life of 2 years will be replaced in the year 2012. Thus, the total replacement cost for the year 2012 will be the sum of the replacement cost of these items plus the total replacement cost in year 2011 as this sum will be incurred each year.
Maintenance costs were calculated assuming that 5 percent of the cost of each item requiring mainte- nance will be spent on maintaining that item. Therefore, 5 percent of all items identified in the MRL column as requiring maintenance have been summed in each year providing the “total annual maintenance cost.” The figure of 5 percent was based on historical maintenance expenditures.
Training costs were calculated in a similar fash- ion, that is, 15 percent of the cost of each item that would require training should be allocated to the training budget based on historical expenditures. Training items are given in the “training” column.
Net present value of future costs The net present value of future costs was calcu-
lated by discounting the total annual costs at a stan- dard discount rate of 40 percent. The discount rate of 40 percent was chosen because it reflects a conserva- tive indicator of the difference between the future value of these costs and the present value of these costs (called the “time value of money”). It should be noted that there is no consensus on the best discount rate to use, and therefore, any reasonable discount rate based on the US market economy is sufficient. Using the rate of 40 percent yields the present value (the value in year 2010) of the costs that will be incurred in each future year until 2020. The sum
of the present values of the costs in each future year is the total present value of future costs. By subtract- ing the capital expenditure of the federal grant from the total present value of future costs, the net present value of future costs is calculated. The net present value of future costs is what will be paid in replace- ment, maintenance, and training costs over the next 10 years. This amount is $517,409.
RESULTS
Part I: Capability dependency of surrounding counties
Carroll County’s response equipment store con- sists of a small supply of personal protection equip- ment, a multigas detector, a light tower, a multiband radio adaptor, and a radiation meter. Carroll County reported that they primarily rely on TEMA for com- mand vehicles, Haz-Mat response equipment, and personnel.
Cass County’s response equipment store consists of a Haz-Mat Trailer, two response vehicles, communica- tions equipment, a 15-kW electric generator on a trailer, and three portable gensets. Cass County seeks assis- tance from the Grissom Air Reserve Base for Haz-Mat incidents. Otherwise they would “have the responsible party call in experts.”
Montgomery County’s response equipment store consists of two portable gensets and a 500-gallon water trailer. This county also has a Haz-Mat Trailer and a Command Trailer that is held by the Craw- fordsville Fire Department. Montgomery County did not indicate to what degree they relied on TEMA to supplement their response capability; however, given that they are such a small county, it was assumed that in the event of a widespread disaster, this county would rely on TEMA to a similar degree as the other counties.
In general, outside of their respective county EMA allocations, TEMA would most likely provide heavy assistance to these other counties. Although Cass and Montgomery counties each have hazmat response trailers, temporary power capabilities, and several vehicles at their disposal, they lack other more sophis- ticated items such as decontamination vehicles or
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
23
self-contained breathing apparatus gear. Carroll County has comparatively less capabilities than Montgomery and Cass counties. If an emergency situ- ation arose in which one or more of these counties needed more specialized equipment, TEMA would be in the position to provide it the fastest. Otherwise, the counties would need to hire outside consultants or pri- vate contractors to provide these services and equip- ment, which would surely come at a very high cost to that county. However, the common attitude was that TEMA defines District 4 for response capabilities.
It was assumed that all districts are within IDHS similar capabilities (K. Holbert, personal communica- tions, April 16, 2010) Therefore, it was assumed that if TEMA were incapacitated in some way, it would be able to obtain similar resources from District 3 or 7.
Mutual aid agreements are governed by the state so that it can ensure that funding and reimbursement are properly allocated. For other counties to assist each other, the requesting-county official or the EMA direc- tor of that county would contact the State Emergency Operations Center who would then contact the assist- ing-county official or EMA director. This process would be the same even if both counties were in the same dis- trict. Mr. Holbert also emphasized that “each district needs to be able to sustain itself. Loss of funding for [TEMA] would be detrimental to District 4.” This fur- ther underscores the high level of dependency that other District 4 counties place on TEMA. Using Cass County as an example, it was noticed that it is equipped with less than a fraction of what is available here at TEMA. If TEMA was unable to provide resour- ces to Cass County, it would be forced to either simply do without aid or turn to a third source. In this case, Cass County has the option of using the Grissom Air Force base for additional response needs. However, other counties, such as Montgomery County, do not have access to this resource and in the event of an actual disaster may simply suffer until a private con- tractor can be hired or assistance from another county is obtained through the Mutual Aid Agreement of 2003. The Mutual Aid Agreement of 2003 is the only document that binds the districts of Indiana to provide mutual aid to each other.7 These counties could also approach District 3 or 7 for aid; however, these districts
would likely face the same issues in providing assis- tance as District 4 would, with the added burden of requesting permission from the state and prioritizing what it can provide without depleting the resources of its own counties. In an interview, the Director of the Carroll County Emergency Management Agency com- mented that if District 4 counties are unable to rely on Tippecanoe County for vehicles, hazmat response, and manpower, “any chemical spill would have to be han- dled by out-of-state contractor, leading to delays and high costs.”
Part II: Determining the Value of TEMA’s response equipment
It is a graphical depiction of TEMA’s capabilities according to the categories assigned. It shows that the support tool, vehicle, and transport groups are where TEMA has the most resources and therefore the strongest capability. This is also in regard with TEMA’s role as a resource provider to other District 4 counties, and therefore, it makes sense that these are the areas in which it would have the most excess capability.
In the natural disaster categories, TEMA’s equip- ment scored 189 “yes” responses of 204 data fields, yielding a preparedness score of 93 percent. In the man-made disaster categories, TEMA’s equipment scored 158 “yes” responses of 204 data fields, yielding a preparedness score of 77 percent. Therefore, in light of TEMA’s role as provider to surrounding counties and possibly other districts as well as its response obligation to its own residents, it was concluded that TEMA’s mix of resources are all vital to their various missions in some degree. The disaster utilization matrix also indicates the man-made disaster areas in which TEMA could add to their resources to be able to respond more effectively. An equipment utilization graph is shown in Figure A1. It shows how all the equipments in TEMA’s inventory scored in the disas- ter utilization matrix column entitled “points.” From this graph it can be concluded that the majority of the equipment items scored 9 or above, indicating that TEMA’s inventory overall is providing a capability that is aligned with the disasters in which it will respond.
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
24
LIFE CYCLE COSTS OF HAZ-MAT TRAILER #2
The net present value of future costs is what TEMA will pay in replacement, maintenance, and training costs over the next 10 years. This amount is $517,409. Although it was not feasible to determine the exact pricing information of every item in the Haz-Mat Trailer #2, the rough estimates provided, as well as the training and maintenance classifications assigned, could be used to estimate the future costs associated with other equipments.
DISCUSSION
The conclusions from this study resulted in rec- ommendations provided to TEMA, in order for them to address the codependency and nominal response time between counties as well as to provide effective means of estimating the utilization and long-term costs of maintaining response equipment.
It was determined from the IDHS District 4 Coordinator that there is no comprehensive equip- ment list maintained showing all the resources and capabilities possessed in the district and that are available to all the county directors. The lack of such information creates a gap in the district’s intelligence that results in decreased awareness of potential resources. It was recommended that a comprehensive inventory list for IDHS District 4 be developed, which will enable coordinators to facilitate the transporta- tion of equipment, resources, and capabilities across counties to respond to emergencies faster.
In addition, mutual aid agreements that are main- tained by the state seem to inhibit the process of inter- district assistance because the request for assistance must pass through the State Emergency Operations Center. This has the potential to slow down the deliv- ery of much-needed aid. Therefore, the introduction of a working plan to facilitate resource sharing while reducing the operational decision-making process was proposed.
The Statewide Mutual Aid is in place for each pub- lic safety agency in Indiana. The details that could be expanded with additional agreements could include compensation for storage and routine costs as well as expanding the pool of trained operators for specialty equipment beyond the current department owner. The
intradistrict plan suggested should take care to identify possible response actions in each county. These would include major transportation corridors, rail carriers, and airports that might add to the county risks. The plans would also identify special equipment available to supplement the specialty equipment inventory that the SHGP has provided to the district. Finally, the more developed urban areas such as Tippecanoe County may be more resourced with equipment, but the personnel needed to staff long-term response actions might exceed those available in a single county. The training for addi- tional personnel should be included in the plans to ensure sufficiency of material and personnel in an emer- gency. This process will only succeed with adequate attention to the training and exercise of the personnel needed. As this plan is envisioned based on a need from a larger disaster response, the district will need to ensure that the numerous departments within the coun- ties are ready to both request support and receive first responders as envisioned in the plan.
As discussed in Part I of the Results section, many counties within District 4 have few contingency response capabilities. This is due to the low popula- tion of some counties as well as the low funding level available to them to purchase their own equipment. Rather than having these counties incur the total cost of purchasing equipment for their own use, it was rec- ommended that a cost-sharing program should be developed for District 4 based on utilization, county populations, or a combination of both. Much of the equipments that belong to TEMA are actually used by other counties, yet the cost of maintenance of that equipment is incurred by TEMA. By tying the cost of using the equipment to the county who actually uses it, a cost-sharing agreement would allocate the costs more effectively to the actual user of the equipment.
Another way District 4 could enhance the resource inventory of smaller counties is by donating old or used equipments that TEMA plans to replace to these smaller, less-populated counties. The smaller county would then only incur the cost of maintaining the item.
TEMA can determine its most mission-critical assets by applying the functional capabilities matrix, the capabilities inventory, the disaster utilization matrix, the equipment utilization graph, and the life
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
25
cycle cost calculator. These models serve as a frame- work for TEMA to identify what it has, what it uses, how much it is costing them, and what it could get rid of if the goal was to cut costs.
The functional capability matrix (Table A1) was developed to 1) identify the most important aspects of each equipment item and 2) use these aspects to thor- oughly analyze burden of that item on TEMA. In other words, what function does this item perform and is having this function worth the cost of the item. By identifying the capabilities, functional components, and required training or prior knowledge needed to operate or use the item, this model effectively exposes many “hidden” costs that are almost always associated with this kind of equipment but seldom considered during procurement. This model was originally devel- oped by the authors for their own use in identifying all costs associated with the Haz-Mat Trailer #2 items; however, it proved to be a practical tool applicable to all scenarios.
The capabilities inventory is designed to be used as a pictorial representation of the functional capability matrix. A person can only draw conclusions from the functional capability matrix by reading it line by line; however, the capabilities inventory shows, at a quick glance, which capabilities have the most resources. The importance of the model is to show where resources are abundant (and could be possibly be cut) and where they are deficient (and thus merit additional spend- ing). As discussed in the Methods section, the capabili- ties inventory is organized according to predesigned categories and subcategories that were determined by TEMA’s missions. However, any response organization could use this model by organizing equipment accord- ing to its own mission-specific categories.
The disaster utilization matrix (Table A2) is the most important model because it uses a qualitative framework to provide a quantitative result. Responders can change the inventory items on the vertical axis to see how it affects their overall response preparedness in natural and man-made disasters. The disasters on the horizontal axis can also be customized to a specific area to further refine the accuracy of the model. Furthermore, the point scheme can be adjusted to increase or decrease the weight of each disaster.
Like the capabilities inventory, the equipment utilization graph (Figure A1) is a visual indicator of the cumulative results of the disaster utilization matrix. Its importance lies in the ability of the viewer to quickly assess the equipment that will be most uti- lized in responding to the specific disasters identified on the horizontal axis of the disaster utilization matrix. It is also a valuable decision-making tool, and can be used to select mission-essential equipment. However, if responders do decide to use the equip- ment utilization graph for this purpose, they must keep in mind that some items may have a low utiliza- tion score, because the disaster for which they are used does not occur frequently. Determination of the relevance of the item then becomes a question of how prepared a responder cares to be for infrequent disas- ters. Also, items whose function is needed for many different kinds of disasters will score higher than items that serve fewer functions or highly specialized disaster-specific items.
Once the responder has used the previous models to determine the most functional mix of response equipment, the life cycle cost model (Table A3) serves to provide the long-term cost associated with the inventory. To achieve the most accurate estimate, which items require maintenance and training and what is the expected life of the item must be deter- mined, as discussed in the Methods section.
The future costs of the equipment in the Haz-Mat #2 Trailer were calculated assuming a 15 percent training cost of the items identified as requiring training. This method of estimating training cost is not very accurate because it assumes the same alloca- tion of training for all items regardless of the fact that different items will require different training. The range of training needed will vary by cost. Therefore, it was recommended that a follow-up study in which the specific types of training are identified according to the type of equipment in their inventory list be conducted.
Similarly, future costs of the equipment in Haz-Mat Trailer #2 were calculated assuming a 5 percent main- tenance cost of the items identified as requiring main- tenance. This method of estimating training cost is not very accurate because it assumes the same allocation of
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
26
maintenance for all items regardless of the fact that dif- ferent items will require different maintenance. It was recommended that “maintenance cards” that identify the tools, consumables, and human expertise needed to perform maintenance on a piece of equipment should be developed. Having these cards will preserve the main- tenance knowledge, provide a standard to ensure that the maintenance is being done properly every time, and if kept in electronic form, can easily be updated as inventory is changed.
The net present value of future costs was calcu- lated using market value prices of the inventory items. However, the values might have been more accurate if the original purchasing data had been used. It was rec- ommended that documentation for future purchases be maintained so that cost estimates can be based on orig- inal purchase amounts.
CONCLUSIONS
This study provides a business case for determin- ing sustainment costs of a key capability in a home- land security district. From 9/11 to Hurricane Katrina, the response needs for individual jurisdictions can be impossible to provide from internal resources in any particular area. By using the methods suggested and by developing the recommended mutual aid plans, even the small rural counties can work together to secure the funding needed from the SHGP to develop the needed capabilities. It was proposed that a method should be developed to determine the sustainment costs based on the original costs and equipment durability. To ensure that the capability exists when needed, the state and local governments have the option of providing the sus- tainment costs from the SHGP as proposed including the training and capability exercise.
ACKNOWLEDGMENTS Successful completion of the project was due to the active collab-
oration, cooperation, and communications between the authors and collaborators. The authors also extend their special thanks to the fol- lowing collaborators who provided their invaluable expertise in this study: Mr. Mark Kirby Director, Tippecanoe County Emergency Management Agency; Ms. Janet Buche, District 4 Coordinator, Indiana Department of Homeland Security; Dr. David Denis, Professor of Finance, Purdue University; Mr. Keith Holbert, Deputy Director, Vigo County Emergency Management Agency; Mr. Dave McDowell, Director, Carroll County Emergency Management Agency; Mr. Alvin Beckman, EMA Director, Cass County Emergency Management Agency; and Mr. Fred Davis, EMA Director, Montgomery County Emergency Management Agency.
Lillian R. Butterworth, MS, Lieutenant, United States Coast Guard,
MSIA, Krannert School of Management, Purdue University, West
Lafayette, Indiana.
Steve Riedel, BS, Graduate Research Assistant, Department of
Agricultural and Biological Engineering, Purdue University, West
Lafayette, Indiana.
J. Eric Dietz, PhD, PE, Associate Professor of Computer and
Information Technology and the Director of the Purdue Homeland
Security Institute, Purdue University, West Lafayette, Indiana.
REFERENCES 1. House Report 109-377: A failure of initiative: Final report of the Select Bipartisan Committee to investigate the preparation for and response to Hurricane Katrina. February 15, 2006. Available at http://www.gpoaccess.gov/serialset/creports/katrina.html. 2. Mayer M, Carafano J: After the 9/11 Act: Homeland Security Grant Program Still Moving in the Wrong Direction. Backgrounder (2059). The Heritage Foundation, August 3, 2007. 3. FEMA: www.FEMA.gov; 2010. Available at http://www.fema.gov/ government/grant/hsgp/index.shtm. Accessed April 24, 2010. 4. Kirby M: Mission of Tippecanoe EMA. Tippecanoe County TEMA Homepage. Available at http://www.tippecanoe.in.gov/TEMA/. Accessed February 26, 2010. 5. Wainscott JE: Maintenance costs; Memorandum. 2010. Available at http://www.in.gov/dhs/files/revised_guidance_maintenance_costs. pdf. 6. Google: Google Maps; 2010. Available at www.maps.google.com. Accessed April 23, 2010. 7. Indiana Department of Homeland Security (IDHS): Mutual Aid Agreement of 2003. Indianapolis: IDHS, 2003.
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
27
APPENDICES
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
28
Table A1. Functional capability matrix
Inventory Item Category Functional description
Capabilities Functional
components
Required training or prior
knowledge
1 Air compressor Tool/sup Compresses air into mechanical use
Enables use of pneumatic tools for repairs, construction, and maintenance
Needs electricity to drive motor
Knowledge of maintenance schedule
2 Cert truck Vehicle Transport vehicle Transports people and equipment up to 80 mph
Needs driver Drivers license
3 Mobile lab #5 Vehicle Transport vehicle Transports people and equipment up to 80 mph
Needs driver Drivers license
4 Arrowboard Tool/sup Lighted traffic arrow
Directs or redirects vehicle and foot traffic
Needs electricity to laminate
None
5 Arrowboard Tool/sup Lighted traffic arrow
Directs or redirects vehicle and foot traffic
Needs electricity to laminate
None
6 Mule ATV Vehicle Off-road transport Access damaged zones, search and rescue, towing small equipment
Needs driver Operator training
7 Mule ATV Vehicle Off-road transport Access damaged zones, search and rescue, towing small equipment
Needs driver Operator training
8 Storm spotter #1
Vehicle Police-type pursuit vehicle
Pursuit, personnel transport, highly durable
Needs driver Drivers license
9 Storm spotter #2
Vehicle Police-type pursuit vehicle
Pursuit, personnel transport, highly durable
Needs driver Drivers license
10 Light tower #1 Tool/sup 30-ft light tower, illuminates up to 7.5 acres
Personnel search, staging area/command center illumination
Needs power source
None
11 Light tower #2 Tool/sup 30-ft light tower, illuminates up to 7.5 acres
Personnel search, staging area/command center illumination
Needs power source
None
12 Light tower #3 Tool/sup 30-ft light tower, illuminates up to 7.5 acres
Personnel search, staging area/command center illumination
Needs power source
None
13 Light tower #4 Tool/sup 30-ft light tower, illuminates up to 7.5 acres
Personnel search, staging area/command center illumination
Needs power source
None
14 Forklift #1 Transport Lift/remove/transp ort heavy items
Remove rubble, load pallets, transport supplies
Needs driver Forklift license
15 Forklift #2 Transport Lift/remove/transp ort heavy items
Remove rubble, load pallets, transport supplies
Needs driver Forklift license
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
29
Table A1. Functional capability matrix (continued)
Inventory Item Category Functional description
Capabilities Functional
components
Required training or prior
knowledge
16 Generator Tool/pow Portable power
Powers equipment such as air compressor, arrow board, light tower, and batteries
None Knowledge of maintenance schedule
17 Generator Tool/pow Portable power
Powers equipment such as air compressor, arrow board, light tower, batteries, and message board
None Knowledge of maintenance schedule
18 Message board Tool/ comm
Electrically illuminated, programmable sign
Mass communication via solar-panel power, battery power, or electric hook-up
Battery, or external power source if solar panel inoperable
How to program, maintenance schedule if applicable
19 Message board Tool/ comm
Electrically illuminated, programmable sign
Mass communication via solar-panel power, battery power, or electric hook-up
Battery, or external power source if solar panel inoperable
How to program, maintenance schedule if applicable
20 Pressure washer
Tool/sup
Dispenses pressurized water or other liquid solution
Rapid cleaning, decontamination
Pressurized air, pump motor, external power source
None
21 Radios 800 MHz Tool/ comm
Satellite radio Interoperable communication
Batteries None
22 MOC Vehicle RV mobile vehicle Personnel transport, storage, mobile operations support
Driver, maintenance, gas
Drivers license, vehicle main- tenance schedule
23 Air unit #7 Transport Flatbed trailer for SCBA and SCVA
Transports SCBA and SCVA capabilities
Vehicle to pull it Driver’s license
24 Cert trailer Transport Trailer Transport oversize, bulky equipment, vehicles, multiplies hauling capacity
Cert truck to pull it, driver
Driver’s license
25 Decon #4 Transport Trailer Transports decon kit Truck to pull it, driver
Driver’s license
26 Decon #4 equipment
Tool/ decon
Decontamination kit
Provides decon and containment capabilities to objects and people
None
Training in the use of individual decon equipment, proper equipment care, and shelf life, if applicable
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
30
Table A1. Functional capability matrix (continued)
Inventory Item Category Functional description
Capabilities Functional
components
Required training or prior
knowledge
27 Flatbed # 12 Transport Open flatbed trailer Transports heavy, bulky equipment such as vehicles with roll-on capability
Truck to pull it, driver
Driver’s license
28 Haz-Mat #1 Transport Trailer Holds, transports 229 hazmat response items
Truck to pull it, driver
Driver’s license
29 Haz-Mat #2 Transport Trailer Holds, transports 1,333 hazmat response items
Truck to pull it, driver
Driver’s license
30 Mule ATV trailer
Transport Live-in single axle trailer
Transports personnel, equipment, provides shelter, cooking, and sanitary facilities
Truck to pull it, driver
Driver’s license
31 Power unit #8 Transport Enclosed single axle cargo trailer
Transports power supplies or large bulky equipment, provides shelter
Truck to pull it, driver
Driver’s license
32 Power unit #8 equipment
Tools/pow Mostly power chords, lights
provides equipment interoperability, enables flexibility on site in providing power to vital equipment
None
Yes—formal training in basic electricity safety and knowledge of each equipment uses
33 Pump trailer Transport Portable pump trailer
Transports pump Truck to pull it, driver
Driver’s license
34 Satellite trailer Transport Holds satellite communications
Transports satellite communications
Truck to pull it, driver
Driver’s license
35 Support #3 Transport Enclosed dual axle trailer
Ample storage space, transports equipment, large items, provides shelter
Truck to pull it, driver
Driver’s license
36 Support #3 equipment
Tool/sup Additional nonspecialized, all- purpose tools
Furniture, cleaning supplies, access tools, jack
None
Yes—on some equipment such as the cutting torch and drill press
37 Travel trailer Transport Live-in RV-style trailer
Transport people and equipment, provides storage, long-term shelter with cooking and sanitary facilities
Driver, fuel Driver’s license, maintenance schedule
Travel trailer equipment
Tool/sup All-purpose support equipment
Blankets, trash cans, smoke and CO detector, jack
None None
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
31
Table A1. Functional capability matrix (continued)
Inventory Item Category Functional description
Capabilities Functional
components
Required training or prior
knowledge
38 Trash pump Tool/sup Waste water pump Portable pump with 264 GPM capacity
Fuel, operator Read manual
39 Chevy #12 Vehicle Truck Transport people, haul/towing, crew chassis
Driver Driver’s license
40 Decon pull truck #4
Vehicle Ford F550 Pulls the decon #4 trailer Driver Driver’s license
41 Fuel tender #9 Vehicle Ford F250 refueling truck
Diesel, contains one 15-gal unleaded tank and one 100- gal diesel tank
Driver Driver’s license
Fuel tender #9 equipment
Tool/pow All-purpose auto and refueling items
Hold fuel, recharge batteries, hitch trailers, jumpstart cars
Driver Driver’s license
42 Haz-Mat #10 Vehicle Ford f-350 pull truck
Contains all purpose support equipment, 4 wheel drive with hitch
Driver Driver’s license
Haz-Mat #10 equipment
Tool/ hazmat
All-purpose support tools
Winches, pulleys, access gear
None None
43 Haz-Mat #11 Vehicle Truck Pull truck Driver Driver’s license
44 Traffic #6 Vehicle Chevy truck Traffic truck Driver Driver’s license
45 Truck #600 Vehicle Truck Pull truck Driver Driver’s license
46 Truck #601 Vehicle Truck C4I capabilities in addition to all purpose support tools
Driver Driver’s license
47 Truck #602 Vehicle Technician truck No cab-suburban, transports people, small equipment
Driver Driver’s license
48 T-27 Warehouse
Warehouse Building Stores equipment of variety of sizes, vehicles
Building maintenance, electricity, facilities
Part-time maintenance staff
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
32
TEMA inventory item Flood
damage
Snow storm
damage
Rain storm
damage
Hurricane damage
Radiation attack
Biological attack
Bomb/ explosion
Chemical attack
Points earned
Air compressor Yes Yes Yes Yes No No Yes No 9
Cert truck Yes Yes Yes Yes Yes Yes Yes Yes 12
Mobile lab #5 Yes Yes Yes Yes Yes Yes Yes Yes 12
Arrowboard Yes Yes Yes Yes Yes Yes Yes Yes 12
Arrowboard Yes Yes Yes Yes Yes Yes Yes Yes 12
Mule ATV Yes Yes Yes Yes No No Yes No 9
Mule ATV Yes Yes Yes Yes No No Yes No 9
Storm spotter #1 Yes Yes Yes Yes Yes Yes Yes Yes 12
Storm spotter #2 Yes Yes Yes Yes Yes Yes Yes Yes 12
Light tower #1 Yes Yes Yes Yes No No Yes No 9
Light tower #2 Yes Yes Yes Yes No No Yes No 9
Light tower #3 Yes Yes Yes Yes No No Yes No 9
Light tower #4 Yes Yes Yes Yes No No Yes No 9
Forklift #1 Yes Yes Yes Yes No No Yes No 9
Forklift #2 Yes Yes Yes Yes No No Yes No 9
Generator Yes Yes Yes Yes No No Yes No 9
Generator Yes Yes Yes Yes No No Yes No 9
Message board Yes Yes Yes Yes Yes Yes Yes Yes 12
Message board Yes Yes Yes Yes Yes Yes Yes Yes 12
Pressure washer Yes Yes Yes Yes Yes Yes Yes Yes 12
Radios 800 MHz Yes Yes Yes Yes Yes Yes Yes Yes 12
MOC Yes Yes Yes Yes Yes Yes Yes Yes 12
Air unit #7 Yes No No No No No No No 2
Key Points
Yes in natural disaster 2
Yes in man-made disaster 1
No 0
Table A2. Disaster utilization matrix
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
33
Table A2. Disaster utilization matrix (continued)
TEMA inventory item Flood
damage
Snow storm
damage
Rain storm
damage
Hurricane damage
Radiation attack
Biological attack
Bomb/ explosion
Chemical attack
Points earned
Cert trailer Yes Yes Yes Yes Yes Yes Yes Yes 12
Decon #4 No No No No Yes Yes Yes Yes 4
Decon #4 equipment No No No No Yes Yes Yes Yes 4
Flatbed # 12 Yes Yes Yes Yes Yes Yes Yes Yes 12
Haz-Mat #1 Yes No Yes Yes No Yes No Yes 8
Haz-Mat #2 Yes No Yes Yes No Yes No Yes 8
Mule ATV trailer Yes Yes Yes Yes Yes Yes Yes Yes 12
Power unit #8 Yes Yes Yes Yes Yes Yes Yes Yes 12
Power unit #8 equipment Yes Yes Yes Yes Yes Yes Yes Yes 12
Pump trailer Yes No Yes Yes No No Yes No 7
Satellite trailer Yes Yes Yes Yes Yes Yes Yes Yes 12
Support #3 Yes Yes Yes Yes Yes Yes Yes Yes 12
Support #3 equipment Yes Yes Yes Yes Yes Yes Yes Yes 12
Travel trailer Yes Yes Yes Yes Yes Yes Yes Yes 12
Travel trailer equipment Yes Yes Yes Yes Yes Yes Yes Yes 12
Trash pump Yes No Yes Yes Yes Yes Yes Yes 10
Chevy # 12 Yes Yes Yes Yes Yes Yes Yes Yes 12
Decon pull truck #4 Yes Yes Yes Yes Yes Yes Yes Yes 12
Fuel tender #9 Yes Yes Yes Yes Yes Yes Yes Yes 12
Fuel tender #9 equipment Yes Yes Yes Yes Yes Yes Yes Yes 12
Haz-Mat #10 Yes Yes Yes Yes Yes Yes Yes Yes 12
Haz-Mat #10 equipment Yes Yes Yes Yes Yes Yes Yes Yes 12
Haz-Mat #11 Yes Yes Yes Yes Yes Yes Yes Yes 12
Traffic #6 Yes Yes Yes Yes No No Yes No 9
Truck #600 Yes Yes Yes Yes Yes Yes Yes Yes 12
Truck #601 Yes Yes Yes Yes Yes Yes Yes Yes 12
Truck #602 Yes Yes Yes Yes Yes Yes Yes Yes 12
T-27 Warehouse Yes Yes Yes Yes Yes Yes Yes Yes 12
15 no 189 yes 46 no 158 yes
Natural disaster 93 percent Prepared
Man-made disaster 77 percent Prepared
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
34
Table A3. Life cycle cost summary of calculations
Figure A1. Equipment utilization graph.
