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FIGURING OUT THE FIXING:

UNDERSTANDING THE UNDERLYING PROCESSES FOR DESIGNING

AND IMPLEMENTING CRISIS MEDICAL RELIEF EFFORTS

Samantha Penta

A dissertation submitted to the Faculty of the University of Delaware in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Sociology

Summer 2017

FIGURING OUT THE FIXING:

UNDERSTANDING THE UNDERLYING PROCESSES FOR DESIGNING

AND IMPLEMENTING CRISIS MEDICAL RELIEF EFFORTS

Samantha Penta

Approved: ______Karen Parker, Ph.D. Chair of the Department of Sociology and Criminal Justice

Approved: ______George Watson, Ph.D. Dean of the College of Arts & Sciences

Approved: ______Ann L. Ardis, Ph.D. Senior Vice Provost for Graduate and Professional Education

I certify that I have read this dissertation and that in my opinion it meets the academic and professional standard required by the University as a dissertation for the degree of Doctor of Philosophy.

Signed: ______Tricia Wachtendorf, Ph.D. Professor in charge of dissertation

Signed: ______Barret Michalec, Ph.D. Member of dissertation committee

Signed: ______James Kendra, Ph.D. Member of dissertation committee

Signed: ______Eric Stern, Ph.D. Member of dissertation committee

ACKNOWLEDGMENTS

I have to extend a huge thank you to my dissertation committee: Tricia Wachtendorf, Barret Michalec, James Kendra, and Eric Stern for all of their support and feedback as I worked on my dissertation and throughout my graduate career. To

Tricia, especially, I owe tremendous thanks. I am so glad I took your Disasters and Society course fall semester of my sophomore year. Thank you so much for everything you have done to guide me through three degrees over the last nine years. I could not have asked for a better mentor. Thank you to everyone at the Disaster Research Center as well, for helping me grow from a nineteen-year-old undergraduate student beginning my first research project, to the professional disaster researcher I am now as I leave the University of Delaware.

During my undergraduate degree, I had the good fortune to find friends who have stayed with me over the last decade. Skyler, Alissa, and Meredith, you all have been such an incredible supportive and grounding force in my life. I have been so fortunate to be surrounded by wonderful graduate student colleagues, both in the Sociology and Criminal Justice Department and at DRC. Whether during classes, in the field on quick response deployments, during our work on research projects, or during weekly lunches, dinners, and coffee runs, I have learned so much from all of you. Of course, my deepest gratitude goes to my parents, Peter and Wavey, who have always supported me in everything I have done. Thank you all for encouraging me through my self-doubt, and celebrating with me during my accomplishments. It is a privilege to have you all in my life.

iv TABLE OF CONTENTS

LIST OF TABLES ...... x LIST OF FIGURES ...... xi ABSTRACT ...... xii

Chapter

1 INTRODUCTION ...... 1

2 LITERATURE REVIEW ...... 5

The Importance of Studying Disaster Medical Response ...... 5 Convergence ...... 11 Decision-Making and Sensemaking (Figuring Out) ...... 12

Models and Theories ...... 12 Characteristics: Distributed Over Time, People, and Decisions/Processes ...... 17

Medical Decision-Making—Influencing Factors ...... 19

Characteristics of the Decision-Maker and Recipient ...... 19 Characteristics of the Decision-Making Context ...... 21

Non-Medical Aspects of Relief ...... 23

3 METHODS ...... 29

Summary of Methodological Approach ...... 29 Sampling ...... 30

Sampling: Extreme Events ...... 30 Events ...... 36

Ebola Epidemic ...... 36 Nepal Earthquake ...... 38

Sampling: Organizations ...... 43 Sampling: Individuals ...... 46

Data Collection ...... 49

Interviews ...... 49 Interview Sample ...... 51

v Documents ...... 52 Observation ...... 53 Human Subjects Considerations ...... 56

Analysis ...... 59

Overall Coding Summary ...... 59 Analyzing the “How” ...... 60 Analyzing the “Why” ...... 61 Additional Coding ...... 63

4 CHARACTERISTICS OF THE DECISION-MAKING SETTING: CONDITIONS AFFECTING DECISIONMAKING AND THE RESPONSE ...... 64

Introduction ...... 64 Characteristics of the Decision-Making Context ...... 65

Characteristics of the Event ...... 65 Political, Legal, Social, and Cultural Context ...... 70 Physical Environment ...... 76

Resources ...... 81

Informational Resources ...... 81

Uncertainty ...... 82

Personnel Resources ...... 87 Materiel Resources ...... 95

Summary ...... 99

5 DEVELOPING SITUATIONAL AWARENESS ...... 102

Gathering and Communicating Information ...... 103

Previous Experience ...... 109 On the Ground Information and Sources ...... 113

Processing that Information (Assessing) ...... 115 Content ...... 116

Comparing ...... 116 Contextualizing ...... 118

vi Assessing Quality (Evaluating and Vetting) ...... 121 Deriving or Making Meaning ...... 126 Content and Objective of Developing Situational Awareness ...... 128 Different Perspectives in Developing Situational Awareness ...... 129

Diverse Backgrounds and Roles ...... 130 Differences in Knowledge ...... 130 Differences in Foci and Approaches ...... 133

Chapter Summary ...... 138

6 DEFINING AND BOUNDING ...... 140

What they Defined ...... 141

What the Event Is ...... 141 Definition of the Target Area and Recipient ...... 144 Definition of the Problem ...... 147

