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Coordination in Emergency Response Management

Developing a framework to analyze coordination patterns occurring in the emergency response life cycle.
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  1. Introduction
  2. Coordination in ERM
  3. Life Cycle Approach
  4. Coordination Life Cycle
  5. Application of Framework
  6. Conclusion
  7. References
  8. Authors
  9. Footnotes
  10. Figures
  11. Tables

Emergency Response Management (ERM) enables and supports emergency response operations across organizational, jurisdictional, and geographical boundaries. Recognizing the growing importance of ERM in countering both natural and manmade hazards, the U.S. government ordered (via Homeland Security Presidential Directive-5) the establishment, at the federal level, of a National Incident Management System (NIMS) [4]. The NIMS prescribes institutional response guidelines that help in establishing rule structures and developing a normative environment with defined tasks regarding what should be done during a response. Howitt and Leonard [6] point out that while NIMS does include a unified approach to incident management and incorporates standard command and management structures and aids coordination, it has certain limitations. For example, NIMS is a technical system that can function effectively when its goals in a particular situation are consistent, clearly prioritized and coherent. However, when situations present complex value conflicts or trade-offs, NIMS lacks the ability to make politically legitimate decisions and to mobilize public support for subsequent action [6].

Effective coordination is an essential ingredient for ERM. The coordination of emergency response is demanding as it involves requirements typical of an emergency situation that include, for example, high uncertainty and necessity for rapid decision making and response under temporal and resource constraints. Yet, the available literature on coordination issues relating to ERM consists largely of practitioner articles, governmental reports, and testimonies to Congress. Academic research in this area, other than [2, 3, 8, 11], is scarce. Given the importance of ERM coordination, this area needs to be studied in greater detail. In this article, we propose a framework to analyze emergency response coordination patterns, based primarily on semi-structured interviews with 32 emergency response personnel, including town, city, county, and state emergency managers and Federal Emergency Management Agency (FEMA) coordinators. We also illustrate the usefulness of the framework by applying it to an actual incident.

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Coordination in ERM

The coordination of emergency response is challenging because it involves factoring in exigencies typical of an emergency situation such as great uncertainty; sudden and unexpected events; the risk of possible mass casualty; high amounts of time pressure and urgency; severe resource shortages; large-scale impact and damage; and the disruption of infrastructure support necessary for coordination like electricity, telecommunications, and transportation. This is complicated by factors such as infrastructure interdependencies; multi-authority and massive personal involvement; conflict of interest; and the high demand for timely information. Table 1 elaborates some of these issues based on our conversations with emergency responders.

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Life Cycle Approach

A life cycle approach provides a broad and systematic view of the activities relating to emergency response management [12]. Therefore, the framework we suggest is adapted to each of the stages in the life cycle. The management of emergency response can be visualized in terms of three distinct sets of activities on the time line continuum [4]. These include actions taken prior to an incident (typically concerning preparedness issues such as planning and training), during the incident, and after the incident. The cycle is completed when de-briefing has occurred and the lessons learned are framed as actionable items designed to affect future preparedness. Many of the core elements of ERM coordination (such as activities, coordination objects, and constraints) differ from stage to stage [12]. Cultural, political, regulatory, and infrastructural (civil structures, people, process, and technology) issues all have an impact on coordination patterns and outcomes. In Figure 1, we present the schema of the framework we developed, which represents not only a development of the work presented by Raghu et al. [9], but also a context modification of that work. The framework considers five basic elements that are applied to each stage of the life cycle:

  • Task flow: tasks and interdependent relationships;
  • Resource: resource utilization management and dependencies;
  • Information: task-critical information collection, analysis, and distribution;
  • Decision: decision roles, rules, and structures; and
  • Responder: relationships, team-think, group dynamics (such as culture), organizational dynamics, and so forth.

This framework conceptualizes the “during-incident” response stage as comprising two distinct coordination patterns: On-site response coordination (Mini-Second Cycle) and Remote response coordination (Many-Second Cycle).

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Coordination Life Cycle

Here, we discuss coordination patterns along the entire coordination life cycle, based on our proposed framework.