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
35
ABSTRACT
Objective: The purpose of this study was to exam- ine the impact of a week-long, full-scale training exer- cise in Kansas on multidisciplinary disaster respon- ders from health and public safety.
Design and setting: Design was structured on phase I (1 to 3 days of classroom training) and phase II (32-hour hands-on collaborative response to a sim- ulated disaster with multiple scenarios). Prospective survey data gathered information from participants in six exercise tracks of Command, Disaster Medicine, Emergency Operations Center, Fire Rescue, Law Enforcement, and Public Information Officer.
Subjects: Three hundred ninety-two multidisci- plinary participants voluntarily enrolled through a continuing education registration mechanism, and all completed the exercise.
Interventions: Surveys were completed at pre- classroom (90 percent completion rate), postclassroom (81 percent), and postdisaster simulation at 6 months after exercise (33-76 percent).
Main outcome measures: Four primary outcome measures were planned before the exercise began.
Results: Since September 11, 2001, one-third of participants attended one or two similar trainings. Fire rescue participants reported lowest levels of new course content, and disaster medicine the highest. Ninety-five percent of participants reported that per- sonal training goals were met. There were increases in substantial confidence levels in self, agency, the south central state region, and the state to respond to
disasters. The least amount of confidence increase was in the state’s ability.
Conclusions: Full-scale exercises require consid- erable time, resources, and funding; however, they offer attainment/enhancement of skills with immediate application in a team-oriented, practical setting, and this experience is invaluable when responding to real disasters caused by environmental forces, emerging infections, or terrorist events.
Key words: disaster exercise, multidisciplinary response, confidence levels of multidisciplinary disas- ter responders
INTRODUCTION
Since September 11, 2001, all-hazards, collabora- tive response training has been a high priority of responders from health and public safety.1-6 Disaster preparedness training ensures high levels of compe- tent response capabilities and encourages updating of disaster preparedness plans.7,8
From 2003 to 2008, The University of Kansas (KU) Medical Center conducted statewide disaster response training entitled, “Can It Happen in Kansas: Response to Terrorist Incidents and Major Disasters.” The ultimate goal was to train 10 percent of the core responder work- force (approximately 15,000 multidisciplinary specialists) by the end of the project. Professions included allied health providers, Emergency Medical Services (EMS) per- sonnel, fire services responders, hospital administrators, law enforcement officers, local health department admin- istrators, mental health professionals, nurses, nurse
Impact of a multidisciplinary disaster response exercise
David J. Cook, PhD Niaman Nazir, MBBS, MPH
Marta Skalacki, BA Carole Dale Grube, MA Won S. Choi, PhD, MPH
JEM
DOI:10.5055/jem.2011.0065
practitioners, pharmacists, physicians, physician assis- tants, and also community volunteers. The training goal was attained, resulting in one trained disaster respon- der/trained community member per approximately 190 Kansans.
The comprehensive training curriculum included three full-scale disaster exercises that were executed in strategic geographic areas of the state over the course of 3 years. The most comprehensive exercise was conducted during the week of October 13-21, 2007, in Wichita, located in the south central region of Kansas, for 918 professionals and community volun- teers. The educational methodology of this exercise was structured on two phases. Phase I consisted of 1 to 3 days of required classroom lectures, case studies, and hands-on training. Phase II was a full-scale 32- hour disaster simulation that incorporated hands-on collaborative response to multiple disaster scenarios, with the primary one being a partially demolished burning structure.
The exercise scenarios were developed during an 18- month planning period by an interdisciplinary commit- tee composed of the five authors of this article (repre- senting fields of communication, continuing education, preventive medicine, public health, and quantitative data management and analysis); representatives from disaster response organizations in south central Kansas; military representatives; project managers from Rescue Training Associates, Inc. (a private com- pany that specializes in hands-on disaster training exer- cises); and community volunteers. The committee met monthly, and the majority of meetings were conducted face to face. This was essential, especially during moments of deadlock about some exercise elements, which required lengthy discussions among the diverse committee members to arrive at compromise.
Continuing education standards guided develop- ment of the exercise. The prevailing criterion, deter- mined in collaboration with the US Department of Health and Human Services (DHHS), was to structure exercise scenarios that would contribute directly to pro- fessional competence across disciplines. One of the planning tasks was implementation of a series of needs assessments to find out gaps of knowledge and skills within the different response disciplines and also to
identify training needs common across disciplines. After information was collected and analyzed, the learning objectives were formulated based on the train- ing needs identified by each discipline. In addition, crosscutting training needs were catalogued, and this instructional information was embedded in the exercise as a whole.
The exercise was composed of 17 tracks, identified during the planning period, that were deemed essential for the south central state region. They were Command; Disaster Medicine; Elected Officials; Emergency Operations Center (EOC); Fire Rescue (with specialized tracks of Technician and Manager); Hospital (with spe- cialized tracks of Surge Capacity, Burn Patients, Toxicology/Radiology Exposures, and Pediatric Disaster Life Support); Hospital Mass Casualty Incident; Law Enforcement (with specialized tracks of Special Weapons and Tactics, Explosive Ordnance Disposal, and Law Enforcement Officers); Public Information Officer (PIO); Public Health; and Regional EMS Disaster Medicine Management and Procedures.
This study focused on responses from participants in six of the 17 tracks, as they had the most active roles in the exercise’s phase II disaster simulation. These six tracks were as follows: Command, Disaster Medicine, EOC, Fire Rescue, Law Enforcement, and PIO. Table 1 offers a brief overview of the tracks through summaries of primary topics of instruction, which were determined during the planning period.
The purpose of this study was to examine the changes in self-efficacy of participants in targeted tracks. As defined by Bandura, “perceived self-efficacy is defined as people’s beliefs about their capabilities to produce designated levels of performance ... People with high assurance in their capabilities approach dif- ficult tasks as challenges to be mastered rather than as threats to be avoided.”9(p1) These attributes have long been embedded in the training of the US military. Their established, detailed, and hands-on training builds self-efficacy in individuals and requires team work. The training objective is to be successful when battling an enemy.10 The intent of disaster response training is very similar, with the adversary being the catastrophes caused by nature or terrorist acts. In addition, a US Marine training manual emphasizes
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
36
that there is no equivalent substitute for live train- ing—as summarized by Confucius, “I hear and I for- get; I see and I remember; I do and I understand.”11(p47)
In this study, changes in self-confidence, the founda- tion of self-efficacy, were assessed at three different times during the course of the exercise along with other objectives. The assessment tools were surveys, which were developed during the planning period.
METHODS
The study population was composed of disaster response personnel from health and public safety who were enrolled in six selected exercise tracks. Enrollment for all tracks was voluntary and random. There was no registration fee, due to DHHS funding, and available spots in the exercise filled very quickly— primarily by responders from the south central state region. Written registration was required through the established system at the KU Continuing Education. As the study was an evaluation of educational strate- gies, it was exempt from Institutional Review Board assessment.
Phase I of the exercise encompassed instructional sessions such as class lecture, case study, and hands- on skill trainings that were held at eight training sites housed in multiple counties of the south central state region. This phase standardized the preparation experience for participants before the culminating disaster simulation, in comparison to some models where participants are sent written documents for self-study weeks before the exercise.12 Eighty-two expert instructors from 11 diverse organizations taught 776 participants and 142 volunteers from 62 organizations. This resulted in 10,742 hours of accredited continuing education instruction for disas- ter responders and an additional 142 hours of instruc- tion for volunteers.
Phase II of the exercise was the disaster simula- tion and consisted of a 32-hour hands-on collaborative response to test newly acquired or enhanced skills. There were multiple disaster scenarios. The primary one was a warehouse fire in down-town Wichita, with initial response by local fire services vehicles and equipment. Another scenario involved terrorist bombers in a nearby office building; this required
hostage negotiation. An additional scenario was a bio- logic threat of the early stages of a disease outbreak. Many hospitals in the region tested their surge capac- ity through the transport of mock-injured victims (com- munity volunteers) from most of the disaster scenarios. Three hundred ninety-two responders from health and public safety, and 142 volunteers originating from 50 counties and 62 agencies including Expeditionary Medical Support (military field hospitals) and the Kansas Air National Guard were deployed. The disas- ter simulation activities of phase II resulted in an addi- tional 4,471 accredited continuing education hours of instruction and 426 volunteer instruction hours for a grand exercise total of over 15,781 hours.
The professional backgrounds of participants in most tracks was from multiple disciplines. This multi- disciplinary enrollment was an expected outcome, as a guiding premise of the exercise was interdisciplinary responder interaction throughout the planning, imple- mentation, and evaluation periods. Elected officials from local and state government also took part in the exercise and had a unique opportunity to learn first- hand about the operations of disaster response and also to meet professionals from the diverse disciplines who fight disasters. Fire Rescue and Law Enforcement tracks were restricted to fire services officers and police officers, respectively, for obvious reasons.
Participant enrollment in the six targeted exer- cise tracks is presented in Table 1. There were 52 in Command (from disciplines of fire services, law enforcement, emergency management, public health, military personnel/National Guard, nursing, and dis- patch); 42 in Disaster Medicine (from disciplines of medicine, EMS, nursing, public health, fire services, law enforcement, military personnel, and allied health); 55 in EOC (from disciplines of public health, education, emergency management, fire services, law enforcement, state and local government, nursing, and military personnel/National Guard); 97 in Fire Rescue (from discipline of fire services); 101 in Law Enforcement (from discipline of law enforcement); and 45 in PIO (from disciplines of media, public infor- mation, public health, state and local government, EMS, fire services, emergency management, law enforcement, military personnel/National Guard,
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
37
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
38
Table 1. Participant enrollment in exercise training tracks by discipline
Training tracks and primary topics Number of participants Participant disciplines
Command
Disaster planning, incident command systems (ICS), incident action plans, ICS forms, emergency support functions, logistics, command hand-off, 24-hour disaster command functions, interoperability/communications, the media, and cost recovery.
52
Fire services, law enforcement, emergency management, public health, military personnel/National Guard, nursing, and dispatch.
Disaster Medicine
Treatment and extrication of simulated patients with severe injuries, confined space medicine, crush syndrome, blast injuries, medical problems resulting from weapons of mass destruction, victim injuries, and canine field medicine.
42 Medicine, EMS, nursing, public health, fire services, law enforcement, and military personnel/National Guard.
Emergency Operations Center (EOC)
Emergency support functions, information systems, unified command structure, EOC tactical operations, response and recovery, and planning and scheduling.
55
Public health, education, emergency management, fire services, law enforcement, state and local government, nursing, and military personnel/National Guard.
Fire Rescue
Technician: Structural shoring, concrete cutting, metal cutting, heavy rigging, crane operations, confined space operations, breaching and breaking, rope rescue, victim packaging, lift bags, equipment logistics, hazardous materials, robotics, extrication, and live site operations. 97 Fire services
Manager: Operational command procedures, personnel accountability, resource allocation, and hot-zone management.
Law Enforcement
Special Weapons and Tactics: Team member operations in dangerous conditions surrounding response to a terrorist incident.
101 Law enforcement Explosive Ordnance Disposal: Team member safe operations in dangerous environments inherent in responding to an actual terrorist incident.
Law Enforcement Officers: Preparation of front line and supervisory officers to manage mass casualty disasters.
Public Information Officer (PIO)
Basic crisis communication principles when developing key messages for release to the public.
45
Media, public information, public health, state and local government, EMS, fire services, emergency management, law enforcement, military personnel/National Guard, finance, human resources, hospital administration, and nursing.
Total 392
finance, human resources, hospital administration, and nursing).
This study was part of the exercise’s internal review and used prospective survey data to gather information about the impact of comprehensive disas- ter preparedness training across six exercise tracks. At the start of phase I, each participant was given an evaluation packet that contained three printed sur- veys. Each three-survey set was marked with a unique identification number, and this was the only identifier that enabled compiling of data from partic- ipants. The first survey was completed before the start of classroom instruction of phase I and was col- lected by exercise evaluators from KU Medical Center. The second survey was completed immedi- ately after classroom instruction and was collected by the same evaluators. The third survey was completed by participants 6 months after phase II disaster sim- ulation and was mailed to evaluators at KU Medical Center via prepaid envelopes.
Surveys were standardized as much as possible and contained crosscutting items common across tracks and also track-specific items as identified through the series of needs assessments conducted during the exercise planning period. Survey items selected for this study were as follows. For phase I, participants were queried about the level of newness of course material, whether their personal goals for attending training were met, and the number of simi- lar trainings attended since September 11, 2001. For phase I (both preclassroom and postclassroom) and phase II (postdisaster simulation), participants were
asked to rate their confidence levels in themselves, their agency, the state region, and the state to respond to real disasters. This was measured on a Likert scale (0 � no confidence; 1 � low confidence; 2 � moderate confidence; and 3 � substantial confidence).
Overall survey completion rates for participants are presented in Table 2. For phase I, the completion rate was 90 percent for preclassroom and 81 percent for postclassroom. For phase II, the completion rate ranged from 33 to 76 percent for postdisaster simula- tion. Response rates were lower for the postdisaster simulation because the follow-up survey was con- ducted 6 months after the exercise. Surveys were entered into MS ACCESS database and imported into SAS v9.1 for statistical analyses. Discrete variables are described using frequencies and percentages.
RESULTS
Demographic data of the participants in tracks of Command, Disaster Medicine, EOC, Fire Rescue, Law Enforcement, and PIO are presented in Table 3. Gender: 79.2 percent of participants were male, and 20.8 percent were female. Age: 79.9 percent of participants were below 50 years. Years of experience: 64.2 percent of par- ticipants reported at least 10 years of experience in their specific profession. An assessment of the number of dis- aster preparedness and response trainings that were completed since September 11, 2001 revealed that 33.1 percent of participants stated that the exercise was their first training, 36.3 percent of participants had attended one or two similar trainings, and only 30.6 percent of participants had attended three or more trainings. Of these data, the most unexpected finding was that one- third of participants had not attended previous training.
Figure 1 presents the results of participants’ eval- uation of the newness of course content in phase I classroom portion of the training. There was greater variability in these results, with only 28.7 percent of Fire Rescue personnel reporting that the majority of course content was new. Participants in Disaster Medicine and PIO tracks reported the highest per- centages, 67.5 percent and 53.8 percent, respectively. The results also show that the majority of partici- pants across all six tracks were very satisfied with the training, with an average of 95 percent reporting
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
39
Table 2. Rates for completion of surveys at three measurement points*
Exercise phases
Completion of surveys
Preclassroom Postclassroom
Postdisaster simulation
(6 months after exercise)
Phase I 90 81 n/a
Phase II n/a n/a 33-76
*Values are expressed in percentage. Abbreviation: n/a, not applicable.
that their personal goals for attending the training were met.
Change in confidence level to respond adequately to a real disaster is reported in Figure 2. Assessment of changes at the highest level of confidence, “sub- stantial” was a key element of evaluation, so the results reported in this figure are for that level, although the trend was similar for other levels of con- fidence. Participants reported an increase in their level of “substantial confidence” at two time points: phase I postclassroom and phase II postdisaster. At preclassroom, only 17.4 percent of participants reported having substantial confidence in their own abilities to adequately respond to real disasters. This increased to 29.8 percent at postclassroom training and increased further after the postdisaster simula- tion to 45.2 percent. The trend was similar for confi- dence in one’s agency or organization and the south central state region. Participants reported the slight- est gains in confidence levels in the state’s ability to respond to disasters. Results are not presented for specific disciplines because the general trend was consistent across all tracks.
DISCUSSION
One key finding was that one-third of the partici- pants had not undergone any comprehensive training similar to the one described in this study since
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
40
Figure 1. Participant feedback on classroom training with respect to new course content and meeting personal goals.
Table 3. Demographic characteristics of participants in the exercise
Demographic variables N (percent)
Gender
Male 282 (79.2)
Female 74 (20.8)
Age, y
<40 168 (47.6)
40-49 114 (32.3)
>50 71 (20.1)
Years of experience
<10 127 (35.8)
10-19 133 (37.5)
>20 95 (26.7)
Number of previous trainings
None 117 (33.1)
1-2 128 (36.3)
>3 108 (30.6)
September 11, 2001, and only an additional one-third had completed one or two trainings. A higher propor- tion of participants was expected to have had at least one training. One factor that could have influenced participation levels was the 2007 tornado that destroyed the town of Greensburg, which is located in south central Kansas. The tornado hit just 5 months before the exercise, and this disaster event could have motivated some responders to seek comprehensive training, especially those who had little or no previous training.13 These results suggest that disaster pre- paredness and response trainings are needed and that they should be conducted more frequently.
This study demonstrates that responders from health and public safety all gain new knowledge and information during disaster exercises. The variation of newness of course content across disciplines was somewhat predictable when viewed through the spec- trum of longevity of established professions. For exam- ple, fire services participants cited the least amount of new course content. This aligns with a well-estab- lished profession that historically conducts frequent in-service trainings.14 In contrast, disaster medicine participants cited the highest amount of new course content. This is also a reasonable result, as disaster medicine is a new specialty with a certification board
and professional academy newly established in the mid-2000s.15
In this study, the high satisfaction rate with attainment of personal goals substantiates the success of planning by a multidisciplinary team that was able to customize the exercise for the south central state region.16 The interdisciplinary planning committee was the engine that directed completion of a full spec- trum of tasks. Members conducted needs assessments to determine gaps of knowledge per discipline and across disciplines; established learning objectives for each discipline with cross-cutting needs embedded; developed exercise tracks and respective curriculums; created multiple disaster scenarios that encompassed incendiary, terrorist, explosive, and biologic disaster incidents; and compiled evaluation surveys.
Although the phase I classroom and phase II dis- aster simulation sessions had differential impacts across tracks, the training activities of both phases had a significant influence on the confidence levels of all participants. Similar patterns were observed in participants’ confidence in their agencies and the response systems in the south central state region. A less graduated increase in assurance was observed in participants’ confidence levels in the state’s ability to respond to disasters. A possible explanation for this
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
41
Figure 2. Change in confidence level to adequately respond to a real disaster (substantial confidence).
result is that the exercise was specifically designed for the south central state region and did not actively draw on or test state capacity to respond to disasters.
Recently published reports question the hands-on methodology of disaster response training in favor of computer-based training.17,18 This type of instruction is deemed less expensive and becoming more widely used in many fields.19,20 For example, military and medical disciplines have well-established training programs, and both use tools that replicate reality such as electronic media and plastic models; however, these devices have limitations. (Note: The tools and devices in this paragraph are referred to as “simula- tions,” which is in direct contrast to the definition of simulation used in this article, where simulation refers to a “staged,” live disaster.) Jones et al. stated that (military) “...simulation is only an approximation of the real world and can be ineffective if it deviates significantly from reality.”21(p28) Ziv et al. stated that “Simulation-based medical education can be a valu- able tool (but) ... Medical training must at some point use live patients to hone the skills of health profes- sionals.”22(p783) The discussion about the most effective use of various training methodologies in disaster response is ongoing. Live events and tools that mimic reality have their strengths and weakness—cost effectiveness is an important part of the analysis. However, the ultimate objective for disaster response training is to conduct training that will enable partic- ipants to engage an adversary, ie, a disaster. It would seem that both training methodologies could comple- ment each other, and it is likely that they will find their places in the disaster training continuum as fur- ther research is conducted. Nevertheless, it is impor- tant to note that from the experiences of military and medical disciplines, the training with the most impact on ability to perform has to be live.
The exercise described in this article was the largest integrated training and disaster simulation ever undertaken in Kansas and has offered agencies and jurisdictions the means to test their skills in real time, to gain the in-depth knowledge and skill levels that only this type of realistic experience can provide, and to build coordinated capacity for disaster and ter- ror response. It is the hands-on, real-time training
acquired through disaster exercises that enhances communication, teamwork, and interdisciplinary and interagency collaborations23,24—all critical skills required in times of a disaster. The results from this study have important implications for future disaster preparedness training for state regions similar to the one in south central Kansas. On a national level, hands-on multidisciplinary full-scale exercises simi- lar to the one presented in this study are essential for the development of a robust disaster response infra- structure in the United States.24,25
In recent years, disasters caused by environmen- tal forces, emerging infections, or terrorist events have revealed the heroism of disaster responders from health and public safety and have also brought to light the limitations of the capabilities of individu- als and systems.26 Kansas responders routinely deal with disasters caused by environmental forces such as tornadoes, storms, and floods. There have been no recent epidemics, and terrorist incidents are consid- ered unlikely. If terrorism strikes Kansas, its likely form would be agroterror due to the state’s high beef and wheat production. Most importantly, an epidemic or terrorist act would activate the same disaster response teams that cope with the natural disasters precipitated by environmental forces. For this reason, the need for training in all-hazards collaborative response remains a high priority in the state. As a result of the disaster response exercise, Kansas is bet- ter prepared to respond to the consequences of regu- larly occurring natural disasters of tornadoes, bliz- zards, floods, possible epidemics caused by emerging infections, and also potential terrorist threats.