Defining in Public Health and General Wellbeing Terms ...... 148

Goals and Objectives ...... 153 Temporal Boundaries of the Event and Response ...... 154 Responders ...... 156 Connections Between Definitions ...... 160

How Responders Worked with Definitions and Boundaries ...... 161

Development and Change: Selective Bridging, Breaching, and Alteration ...... 161 Definitions at Odds ...... 163

Use: Connections to Other Processes ...... 166

Developing Situational Awareness ...... 166 Matching and Aligning ...... 167

Chapter Summary ...... 169

7 MATCHING AND ALIGNING ...... 171

Resources and Activities ...... 171 Structures ...... 175 Procedures to Goals and Objectives ...... 180 Characteristics to Criteria ...... 183

vii Distribution of the Matching Process ...... 185 Role Allocation ...... 188

Organizational Level ...... 190 Individual Level ...... 191 Distribution and Volunteering ...... 193

Disciplinary Differences ...... 194 Chapter Summary ...... 196

8 DECISIONAL LEGACIES AND INERTIA ...... 198

Connections Across Processes ...... 198 Legacies ...... 202 Decisional Inertia ...... 206

Forces ...... 208

Change in the Event (Hazard) ...... 208 Change from other organizational actors ...... 212 Internal Forces ...... 215

Time ...... 215 Important Time Points ...... 218 Things Affecting Inertia, Opening Possibilities, and Facilitating Change ...... 220

Chapter Summary ...... 221

9 DISCUSSION AND CONCLUSIONS ...... 224

Theory and Conclusions ...... 224 Implications for Theory ...... 225

Convergence ...... 228 Models and Theories ...... 230

Decision-Making and Sensemaking (figuring out) ...... 230 Characteristics: Distributed Over time, People, and Decisions/Processes ...... 235 Medical Decision-Making—Influencing Factors ...... 238

Implications for Practice ...... 240 Implications: Trends Across Events ...... 243 Study Strengths, Limitations, and Future Work ...... 245

viii Methods and Application ...... 245

Area of focus ...... 245 Comparison between events ...... 246 Type of Relief Effort ...... 249 Sample ...... 250

Strengths Limitations of the Theory ...... 251

REFERENCES ...... 253

Appendix

A INTERVIEW GUIDE ...... 269 B NEPAL QUICK RESPONSE APPROVAL LETTER ...... 273 C NEPAL QUICK RESPONSE RENEWAL LETTER ...... 275 D APPROVAL LETTER—UNDERSTANDING CRISIS MEDICAL RELIEF EFFORTS ...... 278 E TABLE OF DOCUMENTS ...... 280

ix LIST OF TABLES

Table 1 Table of Events by Crisis Characteristics ...... 40

Table 2 Organizations With Interview and/or Document Data by Event ...... 45

x LIST OF FIGURES

Figure 1 Process of Developing Situational Awareness ...... 103

Figure 2 Conceptual Diagram of Decisional Inertia ...... 217

xi ABSTRACT

Extreme events have the ability to cause substantial harm to the people subjected to them. In particular, disasters and public health emergencies can lead to an increase, sometimes substantial ones, of people in need of medical care. Delivery of that care becomes an important part of the response and relief effort. This research seeks to answer the question “How do the actors that become involved providing international medical relief to an international crisis event plan and implement that effort?” To answer this question, I use a combination of interview, observation, and document data. Using interviews, observation, and document analysis, I study the development of relief efforts of multiple groups involved in response to at least one of two crisis events: the 2014-2016 Ebola outbreak in West Africa and the April 25, 2015 earthquake in Nepal. This decision-making took place in an operational context in which characteristics of the event, the political, legal, social, and cultural environment, physical environment, and resources all influenced those decisions. Relief workers captured information about this setting through the process of developing situational awareness, in which they gathered, communicated, and processed that information.

They worked with definitions and boundaries as they developed that situational awareness. They ultimately made decisions through the use of a matching process. These three processes were linked together through a sort of feedback loop.

Collectively, they created a condition of decisional inertia in decision-making, where as groups committed more resources towards a particular course of action and made more and more decisions over time, fewer and fewer opportunities were available to

xii participate in the broader response, and it became increasingly difficult for organizations to change course in their relief effort. However, when substantial forces acted upon the relief efforts, such a s a change in the event itself or large-scale changes within an organization, new opportunities for participation opened up, allowing for change in organizational activity previously not available.

xiii

Chapter 1

INTRODUCTION

Hurricane Katrina, which disabled a large part of the medical system in New Orleans (Fink 2013) demonstrate the relevance of these issues to high-income nations as well. Given the likelihood that events abroad and at home may occur that require a medical response and an influx of medical responders, it is important to understand how those responses come to be. Previous research has examined decision-making and sensemaking during crises and disasters (e.g. Gralla, Goentzel, and Fine 2016; Weick 1993). Other work has examined decision-making in the medical context (e.g. Charles, Gafni, and Whelan 1999; Rapley 2008; Whitney 2003). However, there are gaps in this literature. Work on decision-making in the medical sociology and health literature focuses primarily on doctors as decisions-makers (as well as patients) (e.g. Charles et al. 1999;