Coordination in Pre-Incident Response. Pre-event coordination establishes the level of operational capacity and overall readiness for resilience during emergency response. A typical disaster includes several invariants, defined as those factors that remain unaffected by the changing conditions of the emergency, such as: creating emergency shelters in appropriate places; dealing with a surge in hospital admissions; working with degraded capacities; maintaining law and order; arranging evacuation across geographic boundaries; and other factors. These issues are addressed during coordinated planning and training exercises involving the stakeholders and results in the development of Standard Operating Procedures (SOP). Planning also addresses issues such as setting up contractual agreements with business entities for providing supplies during an incident and creating infrastructure to deal with first and second responder issues (including effect and behavior). During major emergencies, the limits of local capability are soon reached and multiple agencies are involved in supporting additional response efforts. This typically requires both spatial and temporal coordination with organizations and personnel who follow different norms and practices. Training and exercise help in establishing necessary understanding between different players (whether from the same agency or from different ones) and catalyzes smoother interaction between them during an actual incident. Setting up such training activities and table–top exercises also requires coordination. Therefore, coordination is a key issue in pre-incident activities. Table 2 includes the application of the framework to pre-incident activities.

Coordination During Incident Response. Coordination during an incident impacts both short-term and long-term outcomes. A plan-based approach to emergency response relies heavily on pre-incident preparedness and this sometimes leads to response inflexibility in the face of unexpected events. Variants in a disaster originate from hazard uncertainty; uncertainty as to the course of incident development; informational uncertainty; task flow uncertainty (whether sequential, consequential, or cascading); organizational structure uncertainty; and environmental uncertainty. Uncertainties are managed by improvisations, prioritization, and dynamic sourcing of capacities from other communities and external agencies, such as neighboring counties, state and federal agencies [5]. The variant or situation-dependent layers of knowledge create a context from which one can then understand the Incident Commander’s intent. These layers may indeed serve as temporal agents during mitigation.

To support fast response during complex incidents, responders must make rapid coordination decisions, which pose constraints on their capabilities to analyze coordination problems and explore the solution domain. Response to disasters can be viewed as consisting of an onsite response coordinating entity and a remote management entity such as an emergency operations center (EOC). Onsite response is usually reactive and the time window for coordination is small. We characterize this as the “Mini-Second Coordination Cycle.” It is typically characterized by working with the local picture stemming from the local scenario.

Without a proper understanding of the global picture, actions are motivated as a reaction to incidents from the immediate scene. Good coordination in civilian structures is better motivated by fostering common understanding and this is accomplished by creating a common operating global view that lays out the commander’s intent and strategies. Efficient communication is an essential ingredient in the development and spread of common understanding and buy-in. A supervisory structure such as EOC deals with more strategic issues and works with a global picture, leveraging external resources to help on-site response. The actions of the EOC emanate based on a more reflective and proactive posture and the EOC commanders typically operate with a large time window. We have therefore classified such coordination efforts as “Many-Second Coordination Cycle.” This concept (see Figure 2) is an adaptation from the work by Lewandowski et al. [7] in the area of survivable autonomic response architecture.

The concepts of mini-second and many-second coordination cycle relate to distinct coordination tasks (operation- vs. managerial-level); constraints (small vs. large time window, information/intelligence and capability); and outcome quality (poor vs. good). Mini-second coordination addresses immediate response coordination needs while many-second coordination oversees and supports the former, for instance with resources and information.

This division of coordination tasks and responsibility allows better matches between coordinator expertise and task requirements [1, 10]. Frontline response teams are trained to excel on domain-specific tasks (like firefighting and rescue) and the coordination of these tasks. Remote commanders focus on global issues such as inter-agency coordination, overall logistics, and regulation compliance.

Coordination in Post-Incident Response. Effective response and recovery is vital to the economic health of the affected region and also to the mental health of its citizens. Recovery focuses on the return to normalcy of the impacted region and people. It is also a phase for debriefing and pondering the details of the response effected, to learn from the incident so as to positively impact the building of resiliency to better deal with future incidents. It is also a time to replenish the consumable supplies and to return the response capacity back to readiness against new incidents in the future. Unless properly coordinated, the recovery may introduce new “disasters” for the incident victims and tangibly impact the budget.