CONCLUSIONS
Although large-scale exercises can require consid- erable time, resources, and funding, they are invalu- able training experiences. Training directors, organi- zations that provide funding and support, policy makers, and others in positions of influence must rec- ognize the significance of full-scale multidisciplinary exercises to prepare the responder workforce for the unfortunate disasters that lie ahead. There have not been sufficient studies conducted in the area of disas- ter preparedness and response training to determine
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
42
the effectiveness for all types of trainings.24 However, the results from the Kansas exercise demonstrate that there is an impact on the self-efficacy of disaster responders in terms of their “beliefs about their capa- bilities to produce designated levels of perform- ance”9(p1) when fighting real disasters.
ACKNOWLEDGMENTS The exercise was made possible by a grant from the US
Department of Health and Human Services, Office of the Assistant Secretary for Preparedness and Response, Office of Preparedness and Emergency Operations, grant #6T01HP006627. The South Central Kansas Homeland Security Council was a project collaborator. The council used funds it had attained from the Department of Homeland Security, Office of Domestic Preparedness for the sole purpose of back pay to some participants. The exercise was conducted in partnership with a professional disaster training organization, Rescue Training Associates, Inc. The findings and conclusions presented here are those of the authors and do not necessarily represent the official positions of collaborators, partners, or funding organizations.
David J. Cook, PhD, Associate Vice Chancellor, Outreach, and Associate
Professor, Health Policy and Management, University of Kansas
Medical Center, Kansas City, Kansas.
Niaman Nazir, MBBS, MPH, Research Instructor, Preventive Medicine
and Public Health, University of Kansas Medical Center, Kansas City,
Kansas.
Marta Skalacki, BA, Writer, Outreach, University of Kansas Medical
Center, Kansas City, Kansas.
Carole Dale Grube, MA, Associate Dean, Continuing Education,
University of Kansas Medical Center, Kansas City, Kansas.
Won S. Choi, PhD, MPH, Director and Associate Professor, Preventive
Medicine and Public Health, University of Kansas Medical Center,
Kansas City, Kansas.
REFERENCES 1. Peterson C: Be safe, be prepared: Emergency system for advance registration of volunteer health professionals in disaster response. Online J Issues Nurs. 2007; 12(1): 12. 2. Reissman DB, Howard J: Responder safety and health: Preparing for future disasters. Mt Sinai J Med. 2008; 75(2): 135-141. 3. Secor-Turner M, O’Boyle C: Nurses and emergency disasters: What is known. Am J Infect Control. 2006; 34(7): 414-420. 4. Soto Mas F, Hsu CE, Jacobson H, et al.: Physician assistants and bioterrorism preparedness. Biosecur Bioterror. 2006; 4(3): 301-306. 5. Coleman J, Hollins L, Kreis S, et al.: Roundtable: Training after September 11. Fire Engineering, 2002. Available at http:// www.fireengineering.com/index/articles/display/133385/articles/ fire-engineering/volume-155/issue-1/departments/roundtable/ training-after-september-11.html. Accessed January 12, 2011.
6. Bodrero D: Law enforcement’s new challenge to investigate, interdict, and prevent terrorism. Police Chief. 2002; 69(2): 41, 43- 46, 48. 7. Niska RW, Burt CW: Bioterrorism and mass casualty prepared- ness in hospitals: United States, 2003. Adv Data. 2005; (364): 1-14. 8. Seale GS: Emergency preparedness as a continuous improve- ment cycle: Perspectives from a postacute rehabilitation facility. Rehabil Psychol. 2010; 55(3): 247-254. 9. Bandura A: Self-efficacy. In Ramachaudran VS (ed.): Encyclopedia of Human Behavior. Vol. 4. New York: Academic Press, 1994: 71-81 (Reprinted in Friedman H (ed): Encyclopedia of Mental Health. San Diego: Academic Press, 1998). 10. Department of the Navy, Headquarters, United States Marine Corps: How to Conduct Training. Washington, DC: Department of the Navy, Headquarters, United States Marine Corps, 1996: 1-134. 11. Rogers GF Major: The leader as teacher. Mil Rev. 1983; 63(7): 2-13. 12. De Lisi S: Designing a full-scale exercise for a terrorist incident. Fire Engineering, November 26, 2010. 13. Auf der Heide E: Principles of hospital disaster planning. In Hogan DE, Burstein JL (eds.): Disaster Medicine. 2nd ed. Philadelphia, PA: Lippincott Williams & Wilkins, 2007: 95-126. 14. Smith D: History of Firefighting in America: 300 Years of Courage. New York: Dial Press, 1978. 15. American Association of Physician Specialists: Disaster medi- cine: A history. Available at www.abpsus.org/history-disaster-med icine. Accessed January 12, 2011. 16. Fagel MJ; National Domestic Preparedness Office United States: Disaster drilling prepares for the real incident. Beacon. 2000; 2(9): 3-5. 17. Chung S, Mandl KD, Shannon M, et al.: Efficacy of an educa- tional Web site for educating physicians about bioterrorism. Acad Emerg Med. 2004; 11(2): 143-148. 18. Kincaid P, Donovan J, Pettit B: Simulation techniques for training emergency response. Int J Emerg Med. 2003; 3(1): 238- 246. 19. Lam-Antoniades M, Ratnapalan S, Tait G: Electronic continu- ing education in the health professions: An update on evidence from RCTs. J Contin Educ Health Prof. 2009; 29(1): 44-51. 20. Brusilovsky P, Vassileva J: Course sequencing techniques for large-scale web-based education. Int J Contin Eng Educ Lifelong Learn. 2003; 13(1/2): 75-94. 21. Jones RM, Laird JE, Nielson PE, et al.: Automated intelligent pilots for combat flight simulation. AI Magazine. 1999; 20(1): 27-41. 22. Ziv A, Wolpe PR, Sall S, et al.: Simulation-based medical educa- tion: An ethical imperative. Academic Medicine. 2003; 78(8):783- 788. 23. Schultz CH, Mothershead JL, Field M: Bioterrorism prepared- ness. I. The emergency department and hospital. Emerg Med Clin North Am. 2002; 20(2): 437-455. 24. Perry R: Disaster exercise outcomes for professional emergency personnel and citizen volunteers. J Contingencies Crisis Manage. 2004; 12(2): 64-75. 25. Schlepman AR, Gerbaudo VH, Castronovo FP Jr: Radiation dis- aster response: Preparation and simulation experience at an aca- demic medical center. J Nucl Med Technol. 2004; 32(1): 22-27. 26. McSwain NE Jr: Disaster response. Natural disaster: Katrina. Surg Today. 2010; 40(7): 587-591.
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
43
Individual Articles: Visit www.emergencymanage-
mentjournal.com and click on the abstracts link to
purchase your favorite articles from the past eight
years. Or, to handle copyright clearance, visit the
Copyright Clearance Center at www.copyright.com.
Commercial reprints of journal articles are readily
available for all Journal of Emergency Management
issues. Article reprints carry the prestige, authority,
and quality that you expect from Journal of Emer-
gency Management, and the added value that the
Journal is peer-reviewed by experts in the field.
Reprints can be a powerful promotional tool for the
distribution of up-to-date research and information
among your target audience, whether it be through
your sales force, direct mail campaigns, or as handouts
at conferences and commercial exhibitions. Call our
reprint department for a commercial reprint quote.
Classroom Course Packs are readily available for
all Journal of Emergency Management issues. Article
reprints and course packs are great teaching tools
that bring the real world into the classroom with au-
thority, and quality that you expect from Journal of
Emergency Management and the added value that the
Journal is peer-reviewed by experts in the field.
Course packs are available from Copyright Clearance
Center through their Academic Permissions Service.
Visit www.copyright.com and reference the journal’s
ISSN number to place your order.
Journal of Emergency Management is now a member
of Crossref.org for document cross referencing. Visit
www.crossref.org for more details or utilize the DOI
number now located on the first page of each article.
© Customize your commercial
reprints to suit your needs:
• Printed on high-quality 60 lb. glossy stock
• Four-color and black and white printing
• Eprints - Online Controlled Access Reprints
• Pocket-sized or digest-sized article reprints
• Custom designed covers
• Monographs: A selection of articles printed to-
gether as a booklet, even from different issues
Licensed content:
• Utilize licensed content to provide added value
to your website or promotional materials
Coursework:
• Create entire courses utilizing the journal’s
archives
• Build on the existing research base
Journal of Emergency Management
470 Boston Post Road
Weston, MA 02493
781-899-2702 • fax: 781-899-4900
email: [email protected]
www.emergencymanagementjournal.com
13051 2/09/2011 rev b
Copyright...it’s easy.
In the classroom or in the field
put our extensive library of
articles to use.
13051 8/10/2011 10:23 AM Page 1
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
45
ABSTRACT
The relationship between level of educational attainment and degree of self-reported disaster pre- paredness was investigated with national 2008 data. Americans with a post-secondary degree were expected to be more prepared because of exposure to university emergency systems and because education may impact the degree to which individuals process risk-minimiz- ing information. The �2 procedure produced statisti- cally significant associations between all disaster pre- paredness measures and post-secondary degree status. Logistic regressions confirmed associations between the dependent measures and a post-secondary degree status, with all measures producing statistically signif- icant t values. Positive correlations between post-sec- ondary educational attainment and measures of disas- ter preparedness were stronger for having an emergency plan (b � 0.789) and knowing where to get additional information (b � 0.755).
Key words: disaster preparedness, emergency man- agement systems, emergency notification systems, edu- cational attainment, institutions of higher education
INTRODUCTION
Education builds a culture1 of disaster response and influences disaster preparedness both directly and indirectly. Auf der Heide2 observed that “Public educa- tion about the nature of disaster hazards and the prac- tical counter-measures available can help to offset apa- thy.”2(p30) In the aftermath of the September 11, 2001 terrorist attacks, there has been growing interest in dis- aster instruction and research.3 Survival after a dis- aster often depends on training and preparation, and initiatives such as Ready America4 and Be Red Cross
Ready5,6 are now ambitious public service missions. American colleges and universities have accelerated efforts to develop and maintain campus emergency sys- tems, especially in the wake of the 2007 Virginia Tech shootings.7 What is less well understood is how educa- tional attainment may indirectly impact the disaster preparedness of individuals. Indirect effects may include exposure to university emergency systems and the development of mindsets that better process disas- ter planning information. This study investigated the relationship between level of educational attainment and degree of self-reported preparedness. Are Americans who have earned a post-secondary degree better pre- pared to respond appropriately in an emergency or disas- ter than those with a high school diploma or less?
REVIEW OF LITERATURE
Education is one factor that may shape the degree to which individuals accurately perceive and assess risks— a foundation for disaster preparedness.8 Apathy for pre- paredness occurs as the low probability of disaster events are overshadowed by daily living, and the public percep- tion of risk does not correlate with actual risks.2 Tierney et al.8 observed that “An understanding of how and why households prepare for disasters must be based first on an understanding of how the public perceives and acts on risk information.”8(p29) The involvement of multiple stages for processing information is identified in theory. Nigg9 identified three stages: hearing the information, understanding it, and perceiving its relevance. Tierney et al.8 suggested five stages: attention, comprehension, acceptance, retention, and action. Higher education is believed to explicitly influence these cognitive elements and dispositions. Arnett10 observed that educational
Disaster preparedness and educational attainment
Lauren A. Menard, EdD Robert O. Slater, PhD
Jim Flaitz, PhD
JEM
DOI:10.5055/jem.2011.0066
institutions shape “expectations according to which individuals plan their futures, including their entry from adolescence into adult life.”10(4) It follows, then, that education’s contribution to the development of processes, dispositions, and mindsets in individuals bet- ter enables them to appreciate threats and to process risk-minimizing information.
Emergency Communication Management Systems (ECM) and Emergency Notification Systems (ENS) are becoming common on university campuses.7 Americans with a recent college degree are more likely to have been exposed to disaster and emergency planning infor- mation within an institutional context where the rele- vance of that information is recognized. Commu- nication’s significant role in disaster response was observed following Hurricane Katrina, where signifi- cant breakdowns were documented.11 In reflections on the effects of Katrina on communications and infra- structure, Miller12 observed, “The consequences of this massive communications failure were both swift and severe...In effect, when communications went out some- thing like the fog of war descended upon the Gulf Coast” (emphasis added).12(p196) To better understand the state of university ECM and ENS, the EDUCAUSE Net@EDU Converged Communications Working Group Steering Committee surveyed selected institutions of higher education on the development and management of emergency technology services, policies, and proce- dures.7 Researchers found that 84 percent of the universities surveyed used technology and policies to mitigate emergencies and 88 percent planned future system enhancements.7
Emergency systems and policies on most univer- sity campuses were found to be works in progress.7
Well-organized, connected communication systems make possible a larger network of resources that could aid response to emergency events. For instance, the Association of Schools of Public Health stepped in after Hurricane Katrina to ensure a continuity of instruction when students from Tulane University’s School of Public Health and Tropical Medicine were evacuated from New Orleans less than a week after the semester began.13 Louisiana State University’s texting system “E!TXT” is one example of technology and policy solutions that improve the capacity of
universities to efficiently communicate disaster and emergency information to students.14 Staman et al.7
described a wide variety of campus emergency man- agement and notification tools:
A variety of emergency notification system (ENS) management tools are appropriate for college campuses: These tools range from something as simple as external sirens to solutions involving combinations of various technologies: a campus website, e-mail, landline phones, cell phones, text messaging, paging, external loudspeakers, digital signage, a campus CATV system, network pop-ups, RSS feeds, instant mes- saging (IM), fire panel alarms with voice enunciation, and/or social networking websites.7(p50)
PURPOSE OF THE STUDY
The purpose of this study is to provide empirical evidence to test the hypothesis that the self-reported emergency preparedness of Americans varies as a function of educational attainment level. An expecta- tion is that those with a post-secondary degree are more likely to be prepared than those with a high school diploma or less. A research question furthered the investigation: Is there a positive correlation between a post-secondary level of educational attain- ment and emergency preparedness?
METHODS
Research questions were examined with the 1972-2008 General Social Survey (GSS) datafile. The survey contains core and topic questions designed to track opinions of Americans older than 18 years on social issues and contains 1,427 variables, with more than 230 trends and over 20 data points.15 The data are provided free of charge to researchers on the World Wide Web.16 Full-probability sampling was uti- lized.17 More information on the 2008 GSS survey is available from the Roper Center.17
The number of valid responses in the current study ranged from 1,323-1,342. The number of cases varied because the number of no responses per survey
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
46
question varied slightly. The Survey Documentation Analysis (SDA) of the GSS is a web-based survey analysis program developed by the Computer-assisted Survey Methods Program (CSM) at the University of California, Berkeley.18 Frequency cross-tabulations were performed to observe and compare frequencies and percentages of those with a post-secondary degree and those with a high school diploma or less on five measures of disaster preparedness. Frequencies and Pearson’s �2 values are reported. Samples used in cross- tabulations were from the 2008 GSS Disaster Preparedness topic module and were complex samples. A Rao-Scott adjustment was calculated by SDA for each �2 value to address small significance levels in complex samples. The adjusted Rao-Scott statistic is used to derive an F statistic, which is added to the analysis, and probability levels from the F-value are displayed.
Logistic regressions were performed to further observe relationships between educational attainment level and emergency preparedness. The logistic regres- sion procedure was selected because all variables were dichotomous. Regression coefficients /b/ are reported and measure one unit change effect in the independent variable on the dependent variable logit. The exponen- tial of logistic regression coefficients estimated the odds ratio of observing outcomes and is reported as Exp (B). Coefficients, standard errors, single parame- ter t tests and p values, and Pseudo R2 values were reported. Duffy19 explained that the coefficient of determination (R2) and variations, such as Pseudo R2, have limited meaning in logistic regression. In this study, the Pseudo R2 statistic should only be interpreted in comparison to the Pseudo R2 of other dependent measures used here. A 95% confidence level was applied throughout, and a threshold of 0.05 was used to determine statistical significance.
Independent variable A survey variable for highest degree attained
measured educational attainment. Although this variable is in the replicating core of the GSS, only 2008 responses were used because this is the only survey year that included the dependent variables of interest to this study. The educational attainment variable was recoded as dichotomous, and categories
were collapsed to include one category of those with a high school diploma or less and one category of those with an associate, bachelor, or graduate degree.
Dependent variables Five measures were selected from the 2008 GSS
datafile. Measures and relevance to disaster pre- paredness are shown in Table 1. The selected meas- ures are identified in disaster preparedness litera- ture as being associated with preparedness3-6,20,21 and include the following survey questions:
� Have you or anyone you know developed emergency plans (evacuation, meeting places, etc)?
� Have you or anyone you know stockpiled supplies (food, water, antibiotics, etc)?
� Have you or anyone you know learned where to get more information about terrorism?
� Have you or anyone you know duplicated important documents (birth certificate, medication prescriptions, and passports)?
� Have you or anyone you know become more vigilant or aware of what is going on around them?
A beginning prompt for the GSS disaster pre- paredness topic module connects the 9/11 tragedy with other disaster events: “Community-wide disas- ters happen, and these happen for a variety of rea- sons such as acts of nature, terrorism, industrial accidents, and other causes. Do you know anyone who has done any of the following things because of terrorism since September 11, 2001?”16 Response cat- egories for dependent variables were the following: 0 No; 1 Yes, respondent; 2 Yes, someone respondent knows; 3 Yes, both respondent and someone respon- dent knows. Dependent variables were recoded as dichotomous with one group of “no” and one group of “yes” that contained categories 1 and 3; category 2 was not considered.
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
47
RESULTS
Results of the frequency cross-tabulations and the logistic regressions are shown in Tables 2 and 3, respectively. The �2 procedure resulted in statistically significant associations between all disaster prepared- ness measures and a post-secondary degree, with all probability levels below 0.05 (Table 2). Percentages of “yes” were lower than “no” responses for all measures.
One reason why overall percentage differences between educational attainment groups were large was because of the low proportion of those reporting preparedness, as shown in Figure 1. Probability levels for all t tests were below 0.05, with a magnitude of greater than 2.0 for all measures of preparedness. Attaining a college degree had a positive effect on all dependent measures. Educational attainment explained
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
48
Table 1. Study measures
Measure Relevance to preparedness
Independent variable
Educational Attainment A research hypothesis of the study is that the emergency preparedness of Americans differs by educational attainment—the higher the levels of educational attainment, the greater the preparedness.
Dependent variables
Emergency Plan
While disasters are difficult to predict, households are encouraged to plan for the most likely type of disaster for their environments—home, school, work, and leisure.4-6
Household members should have assigned responsibilities and work as a team. Planning for situations where members are separated is recommended. The plan should include two designated meeting places—one local and one outside area. Emergency contacts for household members and a designated out-of-area contact should be programmed into cell phones. Cards can be printed for storing contact information.19 Contingencies should be established, such as texting, in the event that local phone lines are overloaded or out of service.
Stockpiled Supplies
Emergency items have been identified and listed.6 Without this list, items may not be readily apparent as needed for disasters. A 2-week supply of water and food should be prepared for in-home emergencies and a 3-day supply prepared for evacuations. One gallon of water per person per day is recommended. Nonperishable and easy to prepare food is needed. Baby food, pet food, and medications may be needed. A disaster kit should be water and pet proof, easy to carry, and stored in an easily accessible location.19
Where to Get More Information
Communities change instantly in disasters. Where to turn for information or resources differs by location and event. Citizens should identify those communication systems that will likely be used by local authorities to disseminate information, such as local radio, TV, or weather stations.6
Duplicated Documents Copies of important documents should be placed in a plastic container and stored in an emergency kit, with originals kept in a safety deposit box.
Vigilance
Becoming more aware and vigilant was a frequent recommendation after September 11, 2001. Einhorn and Edwards observed, “Being prepared is the conscious decision to become more aware of your surroundings on a local and global level and do all you can to protect yourself and your loved ones.”20(p14)
the most variance for Having a Plan (Pseudo R2 � 0.022) and Getting Additional Information (Pseudo R2 � 0.022; Table 3). Although many other factors likely have an effect on emergency preparedness, edu- cational attainment appears to represent an impor- tant factor in status of preparedness. The research question investigated relationships between educa- tional attainment level and the following five depend- ent measures.
Emergency plans Those with a college degree (20 percent) were 10
percentage points or 100 percent more likely than those with a high school diploma (10 percent) to have an emergency plan (Figure 1; Table 2). Logistic regression analysis confirmed the significant rela- tionship between having an emergency plan and hav- ing a college degree (b � 0.789), with over twice the odds ratio of observing the effect (Exp [B] � 2.200). Emergency plan had the strongest coefficient, but with a greater standard error (SE [B] � 0.163) than More Information, and the t test for Emergency Plan (t � 4.848) was the second strongest of all five dependent measures (Table 3).
Stockpiling supplies Those with a college degree (13 percent) were 4
percentage points or 44 percent more likely than those with a high school diploma or less (9 percent) to have stockpiled supplies for an emergency. The low percent- ages for Stockpiling Supplies are shown in Figure 1. The relationship between stockpiling supplies and having a college degree was confirmed by regression analysis (b � 0.418), with over one and a half the odds ratio of observing the effect (Exp [B] � 1.518).
Getting additional information Those with a college degree (32 percent) were 14 per-
centage points or 78 percent more likely than those with a high school diploma or less (18 percent) to know where to get more disaster information (Figure 1; Table 2). A regression analysis confirmed the significant relation- ship between knowing where to get more information and having a college degree (b � 0.755), with over twice the odds ratio of observing the effect (Exp [B] � 2.127).
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
49
Table 2. Emergency preparedness responses by educational attainment*,†
Education
HS degree or less
College degree
Emergency plan
No, n (percent) 703 (82) 326 (68)
Yes, n (percent) 83 (10) 91 (20)
�2 statistic 45.70
Rao-Scott statistic F(2, 80) � 12.64 (p � 0.001)
Stockpiled supplies
No, n (percent) 699 (81) 351 (73)
Yes, n (percent) 78 (9) 66 (13)
�2 statistic 11.18
Rao-Scott statistic F(2, 80) � 3.29 (p � 0.04)
Where to get information
No, n (percent) 651 (77) 276 (61)
Yes, n (percent) 160 (18) 169 (32)
�2 statistic 37.79
Rao-Scott statistic F(2, 80) � 7.69 (p � 0.001)
Duplicated documents
No, n (percent) 741 (87) 372 (79)
Yes, n (percent) 94 (11) 94 (18)
�2 statistic 13.78
Rao-Scott statistic F(2, 80) � 3.48 (p � 0.04)
Vigilance
No, n (percent) 355 (42) 141 (28)
Yes, n (percent) 457 (52) 305 (67)
�2 statistic 28.92
Rao-Scott statistic F(2, 80) � 12.01 (p � 0.001)
*Source: ref. 16. †Percents do not total 100 because, as noted, category 2 responses are not included.
More Information was the second to strongest coefficient, but with a smaller standard error (SE [B] � 0.132) than Having a Plan, and the t test was the strongest for More Information (t � 5.697) than for any other dependent measure.
Duplicating documents Those with a college degree (18 percent) were 7 per-
centage points or 63 percent more likely than those with a high school diploma or less (11 percent) to have dupli- cated important documents. The significant relationship
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
50
Table 3. Logistic regression of educational attainment on emergency preparedness*
Logit coefficients Test that each coefficient � 0
b SE (B) Exp (B) Exp (SE [B]) t test Pseudo R2
Emergency Plan 0.789 0.163 2.200 1.177 4.848† 0.022
Stockpiled Supplies 0.418 0.183 1.518 1.201 2.279‡ 0.006
More Information 0.755 0.132 2.127 1.142 5.697† 0.022
Duplicated Documents 0.564 0.163 1.758 1.178 3.451† 0.011
Vigilance 0.625 0.121 1.869 1.129 5.165† 0.015
Note: n � 1,323-1,342. *Source: ref. 16. †p � 0.001. ‡p � 0.02.
Figure 1. Disaster preparedness and educational attainment (in percentages; source: ref. 16). A greater propor- tion of those with a college degree were prepared at each measure. Overall, a greatest proportion of Americans reported becoming more vigilant and a smaller percentage reported duplicating documents. Differences in pro- portions found prepared between college graduates and those with a high school diploma or less were greatest for having an emergency plan (100 percent) and knowing where to get more information (78 percent).
between duplicating important documents and having a college degree was confirmed by regression analysis (b � 0.564), with greater than one and a half the odds ratio of observing the effect (Exp [B] � 1.758).