Kessler 1990; McKinlay, Potter, and Feldman 1996; Sabin, Nosek, Greenwald, and Rivera 2009; Timmermans 2005). While there is some acknowledgement of the other contributors to the decision-making process (e.g. Charles et al. 1999; Rapley 2008), they have received much less attention in the literature. Looking at the kinds of decisions this literature reveals an emphasis on diagnosis and treatment decisions (e.g. Charles et al. 1999; Kessler 1990; Rathore, Ketcham, Alexander, and Epstein 2009; Whitney 2003). There is a lack of work examining other actors relevant to the medical context or on decisions that shape the context and limitations for diagnosis and treatment decisions, such as those responsible for logistics or organizing the effort as a whole. Non-medical actors and conditions like the availability of supplies, equipment, and space are important in the execution of a medical response (Hirsch et al. 2015; Mackersie 2006a; Mackersie 2006b; Schultz and Koenig 2006), yet the majority of the work conducted in the fields of operations management and humanitarian logistics has been undertaken predominantly by logisticians, engineers, and management scholars, not sociologists. This research seeks to answer the question “How do the actors that become involved providing international medical relief to an international crisis event plan and implement that effort?” To answer this question, I use a combination of interview, observation, and document data. I study the development of relief efforts of multiple groups involved in response to at least one of two crisis events: the 2014-2016 Ebola outbreak in West Africa and the April 25, 2015 earthquake in Nepal. I interviewed people occupying decision-making capacities or who could speak to decision-making within a range of groups and different kinds of response efforts (large, nongovernmental organizations, small NGO, government, military, etc.) about decision-

making processes within their organizations, exploring the multiple issues and decisions involved in setting up the context in which medical relief activity will take place. I draw on observation research of one group in the lead up to their Nepal deployment and observation research conducted in Nepal following the earthquake,1 and document analysis of materials produced by responding organizations. This decision-making took place in an operational context in which characteristics of the event, the political, legal, social, and cultural environment, physical environment, and resources all influenced those decisions. Relief workers captured information about this setting through the process of developing situational awareness, in which they gathered, communicated, and processed that information. They worked with definitions and boundaries as they developed that situational awareness. They ultimately made decisions through the use of a matching process. These three processes were linked together through a sort of feedback loop. Collectively, they created a condition of decisional inertia in decision-making, whereas groups committed more resources towards a particular course of action and made more and more decisions over time, fewer and fewer opportunities were available to participate in the broader response, and it became increasingly difficult for organizations to change course in their relief effort. However, when substantial forces acted upon the relief efforts, such a s a change in the event itself or large-scale changes

1 This material is based upon work supported by the National Science Foundation under Grant No’s. 1331269 and 1331572 subcontract 14-007985 A 00 and by the Centers for Disease Control and Prevention (CDC) through grant 5P01TP000288 and research contract 200-2014-60654. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the National Science Foundation or the Centers for Disease Control and Prevention.

within an organization, new opportunities for participation opened up, allowing for change in organizational activity previously not available.2

2 Some of the material presented in this dissertation was presented previously at the 4th International Conference on Urban Disaster Reduction in Wellington, New Zealand on October 17, 2016, and appeared in the associated conference proceedings: Penta, Samantha. Decisions Beyond Treatment: Creating the Operational Context for Crisis Medical Care. Proceedings of the 4th International Conference on Urban Disaster Reduction, GNS Science, Wellington, New Zealand, 2016.

Chapter 2

LITERATURE REVIEW

The Importance of Studying Disaster Medical Response The continued incidence of disasters across the globe marks a continued need to study response to disasters and crises events. Speaking to this trend, Hannigan writes that “Climate change is said to impact disasters in two ways: it triggers a spike in the range and frequency of severe floods, storms, and other weather-related events; and it provokes radical changes in the economies of Southern nations, especially in the agriculture and food sectors” (2012:95). The Center for Research on the Epidemiology of Disasters’ (CRED) annual reports demonstrate the global impact of disasters. While the number of events as defined by CRED and their human and economic impacts have been lower than the previous 10 year averages for 2012, 2013, 2014, and 2015, the report for 2015 did show an increase in the number of country level disasters over in recent years, and all of these reports emphasize that the human impacts, which

CRED presents as the number of deaths and the number of people affected, both as a number and per 100,000 inhabitants, have been significant (Guha-Sapir 2015b; Guha- Sapir 2016). They demonstrate a pattern of particularly severe impacts on lower- and middle-income nations (Guha-Sapir, Hoyois, and Below 2013; Guha-Sapir, Hoyois, and Below 2014; Guha-Sapir, Hoyois, and Below 2015; Guha-Sapir 2015b). What is more, according to this report produced during the Ebola epidemic, the parameters used to determine if events qualified as a disaster in this report exclude epidemics, significant when one considers “the death toll of the on-going Ebola epidemic in West Africa (8,600 deaths) is much higher than the total mortality rate of all natural disasters in 2014” (Guha-Sapir 2015b: n.p.). The number of people whose health is