Framework. In Table 2, we present a framework to analyze the coordination effort for managing response to an emergency. We apply the framework to all the three phases of the emergency life cycle.


To support fast response during complex incidents, responders must make rapid coordination decisions, which pose constraints on their capabilities to analyze coordination problems and explore the solution domain.


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Application of Framework

Here, we demonstrate the real-world application of the coordination framework presented in the previous section to the “during incident” management of an actual incident.

At 3:07 P.M. on Wednesday, July 18, 2001, a CSX Transportation train derailed in the Howard Street Tunnel under the streets of downtown Baltimore, MD (see www.usfa.dhs.gov/downloads/pdf/publications/tr-140.pdf). The train was carrying a variety of freight and hazardous materials, with three locomotives pulling 60 cars. Complicating the scenario was the subsequent rupture of a 40-inch water main that ran directly above the tunnel. The flooding hampered extinguishing efforts, caused several city streets to collapse, knocked out electricity to approximately 1,200 customers, and flooded nearby buildings. The derailment also interrupted a major communications line associated with the Internet and an MCI fiber-optic telephone cable.

During the two-day response, five alarms were requested with 17 engines, eight trucks, and three battalions, in addition to the HazMat, EMS, and rescue teams; 150 firefighters were on the scene, working to extinguish the fire. The fire-extinguishing operations were performed from both ends of the tunnel as well as through manholes located at Howard and Lombard Streets. The city of Baltimore activated the civil defense sirens at 5:45 P.M. to warn citizens of impending danger from the fire and hazardous materials. On the night of the derailment, city officials closed entrances to the city from all major highways and cancelled major public events.

NIMS suggests that the Incident Command Post (ICP) perform an EOC-like function in small-scale incidents [4]. In this response, the on-site management teams assumed the overall management support and supervision role (the many-second coordination cycle) and the individual divisions responded at the operational level (the mini-second coordination cycle). Table 3 shows the application of our framework to this real incident.

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Conclusion

Coordination in the context of emergency response is an understudied research issue. It is an important problem, as it impacts life and property in the affected area. We have proposed a framework to analyze coordination patterns along the emergency response life cycle. This framework may be further utilized by researchers and practitioners to: depict emergency coordination practices along focal dimensions elaborated in the framework; understand the overarching requirements for coordination design and implementation; and identify coordination ineffectiveness and analyze the alternatives for optimal solutions. This article has also applied the framework to a real-life emergency incident as a proof of concept of its relevance and usability. The case application demonstrates not only the applicability of the framework during disasters but also serves as a reminder template of the number of things to consider while countering emergencies and disasters.

It is important to point out that a number of new technologies have emerged in recent years to enable better emergency response coordination. Example solutions include wireless mesh networks (CalMesh; calmesh.calit2.net), sensor networks (ASPECT; www.epa.gov/naturalevents/flyinglab.htm), knowledge management systems (RKBP; www.rkb.mipt.org), geographic information systems (CATS; cats.saic.com), communication standards (CAP; www.incident.com/cap), incident forecast and analysis programs (SLOSH; www.fema.gov/plan/prevent/nhp/slosh_link.shtm), peer-to-peer communication platforms (Microsoft Groove; www.groove.net), collaborative work systems (E-Team; www.eteam.com), and command and control systems (DisasterLAN; www.disasterlan.com). These technology elements address parts of the puzzle and have to be leveraged to improve coordination. However, the discussion of these technologies in the context of emergency response management and coordination systems is beyond the scope of this article will be taken up in future research.

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Figures

F1 Figure 1. Emergency response coordination life cycle.

F2 Figure 2. Mini-second and many-second coordination cycles.

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Tables

T1 Table 1. ERM coordination at a glance.

T2 Table 2. Emergency coordination phases.

T3 Table 3. Application of framework to CSX train derailment and tunnel fire incident, Baltimore, Maryland, 2001.

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    This research has been funded by NSF under grant 0705292. Many emergency response coordinators from FEMA and State of New York (especially Western New York) provided valuable insights toward the development of this article (for details see www.som.buffalo.edu/isinterface/ack.html).

    DOI: http://doi.acm.org/10.1145/1342327.1342340

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