Vigilance Those with a college degree (67 percent) were 15
percentage points or 28 percent more likely than those with a high school diploma or less (52 percent) to have become more vigilant or aware of their surroundings. A regression analysis confirmed the statistically sig- nificant relationship between becoming more aware of surroundings and having a college degree (b � 0.625), with greater than one and a half the odds ratio of observing the effect (Exp [B] � 1.869).
DISCUSSION
Disaster preparedness has been found to differ markedly by the level of educational attainment. Those with a post-secondary degree were more likely to be prepared than High School graduates at each measure (Table 2). Regression analyses confirmed significant, positive correlations between earning a college degree and five dependent measures of disas- ter preparedness (Table 3). These findings support the observations from a 2009 Federal Emergency Management Agency and Citizen Corp study, which found that college graduates were overwhelmingly more prepared than those without a post-secondary degree on several measures.3 However, findings from this study using GSS data observed lower percent- ages of preparedness in Americans than the study using Citizen Corp questionnaires for the measures of stockpiling supplies, having an emergency plan, and knowing where to get more information.3 A finding in support of the premise of this study is that greatest differences in preparedness by educational attain- ment level were found for Emergency Plans (78 per- cent) and More Information (70 percent; Figure 1). These measures connect more closely to university emergency management and communication systems than other measures investigated in the study.
One limitation of the current study, in terms of understanding the relationship between education and disaster and emergency preparedness, is that
self-reported data were analyzed and as such may or may not actually match what people really are doing. Another limitation is the lack of multivariate analy- sis. The inclusion of third variables that influence both education and preparedness, such as income, age, gender, region, or ethnicity, may change associa- tions between educational attainment and disaster preparedness—possibly eliminating the apparent effect of education. A recommendation for further study is to include educational attainment as one pre- dictor of disaster preparedness in a probit model with several additional variables. Future studies with multivariate analyses may identify conditions of unexpectedly weak associations with preparedness, implicating areas where direct disaster preparedness education may be more crucial.
American disaster policy interests were expanded in the wake of the Kobe Earthquake in 1995, the Indian Ocean Tsunami of 2004, the Pakistan Earth- quake in 2005, Hurricane Katrina in the same year, and the 2010 Haiti Earthquake. Since disasters are difficult to predict, policies have focused on planning, preparation, and improving the resilience of commu- nities. This study revealed the low state of disaster preparedness in America (Figure 1) and the strong influence higher education has on preparedness (Table 2; Table 3). Colleges and universities may be underutilized resources for informing individuals and building cultures of disaster preparedness. A recom- mendation is made to invest in policies that strengthen linkages between institutions of higher education and national and international disaster agencies.
Lauren A. Menard, EdD, K12, Vermilion Parish School System,
Abbeville, Louisiana.
Robert O. Slater, PhD, Department of Educational Foundations and
Leadership, University of Louisiana at Lafayette, Lafayette, Louisiana.
Jim Flaitz, PhD, Department of Educational Foundations and
Leadership, University of Louisiana at Lafayette, Lafayette, Louisiana.
REFERENCES 1. Horne J: Survival: How a Culture of Preparedness Can Save You and Your Family from Disasters. New York: Atria Books, 2006.
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
51
2. Auf der Heide E: Disaster Response: Principles of Preparation and Coordination. St. Louis: The C.V. Mosby Company, 1989. 3. Federal Emergency Management Agency: Personal preparedness in America: Findings from the Citizen Corps National Survey August 2009. Summary Sheet (Revised December 2009). Available at http://www.citizencorps.gov/downloads/pdf/ready/2009_Citizen %20Corps_National%20Survey_Findings_SS.pdf. Accessed October 5, 2010. 4. Ready America: Prepare. Plan. Stay informed; June 28, 2010. Available at http://www.ready.gov/america/index.html. Accessed June 28, 2010. 5. American Red Cross: Preparedness fast facts. Available at http:// www.redcross.org/portal/site/en/menuitem.86f46a12f382290517a8f 210b80f78a0/?vgnextoid=fc56d7aada352210VgnVCM10000089f08 70aRCRD&vgnextfmt=default. Accessed June 20, 2010. 6. American Red Cross: Get a kit. Make a plan; 2009. Available at http://www.redcross.org/www-files/Documents/pdf/Preparedness/ checklists/Be_Red_Cross_Ready.pdf. Accessed June 20, 2010. 7. Staman M, Katsouros M, Hach R: The multi-dimensional nature of emergency communications management. EDUCAUSE Rev. 2009; 44(1): 49-63. 8. Tierney KJ, Lindell MK, Perry RW: Facing the Unexpected: Disaster Preparedness and Response in the United States. Washington, DC: John Henry Press, 2001. 9. Nigg JM: Communications under conditions of uncertainty: Understanding earthquake forecasting. J Commun. 1982; 32(1): 27-36. 10. Arnett JJ: Young people’s conceptions of the transition to adult- hood. Youth Soc. 1997; 29: 1-23. 11. Cowie, J, Popescu A, Underwood T: Impact of Hurricane Katrina on internet infrastructure; Renesys, 2005. Available at http://renesys. com/tech/presentations/pdf/Renesys-Katrina-Report-9sep2005.pdf. Accessed October 12, 2010.
12. Miller R: Hurricane Katrina: Communications and infrastruc- ture impacts. In Tussing B (eds.): Threats at Our Threshold: Homeland Defense and Homeland Security in the New Century. Eisenhower National Security Series. Carlisle Barracks, PA: United States Army War College, 2007: 191-203. 13. Raida B, Ramiah R: Academic Public Health Community responds to Hurricane Katrina: A showcase of systems and part- nership. Public Health Rep. 2005; 120(6): 688-691. 14. Louisiana State University: Information Technology Services: Emergency Text Messaging System; April 27, 2010. Available athttp://itsweb.lsu.edu/VCIT/etxt/item8491.html. Accessed June 21, 2010. 15. Neustadtl A, Johnson D, Kling J. SOCY201—Introductory sta- tistics for sociology. Available at http://www.bsos.umd.edu socy/alan/stats/socy201/handouts/SOCY201-01-Introduction- Positivism.pdf. Accessed October 9, 2010. 16. Smith TW, Marsden P, Hout M, et al. General social surveys, 1972- 2010 [machine-readable data file]. Available at http://sda.berkeley. edu/cgi-bin/hsda?harcsda+gss08.2008. Accessed October 9, 2010. 17. Roper Center: General Social Survey 1972-2008. Available at http://www.ropercenter.uconn.edu/data_access/data/datasets/general_ social_survey.html#overview. Accessed October 12, 2010. 18. SDA: Survey Documentation and Analysis; 2010. Available at http://sda.berkeley.edu/index.html. Accessed June 21, 2010. 19. Duffy D: What is logistic regression? StatGun Statistics Consulting; 2007. Available at http://www.statgun.com/tutorials/ logistic-regression.html. Accessed June 20, 2010. 20. Einhorn G, Edwards A: In Preparedness Now: An Emergency Survival Guide for Civilians and Their Families. Los Angeles, CA: Process Media, 2006. 21. Chaumont K: How to prepare for disaster: A Seattle Times special report. The Seattle Times. Available at http://seattletimes.nwsource. com/news/local/links/disaster/prepare.pdf. Accessed June 20, 2010.
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
52
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
53
ABSTRACT
A radiological dispersal device (or dirty bomb) is an affordable, feasible, and economically devastating option for terrorists. By using an input-output modeling technique, the authors present a general method to assess economic impacts resulting from the use of such a device that will aid researchers, government planners, officials, and key stakeholders. The authors extended previous efforts that focused only on direct effects, exploring the indirect and induced effects as well. In applying the method to the case of a mid-sized city, the authors quantified the area within the city with the largest impact, the central business district. More specifically, the detonation of a dirty bomb in this city’s central business district would cost approximately $1.4 billion and impact 860 firms in 270 distinct industries. In addition, approximately 18,000 people would be unemployed immediately following the attack, with an additional 113,000 people affected by the shift in the local economy as a result of indirect and induced effects.
Key words: cost estimation, radiological dispersal event, level of impact analysis, planning
INTRODUCTION
Grotto,1 who is with the Center for American Progress, has argued that among the unconventional weapons that terrorists could use in an attack within the United States, a “radiological weapon, or ‘dirty bomb,’ is the most likely.” Government officials have
reinforced the feasibility of this sentiment in a docu- ment distributed to the Congress, highlighting a radio- logical dispersal event (RDE) as one of 15 viable threats that the government must be prepared to con- front.2,* Moreover, incidents over the last several years have supported these predictions. In May 2003, the US police arrested an American, Jose Padilla, in Chicago’s O’Hare airport for his involvement with Al Qaeda in planning a radiological attack on the United States. In January 2003, British officials found documents in Herat, Afghanistan, indicating that Al Qaeda had suc- cessfully built a small radiological explosive device and that they possessed training manuals on how to employ it.3 The failed attempt, in April 2010, to deliver a con- ventional car bomb in New York’s Times Square high- lights these risks even further.4
An RDE may be the result of a radiological dis- persal device (RDD), commonly termed a “dirty bomb.” Generally, an RDD is a low-yield conventional bomb surrounded by radiological material such as cesium-137 or cobalt-60. On detonation, the blast of the conventional explosive is designed to spread radioactive material over a wide area where it can be
Radiological dispersal events within urban environments: A general method of measuring the economic impacts
Antoine N. Munfakh, MS David A. Smith, PhD Daniel T. Holt, PhD
Leonard J. Kloft, PhD Eric J. Unger, PhD
Jeremy M. Slagley, PhD
JEM
DOI:10.5055/jem.2011.0067
*The US Department of Homeland Security developed the National Planning Scenarios,2 a strategic planning document outlining 15 key threat scenarios. Scenario 11 considered an attack using a radiological dispersal device, estimating 180 fatalities, 270 injuries, and 20,000 instances of contamination, resulting in 10,000 people being evacuated to shelters with an additional 25,000 people being ordered to shelter in place. The best estimate analysts derived for the economic impact were simply “up to billions of dollars.”
inhaled or ingested by people, or otherwise absorbed into the environment. Terrorist groups have expressed an interest in using RDDs because they may be poten- tially devastating economically and psychologically. They are also quite feasible, as the radioactive materi- als included in RDDs can be stolen or acquired cheaply from the millions of radioactive sources used worldwide in industry, medical applications, and aca- demic research.5 The US Nuclear Regulatory Commission has, in fact, estimated that within the United States, radioactive material is lost, abandoned, or stolen every day of the year.6
Smith et al.7 have provided an integrated approach that can be used to guide stakeholders as they plan and prepare for any RDE, called a level of impact analysis. Synthesizing several approaches to general risk assessments (eg, Ecological Risk Assessment and Human Health Risk Assessment), Smith et al.’s app- roach is designed to help assess the impact of an RDE and future risks to ensure efficient recovery. Largely qualitative, the level of impact analysis focuses on the critical factors agreed on by the stakeholders, namely, an economic parameter (representing the economic disruption the event may have on the regional or sub- regional economy), an ecological parameter (represent- ing the degradation of or impact on a defined ecological receptor or services), a social impact parameter (repre- senting the impact the adverse event has on the qual- ity of life in the subregion), a human health risk parameter (representing the actual risk to human health as a result of insult from radioactive material), and a cost of remediation parameter (representing an estimate of remediation costs).
In this article, we further explicate one element of the level of impact analysis,7 the economic parameter. More specifically, we present a general method that can be used to assess estimate economic impacts resulting from an RDE, occurring in any location and affecting any industry. By fulfilling this objective, we make several theoretical and practical contributions. Theoretically, our work fills a gap in the literature as there is neither a universal approach for measuring the costs or economic impacts on businesses nor a common framework for estimating economic impacts of a radiological event triggered by a dirty bomb,
with this gap leading to inaccurate and unverifiable estimates.
Practically, a general model of assessing costs should improve RDE response efforts by providing government officials and key stakeholders an eco- nomic assessment tool that can be used to quantify the economic impacts, thereby facilitating the strategic decision-making process. For instance, local interac- tions with the Federal Emergency Management Agency (FEMA), the federal government’s most visible branch of emergency managers, would be improved as FEMA would be involved once the President declares a disaster in the affected regions. This declaration enables special funding to be allocated to defer the costs incurred by private sector individuals and organ- izations (ie, federal assistance to households, individu- als, and businesses) as well as public sector organiza- tions.† To obtain this funding, however, cost estimates must be conducted in the immediate aftermath of a disaster to determine the extent of damage and the costs incurred by public sector organizations’ response. Moreover, federal guidelines call for esti- mates that are accurate to 10 percent within 90 days after the declaration of disaster.8
While our manuscript offers a tool that focuses on estimating costs incurred by the private sector, we feel this method could also be used by public sector agen- cies like FEMA. Currently, FEMA estimates and sub- mits a budget request to have these funds available for a particular fiscal year in the preceding fiscal year as part of the congressional appropriations process. FEMA uses the 5-year annual average level of obliga- tions for past disasters, adjusted for inflation, as its estimate of the total cost of disasters anticipated to occur during the current fiscal year. To estimate when
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
54
†The President is granted this authority under the Stafford Act. Through this act, cities and states can receive grants to reimburse uninsured extraordinary costs of an emergency response (eg, police and fire department overtime, replace equipment that was damaged or expended in the response, and repair or rebuild affected facilities). In addition, individuals can be given unemployment payments, low-inter- est loans, and limited grants while businesses may qualify for low- interest loans and limited grant programs designed to recover unin- sured losses. Public and private costs are estimated and differentiated during the damage assessment for a Stafford Act declaration, and our article focuses on a technique to estimate the private sector costs—an issue discussed at length in the Discussion section.
these funds are expected to be distributed throughout the year as disasters occur, FEMA simply allows the 5- year annual average to decline at a constant rate (8 percent) each month during the fiscal year. “Using this approach, FEMA estimates that disasters costing about $500 million will occur in August and September 2000. However, these months represent the height of the hurricane season, and over the last 5 years, the average cost for disasters to FEMA has been twice this amount,”9 and as such, FEMA is regularly underesti- mating the cost of disaster events, forcing the agency to request additional funds from the Congress. These errors reverberate through the system where funds are shifted from other programs or debt is increased.
ECONOMIC IMPACT OF THE RDE THREAT
The Council on Foreign Relations10 classifies RDDs as weapons of mass destruction (WMD). Although in the same category as nuclear, biological, or chemical weapons, RDDs are not devices that gen- erate the same widespread destruction and fatalities that are generally linked to other WMD. Although RDDs do lead to destruction and fatalities, the WMD label is applied largely because RDDs are intended to disrupt the normal functioning of society through widespread panic. This is expected to arise from the psychological anxiety that RDDs may trigger based on people’s fear and general misunderstanding of radioactive materials. Hospitals, for instance, would likely be overrun with people complaining of and pos- sibly showing symptoms of radiation sickness, even if they were nowhere near an attack site or radioactive fallout. In Brazil, for example, Warwick11 reported that 249 people were exposed to a radioactive sub- stance, but once the incident became public, 135,000 requested screening for exposure and 5,000 people who were never exposed to the materials showed psy- chosomatic symptoms of nausea and skin rashes that mimicked symptoms of actual exposure. Warwick argued that false reporting, caused by the anxiety of potential exposure, created significant congestion in the healthcare system and delayed treatment to those who were actually affected.
“The economic impact of a radiological attack has the potential to be as devastating, if not more, than
the physical attack itself,” according to the Monterey Institute of International Studies Center for Non- proliferation Studies.12 Although (and quite fortu- nately) there have been no successful malicious incidents of radiological terrorism using dirty bombs, there have been several notable radiological accidents and terrorist attacks that provide insights into the financial and economic effects a radiological terrorist attack would have. Several specific incidents are sum- marized in Table 1, highlighting the costs that were associated with each of these incidents. The incidents range from nuclear accidents like the one at Three Mile Island (TMI), Pennsylvania, to the conventional terrorist attacks like the one of September 11, 2001 at the World Trade Centers in the United States.
Generally, these estimates have focused on the direct effects that represent the known or predicted change in the local economy that is attacked. The eco- nomic loss associated with the September 11, 2001 attack, for instance, represented a $30.5 billion loss, of which $21.8 billion was the cost to replace buildings, infrastructure, and tenant assets, and $8.7 billion was an estimate of the future earnings of those who died.13
The TMI accident, by contrast, had an immediate cost of $18 million, as 144,000 people were evacuated within a 15-mile radius of the island.16 Additionally, the effects on business during the week after the inci- dent were approximately $7.7 million for manufactur- ing firms and $74.2 million for nonmanufacturing firms.16,17
Each of these incidents has also suggested that there would be lingering effects associated with an RDD. The Chernobyl nuclear accident highlighted this point on a grand, national scale. Beyond the $235 billion estimate in costs for Belarus alone,18 the long- term restrictions on agricultural production crippled the market for foodstuffs and other products from the affected area, resulting in losses from 6 to 22 percent of Belarus’ gross domestic product.18 More inline with what might be seen with an RDD, the citizens of Goiania, Brazil, saw the sales of their cattle, cereals, and agricultural produce fall by 25 percent in the period after an accidental release of a radioactive material.14,15 In addition, the Gross City Product for Goiania decreased by 20 percent and did not recover
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
55
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
56
Table 1. Summary of incidents providing economic estimates of conventional and radiological dispersal events
Event Type Description Economic estimates Reference
September 11, 2001 World Trade Center Attack
Purposeful use of “conventional” (ie, non- nuclear) explosives by terrorists in a large commercial center
A group of hijackers flew fueled passenger jets into each of the World Trade Center buildings, leading to the collapse of each building.
• Infrastructure replacement costs of $21.8 billion
• Future earnings of fatalities $8.7 billion
• Gross City Product (GCP) loss: $27.3 billion (year immediately following attack)
Thompson13
Improper handling of abandoned radioactive medical equipment, Goiania, Brazil (1987)
Accidental release of cesium-137
Two persons entered an abandoned radiation therapy unit after the physician had relocated his practice, taking a piece of medical equipment composed of cesium-137. At home, they dismantled and ruptured the capsule holding the radioactive material. A total of 249 people were externally irradiated, 129 were internally irradiated, and four deaths were caused.
• Infrastructure clean up and replacement costs $27.2 million
• Industry sales from the region fell 25 percent after the incident.
• GCP loss: 20 percent decrease with no recovery after 5 years.
Warwick11; IAEA14; Sohier and Hardeman15
Release of radioactive material, Three Mile Island Nuclear Generating Station, Pennsylvania (1979)
Accidental release of radioactive noble gases (primarily xenon) and iodine-131
Failures in a non-nuclear secondary system, followed by a pilot-operated relief valve in the primary system that was stuck in an improper configuration led to the release of reactor coolant from a pressurized water reactor. No significant levels of radiation were detected outside of the facility.
• Evacuation costs (144,000 people in 15-mile radius): $18 million
• Manufacturing plant losses: $7.7 million
• Nonmanufacturing plant losses: $74.2 million
• Qualitative costs reported (not captured in monetary terms): Increases in (a) workdays lost, (b) hospital visits, (c) antianxiety medications, and (d) radiation sickness symptoms (although there was no exposure).
Flynn16; Walker17
Release of radioactive material after explosion at the Chernobyl Nuclear power plant (1986)
Accidental release of an estimated 40 million curies of iodine-131, three million curies of cesium-137, and 50 million curies of radioxenones and radiokryptons
Operators at the Chernobyl nuclear power plant were doing a scheduled low-power engineering test when a succession of human errors coupled with design flaws culminated in a series of explosions, destroying the reactor. Only 31 people died due to the accident directly, whereas 237 people suffered from severe exposure. A total of 330,000 people within a 30-kilometer radius were evacuated, and there have been enduring issues in the area.
• Total cost estimate: $235 billion (Belarus alone)
• GDP cost estimates: Range from 6 to 22 percent
• Qualitative costs reported (not captured in monetary terms): Lower wages; higher unemployment; and restricted agriculture production
IAEA18
(continued)
to pre-release levels for an additional 5 years. In sum- mary, these estimates suggest that focusing purely on the direct effects may underestimate the costs associ- ated with such an incident.
LeBrun21 took a key step in developing an approach to predict economic effects beyond the direct effects, capturing the indirect and induced effects as well. The indirect effects represent the business-to- business transactions required to satisfy the direct effect. The induced effect is derived from local spend- ing on goods and services by people working to satisfy the direct and indirect effects. He estimated the total effects that an RDD would have on revenues and employment in the retail center of a mid-sized city based on the relationship between revenue and a retail space’s square footage and the Bureau of Labor Statistics (BLS) employment data. He concluded that
the total impact of an RDD would be approximately $1.2 billion (in 2003 dollars), impacting more than 21,000 jobs. In addition, LeBrun21 suggested that planners should assess the economic impact of an RDE by examining the strategic placement of the device within a metropolitan area. More specifically, he identified three key economic centers within any city that would be attractive targets for an RDE: the business districts, the industrial centers, and the retail areas. Although large urban environments may have numerous districts fitting into each of these cat- egories, he recommended that research focused on the most central of these areas. For instance, the central business district typically contains banks, corporate offices, and service industries such as law firms and accounting agencies and is typically considered the heart of any metropolitan area.
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
57
Table 1. Summary of incidents providing economic estimates of conventional and radiological dispersal events (continued)
Event Type Description Economic estimates Reference
Hypothetical model of an RDD at ports of Los Angeles and Long Beach, California
Simulation of purposeful use of RDD by terrorists at major US ports
Center for Risk and Economic Analysis of Terrorism Events estimated the cost of an RDD being shipped to and detonated on arrival to the ports of Los Angeles and Long Beach.
• Costs of short-term closure (15 days): $300 million
• Costs of mid-term closure (120 period): $63 billion
• Costs of long-term closure (1 year): $252 billion.
Rosoff and von Winterfeldt19
Chechen militants’ use of RDDs (1995 and 1998)
Purposeful placement of radioactive material in Moscow’s Izmailovsky Park (1995) and the placement of a dirty bomb near a Russian railway line (1998)
• Under Commander Shamil Basayev, militants placed a small quantity of cesium-137, which was thought to be obtained from a nuclear waste storage facility in Moscow’s Izmailovsky Park. Although not dispersing the material, the placement of the material created a media storm as a television news crew was directed to the location.
• In a second incident, the pro- Russian Chechen Security Service found a dirty bomb consisting of a land mine combined with radioactive materials next to a railway line frequently used to transport Russian troops. Chechen militants were suspected to have placed the device.
• No economic estimates were available.
Burton20
GENERAL ECONOMIC MODEL USING INPUT-OUTPUT
MODELING TECHNIQUES
Building on LeBrun’s21 effort and extending the work of those who have examined only direct effects (known changes in the local economy where an incident occurred), we present a model to estimate the indirect effects (ie, costs associated with the business-to-business transactions that would be lost) and induced effects (ie, costs from local spending on goods and services by peo- ple working to satisfy the direct and indirect functions) as well. These can be captured using an input-output model. The input-output model is a detailed accounting system of interindustry activities within a local economy and is predicated on the economic theory that the output of one industry often serves the input to other indus- tries.22 Because of recent improvements in data collec- tion made by the Bureau of Economic Analysis, several governmental and private organizations have suggested that input-output modeling is the most accurate method for measuring the economic impacts of policy changes on a region.23 Moreover, input-output models have been applied to estimate the economic disruption of other events such as electric power outages,24 hypothetical earthquakes,25 and hurricanes.26
The Impact Analysis for Planning (IMPLAN)27
software is one package designed for input-output modeling used to compute the direct, indirect, and induced effects by developing a social accounting sys- tem to describe transactions that occur between pro- ducers, intermediate customers, and final consumers.28
It does this through a clear picture of an area’s busi- nesses and industries that are described by the researcher and planner. With this data, the IMPLAN input-output modeling program uses an empirically derived social accounting matrix that represents the flows of economic transactions between industries, cap- turing the indirect and induced effects that result as a “shock” (ie, policy change, natural disaster, or RDD) ripples through the local economy based on the inter- relationships among businesses and industries. In addition, IMPLAN derives a multiplier model mathe- matically, giving it predictive ability in economic impact analysis.28
Although the specifics of the software are beyond the scope of this article, the general steps that need to
be taken to apply this technique in examining an RDD are summarized in Table 2. These steps include a) identifying key commercial, industry, and retail centers within a city; b) determining the specific busi- nesses that will be influenced by overlaying the impact area on a map; and c) gathering economic and employment data for the area from the BLS. Finally, the data can be analyzed and the lost revenues and employment can be estimated, testing how different economies of scale influence the area as well as cap- turing the specific seasonal effects.