compromised by these events underscores the importance of understanding the medical response to them. Further, Morton and Vu (2011) note that there has been an increase in interest in international emergency medicine (at least international work) among emergency medicine residents, indicating a potential growth in this area. While the effects of these events may be most pronounced for the developing world, high-income nations, including the United States, will not remain untouched by disasters or public health emergencies in the future. Both the actual and perceived risks of these kinds of events occurring in the United States are very real. Consequently, the clear benefits to learning about implementing a medical response in the context of the developing world may yield valuable insight into not just medical response in developing nations, but for domestic response as well. While developed nations do not have the chronic infrastructural and resources problems (most likely, although segments of the community may experience such challenges) that frequently occur in underdeveloped nations (and which may be worsened by the disaster), the last few years have provided multiple instances in which a disaster or emergency event has destroyed or severely disabled a hospital or larger medical system. During the February 22, 2011 earthquake in Christchurch, New Zealand, for example, the acute-care hospital experienced shaking and damage, including flooding from broken pipes. The hospital had generators that generally worked, but did experience multiple generator failures, and a section of the ambulance bay collapsed. Damage to larger infrastructure including roads meant that many people could not get to the acute care facility in Christchurch, requiring primary care providers and non- acute care hospitals to meet post-earthquake medical demands (Ardagh et al. 2012). Essentially, the damage from the event adjusted who performed what kind of services

and how those services were provided (with different resources than usual). In the United States, an Enhanced Fujita Scale (EF) 5 tornado directly hit a hospital in Joplin, Missouri, in 2011, requiring a full evacuation of the entire facility and making an important source of medical care unavailable (Charney, Rebmann, and Flood 2014). Two years later, Moore Medical Center was destroyed by an EF5 tornado, which required the full evacuation of the facility and redirection of patients (Moore Medical Center 2014). All of these events demonstrate the possibility of severe and disruptive hospital damage. The case of Hurricane Sandy in 2012 shows that even a small degree of damage can cause sufficient disruption to effectively disable an entire facility. In the after action report on Hurricane Sandy, Gibbs and Holloway write that “Sandy’s unprecedented storm surge caused widespread power outages and flooding the ultimately compromised the ability of five hospitals and approximately 30 residential facilities to shelter in place throughout the storm”, evacuating and relocating the patients in these facilities (2013:8). New York Downtown Hospital proactively vacated the facility before the storm for fear of power loss that was expected in the area (Farley 2013:5; Gibbs and Holloway 2013:8). New York University Hospital and Coney Island Hospital both evacuated after the storm (Farley 2013). Finally, the experience at Bellevue Hospital in particular demonstrates the surprising ways medical resources and facilities can be compromised. It was not structural damage, but disruption of systems necessary for providing care that lead to evacuation. After circumventing flood-induced generator failure through manual fuel transport, the exhaustion of water supplies when flooding compromised the water pumps pushed them to evacuate after the storm (Farley 2013; Ofri 2012). Many of the facilities that

evacuated in New York City were not hospitals, but were facilities like nursing homes that offered other types of care (Gibbs and Holloway 2013). This is important given work indicating not only that these facilities look to hospitals to support, but that hospitals may also be relying on these kinds of facilities in their emergency plans, perhaps unbeknownst to the workers or administrators of these facilities (Kendra et al. 2012). During and after Hurricane Katrina in 2005, Memorial Hospital suffered flooding and complete power loss, requiring evacuation of the building, made even more challenging by the unsafe rising flood waters in the city. Memorial was not the only hospital facing these conditions. Other hospitals in the city were forced to evacuate as well, driving competition for resources, particularly transportation resources. In other words, Katrina disabled not just a hospital, but the ability of a large portion of an entire municipal medical system to provide care (Fink 2013). What we see in these cases are instances or conditions in which taken-for-granted infrastructure and resource systems are not available or cannot be relied upon. Further, there are expectations that a major event could disrupt medical systems in the future. For instance, multiple areas in the western United States have developed exercises to help them prepare for earthquakes. These exercises are based on earthquake scenarios developed by an array of engineers, geologists, and social scientists to represent plausible and realistic depictions of what the earthquake and post-earthquake environment would be like. The ShakeOut scenario for the Los

Angeles area anticipates damage to hospital structures (Jones et al. 2008). Likewise, the scenario for the Cascadia Rising exercise for the Cascadia Subduction Zone earthquake and tsunami anticipate damage to hospitals in both Washington and

Oregon, as well as compromised functioning from damage to non-structural systems, utility loss, and damaged or destroyed transportation systems (Western Washington University Resilience Institute and Scenario Sub-Working Group 2015). Assessments of hospitals in the Hayward fault area anticipate damage to their facilities as hospitals struggle to meet retrofitting deadlines (Maffei 2010). Even if the event is not expected to destroy the physical infrastructure, the increase in medical need after a disaster or crisis event, especially from a situation like an epidemic or pandemic may overwhelm that infrastructure and personnel and material supplies. This happened during the 1918-1920 Influenza pandemic when high rates of infection and death severely taxed medical resources, to the point in which the medical system in Canada had to involve vast amounts of volunteers in the medical effort (Scanlon, Hurrel, and McMahon 2009). More recently, concern for epidemics and pandemics in the United States has appeared in discussions of pandemic influenza. In response to this fear, the Homeland Security Council produced a “National Strategy for Pandemic Influenza” in November of 2005, followed by the “National Strategy for Pandemic Influenza Implementation Plan” in May, 2006. Developed in light of what was then considered the current or immediate threat posed by H5N1 avian influenza, both documents highlight the potential pandemic threat all strains of the virus pose.