Consistent with the planning process laid out by Smith et al.,7 the first step in the method is locating the distinct sites within the metropolitan area that would be attractive targets. Smith et al.7 suggested that vulnerability assessments should aid in the iden- tification of the most attractive target areas from a terrorist’s perspective. With that said, planners can use a basic understanding of terrorists and their moti- vations to guide planning. Terrorist acts are typically prompted by psychological, political, religious, cul- tural, or economic motivations,32 and terrorists prefer that their operations be executed in highly visible, public areas that dramatically influence a region.33 As such, LeBrun21 has persuasively argued that the key targets for an RDE are an area’s central business dis- trict, its industrial center, and its retail center.
In the second step, stakeholders must determine what commerce would be affected in the target areas. The Department of Homeland Security’s National Planning Scenario2 offers considerable guidance as this is done. Specifically, it indicates that nearly all of the fallout from an RDD would likely be con- tained within a 1-mile diameter zone centered on the detonation site. With this, planners can simply overlay concentric circles onto an aerial photomap of the central business district, industrial center, and retail centers to provide a clear picture as to which businesses within a particular region would be directly affected with contamination. Partnering with the BLS, which compiles data by zip code, the specific businesses within an affected area can be identified and refined to a specific area (ie, a 1-mile diameter around a specific detonation site). These firms must be organized into industry-specific
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
58
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
59
Table 2. Economic modeling steps
Modeling step Issues to consider and actions taken
Identification of attractive target areas
Leaders should conduct or rely on formal vulnerability assessments to identify the most attractive target areas from a terrorist’s perspective. As a general guide, leaders should identify the following: • Key commercial centers to include the metropolitan areas central business district. • Key industrial centers that employ significant numbers of employees and have several
complementary industries collocated within a mile. • Key retail areas that have considerable service providers and have considerable traffic of
patrons.
Identification of the specific businesses within a particular target area
Leaders should rely on the Department of Homeland’s scenario that describes an RDD to guide the identification of businesses. Thus, leaders should consider the following: • 97 percent of fallout is expected to be within a 1-mile diameter of the detonation site. • Weather conditions are calm (ie, light winds of 3-8 mph) and there is no precipitation,
allowing an initial estimation to be circular around the detonation site. • All businesses within the 1-mile diameter will be closed for an extended duration. With this, leaders can (a) overlay a circle (or concentric circles to estimate areas of decreasing impact and compute various estimates) onto an aerial map to highlight impacted areas; (b) identify affected zip codes; (c) forward this information to the Bureau of Labor Statistics (BLS) to identify specific businesses; and (d) recode these businesses according to their North American Industrial Classification System (NAICS) codes (which is necessary for input-output modeling.
Collection of economic and employment data within a particular target area
Leaders should focus on revenues and employment as these numbers are the key measures of economic impact and can be easily obtained by partnering with the BLS. In addition, leaders should consider the following sources. • US Census Bureau 2007 Economic Census29
• County Business Patterns (2007)30
• American Fact Finder: Economic Patterns31
Scale the data to reflect a specific region in a metropolitan area and capture economies of scale
Leaders should test two distinct functions: a constant economy of scale function and a linear economy of scale function. The constant economy of scale function provides a simple baseline. Under the linear economy of scale function, employees in larger firms produce more revenue than their counterparts in smaller firms. The constant economy of scale baseline can be developed based on ratio of employees in each size category to total employees within a given industry. This allows the distribution of the annual revenue based on the given weights revealing approximate annual revenue based on categorized firm sizes for each industry. With this, a weight is developed based on the specific site to be tested. This scale used the ratio of employees in a given category at the site-specific level to the number of employees for the same industry and size category for the metropolitan area.*
Test the seasonal affects associated with an RDD for a particular target area
Leaders should consider the timing of the RDD. Monthly revenue data are published and can be used to compute a total effect by month. Then, seasonal effects can be identified by taking the difference between the cumulative seasonal effects from the cumulative nonseasonal impact.
*To compute this linear function and calculate revenues, two integrals are computed: Total revenue � ; Weight �
; n � number of employees in an industry; a � 1+ number of employees in ALL previous size categories;
b � number of employees in a size category + number in ALL previous size categories.
mx dx mx dx a
b n
( ) ( )/∫ ∫ 1
mx dx n
( ) 1 ∫
groups using the North American Industrial Classification System (NAICS).‡
With the affected businesses identified and grouped in the NAICS categories, the economic parameters necessary to calculate the economic impacts should be defined. For most cases, annual revenues and employment data would be recom- mended. These data can be collected from the BLS or a number of other sources, namely, the US Census Bureau 2007 Economic Census34; County Business Patterns (2007 data were published in 2009)29; and American Fact Finder: Economic Patterns.30 The BLS can further refine the data to the six-level NAICS identifier because data collected from online sources will be masked at such a high level of fidelity and would need to be unmasked (which can be done on special request without identifying individual firms).
Revenue data may only be available at the level of the metropolitan area rather than a more specific area (ie, a specific business district, industrial center, or retail center). Thus, these data would need to be scaled to estimate revenue generated within a more particu- lar area. This scaling can be conducted in several ways, but it is suggested that two distinct functions be tested: (a) a constant economy of scale function and (b) a linear economy of scale function (which is used for sensitivity analysis in the subsequent step). Briefly, economies of scale are the cost advantages that a busi- ness obtains as it expands (ie, increases its scale) by decreasing the average cost per unit produced. The most common advantages a firm may experience by increasing its scale are as follows: purchasing (ie, bulk-buying of materials through long-term con- tracts), managerial (ie, increasing the efficiency through the specialization of managers), financial (ie, obtaining lower interest charges when borrowing from banks and having access to a greater range of finan- cial instruments), and marketing (ie, spreading the cost of advertising over a greater range of output in
media markets). The constant economy of scale func- tion provides a baseline under the assumption that an employee in a given industry produces the same rev- enue as any other employee in that industry.
Although economies of scale vary from linear to exponential functions depending on the individual firm and industry,31 a linear economy of scale function can begin to capture the dynamic environment in which employees in larger firms tend to produce more revenue than their counterparts in smaller firms. By varying economies of scale between 1 and 100 percent, a range of the impacts can be determined, providing a key sensitivity analysis. From this analysis, ranges of the expected effect can be computed. This provides civic leaders using the current model with an estimate of the range of damage that would emerge.
Finally, the timing of the RDD is critical and should be considered as the economic impacts are assessed. A retail center in the United States, for instance, typically makes most of its revenue in October, November, and December. A detonation of an RDD during the fall months would likely increase the economic impact of the RDE by disrupting business during the peak, revenue producing months. To model seasonality, monthly industry revenue data can be used and monthly percentages can be computed for each industry in a particular area. To determine which month results in the largest economic impact, the sea- sonal effects must be isolated from the total effects by differentiating the cumulative seasonal effects from the cumulative nonseasonal impact. To demonstrate the model, we examined the effect of an RDD on a mid- sized (population ~500,000) city in the Midwest sur- rounded by crop land and located in a watershed, near the source of the city’s drinking water.
APPLICATION OF THE MODEL: THE CASE
OF A MIDWESTERN CITY
The city chosen to demonstrate the model repre- sents an appropriate application because it has several business districts, industrial centers, and retail centers. The particular business, industry, and retail centers examined represent the largest of their types in the entire metropolitan area, giving decision makers the worst-case scenario. The business district chosen has
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
60
‡This is important as IMPLAN analyzes impacts on individual indus- tries, not individual businesses. NAICS groupings are the standard used by federal statistical agencies in classifying business establishments for the purpose of collecting, analyzing, and publishing statistical data related to the economy. Moreover, IMPLAN further consolidates these industries into sectors, examining 509 different economic sectors.
approximately 15 percent of the metropolitan area’s business firms and accounts for nearly 12.5 percent of the metropolitan area’s revenue. When compared with the area’s three other major business centers, the busi- ness district chosen produces 50 percent more revenue on average. The industrial center chosen includes a large vehicle assembly plant but contains only 3 per- cent of the area’s industrial firms. Still, it accounts for 18.4 percent of the revenue from the metropolitan area’s industrial sector; also, it makes on average 67 percent more revenue than four other industrial areas within this particular metropolitan area. The retail cen- ter contains 8 percent of the metropolitan area’s retail firms, accounts for 17.84 percent of the total revenue in this sector with an average of nearly 30 percent more revenues than other area retail centers.
The incident considered was consistent with the Department of Homeland Security’s National Planning Scenario.2 As noted, this scenario suggests that 97 percent of the fallout of the radioactive material would fall within a 36-block or 1-mile (diameter) area; 90 percent of the radiation source would be aerosolized and carried by winds, with radioactive particles ranging in size from 1 to 150 �m. The remaining fallout would create debris and contami- nate surrounding structures. Accordingly, businesses within the 1-mile area would be closed for an extended duration while contamination would be remediated. Moreover, we assumed that there was no precipitation with light, variable winds of 5 to 13 km/h (3-8 mph), and the temperature is 18�C (65�F).§
The RDD was assumed to contain cesium (Cs-137; 2,300 curies), because this radioactive isotope is one of two (cobalt-60 being the other) elements most com- monly used within industrial and commercial radioactive sources. Although the most hazardous radioactive materials are found in nuclear power plants and sites where nuclear weapons are made, experts argue that these are extremely difficult (although not impossible) to obtain because security at these locations is high. Thus, the most likely radioac-
tive materials in RDDs would be cesium or cobalt that come from low-level waste generated through medical laboratories (eg, diagnostic procedures and cancer treatments) or welding shops and construction sites (eg, industrial radiography).19
As outlined in our process, the detonation site was centered to include as many firms in each area as possible. The scenario described was overlaid on a map such that specific businesses could be identified and coded in accordance with the NAICS. Then, the annual revenue and employment data were easily col- lected. For this example, revenue and employment data was obtained from the 2007 Economic Census; the BLS assisted in unmasking the data that had not been divulged previously to prevent individual firms from being identified. Once the data were unmasked, the revenue data were scaled for each industry to reflect the actual composition of industries in the cen- tral business district, the industrial area, and the retail center. The direct, indirect, and induced effects on revenues and employment for each of these areas over a 1-year period, while holding economies of scale constant, are summarized in Table 3. Given these parameters, it was no surprise to see that the direct, indirect, and induced estimates vary based on the location where the RDD was detonated within the city, namely, the central business district, the indus- trial area, or the retail center. Still, the proportions of costs attributed to direct, indirect, and induced effects remained consistent independent of the particular site (ie, business, industry, or retail) with approxi- mately 60 percent coming from direct costs, 15 per- cent from indirect costs, and 25 percent from induced costs.
In this particular city, the central business district was, without any doubt, the area that would be most affected economically by an RDD. This was not unex- pected as the central business district is at the heart of many metropolitan areas, containing the largest number of firms that generate significant revenues. It might be reasonable to expect that a disruption in the central business district of most metropolitan areas would yield the greatest impact.35 In this particular city, the total annual economic impact would be expected to be approximately $1.4 billion (with a
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
61
§To make estimates more robust, more specific weather conditions can be estimated as these weather conditions change the shape and size of the contamination area. With our assumption of good weather, the dis- tribution of contamination would be circular.
range of �$101.3 million), affecting approximately 18,000 people directly and another 113,000 from indi- rect and induced effects. In addition, the central busi- ness district in this city contained numerous public buildings such as courthouses and the city hall. Moreover, it had high vehicular and pedestrian traffic and contained the central node to the public trans- portation system that allowed low-income individuals who did not have vehicles of their own to access the city suburbs, having significant induced affects.
There were considerable economic impacts if an RDD were detonated in the industry and retail cen- ters as well. The total annual economic impact in the industrial center would be approximately $1.1 billion (where direct costs were $696 million, indirect costs were $168 million, and induced costs were $236 million), affecting approximately 20,000 people directly and another 99,000 from indirect and induced effects. A detonation in the retail center would cost approxi- mately $891 million (where direct costs were $522 mil- lion, indirect costs were $138 million, and induced costs were $231 million). In terms of jobs, about 12,000 individuals would be affected directly and nearly another 75,000 would be affected through indirect and induced effects.
Sensitivity analysis By accounting for how much more revenue large
firms typically generate when compared with smaller firms (ie, varying economies of scale), it was possible to develop a range of effects and ensure the model was capturing variation as it should and give policy makers a range of costs. As such, we varied the economies of scale linearly from 1 to 100 percent. Our analysis indi- cated that the most variation in the costs were within the central business district. The direct effects of an RDD would seem to vary the most with a minimum cost estimate of $812.8 million (when the economies of scale were 1 percent) to $883.9 million (when the economies of scale were 100 percent). Indirect costs ranged from $244.9 to $260.9 million while the induced costs varied from $315.2 to $345.6 million. Moreover, we observed that as a larger firm’s employees produced more revenues (ie, economies of scale approached 100 percent more revenue per employee for a larger firm), the effects were magnified. This was expected because the central business district had numerous firms of varying size that were collocated and vying for the same business (ie, several accounting firms competing for the same customers). As the economies of scale are varied, the range of costs would vary accordingly.
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
62
Table 3. Direct, indirect, induced, and total effects on revenues and employment for the case of a mid-sized city
Impact on revenue (LB based on 1 percent EoS, UB based on 100 percent EoS)
Impact on employment
Direct effect Indirect effect Induced effect Total effect Direct effect
Indirect effect
Induced effect
Total effect
Central Business District (affecting 860 businesses)
$840.1 ($812.8, $883.9)
$250.8 ($244.9, $260.9)
$327.2 ($315.2, $345.6)
$1.42 billion ($1.37 billion, $1.49 billion)
18,137 46,020 66,837 130,994
Industrial Center (affecting 580 businesses)
$696.5 ($683.8, $710.4)
$168.4 ($166.5, $170.2)
$236.4 ($232.0, $242.0)
$1.1 billion ($1.08 billion, $1.12 billion)
20,248 43,737 55,167 119,152
Retail Center (affecting 575 businesses)
$522.1 ($498.2, $538.8)
$137.8 ($131.1, $142.4)
$231.1 ($221.1, $238.2)
$891.0 ($850.4, $919.4)
12,156 28,143 46,562 86,861
Note: All values in millions unless noted. Abbreviations: LB, lower bound; EoS, economy of scale varied linearly; UB, upper bound.
In contrast, the least variance was observed in the industrial center as most of the businesses collo- cated in this area were complementary (eg, a brake manufacturing plant produced a product in support of or in conjunction with a vehicle assembly plant) and the firms tended to be of similar size. Moreover, the smaller firms that were located in this area were gen- erally not competitors and were instead services dependent on the main industry (eg, restaurants, bar- ber shops, or gas stations). The direct effects of an RDD would seem to vary the most with a minimum cost estimate of $683.8 million (when the economies of scale were 1 percent) to $710.4 million (when the economies of scale were 100 percent). Indirect costs ranged from $166.5 to $170.2 million, whereas the induced costs varied from $232.0 to $242.0 million.
Although the variation in the retail center would not be expected to be as great as that observed in the central business district, it would be expected to be greater than the industrial center. The retail center was made up of an interesting combination of compet- ing (eg, large department stores) and complementary businesses (eg, food and spa services). In addition, the size of the firms competing with one another was largely the same (eg, one anchor store of a mall does not typically vary dramatically in size when com- pared with another). Still, the direct effects would seem to vary the most with a minimum cost estimate of $498.2 million (when the economies of scale were 1 percent) to $538.8 million (when the economies of scale were 100 percent). Indirect costs ranged from $131.1 to $142.2 million, whereas the induced costs varied from $221.1 to $238.2 million.
Seasonality analysis Finally, we analyzed the seasonal effects of an
RDD in this region. Perhaps naively, we originally assumed that an attack in October, as this would influence the retail businesses the most dramatically, would be the most costly for all areas. Yet, the analy- sis indicated that an attack in the summer months would result in the largest economic impact for the central business district and the industrial center. Specifically, an RDD detonated in the central busi- ness district in June would result in an additional
$6.7 million in economic losses above the cumulative (nonseasonal) average. Conversely, an attack in December would net $9.4 million below the cumula- tive average. Similarly, the summer months would be most costly to this city’s industrial center with a July attack leading to a cost of $14 million above the non- seasonal average, whereas a December attack would result in an impact $12 million below average.
The retail center did reveal the findings we expected. An RDD detonation in October at the start of the peak period of consumer purchases, which typ- ically occur from October to December, would most dramatically disrupt this area. Our data supported this, showing an October attack would have $51 mil- lion effect above the average. An attack in January, immediately after the peak season, would have effects $70 million below the nonseasonal average.
DISCUSSION
Smith et al.7 offered a streamlined, adaptive plan- ning approach that should be used by key stakeholders as they plan and prepare for an RDE. One critical ele- ment that they suggest to be considered through the planning and deliberations are the economic costs. Kelly36 also argued that the reliance on “no cost limit” emergency appropriations after an event can con- tribute to dysfunctional recovery strategies and ineffi- cient responses. Accordingly, we present a repeatable method that can be used in any metropolitan area to estimate the impact of an RDE. This process entails (a) the identification of key target areas, which are likely the commercial, industry, and retail centers within a city; (b) the identification of specific businesses that will be influenced by overlaying the impact area on a map using the Department of Homeland Security’s guidance regarding an RDD; (c) the collection of eco- nomic and employment data from the BLS; (d) the analysis of the data with an input-output modeling software package like IMPLAN (another program is RIMS II from the Bureau of Economic Analysis; ref. 37); and (e) the exploration of the model’s sensitivity (ie, examining different economies of scale) and the seasonal effects.
This general approach offers several advantages. By applying this method, planners are able to estimate
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
63
the indirect and induced effects as well as the direct effects, which would be an improvement over other esti- mates as these costs account for a substantial economic impact. An input-output modeling technique captures direct, indirect, and induced effects for any given indus- try in any given location by accounting for the relation- ships among industries in the specified geographical area. In addition, our method can more effectively account for the dynamic and complex nature of the event despite the fact that it is based on historical eco- nomic data. This is because it can be updated relatively easily to reflect the changing industry composition within a particular region and account for changing economic conditions as the BLS continually publishes updated data regarding a region. Finally, leaders can get a “worst-case scenario” by initially identifying and estimating the impacts to the largest (by overall rev- enue generated) commercial, industrial, and retail dis- tricts within a particular metropolitan area. To further account for uncertainty and improve the estimate for planners, a range of predicted costs can be estimated by taking the economies of scale into account and examin- ing the seasonal effects on the region.
As we applied this method to evaluate the costs of a scenario suggested by the Department of Homeland Security2 on one mid-sized Midwestern city, we found the effects of an RDD to be devastating. The most substantial impact would occur if an RDD were detonated within this city’s central business district. Such an attack would result in a total effect of $1.4 billion over a 1-year period and an attack during the summer months of June, July, and August would produce the greatest seasonal costs. Additional factors would also magnify the effect of an attack on a city’s central business district. This area typ- ically includes transportation and decision-making (like city hall) nodes hampering coordination among fire, police, and medical responders, disrupting citywide traf- fic flow, and restricting the movements of residents as well as goods and services. Still, our analysis of a partic- ular city indicated that attacks on an industrial and retail center should not be discounted, as they would have a 1-year total effect of $1.1 billion and $900 million, respectively.
We also found that the direct, indirect, and induced costs represented approximately the same proportion of
the total costs regardless of the detonation site (ie, cen- tral business district, industrial center, or retail center). That is, the direct, indirect, and induced costs repre- sented approximately 60, 15, and 25 percent of the total costs, respectively. This is significant for several rea- sons. First, this improves previous estimates that have focused only on the direct effects and may have over- looked key factors in the total costs associated with an RDD. Second, this information should help planners to more accurately quantify a well-understood phenom- ena, namely, there are time-lagging effects to any disas- ter. In the case of an RDD, our data suggest that nearly 40 percent of the economic effects will be realized months after the RDD. When these are not considered, the effects are broadly underestimated that has consid- erable policy ramifications at all levels of government. FEMA, for instance, has routinely underestimated the cost of disaster events by nearly half (which is consis- tent with our results), forcing the agency to request additional funds from the Congress.10 As we have noted, additional requests reverberate through the govern- ment’s system where funds are shifted from other pro- grams or debt is increased. Thus, improved cost estimates of events can improve the efficiency and effectiveness of the entire system.
Although not the focus of our effort, we also noted a relationship between the estimated economic impact of an RDE and the number of firms impacted by a detonation in a particular site. It was not sur- prising that as the number of firms increased, the cost associated with the attack increased. In our case, 860 firms were affected directly, indirectly, and induc- tively by an attack on the central business district. The total cost of such an attack was estimated at $1.4 billion. In contrast, an attack on this city’s industrial center was estimated to be $1.1 billion while affecting 580 firms. Although we do not suggest that this rela- tionship could be used in lieu of an application of our entire method, it can be used in the early planning stages to facilitate early decision making in response to the threat. For researchers, this relationship between the number of firms within an area and the total effects in a particular detonation site can be used to validate the estimates generated from the method presented.
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
64
Despite all of the advantages, our method is not without limitations. The 1-mile radius for evacuation and the associated costs may be conservative as this radius does not reflect the plume of radioactive mate- rial (which shifts with the winds). Still, the economic disruption occurs with evacuations that are not typi- cally driven by the predicted plume and instead based on a 360( potential hazard zone, effectively eliminat- ing the wind direction considerations. Musolino and Harper,38 in fact, discouraged the consideration of wind direction “especially in an urban setting where the wind field can be very complex.” Although Musolino and Harper38 suggested an initial 500-m radius, the 1-mile diameter still appears plausible as the psychological reactions to radioactivity are con- sidered and these are coupled with the conservative nature of policy makers. Zeigler and Johnson39 exam- ined evacuation behavior in response to the TMI nuclear generating station. During non-nuclear emer- gencies, they concluded that individuals and families seem to evacuate based on direct sensory evidence of danger or explicit, convincing messages of impending danger. In contrast, individuals respond quite differ- ently to nuclear accidents. Given that pregnant women and children aged below 5 years within 5 miles of TMI were encouraged to evacuate, approxi- mately 500 pregnant women and 3,000 preschool chil- dren were expected to have left. In actuality, approxi- mately 144,000 people within a 15-mile radius evacuated. This has also been substantiated in smaller, less potentially devastating incidents. As noted, 135,000 people in Brazil requested screening for exposure when only 249 people were actually exposed to radiation and 5,000 people who were never exposed to the materials showed psychosomatic symptoms of nausea that mimicked symptoms of actual exposure.11 In summary, significant economic disrup- tions would likely occur and more nuanced models could be tested with subsequent research.
Moreover, this input-output modeling is unable to account for costs resulting from recovery, cleanup, or remediation efforts, instead focusing on the private sector losses in revenues and employment. Thus, plan- ners should incorporate the costs that may be incurred through the recovery process that include police and
fire department overtime, equipment that was dam- aged or expended in the response, and repair (or replacement) of government facilities (all of which may qualify for federal aid under the Stafford Act). Remediation costs associated with an RDD would likely include (a) the treatment and decontamination of victims, (b) evacuation and relocation of people from the affected area, (c) decontamination of the interior and exterior (or demolition) of affected buildings, (d) and safe discard of the radioactive debris. The costs of reconstruction and clean up after the September 11, 2001, World Trade Center attack might be at one end of the cost continuum. According to the Executive Director of the Port Authority of New York and New Jersey, these costs were approximately $16 billion with 1.5 million tons of debris removed.16 Of course, this estimate would vary widely based on geographic region, but will be another cost in addition to the loss of employment and revenues explicated by our method.
Still, these recovery and remediation costs can be considered as a desired end state discussed among planners—a key part of Smith et al.’s7 level of impact planning process. Unfortunately, no nationally, or internationally, acceptable levels of residual contami- nation40,41 have been established. Generally, however, US Federal Guidelines, issued by the Environmental Protection Agency in 2009, have recommended reduc- ing the cancer risk from remaining radiation to extremely low levels. Although abandonment or dem- olition might be an option, this may not be feasible in an urban area where thousands could lose their homes, jobs, and schools. Accordingly, these additional costs would be expected to be substantially valued at “hundreds of millions of dollars per site.”2
Another shortcoming was our linear representa- tion of economies of scale. We recognized that actual economies of scale are generally not linear; rather, they tend to follow a geometric or exponential growth curve. A linear approximation, however, is sufficient in that it better reflects the revenue distribution between small firms and large firms proportionally within an economy and is an improvement over esti- mates that hold economies of scale constant. In fact, this approximation confirmed differences between a method that accounted for economies of scale and one
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
65
that did not. In addition, we found that the accuracy lost by applying a linear function to the economies of scale did not appear substantial enough to warrant the more complex modeling that would be required for this method to be practical. Still, we recommend future research to be done to explore differing models for economies of scale.
Along with the limitations presenting opportuni- ties for researchers, we would recommend several other research avenues as well. First, we recommend repeated iterations using our method in various met- ropolitan areas to further validate our work and, more importantly perhaps, to provide new insights into the effects and interactions between distinct intracity regions. Clearly, different sites of similar type would have varying revenues and factors associ- ated with that particular location. Yet, there may be similarities that can help the planning process across regions. Although we focused on the commercial eco- nomic impacts, we would also recommend future researchers to quantify other impacts. Residential considerations are particularly interesting because residential areas do present an attractive target to terrorists given their fear-striking motive. An attack in a residential area would not only a direct effect on residential property values but also have significant indirect and induced costs triggered by the exodus of people from the impacted area. Moreover, costs would also be linked to other psychological factors that arise with RDDs. We also did not examine the costs associ- ated with disruptions in traffic flows; these costs when considered would undoubtedly increase the indirect and induced costs associated with an RDD.
Even with these limitations, we have illustrated that the economic fallout resulting from an RDD has the potential to be quite devastating. If recovery and resiliency to an RDD are to be maximized, effective and efficient planning is critical. Accordingly, we rec- ommend that officials and planners at all levels of gov- ernment to assume a proactive posture as this threat is considered. By conducting an economic impact analysis, key stakeholders can attain a better under- standing of the possible magnitudes and ranges of possible economic impacts resulting from an RDD. From these results, they can better determine where
to allocate limited resources to prevent or even deter an RDD attack. The method we outline serves as a tool that can guide officials in any location to facilitate their planning and decision making. We applied the method to three distinct regions of a mid-sized urban economy but it can be used by any city throughout the United States to determine the effects (direct, indi- rect, and induced) that an RDE would have on the economy. As an initial estimate, we recommend lead- ers to compute the economic impacts based on the relationship between the effect of the impact and the density of firms surrounding the RDD site, a relation- ship discovered as part of our analysis. From all of this, preventive measures can be in place, resources can be efficiently allocated, and recovery and resiliency can be maximized before the RDD occurs.
Antoine N. Munfakh, MS, Student Pilot, 47 Operation Support
Squadron, Laughlin Air Force Base, Texas.
David A. Smith, PhD, Chief of Radiation Health, Office of the Air Force
Surgeon General, Washington, District of Columbia.
Leonard J. Kloft, PhD, Assistant Dean, College of Business
Administration, University Detroit Mercy, Detroit, Michigan.
Daniel T. Holt, PhD, Department of Management and Information
Systems, Mississippi State University, Mississippi State, Mississippi.
Eric J. Unger, PhD, Department of Systems and Engineering
Management, Air Force Institute of Technology, Wright Patterson Air
Force Base, Ohio.
Jeremy M. Slagley, PhD, Technical Services Branch, US Air Force School
of Aerospace Medicine, Kettering, Ohio.
REFERENCES 1. Grotto A: Defusing the Threat of Radiological Weapons: Integrting Prevention and Detection and Response. Washington, DC: Center for American Progress, 2005. 2. US Department of Homeland Security: National Disaster Planning Scenarios. Washington, DC: US Department of Homeland Security, 2006. 3. Gardner F: Al-Qaeda “was making a dirty bomb”. BBC News World Edition, January 31, 2003. 4. Baker A, Rashbaum WK: Police find car bomb in Times Square. New York Times, May 1, 2010. 5. Frost RM: Nuclear Terrorism After 9/11. New York: Routledge, 2005. 6. Ferguson CD, Kazi T, Perera J: Commercial Radioactive Sources: Surveying the Security Risks. Monteray, CA: Center for Non- proliferation Studies, Monterey Institute of International Studies, 2003. 7. Smith DA, Holt DT, Fentiman A: A conceptual model for deter- mining the level of impact from a radiological dispersal event. J Emerg Manage. 2010; 8: 25-36.
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
66
8. United States General Accountability Office (GAO): Disaster cost estimates: FEMA can improve its learning from past experiences and management of disaster-related resources. Report to Congressional Committee. Washington, DC: US GAO, 2008. 9. United States General Accountability Office (GAO): Disaster relief fund: FEMA’s estimates of funding requirements can be improved. Washington, DC: US GAO, 2000. 10. Council on Foreign Relations: Backgrounder: Dirty bombs. New York: Council on Foreign Relations; October 19, 2006. Available at http://www.cfr.org/publication/9548/. Accessed May 21, 2010. 11. Warwick M: Psychological effects of weapons of mass destruc- tion. The Beacon: National Domestic Preparedness Office Newsletter. 2001; 3: 1-4. 12. Monterey Institute of International Studies Center for Nonproliferation Studies: Radiologial Terrorism. Nuclear Threat Initiative. Monterey, CA: Monterey Institute of International Studies, 2004. 13. Thompson WC Jr: One Year Later: The Fiscal Impact of 9/11 on New York City. New York: Comptroller of the City of New York. Available at http://comptroller.nyc.gov/bureaus/bud/reports/impact- 9-11-year-later.pdf. Accessed July 18, 2011. 14. International Atomic Energy Agency (IAEA): The Radiological Accident in Goiania. Vienna, Austria: IAEA, 1988. 15. Sohier A, Hardeman F: Radiological dispersion devices: Are we prepared? J Environ Radioactivity. 2006; 85: 171-181. 16. Flynn CB: Three Mile Island Telephone Survey: Preliminary Report on Procedures and Findings. Tempe, AZ: Mountain West Research, Inc, 1979. 17. Walker SJ: Three Mile Island: A Nuclear Crisis in Historical Perspective. Berkeley, CA: University of California Press, 2004. 18. International Atomic Energy Agency (IAEA): Chernobyl’s Legacy: Health, Environmental, and Socio-Economic Impacts and Recommendations to the Governments of Belarus, the Russian Federation and Ukraine. The Chernobyl Forum 2003-2005. Vienna, Austria: Division of Public Information, IAEA, 2006. 19. Rosoff H, von Winterfeldt D: A risk and economic analysis of dirty bomb attacks on the ports of Los Angeles and Long Beach. Risk Anal. 2007; 27: 533-546. 20. Burton F: Dirty bombs: Weapons of mass disruption. Secure Community Network; October 4, 2006. Available at http://www. scnus.org/page.aspx?id=101461. Accessed September 30, 2010. 21. LeBrun MT: The Economic Impact of a Radiological Dispersal Event (RDE). Wright Patterson Air Force Base, OH: Air Force Institute of Technology, 2009. 22. Leontief WW: Input-Output Economics. 2nd ed. New York: Oxford University Press, 1986. 23. Cheng S, Stough RR, Kocornik-Mina A: Estimating the eco- nomic consequences of terrorist disruptions in the national capital region: An application of input-output analysis. J Homeland Secur Emerg Manage. 2006; 3: Article 12. 24. Rose A, Oladosu G, Liao S-Y: Business interuption impacts of a terrorist attack on the electric power system of Los Angeles:
Customer resilience to a total blackout. Risk Anal. 1997; 27: 513-531. 25. Okuyama Y, Hewings GJ, Kim TJ, et al.: Economic impact of an earthquake in the New Madrid siesmic zone: A multiregional analy- sis. In Proceedings of the 5th US Conference on Lifeline Earthquake Engineering. Seattle, WA: U.S. Geological Society, 1999. 26. Lamb RP: An exposure based analysis of property and casualty insurer stock values around Hurricane Andrew. J Risk Insur. 1995; 62: 111-123. 27. Minnesota IMPLAN Group: IMPLAN economic impact modeling solutions. Available at www.IMPLAN.com. Accessed May 21, 2010. 28. Natural Resources Conservation Service: IMPLAN model. Department of Agriculture. Available at http://www.economics.nrcs. usda.gov/technical/implan/implanmodel.html. Accessed May 21, 2010. 29. US Census Bureau: County Business Patterns. Available at http://www.census.gov/econ/cbp/index.html. Accessed May 21, 2010. 30. US Census Bureau: American Fact Finder. Available at http:// factfinder.census.gov/home/saff/main.html?_lang=en. Accessed May 21, 2010. 31. Clark J: Estimation of economies of scale in banking using a gen- eralized functional form. J Money Credit Banking. 1984; 16: 53-68. 32. Club de Madrid: Addressing the Causes of Terrorism: The Club de Madrid Series on Democracy and Terrorism. The International Summet on Democracy, Terrorism, and Security. I. Madrid, Spain: Club de Madrid, 2005. 33. Center for Non-Proliferation Studies: Center for non-prolifera- tion studies. M. I. Studies, Producer, Radiological Terrorism Tutorial; Chapters 2 and 4: Available at http://www.nti.org/h_learn more/radtutorial/index.html. Accessed May 21, 2010. 34. US Census Bureau: 2007 Economic Census. Available at http://www.census.gov/econ/census07/. Accessed May 21, 2010. 35. Blair JP, Carroll MC: Local Economic Development: Analysis, Practices, and Globalization. 2nd ed. Thousand Oaks, CA: Sage Publications, 2009. 36. Kelly C: A framework for improving operational effectiveness and cost efficiency in emergency planning and response. Disaster Prev Manage. 1995; 4: 25-31. 37. U.S. Department of Commerce, Bureau of Economic Analysis: Regional Input-Output Modeling System (RIMS II): Estimation, Evaluation, and Application of a Disaggregated Regional Impact Model. Washington, DC: Government Printing Office, 1981. 38. Musolino SV, Harper FT: Emergency response guidance for the first 48 hours after the outdoor detonation of an explosive radiolog- ical dispersal device. Health Phys. 2006, 90: 377-385. 39. Zeigler DJ, Johnson JH Jr: Evacuation behavior in response to nuclear power plant accidents. Prof Geographer. 1984; 36(2): 207-215. 40. Steinhausler F: Chernobyl and Goiänia lessons for responding to radiological terrorism. Health Phys. 2005; 89: 566-574. 41. Conklin CW: Proposed framework for cleanup and site restora- tion following a terrorist incident involving radioactive material. Health Phys. 2005; 89: 575-588.
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
67
REPRINT ORDER FORM
Note: While one photocopy is permissible, multiple reproduction of materials published in Journal�of
Emergency�Management is prohibited without written permission of the publisher. For educational classroom
use, quantity 200 or less, contact Copyright Clearance Center (222 Rosewood Dr., Danvers, MA 01923,
978-750-8400) directly. For all other uses, please order reprints using this form.
Author____________________________Issue____________________________________________
Title of article ______________________________________________________________________
Page Nos. _________________________Quantity_________________________________________
Minimum order, 100 — minimum price based on 4 pages. For orders over 500, please write or call for quotation. Postage and/or freight included. For commercial reprints and articles over 20 pages, call for rates. 4-color reprints additional $1250 4-color charge. All reprint prices in effect for 1-year from publication date. Past 1-year, call for rates. Delivery time 4-6 weeks. All reprints run on Docutech. For reprints printed Offset on coated stock, call for custom quote.
Pages 1-4 5-8 9-12 13-16 17-20
100 Copies 105.00 215.00 310.00 415.00 545.00
200 Copies 200.00 400.00 600.00 800.00 1000.00
300 Copies 285.00 570.00 855.00 1140.00 1425.00
400 Copies 360.00 720.00 1080.00 1440.00 1800.00
500 Copies 425.00 850.00 1275.00 1700.00 2125.00
Billing Info:
q All orders must be prepaid by check, credit card or purchase order
q Check enclosed (remit in US dollars.) Make checks payable to: Journal�of�Emergency�Management.
q Charge my q Visa q MasterCard q AMEX Account #
__ __ __ __ __ __ __ __ __ __ __ __ __ __ __ __
Expiration date___________Security code _________
Signature____________________________________
Cardholder address____________________________
Tel ( ) _______________Fax ( )_____________
E-mail ______________________________________
Billing order/purchase number___________________
Journal of Emergency Management 470 Boston Post Road, Weston, MA 02493 • 781-899-2702 • Fax: 781-899-4900
www.emergencymanagementjournal.com 12236 4/14/10 Rev. d
Ordering Info:
___________________________________________ Ordered by ___________________________________________ Institution ___________________________________________ Address ___________________________________________ City State Zip ___________________________________________ E-mail
Ship To:
___________________________________________ Name ___________________________________________ Institution ___________________________________________ Address ___________________________________________ City State Zip ___________________________________________ E-mail
12236_12236.qxd 8/10/2011 10:26 AM Page 1
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
69
ABSTRACT
Disaster response to incidents such as the 2010 Deepwater Horizon oil spill requires rapid access to comprehensive, consumable, and actionable data. Providing effective situation awareness requires data collection methodologies capable of account for the inherent spatial and temporal characteristics of the incident. However, data collection is often encumbered by complex technologies that require specialized knowledge for use. Consequently, these requirements can impede the effectiveness of disaster response. To compensate for these challenges, an easy-to-use and spatially accurate incident reporting system was designed for responders tasked with identifying the location and extent of oil infiltration within marshes and bays of south Louisiana following the disaster. This workflow was assembled around a Global Positioning System (GPS)-enabled digital camera capable of receiving positioning corrections from GPS reference networks. Images depicting oiled beaches, habitats, and wildlife were automatically georefer- enced and displayed using common geographic data visualization applications. Whether uploaded to data servers or printed, the imagery was shared across a wide audience, fostering collaboration among all response agencies.
Key words: situational awareness, global naviga- tion satellite systems, geographic information systems, geovisualization, geotagging
INTRODUCTION
A fundamental objective of all disaster response activities is the formation of effective situation aware- ness (SA): a synoptic understanding of phenomena
that occur during complex and rapidly changing con- ditions.1 SA relies on the responders’ ability to rapidly collect and to effectively integrate comprehensive and reliable information into their decision-making process. To accomplish these objectives, actionable data must be captured and used relative to the spa- tiotemporal contexts in which it occurred.2,3 The two key resources for deriving actionable data include aer- ial photography and global navigation satellite sys- tems (GNSS). Aerial photography acquired immedi- ately after an event provides a “big-picture” overview typically desired during an evolving scenario.4 GNSS technologies, which include Global Positioning Systems (GPS), provide the positional accuracy that makes it possible to locate phenomena and to direct resources where they are most effective. Geographic information systems (GIS) provide the collaborative and analytical platform on which actionable data are compiled, ana- lyzed, and used.2,5-7
As an emergency unfolds, however, the time needed to acquire imagery, collect samples, or simply assess the scale of a disaster can further endanger life, property, and the environment. Because the techniques for collecting and synthesizing actionable data often require advanced logistical and technical capabilities, these important but time-consuming resources are eas- ily excluded from the initial phase of a response.8
Conversely, these resources become more valuable as response activities transition into recovery and restoration efforts.2,7,9 To overcome this discrepancy, an incident reporting system must be able to capture and synthesize pertinent information in a manner relative to the operational requirements of the response. This article presents the practical application of a simple
A spatially accurate incident reporting system during the 2010 Gulf of Mexico oil spill disaster
Joshua D. Kent, PhD Roy K. Dokka, PhD
JEM
DOI:10.5055/jem.2011.0068
incident reporting workflow that combined an easy-to- use GNSS-enabled digital camera with intuitive geovi- sualization software. This workflow was implemented by emergency responders tasked with identifying the location, extent, and impact of oil infiltration along coastal Louisiana during the 2010 Deepwater Horizon oil spill disaster in the Gulf of Mexico.
THE 2010 GULF OF MEXICO OIL SPILL DISASTER
Between April 20 and 22, 2010, the offshore oil drilling rig, Deepwater Horizon, caught fire, exploded, and subsequently sank in the Gulf of Mexico. In addi- tion to the 11 fatalities and 17 injuries, the Deepwater Horizon disaster has caused significant environmental
and economic hardship across the coastal region.10
The spill originated from the rig’s damaged wellhead positioned approximately 1,500 m (�1 mile) below the Gulf surface and located about 240 km (�150 miles) southeast of New Orleans, Louisiana, in the Macondo Prospect oil and gas field of the Mississippi Canyon Block 252 (Figure 1). Despite efforts to stem the flow, oil continued to emanate from the sea floor for approx- imately 3 months. The disaster impacted much of the northern Gulf of Mexico, affecting various portions of coastal Louisiana, Mississippi, Alabama, Florida, and Texas.11 Although quantification of the flow rate remains uncertain, an assessment released in August 2010 estimated that approximately 4.9 million barrels of
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
70
Figure 1. Map depicting the extent of the Deepwater Horizon oil spill into the Gulf of Mexico. The map illustrates closed fisheries as of late June 2010.11
oil (~206 million US gallons or 779 million liters) were released from the well prior to its closure.12 By the time the well was capped on July 15, 2010, the Deepwater Horizon disaster had become the largest offshore oil spill in the history of the petroleum industry, surpassing the 1998 Exxon Valdez and the 1979 Ixtoc I spills.13 In an effort to minimize the threat to human health and the environment, the state and federal officials closed numerous commercial and recreational fisheries and deployed floating protection booms at various bays and inlets. In Louisiana, the state and local officials initiated their own disaster response activities after oil was observed entering Barataria Bay, the Bretton Sound estuary, and nearby beaches.
By mid-May 2010, municipal and parish first responders from the barrier island of Grand Isle, Louisiana, received sporadic reports of tar balls and oil washing ashore.14 These reports coincided with accounts by local fishermen of visible oil sheens on the water surface. Given the size of the area at risk and irregularity of reported incidents, officials found it difficult to produce a meaningful strategy for deal- ing with fouled beaches and marshes, the threat to population centers and wetland habitats, and the eco- nomic consequences on the energy production facili- ties at Port Fourchon.* For these reasons, the local and regional incident commanders coordinated with the state and federal agencies to organize a compre- hensive response strategy. With additional support provided by the Unified Command (composed of fed- eral and petroleum industry stakeholders), local responders began developing an incident reporting and management system to catalog and to respond to the threat. The information obtained from these sys- tems would not be limited to assessments of fouled beaches or bays. The data would also be used to devise pre-emptive strategies for minimizing further damage. To meet the needs of all potential response agencies, the system had to follow a well-conceived workflow that met the particular functional, perform- ance, and design criteria identified by the local responders.
SYSTEM REQUIREMENTS
Actionable data are predicated on the ability to detect, collect, synthesize, and analyze information from multiple, disparate sources. Furthermore, the nature and effectiveness of these data during a response are both event and location specific.2 Accordingly, each response agency required a customizable incident reporting system that could comprehensively capture the location, nature, and extent of oil entering their region. However, collecting actionable data at an appro- priate synoptic scale was particularly challenging for this event. This was partially attributed to the seem- ingly random nature in which the oil propagated into the region. The location and extent of oil infiltration had been significantly manipulated by weather patterns and the Gulf’s prevailing steering currents. The response, containment, and cleanup efforts were further compli- cated by the rough seas caused by tropical cyclones active within the Gulf (eg, Hurricane Alex in late June). Accordingly, emergency managers emphasized the immediacy in which incidents had to be reported and processed. To accomplish this, the incident reporting sys- tem had to be agile: quickly and easily deployable at a moment’s notice and capable of operating in remote and often hard-to-access areas. Furthermore, the urgency of the event and varying procurement policies demanded that the system be constructed using readily available technologies. Following a general assessment of existing operations, the Center for GeoInformatics (C4G) at the Louisiana State University (LSU) was asked to devise a scalable incident reporting system based on the various technological and operational requirements specified by the incident commanders.
Technological requirements The technical requirements defined for this inci-
dent reporting workflow were primarily applied to resources used during the data acquisition stage. These requirements have been subdivided into three cate- gories: functional, performance, and design specifica- tions (Table 1). Functional requirements specify the criteria for accomplishing a task. Accordingly, the acquisition stage required a data capture device capa- ble of recording both the nature and location of the oil infiltration. Noting the adage that a picture is worth a
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
71
*Port Fourchon is the hub for approximately 90% of the domestic oil and gas production facilities operating in the Gulf of Mexico.15
thousand words, the device had to be able to photo- graph the particular characteristics of each incident the responder identified. To achieve location awareness, the device had to be able to rapidly capture and to store both the geographic coordinates and cardinal direction of the recorded phenomena. The second technical requirement established performance criteria for the data acquisition hardware. Specifically, the captured device had to achieve photographic and geographic resolutions at scales suitable for establishing a con- text for the infiltration. Incident commanders also requested that the device be capable of linking opera- tor-provided field notes with the photographs. Additionally, the hardware had to be sufficiently reli- able and fault tolerant, eg, long battery life, support multiple storage capabilities, and provide automatic and manual settings. Finally, the design require- ments established build specifications for the compo- nents used during reconnaissance. In addition to a portable form factor, the essential requisites for these technologies included ruggedized exterior for opera- tion in harsh environmental conditions (eg, water resistant), multiple communication protocols for data transfer and file synchronization, and extensible technologies that support advanced hardware upgrades (eg, use an external GNSS antenna).
Operational requirements The operational specifications for this system
define how captured data are used to produce SA. Like those defined for the technical specifications, the operational criteria were organized according to func- tional, performance, and design requirements (Table 1). As noted earlier, GIS software fulfills many of the functional requirements for visualizing and synthe- sizing heterogeneous information into actionable data. However, GIS platforms are well known for their technical complexity and steep learning curve. Because response teams operate in rapidly evolving situations, they require simple and effective tools with intuitive user interfaces. Accordingly, these func- tional requirements specified the utility of the sys- tem. First, the GIS software had to extract, trans- form, and load spatial and nonspatial information quickly and efficiently. Because visualization is a crit- ical component for emergency operations, the applica- tion required high-performance computing and graphic rendering capabilities. These criteria segued into specific performance requirements. For example, the software needed to be easy to use and require lit- tle to no training. Additionally, the system had to pro- vide a well-defined user interface that minimized steps required to complete a task. It also had to meet
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
72
Table 1. Technological and operational requirements
Technological Operational
Functional • Image acquisition • Capture geographic reference
• Synthesize multiple datasets • High-performance graphic rendering • Heterogeneous data support
Performance • Image resolution • Spatial accuracy and precision
• Intuitive user interface • Responsive interface • Match user expectations
Design
• Ruggedized casing • Communications • Power efficiency • Scalable hardware
• Software interoperability • Platform agnostic • Collaborative
Functional requirements specify criteria for accomplishing a task and criteria used to judge the operation of the system. Performance requirements establish parameters for efficiency. Design requirements define specifications needed for the system’s use.
end-user expectations without complex configura- tions or risk of failure. Finally, the system’s design requirements needed to emphasize interoperability and collaboration. Examples included the ability to operate with nontraditional communication technolo- gies such as mobile “smart” phones and netbook plat- forms. Similarly, output from this system had to be easily exchanged among all response professionals. Thus, the system had to support group visualization, map sharing, and information sharing.
IMPLEMENTATION
Based on the technological and operational crite- ria defined earlier, a simple incident reporting work- flow was devised for local responders operating during the Gulf oil spill (Figure 2). As a manually imple- mented system, the three-staged workflow was designed to be intuitive, flexible, and agile. It is based on an extensible hardware and application framework that can be modified according to the particular needs of the response agency.
Acquisition The principle resource for capturing the nature,
location, and extent of the oil infiltration was the Ricoh™ 500se GPS-enabled digital camera. The 500se
was selected because of its small and lightweight form factor, point-and-shoot capabilities, and its water-, dust-, and shock-resistant case. Moreover, the camera can capture eight megapixel resolution images, has an adjustable focal length, includes Wi-Fi and Bluetooth communication protocols, and can be configured with a GPS module attached to the camera body. The cam- era uses industry-standard memory cards for a stor- age capacity of up to 2 GB of data. Alternatively, the camera can rely on its built-in 26 MB internal mem- ory whenever redundancy is needed. Geographic coor- dinates are automatically stored within the photo- graph’s exchangeable image file format (EXIF) header, a metadata format that can be used to instantly geo- reference the photograph onto a map. In addition to the location, the GPS module can be configured to record the cardinal direction of the photograph. Furthermore, the camera supports a memo function that allows the operator to store valuable contextual information about a captured image. Finally, the cam- era operates for an average of 3 hours using the sup- plied rechargeable battery, which can be substituted with two standard-sized batteries.
Another important feature of the camera is its extensible technology. For rapid deployment into the field, the 40-channel, Wide Area Augmentation System (WAAS)-enabled GPS module can fix onto satellites in 5 minutes and achieve an average hori- zontal positional accuracy of 3-5 m (10-16 feet). For higher accuracy, an external GNSS receiver (eg, Trimble® R8 dual frequency antenna with differen- tial GPS) can be tethered to the camera via Bluetooth wireless communications. With this configuration, the external receiver is capable of delivering submeter positioning, which is beneficial when site revisits are necessary. When centimeter precision and accuracy are required, an external data collector capable of receiving real-time kinematic (RTK) corrections can be synchronized with the camera. To accomplish this, a survey-grade data collector was preconfigured to combine the signal from the external GNSS receiver and the corrections issued by the LSU GULFNet†
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
73
Figure 2. Diagram of the proposed incident report- ing workflow.