The National Strategy (2005) highlights the millions of deaths wrought by previous influenza epidemics, indicates the very real possibility of another influenza outbreak in the country in the future, and notes the connection between disease outbreaks in other parts of the world and their implications for the United States (Homeland Security Council 2005). The Implementation Plan reveals “it is projected that a modern pandemic could lead to the deaths of 200,000 to 2 million people in the United

States alone” and goes on to say that “The economic and societal disruption of an influenza pandemic could be significant” (Homeland Security Council 2006:1). This sense of heightened risk is repeated in the “National Strategy for Pandemic Influenza Implementation Plan One Year Summary” published in July 2007 (Homeland Security Council 2007). These concerns for both the incidence of an epidemic and the ability of current surge capacity to meet the need are echoed in the literature. Toner and Waldhorn

(2006) argue for the importance of preparing for pandemic influenza. Drawing information from the Pandemic Influenza Plan, they write, “There is a consensus that the next pandemic is not far off” (Toner and Waldhorn 2006:397), and while containment measures are expected, so too are severe effects on hospitals. In routine operations, hospitals already see a decrease in space available, healthcare worker shortages, emergency department overcrowding (Toner and Waldhorn 2006), and a general practice of running at least at nearly full to maximum capacity, which limits surge capacity capability (Schultz and Koenig 2006; Toner and Waldhorn 2006). These same issues of surge capacity challenges appeared in Christchurch after those seismic events (Ardagh et al. 2012). In the event of pandemic influenza, Toner and Waldhorn (2006) anticipate a decrease in the workforce as they or their family members get sick. While the nature of risk is not the focus of this study, it should be noted that this discussion just highlights the extent to which known risks might appear. There are limits to our knowledge of what the actual risks are. Even in areas where there is hazard mapping, planning, and building to code, the full extent of the potential hazard may not be known, like when the Christchurch earthquake revealed the Canterbury

area to be more seismically risky than previously believed (Richardson and Ardagh 2013). Similarly, the storm surge associated with Sandy was worse than was predicted (Farley 2013). The implication is that even with aggressive planning, preparedness, and mitigation activity, responders and medical responders in particular, even in the most proactive countries, may face unanticipated events that comprise the existing medical system, forcing personnel in the area and those who may converge from outside to figure out how to perform their medical duties in the new operational context.

Convergence The real or perceived demand for resources after a disaster is often met by convergence. According to Fritz and Mathewson, convergence is “movement or inclination and approach toward a particular point” (1957:3). Fritz and Mathewson (1957) identify three types of convergence: personal, materiel, and informational convergence. All three types of convergence are well-documented in the disaster research literature. Material convergence has been documented during both domestic and international efforts (Argothy 2003; Holguín-Veras et al. 2014; Kendra and Wachtendorf 2001). In a similar way, scholars have noted the convergence of people during and after crises, including after the Oklahoma City bombing (Larson, Metzger, and Cahn 2006), in New York City after the September 11, 2001 terrorist attacks (Argothy 2003; Kendra and Wachtendorf 2001; Kendra and Wachtendorf 2003; Kendra and Wachtendorf 2016), the Halifax explosion in 1917 (Scanlon and Osborne

1992), and the Spanish Influenza pandemic (Scanlon et al. 2009) to list a few examples. Humanitarian relief efforts are examples of all three forms of convergence, typically triggering the movement of people, material, and information. Even if a

group is only focused in one of the forms of convergence, for instance, in bringing in medical personnel to provide medical services, they are still engaged in the other forms as well. In this example, medical volunteers may bring with them medical supplies, non-medical supplies needed to support their own personnel, they may purchase supplies while they are in the area, and they become sites and conduits of information convergence as they seek out information relevant to their efforts and likely share information with others in the process. Once they set up an operation, they may become a location of convergence.

Decision-Making and Sensemaking (Figuring Out)

Models and Theories The existing literature offers some insight into how decision-making may work in relation to medical humanitarian relief. Some literature has used Game Theory to explain organizations’ supply chain decisions. A mathematical theory also used in studies in political science, economics, and to understand commercial supply chains, it accounts for the decentralized nature of decision-making due to multiple actors (Muggy and Heier Stamm 2014). Muggy and Heier Stamm (2014) offer an extensive review of humanitarian logistics literature using Game Theory. This theory and the research applying it, explain decision-making at the level of different organizations (and other entities like government) interacting with or responding to each other. The organization, such as an NGO, makes a decision based on information it does or does not have and actions other entities do or do not make. Game Theory has been used to model cooperation between groups and to model interactions between decision-makers in different kinds of groups, like government and NGOs. However, the focus of work

appears to be decision-making as it relates to other groups. It does little to reveal what occurs within those groups to generate those decisions and outcomes. Sensemaking is another theory that has been used to understand organizational response to crisis events. As the name suggests, the theory describes how people in organizations make sense of their environments upon some kind of interruption. Weick, Sutcliffe, and Obstfeld describe “sensemaking as a process that is ongoing, instrumental, subtle, swift, social, and easily taken for granted” (2005:209). Dealing with interruption is central to sensemaking and it is both an individual and social process (Weick 1995). There are seven properties or characteristics of sensemaking:

1. “Grounded in identity construction

2. Retrospective

3. Enactive of sensible environments

4. Social

5. Ongoing

6. Focused on and by extracted cues

7. Driven by plausibility rather than accuracy” (Weick 1995:17). Key here is that the identity of the group is important and is at least partially determined by action. Sensemaking is retrospective in that action always precedes a little ahead of understanding the situation, and that understanding is guided by priorities and values. Through the process of enactment, people in reacting to an environment contribute to further creating the environment, and people and environments create each other (Weick 1988; Weick 1995). Their actions become a part of the operational context. Applied to humanitarian relief, the relief efforts generated to deal with the crisis in turn become part of the situational context in which

people participating in humanitarian relief make sense of and make decisions in. It is a social process, whether or not other people are physically present at the time of the sensemaking process. Sensemaking is affected by the context in which it occurs (through the effect of context on extracted cues, both what becomes a cue and how it is interpreted). Weick summarized how the seven components work together: “Once people begin to act (enactment), they generate tangible outcomes (cues) in some context (social), and this helps them discover (retrospect) what is occurring (ongoing), what needs to be explained (plausibility), and what should be done next (identity management)” (Weick 1995:55). Sensemaking occurs under conditions of ambiguity (when multiple interpretations are possible simultaneously) and uncertainty, of which there are three types: how the environment is changing, how that change will affect the organization, and uncertainty about what response options are available (Weick 1995:95). Sensemaking is typically used to understand situations of brief duration (minutes, hours, or perhaps a couple days). For example, Weick uses sensemaking to understand the Mann Gulch fire disaster in which 13 smoke jumpers were killed, an event which from beginning to end lasted only a few hours (Weick 1993). In a later piece, Weick et al. (2005) use the case of a nurse observing the condition of an infant patient over a few hours to illustrate this process. Gralla et al. identify one shortcoming of sensemaking: that it “was developed by studying problems in which solving is not important: an understanding of the situation is sufficient to generate an appropriate action” (2016:24). They build on sensemaking theory to understand decision-making behavior among logisticians by linking the processes of problem formulation and problem solving. Examining

decision-making among experienced logisticians making transportation decisions during a World Food Program exercise, they offer the following four propositions to explain this formulation and solving process:

The problem was formulated through a sensemaking process, in which a formulation was built up over time through interaction with the problem (Gralla et al. 2016:28).

The problem formulation consisted of goals, constraints, and dynamic perception (Gralla et al. 2016:29).

The problem was solved through a process resembling a greedy search algorithm; at each iteration, choice was made among a limited set of perceived possible dispatches (Gralla et al. 2016:31).

Sensemaking was the governing process of problem solving, and it influenced search via the components of the formulation: constraints defined the problem space, dynamic perception limited the perceived options at each service iteration, and goals directed choice among them (Gralla et al. 2016:32). Essentially, the problem-solving process was linked to the problem formulation process, wherein “A problem formulation emerged over time as the problem was progressively solved, through iteration between formulating and solving” (Gralla et al. 2016:28). This theory, they argue, is useful for understanding how people deal with urgent but ill-defined problems, of which the challenge of how to provide humanitarian relief fits, though the authors call for additional research to better understand the boundaries and generalizability of this theory (Gralla et al. 2016). Fuzzy Trace Theory offers an explanation of how people use information in decision-making and the role of experience in influencing those decisions. According to Fuzzy Trace Theory, people both gather verbatim (literal) information and gists (general meanings), but they generally depend on gists during decision-making. People will revert to the most basic level of meaning they can (relying on categorical

levels of understanding) unless forced to work with more precise information and meanings. Further, the inclination to rely on gists when making decisions increases with increased experience and expertise (Reyna 2008). It is not experience per se that matters, but the meaning that is derived from past experience. The literature recognizes multiple forms of decision-making in the medical context. Charles et al. (1999) identify three forms of medical decisions making: paternalistic decision-making, informed decision-making, and shared decisions making.3 While they acknowledge that decision-making involves more than the doctor and the patient, their comparisons of different models focus on the doctor-patient interaction. As explained by Charles et al. (1999), the informed and shared decision- making models developed in reaction to perceived shortcomings of the paternalistic model, and other scholars have indicated that shared decision-making is the preferred decision-making model (Körner, Ehrhardt, and Steger 2013), suggesting the role that values may come to play in influencing decision-making models or approaches.

However, the framework put forth by Whitney (2003) suggests that all three models are valid in different situations. According to Whitney, decisions exist on a plane defined by the importance of the decision for the patient on one side and the certainty of the decision (meaning the availability of good quality data indicating a single preferred intervention) on the other. A decision’s level of importance and uncertainty

3 It should be noted that there is quite a bit of variation in what is meant by the term “shared decision making” (SDM). Moumjid, Gafini, Bremond, and Carrere (2007) found in their review of the SDM literature that there was a lack of clarity in the term’s use: some papers did not provide an explanation of what they meant by the term, others used the terms “shared decision making” and “informed decision making” interchangeably, and definitions varied between papers. In essence, the definition of SDM varied across and within papers on the topic, thus requiring caution when interpreting and comparing results related to SDM research (Moumjid et al. 2007).

determines the most appropriate model of decision-making (participation of the doctor relative to patient). While this model is not validated and based largely on anecdotal experience, it does show a more nuanced view of appropriate decision-making, suggesting that who should be involved and the degree of their involvement can vary by situation. Rather than one model fitting all situations, different models are appropriate depending on the context (Whitney 2003). To apply lessons from this more broadly, characteristics of the decision itself affect the decision-making process.