†GULFNet is part of the nationwide Continuously Operating Reference Station network managed by the National Geodetic Survey (NGS).
real-time network of Continuously Operating Reference Stations. Tests performed using this config- uration achieved horizontal positional accuracy of 10 cm (4 in) or less. Although each level of positional accuracy required additional hardware and technical skills, these configurations were optimized for speed and simplicity. Figure 3 illustrates the hardware resources selected for this incident reporting work- flow. Preconfigured kits were available for loan to any of the participating response entities.
Processing The first step of the postprocessing stage of the
workflow involved synchronizing the photographs stored on the camera with the computer systems located at the incident command center. The principle method for transferring the files was accomplished by physically removing the memory card from the camera and insert- ing it into a networked computer. Alternatively, the cam- era could be configured to support a wireless workflow for transferring files from the camera via Bluetooth or local area network (eg, IEEE 802.11x standard). Images stored on the network ensured that the information was preserved and secured in a location accessible to all members of the operation.
In accordance with the operational requirements defined earlier, the Picasa™ image-processing applica- tion was proposed for postacquisition processing. Picasa™ is a freely downloadable application designed to perform basic adjustments to digital photographs using an intuitive and responsive user interface that requires little to no training. More fundamentally, the software recognizes the embedded geographic coordi- nates stored within a photograph’s EXIF header, mak- ing it possible to export the files to various geographic information platforms. Naturally, the incident com- mand system was not restricted to any particular image- processing application. Alternative image-editing soft- ware exist, some for free and some for a fee, that meet the operational criteria. The only technical requirement for these applications is an ability to read and process the geotagged EXIF header.
Utilization By design, the choice of the geographic visualization
and analysis software was contingent on the immediate needs and capabilities of the responders. For incident commanders requiring simple visualization capabili- ties, images could be exported to Google™ Earth (GE). As a freely downloadable software package, GE pro- vides the necessary tools for users to geographically explore, combine, and visualize incident information via a responsive and intuitive application. Because it is available for the personal computer, Mac, and mobile devices, GE met the design requirements that speci- fied platform interoperability and collaboration. Incident commanders were not restricted to GE. Geotagged images could also be displayed using desk- top (eg, ArcGIS™ Explorer, Global Mapper™, or NASA World Wind™) or web-based mapping platforms (eg, Google™ Maps, Bing™ Maps, or Yahoo!™ Maps). Whenever the decision-making process required enhanced geographic inquiry (eg, spatial queries and overlays of multiple data sources) or sophisticated analysis (eg, data creation, modeling, spatial statistics, and simulations), the geotagged images could be imported into any professional-level GIS software pack- age. Although not applicable during this event, com- manders with limited or no internet access required
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
74
Figure 3. Incident reporting toolkit includes the (a) GPS-enabled camera, (b) external GNSS antenna, (c) preconfigured data collector, (d) ruggedized laptop, (e) cellular modem and router, and (f) travel case. Collaboration accomplished by distributing the inci- dent data via Google Earth on (g) thin-client mobile device and (h) smart phone.
stand-alone desktop GIS products to meet their map- ping and visualization needs.
PRACTICAL APPLICATION
The following paragraphs detail how this incident reporting workflow was implemented by emergency responders in Grand Isle, Port Fourchon, and the Barataria-Terrebonne National Estuary (BTNE) located along the Gulf Coast of southeastern Louisiana. Details regarding the tangible results and challenges experienced by these responders are also presented.
Grand Isle, Louisiana Emergency responders from Grand Isle, LA,
quickly recognized the value of the incident reporting workflow following a demonstration of the system by LSU C4G personnel. As a result, the Grand Isle incident command regularly made use of the GPS camera while carrying out aerial surveys of the coast (T. Gautreau, personal communication, June 29, 2010). The lightweight and easy-to-use camera made it possible for responders to quickly and conveniently develop SA within their jurisdiction. Twice a day, offi- cials used helicopters to fly along the chain of barrier islands to photograph oil as it spoiled beaches, infil- trated bays, and became trapped within marshes (Figure 4). After each flight, images were immediately distributed among staff at the incident command
center for visualization and assessment. Photographs were often distributed as printouts with the date and coordinates stamped on the image. When uploaded to the computer network, the photos were packaged, shared, and displayed using GE (Figure 5). Overall, the system enhanced their ability to direct clean-up crews to spoiled beaches and to maintain SA on the
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
75
Figure 4. Photographs like these taken by responders from Grand Isle, LA, were processed and geotagged for use by incident commanders.
Figure 5. The Google™ Earth callout depicts the location of an oiled beach. The Grand Isle, LA, inci- dent command used this tool to display geotagged images captured from helicopter surveys of barrier islands along Barataria Bay. Custom icons were added to differentiate the severity of oil infiltration and contamination.
effectiveness of the numerous oil protection booms. Despite the obvious collaborative and operational advantages of the proposed workflow, the geovisual- ization software proved to be underutilized. This lim- itation was primarily attributed to the volume of incoming data captured by the numerous responders jointly operating from the Grand Isle, LA, incident command system. Ultimately, the shared printouts provided the quickest and the most effective approach for their operations.
Greater Lafourche Port Commission Incident commanders from the Greater Lafourche
Port Commission (GLPC) at Port Fourchon regularly made use of GPS cameras to augment their existing command and control framework (A. Danos, personal communication, July 7, 2010). With the camera in hand, port personnel were dispatched and directed to take photographs of all oil-related contamination. On returning to the operations center, the images were immediately uploaded to their network and transferred to decision makers for assessment. In addition to the photographs, response personnel were encouraged to include descriptive commentary of the individual inci- dents as part of their reporting protocols. Port officials modified the incident reporting system by configuring the camera to display the date and geographic coordi- nates onto the photographs. Furthermore, the images were automatically georeferenced using the third-party application, Wind Image™, which was already in use by the Port’s information technology section. A data man- agement solution was implemented to administer the volume of data collected during the event and to increase the speed in which images were processed.
The utilization stage of the workflow was also modified. Processed images were uploaded into the Commission’s “GLPC-C4” incident command system (Command-Control-Communication-Collaboration; Figure 6). The system was derived from the Knowledge, Display, and Aggregation System used by the US Department of Defense. The Port uses the sys- tem to establish a common operational picture for acquiring and promoting SA and maritime domain awareness. This customized GE application allowed GLPC-C4 users to combine data assets from a variety
of sources, including radio dispatch, geographic data services, security sensors, and closed circuit television cameras. Uploaded geotagged images made it possi- ble for officials to devise appropriate incident response by examining the oil’s impact in context to critical infra- structure and surrounding environment (Figure 7). Although the authorities never needed the enhanced positioning capabilities of an external GNSS antenna, the GLPC were able to keep the port operat- ing at expected efficiencies by sustaining constant vigilance and deploying effective response strategies on the infiltrating oil.
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
76
Figure 6. Command and control software (GLPC-C4) used by the Greater Lafourche Port Commission.
Figure 7. Oil protection booms were often photo- graphed and georeferenced to maintain SA on miti- gation efforts.
BTNE Program News of this simple workflow quickly spread
among other local incident commanders in the region. Responders from the BTNE Program (BTNEP) adopted elements of the system for their own operations (M. Landry, personal communication, September 2, 2010). With support from various partners, including the US Fish and Wildlife Service (USFWS), the BTNEP agents were able to coordinate sea, land, and air patrols to maintain SA over the numerous wild bird nesting grounds (ie, rookeries) in the estuary (Figure 8). Figure 9 illustrates how the camera was used to document and geographically reference wildlife res- cued by USFWS agents. In all, five cameras were used by the BTNEP and its partners to monitor oil protec- tion booms, impact to wildlife, and damage to the shore. Data rapidly streamed into the incident com- mand system, which challenged their ability to man- age the data and to leverage the geovisualization com- ponent of the workflow. Like their Jefferson Parish counterparts, the BTNEP responders found that collaboration was best achieved using printouts stamped with dates and locations. And while their approach did not exactly follow the prescribed work- flow, the ease in which the BTNEP responders were able to exploit the system’s capabilities further demonstrates the intuitive nature and effectiveness of this simple system.
DISCUSSION AND CONCLUSION
The incident reporting system detailed in this text was conceived with the intent to provide a simple yet comprehensive solution for identifying, locating, and reporting on the occurrence and impact of oil infiltrat- ing Louisiana’s bays and wetlands. To that end, this three-staged workflow was designed to meet the immediate needs and to enhance the existing capabil- ities of local emergency management personnel engaged in response and recovery activities following the Deepwater Horizon oil spill. The individual tech- nologies and applications used in this system repre- sent the best commercially available (ie, off the shelf) resources accessible by incident commanders. The Ricoh™ GPS-enabled camera satisfied most of the technical requirements defined for the data acquisi- tion stage. As a digital still camera, the unit offered responders with a portable, easy-to-use, durable, and highly effective means of capturing actionable infor- mation about the incident. Because it supports numer- ous communication protocols, the camera could be con- nected to external GNSS receivers and antennas, thus extending the positional accuracy of the geotagged imagery according to the needs of the response: deliv- ering a default horizontal precision of 3-5 m (10-16 feet), an enhanced resolution of submeter, and an advanced positioning of (10 cm �4 in). The software recommended for the data processing stage was the
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
77
Figure 9. A Laughing Gull, Larus atricilla, waterfowl rescued in Bay Ronquille by the US Fish and Wildlife Service agents in July 2010.
Figure 8. Island populated by nesting water fowl in Bay Ronquille, located in the Barataria-Terrebonne National Estuary.
Picasa™ digital photo editing package. This applica- tion was attractive because it offered a free and intu- itive solution for image postprocessing and data man- agement. More importantly, it allowed users to easily export the geotagged images into formats compatible with multiple GIS and geovisualization software plat- forms. Combining multiple solutions within a single, easy-to-use application made it possible to streamline the processing workflow. For the utilization phase, GE was chosen as the primary geovisualization tool for collaboration and decision making. It provided a fast, platform neutral, and easy-to-use application for com- bining multiple, disparate data sources within a geo- graphic framework. Although GE cannot replace tra- ditional GIS in terms of data integration, geoprocessing, or spatial analytical capabilities, it clearly demon- strates how geovisualization tools are rapidly becom- ing mainstream spatial data platforms. Furthermore, because GE is almost entirely platform agnostic, it can be deployed across traditional and nontraditional computing technologies (eg, workstations, laptops, net- books, tablets, and mobile smart phones). This diver- sity ensures collaboration across all sectors of the emergency response.
What makes this simple incident reporting system novel is its extensibility. Each phase of the workflow (eg, data acquisition, processing, and utilization) incor- porated technologies and applications that delivered three levels of performance: basic, enhanced, and advanced (Figure 3). This design ensured that the inci- dent commanders could take advantage of a one-sys- tem solution. For the responders in Grand Isle and the BTNEP, only the “basic” data capture settings were used. Response managers from each command center were able to construct sufficient geospatial intelligence using the default GPS readings from the camera (ie, 3- 5 m horizontal accuracy). During the processing and utilization phases, incident commanders found that the geotagged photos yielded the most collaboration when the images were stamped with the date, time, and location. For officials at Port Fourchon, geotagged images were incorporated within their existing com- mand and control technology, GLPC-C4. Because the Port authorities implemented a data management
solution, they were able to more quickly and efficiently organize the vast quantity of imagery entering their system. This approach allowed the Port’s incident com- manders to extend their SA by establishing a spatial index on which multiple data resources (both spatial and nonspatial) could be associated. The capabilities of the GLPC-C4 system were not lost to the officials from the BTNEP. With the wellhead capped and the threat waning, BTNEP managers have started to plan their own geospatial incident reporting system (M. Landry, personal communication, September 2, 2010). Along with a robust data management solution, such devel- opments ensure that the BTNEP will be able to sustain a long-term framework for monitoring the wellbeing of the estuary and its diverse wildlife.
From a broader perspective, the workflow pre- sented here demonstrates how an elementary incident reporting system that can quickly and easily capture, manage, and share data is indispensable for emergency operations. This approach works because geospatial intelligence makes it possible for emergency managers to develop customized strategies for establishing SA and deploying response activities. Despite the broad appeal of this system, the partial implementations of the workflow demonstrate that geospatial intelligence is most effective when a response agency has the capac- ity to exploit it. Even though each of the incident com- mands featured in this text struggled with the volume of data entering their system, they were able to devise some measure of SA using the GPS camera. However, the incident commanders from the Port Fourchon facil- ity were best able to leverage the proposed workflow because they had already established a system capable of managing and using the data. If the capabilities and robustness of the Port Fourchon system were repli- cated, a more capable and coordinated response frame- work could be established within the region.
Although the response agencies discussed in this text have thus far only leveraged the basic to interme- diate capabilities of this workflow, the long-term needs of the recovery may require more advanced resources. When such a scenario becomes necessary, responders can transition their existing data capturing capabili- ties to the intermediate and/or advanced levels without
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
78
having to learn a fundamentally new system or modi- fying their existing processes. In this way, incident commanders will be able to capture increasingly higher positional accuracy via external GNSS antenna or real-time networks, expand their situational aware- ness using advanced GIS functionality, and enhance their decision-making process to devise the best strate- gies for monitoring the consequences of the oil’s impact on the local environment, community, and economy.
ACKNOWLEDGMENTS The authors thank the following contributors to this research: Ms
April Danos of the Greater Lafourche Port Commission; Mr Timothy S. Gautreau, Jr, of the Jefferson Parish Department of Emergency Management; Mr Wayne Keller, Executive Director of the Grand Isle Port Commission; Mr Mel Landry of the Barataria-Terrebonne National Estuary Program; and Mr Tim Osborn of the National Oceanic and Atmospheric Administration (NOAA). Select examples of geotagged images captured during the Deepwater Horizon oil spill response are available from the Louisiana State University Center for GeoInformatics Web site at http://goo.gl/XUEMP. Finally, some of the figures in this manuscript were presented at the 2010 Trimble Dimensions Conference in Las Vegas, NV (November 8-10, 2010).
Joshua D. Kent, PhD, GIS Manager, Center for GeoInformatics,
Louisiana State University, Baton Rouge, Louisiana.
Roy K. Dokka, PhD, Executive Director, Center for GeoInformatics,
Louisiana State University, Baton Rouge, Louisiana.
REFERENCES 1. Endsley MR: Toward a theory of situation awareness in dynamic systems. Hum Factors. 1995; 37(1): 32-64. 2. Cutter S: GI Science, disasters, and emergency management. Trans GIS. 2003; 7(4): 439-445. 3. Fuhrmann S, MacEachren A, Cai G: Geoinformation technologies to support collaborative emergency management. In Chen H, Brandt L, Gregg V, Traunmüller R, Dawes S, Hovy E, Macintosh A, Larson CA (eds.): Digital Government. New York, NY: Springer, 2008: 395-420. 4. Allenbach B, Andreoli R, Battiston S, et al.: Rapid EO disaster mapping service: Added value, feedback and perspectives after
4 years of charter actions. In IEEE Proceedings of International Geoscience and Remote Sensing Symposium. July 2005; Vol. 6: 4373-4378. 5. Alexander D: Information technology in real-time for monitoring and managing natural disasters. Prog Phys Geogr. 1991; 15(3): 238- 260. 6. Montoya L: Geo-data acquisition through mobile GIS and digital video: An urban disaster management perspective. Environ Model Software. 2003; 18(10): 869-876. 7. Resch B, Schmidt D, Blaschke T: Enabling geographic situational awareness in emergency management. Paper presentation at the Proceedings of the 2nd Geospatial Integration for Public Safety Conference, April 15-17, 2007, New Orleans, LA. 8. Zerger A, Smith D: Impediments to using GIS for real-time dis- aster decision support. Comput Environ Urban Syst. 2003; 27(2): 123-141. 9. Johnson R: GIS Technology for Disasters and Emergency Management. Redlands, CA: Environmental Systems Research Institute, Inc., 2000. 10. Trevors JT, Saier MH: The legacy of oil spills. Water Air Soil Pollut. 2010; 211(1): 1-3. 11. NOAA: BP oil spill: NOAA modifies commercial and recre- ational fishing closure in the oil-affected portions of the Gulf of Mexico. National Marine Fisheries Service. St. Petersburg, FL: National Oceanic and Atmospheric Administration. Available at http://sero.nmfs.noaa.gov/bulletins/pdfs/2010/FB10-057_BP_ Oil_Spill_Closure_062310.pdf. Accessed January 13, 2011. 12. Unified Command for the Deepwater BP Oil Spill: U.S. scien- tific teams refine estimates of oil flow from BP’s well prior to cap- ping; 2010. Available at http://app.restorethegulf.gov/release/ 2010/08/02/us-scientific-teams-refine-estimates-oil-flow-bps-well- prior-capping. Accessed January 13, 2011. 13. Wikipedia: Deepwater Horizon; 2010. Wikipedia, The Free Encyclopedia. Available at http://en.wikipedia.org/w/index. php?title�Deepwater_Horizon&oldid�368394104. Accessed June 16, 2010. 14. Jefferson Parish. 2010. Grand Isle Beach Closed. Press Release; May 23, 2010. Available at http://www.jeffparish.net/downloads/ 6972/7020-Grand%20Isle%20Beach%20Closed.pdf. Accessed September 21, 2010. 15. Loren C. Scott & Associates: The economic impacts of Port Fourchon on the National and Houma MSA economies; 2008. Port Fourchon Economic Impact Study. Available at http://www. portfourchon.com/site100-01/1001757/docs/port_fourchon_economic_ impact_study.pdf. Accessed September 21, 2010.
Journal of Emergency Management Vol. 9, No. 4, July/August 2011
79
The Most Pressing Issues in Our Industry Published bi-monthly, every issue of the Journal of Emergency Management is peer-reviewed and packed with invaluable information and insight. Topics include:
Emergency planning and response
Disaster recovery and business continuity planning
Emergency preparedness and response legislation
Risk management
Emergency management today, tomorrow and in the future
Severe weather, � ood and hurricane studies
Emergency communications
Continuity of operations and infrastructure protection
Preparation and evacuation for the disabled
Cross-training in emergency management
And much more, including a special focus on EM training and higher education
The Most Respected Names in Emergency Management � e Journal of Emergency Management is edited, written and peer reviewed by a nationally recognized team of the country’s foremost, hands-on EM experts. � ey include top professionals from the public and private sectors who o� er real world experience and practical solutions, and leading academics who provide perspective and analysis on the latest research and studies. Together, they bring you the most thorough, relevant and useful source of information on emergency management.
The Most Important Thing You Can Do for Yourself and Your EM Team Make sure you and your team stay one step ahead of disaster. Subscribe to the Journal of Emergency Management by calling 1-800-743-7206, visit www. emergencymanagementjournal.com enclosed card. Subscribe now, and be prepared for anything!
JOURNAL OF EMERGENCY MANAGEMENT
Preparing You for Whatever Disaster Comes Your Way
www.emergencymanagementjournal.com
4 Ways to Subscribe
WEB www.emergencymanagementjournal.com
PHONE 800-743-7206 x108 (Toll Free) 781-899-2702 x108 (Outside USA)
Mail 470 Boston Post Road, Weston, MA 02493
Fax 781-899-4900 (24 hours/day)
1:11:44 PM
JEM-9-4-jemsubad 8/10/2011 11:01 AM Page 1
Dr. Geoffrey Simmons, MD, CERT Trainer, applies this most uncommon of senses to the serious subject of disaster preparedness, giving an in- valuable primer in an area where proactive may be the ideal, but reactive is often the reality...sometimes with tragic consequences.
With the chance of you being involved in a disaster during your lifetime one in four, this guide belongs in your home along with your well-equipped first aid kit.
Dr. Simmons designed Com- mon Sense and Disaster Pre- paredness to be succinct, comprehensive, durable and sized (4”x9”) to fit right in your back pocket!
This guide will show you how most life-saving preparatory steps are easy, logical and inex- pensive.
The guide is organized in sev- eral sections, before a disaster, during a disaster, after a disas- ter and includes a special sec- tion for medical emergencies. This last section was written to make it easy for the non-med- ical person to deal with most life-threatening injuries during a disaster.
The guide includes a compre- hensive table of contents and a detailed index that allows the user to quickly find critical in- formation.
Order your copy today! It makes a great gift for friends and relatives!
Perfect for outreach to your at-risk citizen populations!
����������������������������������������������
������������������������������������������������������������
�� � ��������������������������������������������������������
��� ��� ����������������������������������������������������
� ��� �������� ������������������������������������������������
�� � ��������������������������������������������������������
� � �������������������� � ����� �� ����������������������������
����� �� ������������������������������������������������������
� � � � � � � � � � � �� �� ��� ���������� � � ����������������
�
� ����� ������������� � ��� ���������� !�� �� �"##$%&'$%(#)�*+#",���*� ����� �!� �%"+$"--$&-##� ��!�� � ����� �!� . / !! ��0�������������� ���1�����������,�&%#�2 � ��1 � �� ��,�3�� �,�4��#(&-'����5����� ��$�����5� !