Characteristics: Distributed Over Time, People, and Decisions/Processes One characteristic of the decision-making and sensemaking processes that research makes apparent is the distributed nature of these processes. In identifying areas of future research, Weick et al. (2005) call for more work on the distributed nature of sensemaking, which other scholars have pursued, including Kendra and Wachtendorf who propose the concept of diffuse sensemaking (Kendra and

Wachtendorf 2016; Maitlis and Christianson 2014). Research indicates that decision- making occurs across multiple people and is not confined to a single moment for both medical personnel and patients (Charles et al. 1999; Rapley 2008; Goodwin 2014). Decision-making is not a singular isolated cognitive event. Decision-making occurs across multiple people and over multiple interactions over time. Patients make decisions in the context of interactions with friends and family members in addition to medical professionals. People ranging from acquaintances to professionals can influence and take part in these decisions. This is a ‘collective patient’ indicating that decision-making occurs across multiple people. Similarly, “decision-making practices are simultaneously retrospective, current and prospective in orientation” (Rapley 2008:438) indicating distribution over time as well.

Just as sensemaking is described as ongoing (Weick et al. 2005), Charles et al. (1999) describe decision-making as being comprised of three analytical stages— information exchange, deliberation stage, and decision on the treatment to implement—which they explain are iterative or simultaneous processes. Further, decision-making occurs during encounters with human and material things. Developed looking at acute and chronic decisions, distributed decision-making is grounded in the claims that such decision-making occurs with non-human items and over time. Even in a hyperacute situation, such as a paramedic dealing with an unconscious patient, the decision is still informed by past experiences, discussions, training, and “mundane and digital diagnostic technologies that interact with the patient” (Rapley 2008:440). Thus, not only is decision-making shared with active participants in the current situation, but according to Rapley, the decisions are shaped by actors and informants from outside of that group, even with the extreme power imbalance in which the patient is physically unable to participate.

Goodwin adds to this discussion by showing that not only is decision-making distributed over time and people, but the decisions themselves may not necessarily be solutions. Rather, treatments are experiments that can be evaluated later for their success or for further information. According to Goodwin (2014), decision-making is collaborative, and in the case of drug administration, is an experiment, not a solution. It is not a linear process. It is “transient and evolving” (Goodwin 2014:54) and gives the sense that “no single person is responsible” (Goodwin 2014:57). Rather than predetermining responsibilities, the best (or an effective way) of organizing work is “an efficient (albeit frenzied) performance that hinges on participants interactively and contemporaneously distributing work among themselves” (Goodwin 2014:54) that

includes people communicating nonverbally to determine tasks. Decisions are not made by single individuals in single well-defined cognitive moments. What all of these pieces illustrate is the extended and expanded nature of decision-making both for the patient in terms of treatment and lifestyle choices, and for medical personnel directly involved in providing care.

Medical Decision-Making—Influencing Factors

In addition to theories and models of decision-making, a number of authors have demonstrated that social factors play an important role in shaping interpretations of information, perceptions of people, and decision-making in the medical context (Bodenhausen 1988; Fox 1980; Haider et al. 2011; Kessler 1990, Lincoln 2006; McKinlay et al. 1996; Rathore et al. 2009; Sabin et al. 2009; Timmermans 2005; Varkey et al. 2009;). There are three kinds of social characteristics that can shape decision-making: characteristics of the decision-maker, characteristics of the person/group about whom the decision is being made (referred to as ‘recipients’ here), and characteristics of the decision-making setting (McKinlay et al. 1996).

Characteristics of the Decision-Maker and Recipient Characteristics of the doctor and patient shape interpretations and decisions. According to McKinley et al., “Despite their ‘objective’ medical training, physicians remain human actors, socially conditioned to engage in stereotyping, whether consciously or not. In that respect, medical decision-making can be a function of who the patient is as much as what the patient has” (McKinlay et al. 1996:1769). Characteristics such as patient age (McKinlay et al. 1996) and patient race/ethnicity,

living arrangement, family involvement, source to the psychiatric emergency room, and gender (Lincoln 2006) appear to influence decision-making. In talking about the information exchange stage, Charles et al. (1999) claim that patients are not blank slates, but understand information in a context of values and beliefs. This means that the message the patient learns may differ from what the doctor is trying to communicate (Charles et al. 1999). While they talk about this in terms of patients, one could expect values and beliefs to effect other kinds of actors and decision-makers as well. Surveying 18 logistics experts involved in the United Nations Logistics cluster and focusing on the emergency response/initial phase, Gralla,

Goentzel, and Fine (2014) found that priorities affect decision-making. In this particular study, effectiveness was prioritized over equity and efficiency, and cost was of lower priority. There is evidence that stereotypes can play a role in decision-making. Bodenhausen’s (1988) work indicates stereotype activation affected evaluation of evidence and perceptions of guilt. Looking within the healthcare context, there is evidence both that doctors have biases and that those biases influence treatment decisions. In one study, doctors of all races expressed implicit preferences for white patients (except for African American doctors who expressed no implicit preference) on implicit association tests for race, as did both male and female doctors, important because implicit associations and attitudes shape discriminatory behavior, though the strength of the implicit preferences varied by race (strongest among white males)

(Sabin et al. 2009). In the context of international relief, it is possible that stereotypes may work to affect recipients of medical aid on an individual level in terms of treatment decisions and diagnoses, but it is also possible that stereotypes towards a

country (as opposed to a particular racial or ethnic identity) or the developing world/low-income countries as a whole may affect the entire approach to medical aid delivery. A study by Haider et al. (2011) had first year medical students take an implicit association test for race and class (the latter is not validated) and then offer a treatment recommendation to vignettes. While they found that the medical students did have biases in favor of white and higher-class patients, those biases did not appear to affect their treatment recommendations, a finding the authors note contradicts research on doctors (Haider et al. 2011), supporting Reyna (2008) in suggesting the level of knowledge and expertise may play a role in shaping decision-making.