���������� ����
���� �������� ��� ����!���"#���������������������
�������$ ���������������������������������������������
�% $�&� ����������������������������������������������
������������� ����� ������������������������������������
���������������� ����������������������������������������
! ��������������������������������������������������� �������� ���� �����������'�� ������(�����
������ ���� ���� �� �� �������
)*�(������ ����������� ����� �� ��+
Common Sense and Disaster Preparedness: A Quick Guide for Staying Safe Before, During and
After Any Disaster By Geoffrey Simmons, MD, CERT Trainer
“Chance favors the prepared mind.” - Louis Pasteur ,-.� �'��
� ��������������� ���/���������� �� ���� �������� ����� �0 0��� ��/ �� � 6'-5-7 8��� � ��1������. ��� � 6'"5-7�����1 ���� � 6'%5-7�����1 ������� 6'75-7�����1 ������ � 6'&5-7�����1 2�� �����3����� ��'4�"� �����3�4�����5-6$78
2�92�92�92�9�������7:;7:;7:;7:;.7<.7<.7<.7<,;<,;<,;<,;<68.68.68.68.;;;;
� �� ��� �� �� ������
� � � �� �
�������� ���������������
��������� !"���
#��"���$%
- 01_07_2011_001
- 01_07_2011_002
- 01_07_2011_003
- 01_07_2011_004
- 01_07_2011_005
- 01_07_2011_006
- 01_07_2011_007
- 01_07_2011_008
- 01_07_2011_009
- 01_07_2011_010
- 01_07_2011_011
- 01_07_2011_012
- 01_07_2011_013
- 01_07_2011_014
- 01_07_2011_015
- 01_07_2011_016
- 01_07_2011_017
- 01_07_2011_018
- 01_07_2011_019
- 01_07_2011_020
- 01_07_2011_021
- 01_07_2011_022
- 01_07_2011_023
- 01_07_2011_024
- 01_07_2011_025
- 01_07_2011_026
- 01_07_2011_027
- 01_07_2011_028
- 01_07_2011_029
- 01_07_2011_030
- 01_07_2011_031
- 01_07_2011_032
- 01_07_2011_033
- 01_07_2011_034
- 01_07_2011_035
- 01_07_2011_036
- 01_07_2011_037
- 01_07_2011_038
- 01_07_2011_039
- 01_07_2011_040
- 01_07_2011_041
- 01_07_2011_042
- 01_07_2011_043
- 01_07_2011_044
- 01_07_2011_045
- 01_07_2011_046
- 01_07_2011_047
- 01_07_2011_048
- 01_07_2011_049
- 01_07_2011_050
- 01_07_2011_051
- 01_07_2011_052
- 01_07_2011_053
- 01_07_2011_054
- 01_07_2011_055
- 01_07_2011_056
- 01_07_2011_057
- 01_07_2011_058
- 01_07_2011_059
- 01_07_2011_060
- 01_07_2011_061
- 01_07_2011_062
- 01_07_2011_063
- 01_07_2011_064
- 01_07_2011_065
- 01_07_2011_066
- 01_07_2011_067
- 01_07_2011_068
- 01_07_2011_069
- 01_07_2011_070
- 01_07_2011_071
- 01_07_2011_072
- 01_07_2011_073
- 01_07_2011_074
- 01_07_2011_075
- 01_07_2011_076
- 01_07_2011_077
- 01_07_2011_078
- 01_07_2011_079
- 01_07_2011_080
- 01_07_2011_081
- 01_07_2011_082
- 01_07_2011_083
- 01_07_2011_084
<< /ASCII85EncodePages false /AllowTransparency false /AutoPositionEPSFiles true /AutoRotatePages /All /Binding /Left /CalGrayProfile (Dot Gain 20%) /CalRGBProfile (Adobe RGB \0501998\051) /CalCMYKProfile (Photoshop 5 Default CMYK) /sRGBProfile (sRGB IEC61966-2.1) /CannotEmbedFontPolicy /Warning /CompatibilityLevel 1.3 /CompressObjects /Tags /CompressPages true /ConvertImagesToIndexed true /PassThroughJPEGImages true /CreateJobTicket false /DefaultRenderingIntent /Default /DetectBlends false /DetectCurves 0.1000 /ColorConversionStrategy /LeaveColorUnchanged /DoThumbnails false /EmbedAllFonts true /EmbedOpenType false /ParseICCProfilesInComments true /EmbedJobOptions true /DSCReportingLevel 0 /EmitDSCWarnings false /EndPage -1 /ImageMemory 1048576 /LockDistillerParams true /MaxSubsetPct 100 /Optimize true /OPM 1 /ParseDSCComments true /ParseDSCCommentsForDocInfo false /PreserveCopyPage true /PreserveDICMYKValues true /PreserveEPSInfo true /PreserveFlatness false /PreserveHalftoneInfo false /PreserveOPIComments false /PreserveOverprintSettings true /StartPage 1 /SubsetFonts true /TransferFunctionInfo /Apply /UCRandBGInfo /Remove /UsePrologue false /ColorSettingsFile () /AlwaysEmbed [ true /Algerian /Arial-Black /Arial-BoldItalicMT /Arial-BoldMT /Arial-ItalicMT /ArialMT /ArialNarrow /ArialNarrow-Bold /ArialNarrow-BoldItalic /ArialNarrow-Italic /ArialUnicodeMS /BaskOldFace /Bauhaus93 /BellMT /BellMTBold /BellMTItalic /BerlinSansFB-Bold /BerlinSansFBDemi-Bold /BerlinSansFB-Reg /BernardMT-Condensed /BodoniMTPosterCompressed /BookAntiqua /BookAntiqua-Bold /BookAntiqua-BoldItalic /BookAntiqua-Italic /BookmanOldStyle /BookmanOldStyle-Bold /BookmanOldStyle-BoldItalic /BookmanOldStyle-Italic /BritannicBold /Broadway /BrushScriptMT /Calibri /Calibri-Bold /Calibri-BoldItalic /Calibri-Italic /CalifornianFB-Bold /CalifornianFB-Italic /CalifornianFB-Reg /Cambria /Cambria-Bold /Cambria-BoldItalic /Cambria-Italic /CambriaMath /Candara /Candara-Bold /Candara-BoldItalic /Candara-Italic /Centaur /Century /CenturyGothic /CenturyGothic-Bold /CenturyGothic-BoldItalic /CenturyGothic-Italic /Chiller-Regular /ColonnaMT /ComicSansMS /ComicSansMS-Bold /Consolas /Consolas-Bold /Consolas-BoldItalic /Consolas-Italic /Constantia /Constantia-Bold /Constantia-BoldItalic /Constantia-Italic /CooperBlack /Corbel /Corbel-Bold /Corbel-BoldItalic /Corbel-Italic /CourierNewPS-BoldItalicMT /CourierNewPS-BoldMT /CourierNewPS-ItalicMT /CourierNewPSMT /DejaVuSans /DejaVuSans-Bold /DejaVuSans-BoldOblique /DejaVuSansCondensed /DejaVuSansCondensed-Bold /DejaVuSansCondensed-BoldOblique /DejaVuSansCondensed-Oblique /DejaVuSans-ExtraLight /DejaVuSansMono /DejaVuSansMono-Bold /DejaVuSansMono-BoldOblique /DejaVuSansMono-Oblique /DejaVuSans-Oblique /DejaVuSerif /DejaVuSerif-Bold /DejaVuSerif-BoldItalic /DejaVuSerifCondensed /DejaVuSerifCondensed-Bold /DejaVuSerifCondensed-BoldItalic /DejaVuSerifCondensed-Italic /DejaVuSerif-Italic /EstrangeloEdessa /FootlightMTLight /FranklinGothic-Medium /FranklinGothic-MediumItalic /FreestyleScript-Regular /Garamond /Garamond-Bold /Garamond-Italic /Gautami /Georgia /Georgia-Bold /Georgia-BoldItalic /Georgia-Italic /Haettenschweiler /HarlowSolid /Harrington /HighTowerText-Italic /HighTowerText-Reg /Impact /InformalRoman-Regular /Jokerman-Regular /JuiceITC-Regular /Kartika /KristenITC-Regular /KunstlerScript /Latha /LatinWide /LucidaBright /LucidaBright-Demi /LucidaBright-DemiItalic /LucidaBright-Italic /LucidaCalligraphy-Italic /LucidaConsole /LucidaFax /LucidaFax-Demi /LucidaFax-DemiItalic /LucidaFax-Italic /LucidaHandwriting-Italic /LucidaSans /LucidaSans-Demi /LucidaSans-DemiItalic /LucidaSans-Italic /LucidaSansUnicode /Magneto-Bold /Mangal-Regular /MaturaMTScriptCapitals /MicrosoftSansSerif /Mistral /Modern-Regular /MonotypeCorsiva /MS-Mincho /MVBoli /NiagaraEngraved-Reg /NiagaraSolid-Reg /OldEnglishTextMT /Onyx /OpenSymbol /PalatinoLinotype-Bold /PalatinoLinotype-BoldItalic /PalatinoLinotype-Italic /PalatinoLinotype-Roman /Parchment-Regular /Playbill /PoorRichard-Regular /Raavi /Ravie /SegoeUI /SegoeUI-Bold /SegoeUI-BoldItalic /SegoeUI-Italic /ShowcardGothic-Reg /Shruti /SnapITC-Regular /Stencil /Sylfaen /SymbolMT /Tahoma /Tahoma-Bold /TempusSansITC /TimesNewRomanPS-BoldItalicMT /TimesNewRomanPS-BoldMT /TimesNewRomanPS-ItalicMT /TimesNewRomanPSMT /Trebuchet-BoldItalic /TrebuchetMS /TrebuchetMS-Bold /TrebuchetMS-Italic /Tunga-Regular /Verdana /Verdana-Bold /Verdana-BoldItalic /Verdana-Italic /VinerHandITC /Vivaldii /VladimirScript /Vrinda /Webdings /Wingdings2 /Wingdings3 /Wingdings-Regular /ZWAdobeF ] /NeverEmbed [ true ] /AntiAliasColorImages false /CropColorImages false /ColorImageMinResolution 150 /ColorImageMinResolutionPolicy /OK /DownsampleColorImages true /ColorImageDownsampleType /Bicubic /ColorImageResolution 150 /ColorImageDepth -1 /ColorImageMinDownsampleDepth 1 /ColorImageDownsampleThreshold 1.00667 /EncodeColorImages true /ColorImageFilter /DCTEncode /AutoFilterColorImages false /ColorImageAutoFilterStrategy /JPEG /ColorACSImageDict << /QFactor 0.15 /HSamples [1 1 1 1] /VSamples [1 1 1 1] >> /ColorImageDict << /QFactor 0.15 /HSamples [1 1 1 1] /VSamples [1 1 1 1] >> /JPEG2000ColorACSImageDict << /TileWidth 256 /TileHeight 256 /Quality 30 >> /JPEG2000ColorImageDict << /TileWidth 256 /TileHeight 256 /Quality 30 >> /AntiAliasGrayImages false /CropGrayImages false /GrayImageMinResolution 150 /GrayImageMinResolutionPolicy /OK /DownsampleGrayImages true /GrayImageDownsampleType /Bicubic /GrayImageResolution 150 /GrayImageDepth -1 /GrayImageMinDownsampleDepth 2 /GrayImageDownsampleThreshold 1.00667 /EncodeGrayImages true /GrayImageFilter /DCTEncode /AutoFilterGrayImages false /GrayImageAutoFilterStrategy /JPEG /GrayACSImageDict << /QFactor 0.15 /HSamples [1 1 1 1] /VSamples [1 1 1 1] >> /GrayImageDict << /QFactor 0.15 /HSamples [1 1 1 1] /VSamples [1 1 1 1] >> /JPEG2000GrayACSImageDict << /TileWidth 256 /TileHeight 256 /Quality 30 >> /JPEG2000GrayImageDict << /TileWidth 256 /TileHeight 256 /Quality 30 >> /AntiAliasMonoImages true /CropMonoImages false /MonoImageMinResolution 300 /MonoImageMinResolutionPolicy /OK /DownsampleMonoImages true /MonoImageDownsampleType /Bicubic /MonoImageResolution 300 /MonoImageDepth 8 /MonoImageDownsampleThreshold 1.00333 /EncodeMonoImages true /MonoImageFilter /CCITTFaxEncode /MonoImageDict << /K -1 >> /AllowPSXObjects false /CheckCompliance [ /None ] /PDFX1aCheck false /PDFX3Check false /PDFXCompliantPDFOnly true /PDFXNoTrimBoxError true /PDFXTrimBoxToMediaBoxOffset [ 0.00000 0.00000 0.00000 0.00000 ] /PDFXSetBleedBoxToMediaBox true /PDFXBleedBoxToTrimBoxOffset [ 0.00000 0.00000 0.00000 0.00000 ] /PDFXOutputIntentProfile (sRGB IEC61966-2.1) /PDFXOutputConditionIdentifier () /PDFXOutputCondition () /PDFXRegistryName () /PDFXTrapped /False /CreateJDFFile false /Description << /ENU ([Based on 'INDESIGN'] [Based on '[DOWNSAMPLE150]'] Use these settings to create Adobe PDF documents for quality printing on desktop printers and proofers. Created PDF documents can be opened with Acrobat and Adobe Reader 5.0 and later.) >> /Namespace [ (Adobe) (Common) (1.0) ] /OtherNamespaces [ << /AsReaderSpreads false /CropImagesToFrames false /ErrorControl /WarnAndContinue /FlattenerIgnoreSpreadOverrides false /IncludeGuidesGrids false /IncludeNonPrinting false /IncludeSlug false /Namespace [ (Adobe) (InDesign) (4.0) ] /OmitPlacedBitmaps false /OmitPlacedEPS false /OmitPlacedPDF false /SimulateOverprint /Legacy >> << /AddBleedMarks false /AddColorBars false /AddCropMarks false /AddPageInfo false /AddRegMarks false /BleedOffset [ 0 8.503940 0 0 ] /ConvertColors /NoConversion /DestinationProfileName () /DestinationProfileSelector /NA /Downsample16BitImages true /FlattenerPreset << /ClipComplexRegions true /ConvertStrokesToOutlines false /ConvertTextToOutlines false /GradientResolution 300 /LineArtTextResolution 1200 /PresetName ([High Resolution]) /PresetSelector /HighResolution /RasterVectorBalance 1 >> /FormElements false /GenerateStructure true /IncludeBookmarks false /IncludeHyperlinks false /IncludeInteractive false /IncludeLayers false /IncludeProfiles false /MarksOffset 6 /MarksWeight 0.250000 /MultimediaHandling /UseObjectSettings /Namespace [ (Adobe) (CreativeSuite) (2.0) ] /PDFXOutputIntentProfileSelector /NA /PageMarksFile /RomanDefault /PreserveEditing true /UntaggedCMYKHandling /LeaveUntagged /UntaggedRGBHandling /LeaveUntagged /UseDocumentBleed false >> << /AllowImageBreaks true /AllowTableBreaks true /ExpandPage false /HonorBaseURL true /HonorRolloverEffect false /IgnoreHTMLPageBreaks false /IncludeHeaderFooter false /MarginOffset [ 0 0 0 0 ] /MetadataAuthor () /MetadataKeywords () /MetadataSubject () /MetadataTitle () /MetricPageSize [ 0 0 ] /MetricUnit /inch /MobileCompatible 0 /Namespace [ (Adobe) (GoLive) (8.0) ] /OpenZoomToHTMLFontSize false /PageOrientation /Portrait /RemoveBackground false /ShrinkContent true /TreatColorsAs /MainMonitorColors /UseEmbeddedProfiles false /UseHTMLTitleAsMetadata true >> ] >> setdistillerparams << /HWResolution [600 600] /PageSize [595.440 841.680] >> setpagedevice
<< /ASCII85EncodePages false /AllowTransparency false /AutoPositionEPSFiles true /AutoRotatePages /All /Binding /Left /CalGrayProfile (Dot Gain 20%) /CalRGBProfile (Adobe RGB \0501998\051) /CalCMYKProfile (Photoshop 5 Default CMYK) /sRGBProfile (sRGB IEC61966-2.1) /CannotEmbedFontPolicy /Warning /CompatibilityLevel 1.3 /CompressObjects /Tags /CompressPages true /ConvertImagesToIndexed true /PassThroughJPEGImages true /CreateJobTicket false /DefaultRenderingIntent /Default /DetectBlends false /DetectCurves 0.1000 /ColorConversionStrategy /LeaveColorUnchanged /DoThumbnails false /EmbedAllFonts true /EmbedOpenType false /ParseICCProfilesInComments true /EmbedJobOptions true /DSCReportingLevel 0 /EmitDSCWarnings false /EndPage -1 /ImageMemory 1048576 /LockDistillerParams true /MaxSubsetPct 100 /Optimize true /OPM 1 /ParseDSCComments true /ParseDSCCommentsForDocInfo false /PreserveCopyPage true /PreserveDICMYKValues true /PreserveEPSInfo true /PreserveFlatness false /PreserveHalftoneInfo false /PreserveOPIComments false /PreserveOverprintSettings true /StartPage 1 /SubsetFonts true /TransferFunctionInfo /Apply /UCRandBGInfo /Remove /UsePrologue false /ColorSettingsFile () /AlwaysEmbed [ true /Algerian /Arial-Black /Arial-BoldItalicMT /Arial-BoldMT /Arial-ItalicMT /ArialMT /ArialNarrow /ArialNarrow-Bold /ArialNarrow-BoldItalic /ArialNarrow-Italic /ArialUnicodeMS /BaskOldFace /Bauhaus93 /BellMT /BellMTBold /BellMTItalic /BerlinSansFB-Bold /BerlinSansFBDemi-Bold /BerlinSansFB-Reg /BernardMT-Condensed /BodoniMTPosterCompressed /BookAntiqua /BookAntiqua-Bold /BookAntiqua-BoldItalic /BookAntiqua-Italic /BookmanOldStyle /BookmanOldStyle-Bold /BookmanOldStyle-BoldItalic /BookmanOldStyle-Italic /BritannicBold /Broadway /BrushScriptMT /Calibri /Calibri-Bold /Calibri-BoldItalic /Calibri-Italic /CalifornianFB-Bold /CalifornianFB-Italic /CalifornianFB-Reg /Cambria /Cambria-Bold /Cambria-BoldItalic /Cambria-Italic /CambriaMath /Candara /Candara-Bold /Candara-BoldItalic /Candara-Italic /Centaur /Century /CenturyGothic /CenturyGothic-Bold /CenturyGothic-BoldItalic /CenturyGothic-Italic /Chiller-Regular /ColonnaMT /ComicSansMS /ComicSansMS-Bold /Consolas /Consolas-Bold /Consolas-BoldItalic /Consolas-Italic /Constantia /Constantia-Bold /Constantia-BoldItalic /Constantia-Italic /CooperBlack /Corbel /Corbel-Bold /Corbel-BoldItalic /Corbel-Italic /CourierNewPS-BoldItalicMT /CourierNewPS-BoldMT /CourierNewPS-ItalicMT /CourierNewPSMT /DejaVuSans /DejaVuSans-Bold /DejaVuSans-BoldOblique /DejaVuSansCondensed /DejaVuSansCondensed-Bold /DejaVuSansCondensed-BoldOblique /DejaVuSansCondensed-Oblique /DejaVuSans-ExtraLight /DejaVuSansMono /DejaVuSansMono-Bold /DejaVuSansMono-BoldOblique /DejaVuSansMono-Oblique /DejaVuSans-Oblique /DejaVuSerif /DejaVuSerif-Bold /DejaVuSerif-BoldItalic /DejaVuSerifCondensed /DejaVuSerifCondensed-Bold /DejaVuSerifCondensed-BoldItalic /DejaVuSerifCondensed-Italic /DejaVuSerif-Italic /EstrangeloEdessa /FootlightMTLight /FranklinGothic-Medium /FranklinGothic-MediumItalic /FreestyleScript-Regular /Garamond /Garamond-Bold /Garamond-Italic /Gautami /Georgia /Georgia-Bold /Georgia-BoldItalic /Georgia-Italic /Haettenschweiler /HarlowSolid /Harrington /HighTowerText-Italic /HighTowerText-Reg /Impact /InformalRoman-Regular /Jokerman-Regular /JuiceITC-Regular /Kartika /KristenITC-Regular /KunstlerScript /Latha /LatinWide /LucidaBright /LucidaBright-Demi /LucidaBright-DemiItalic /LucidaBright-Italic /LucidaCalligraphy-Italic /LucidaConsole /LucidaFax /LucidaFax-Demi /LucidaFax-DemiItalic /LucidaFax-Italic /LucidaHandwriting-Italic /LucidaSans /LucidaSans-Demi /LucidaSans-DemiItalic /LucidaSans-Italic /LucidaSansUnicode /Magneto-Bold /Mangal-Regular /MaturaMTScriptCapitals /MicrosoftSansSerif /Mistral /Modern-Regular /MonotypeCorsiva /MS-Mincho /MVBoli /NiagaraEngraved-Reg /NiagaraSolid-Reg /OldEnglishTextMT /Onyx /OpenSymbol /PalatinoLinotype-Bold /PalatinoLinotype-BoldItalic /PalatinoLinotype-Italic /PalatinoLinotype-Roman /Parchment-Regular /Playbill /PoorRichard-Regular /Raavi /Ravie /SegoeUI /SegoeUI-Bold /SegoeUI-BoldItalic /SegoeUI-Italic /ShowcardGothic-Reg /Shruti /SnapITC-Regular /Stencil /Sylfaen /SymbolMT /Tahoma /Tahoma-Bold /TempusSansITC /TimesNewRomanPS-BoldItalicMT /TimesNewRomanPS-BoldMT /TimesNewRomanPS-ItalicMT /TimesNewRomanPSMT /Trebuchet-BoldItalic /TrebuchetMS /TrebuchetMS-Bold /TrebuchetMS-Italic /Tunga-Regular /Verdana /Verdana-Bold /Verdana-BoldItalic /Verdana-Italic /VinerHandITC /Vivaldii /VladimirScript /Vrinda /Webdings /Wingdings2 /Wingdings3 /Wingdings-Regular /ZWAdobeF ] /NeverEmbed [ true ] /AntiAliasColorImages false /CropColorImages false /ColorImageMinResolution 150 /ColorImageMinResolutionPolicy /OK /DownsampleColorImages true /ColorImageDownsampleType /Bicubic /ColorImageResolution 150 /ColorImageDepth -1 /ColorImageMinDownsampleDepth 1 /ColorImageDownsampleThreshold 1.00667 /EncodeColorImages true /ColorImageFilter /DCTEncode /AutoFilterColorImages false /ColorImageAutoFilterStrategy /JPEG /ColorACSImageDict << /QFactor 0.15 /HSamples [1 1 1 1] /VSamples [1 1 1 1] >> /ColorImageDict << /QFactor 0.15 /HSamples [1 1 1 1] /VSamples [1 1 1 1] >> /JPEG2000ColorACSImageDict << /TileWidth 256 /TileHeight 256 /Quality 30 >> /JPEG2000ColorImageDict << /TileWidth 256 /TileHeight 256 /Quality 30 >> /AntiAliasGrayImages false /CropGrayImages false /GrayImageMinResolution 150 /GrayImageMinResolutionPolicy /OK /DownsampleGrayImages true /GrayImageDownsampleType /Bicubic /GrayImageResolution 150 /GrayImageDepth -1 /GrayImageMinDownsampleDepth 2 /GrayImageDownsampleThreshold 1.00667 /EncodeGrayImages true /GrayImageFilter /DCTEncode /AutoFilterGrayImages false /GrayImageAutoFilterStrategy /JPEG /GrayACSImageDict << /QFactor 0.15 /HSamples [1 1 1 1] /VSamples [1 1 1 1] >> /GrayImageDict << /QFactor 0.15 /HSamples [1 1 1 1] /VSamples [1 1 1 1] >> /JPEG2000GrayACSImageDict << /TileWidth 256 /TileHeight 256 /Quality 30 >> /JPEG2000GrayImageDict << /TileWidth 256 /TileHeight 256 /Quality 30 >> /AntiAliasMonoImages true /CropMonoImages false /MonoImageMinResolution 300 /MonoImageMinResolutionPolicy /OK /DownsampleMonoImages true /MonoImageDownsampleType /Bicubic /MonoImageResolution 300 /MonoImageDepth 8 /MonoImageDownsampleThreshold 1.00333 /EncodeMonoImages true /MonoImageFilter /CCITTFaxEncode /MonoImageDict << /K -1 >> /AllowPSXObjects false /CheckCompliance [ /None ] /PDFX1aCheck false /PDFX3Check false /PDFXCompliantPDFOnly true /PDFXNoTrimBoxError true /PDFXTrimBoxToMediaBoxOffset [ 0.00000 0.00000 0.00000 0.00000 ] /PDFXSetBleedBoxToMediaBox true /PDFXBleedBoxToTrimBoxOffset [ 0.00000 0.00000 0.00000 0.00000 ] /PDFXOutputIntentProfile (sRGB IEC61966-2.1) /PDFXOutputConditionIdentifier () /PDFXOutputCondition () /PDFXRegistryName () /PDFXTrapped /False /CreateJDFFile false /Description << /ENU ([Based on 'INDESIGN'] [Based on '[DOWNSAMPLE150]'] Use these settings to create Adobe PDF documents for quality printing on desktop printers and proofers. Created PDF documents can be opened with Acrobat and Adobe Reader 5.0 and later.) >> /Namespace [ (Adobe) (Common) (1.0) ] /OtherNamespaces [ << /AsReaderSpreads false /CropImagesToFrames false /ErrorControl /WarnAndContinue /FlattenerIgnoreSpreadOverrides false /IncludeGuidesGrids false /IncludeNonPrinting false /IncludeSlug false /Namespace [ (Adobe) (InDesign) (4.0) ] /OmitPlacedBitmaps false /OmitPlacedEPS false /OmitPlacedPDF false /SimulateOverprint /Legacy >> << /AddBleedMarks false /AddColorBars false /AddCropMarks false /AddPageInfo false /AddRegMarks false /BleedOffset [ 0 8.503940 0 0 ] /ConvertColors /NoConversion /DestinationProfileName () /DestinationProfileSelector /NA /Downsample16BitImages true /FlattenerPreset << /ClipComplexRegions true /ConvertStrokesToOutlines false /ConvertTextToOutlines false /GradientResolution 300 /LineArtTextResolution 1200 /PresetName ([High Resolution]) /PresetSelector /HighResolution /RasterVectorBalance 1 >> /FormElements false /GenerateStructure true /IncludeBookmarks false /IncludeHyperlinks false /IncludeInteractive false /IncludeLayers false /IncludeProfiles false /MarksOffset 6 /MarksWeight 0.250000 /MultimediaHandling /UseObjectSettings /Namespace [ (Adobe) (CreativeSuite) (2.0) ] /PDFXOutputIntentProfileSelector /NA /PageMarksFile /RomanDefault /PreserveEditing true /UntaggedCMYKHandling /LeaveUntagged /UntaggedRGBHandling /LeaveUntagged /UseDocumentBleed false >> << /AllowImageBreaks true /AllowTableBreaks true /ExpandPage false /HonorBaseURL true /HonorRolloverEffect false /IgnoreHTMLPageBreaks false /IncludeHeaderFooter false /MarginOffset [ 0 0 0 0 ] /MetadataAuthor () /MetadataKeywords () /MetadataSubject () /MetadataTitle () /MetricPageSize [ 0 0 ] /MetricUnit /inch /MobileCompatible 0 /Namespace [ (Adobe) (GoLive) (8.0) ] /OpenZoomToHTMLFontSize false /PageOrientation /Portrait /RemoveBackground false /ShrinkContent true /TreatColorsAs /MainMonitorColors /UseEmbeddedProfiles false /UseHTMLTitleAsMetadata true >> ] >> setdistillerparams << /HWResolution [600 600] /PageSize [595.440 841.680] >> setpagedevice