Characteristics of the Decision-Making Context The context in which decisions are made influences decision-making. One factor that shapes decision-making is that of uncertainty (Fox 1980, Rathore et al. 2009; Sabin et al. 2009; Varkey et al. 2009). Rathore et al. (2009), for instance, found only minimal support that patient race influenced doctor prescription decisions, but indicated that the results might be due to a lack of medical uncertainty in the scenarios they presented their subjects with, and discuss other research that indicates patient race only influences decisions in situations of clinical uncertainty while in the vignettes in their study the treatment was clear (Rathore et al. 2009). Similarly, Varkey et al.

(2009) and Sabin et al. (2009) suggest that uncertainty can work to increase the influence of racial bias, potentially working in combination with or exasperating difficult working conditions which may foster discrimination. Austin et al. (2013) present five different situations of medical uncertainty, all of which focus on the uncertainty associated with the correctness of a diagnostic test, the likelihood of getting a condition with or without a risk factor or treatment, and the risk of

experiencing a negative side effect with an intervention (Austin, Reventlow, Sandoe, and Brodersen 2013). What they, like the other research outlined here, do not address are uncertainties outside of the diagnostic process. There is a need for work at looking at how uncertainties in the broader context, for instance in the availability or quality of supplies and personnel, disease characteristics, and policy approaches of other institutions and organizational bodies may affect decisions. In addition, Gralla, Goentzel, and Van de Walle (2015) comment that there is limited work available identifying responder information needs, prompting their study of information need during the response time period as identified by 18 logistics experts involved in large response NGOs from a range of fields. While they derived some information needs, they comment on the context-dependent nature of these needs, particularly given the tendency of responding organizations to specialize in a couple of objectives or tasks. They call for more wok to explore these specialized needs (Gralla et al. 2015). Factors related to the healthcare setting and the larger context within which a doctor operates can shape decision-making as well. Among white male physicians in one study, doctors in HMO-based practices offered different responses to vignettes than respondents from office or hospital based practices (McKinlay et al. 1996). Research on medical examiners’ (ME) determinations of deaths as suicide found that these decisions were not just determined by the available evidence. MEs were also influenced by efforts to maintain professional credibility and dominance, where incorrectly labeling a death as a suicide can pose a threat to credibility and challenge professional authority (Timmermans 2005). Even the larger culture can shape decisions. Kessler (1990) demonstrates that sex assignment is based on the cultural assumption that there are two and only two genders. Doctors’ decisions to surgically

assign sex to intersexed infants reflect the power of culture to shape a decision to perform surgery on a healthy child, and suggests that doctors’ commitment to a gender once they have made a decision and other aspects of the sex assignment experience represent doctor’s striving to show credibility and professional legitimacy (Kessler 1990). Of course, the availability of resources and what those resources are can influence triage and treatment decisions as treatment options become or cease to be viable (Fink 2013; Mackersie 2006a; Mackersie 2006b; Salomone 2006).

Non-Medical Aspects of Relief Kovács and Spens (2007) offer some definitions of what humanitarian relief is. Quoting Long and Wood (1995), Kovács and Spens explain “Relief itself can be defined as ‘foreign intervention into a society with the intention of helping local citizens’ (Long and Wood, 1995, p. 213)” (2007:101). When humanitarian relief arrives in the form of disaster relief, it is typically in response to a natural and sudden onset event, though some kinds of human-induced events and famine relief can fall under this umbrella. The purpose of these efforts is to get the necessary resources and personnel to the multiple locations of need while removing people from the affected area (Kovács and Spens 2007). Humanitarian logistics are an important part of humanitarian relief. The literature offers multiple definitions of humanitarian logistics, but they generally center on organizing the movement and management of material goods, money, and information from their respective sources and to the intended recipients: people who are in need (Van Wassenhove 2006; McCoy 2008; Kovács and

Spens 2007). In particular, Van Wassenhove writes, “Essentially for humanitarians, logistics is the processes and systems involved in mobilizing people, resources, skills and knowledge to help vulnerable people affected by disaster” (2006:476).

Humanitarian logistics includes, but is not limited to disaster relief. It includes longer or continuous support, such as development projects (Kovács and Spens 2007). A component of humanitarian logistics is supply chain management, where supply chains are “network[s] consisting of suppliers, manufacturers, distributors, retailers and customers” facilitating the movement of materials, information, and finances (Van Wassenhove 2006:480). Supply chain management is about “getting the right goods, at the right time, to the right place and distributed to the right people” (Van

Wassenhove 2006:480). Logistics is an important part of relief operations (Kovács and Spens 2011; Titus 2011; Van Wassenhove 2006). According to Van Wassenhove, “disaster relief is about 80% logistics” (2006:475). Its importance is especially highlighted by medical humanitarian relief. When dealing with a situation in which whatever is harming the patient can transfer to the medical provider and harm them, the availability of personal protective equipment (PPE) is important. PPE is key in preventing disease spread

(though so is procedure: personnel need to know and execute correct donning and doffing) (Fischer, Hynes, and Perl 2014). Thus, logistics and operations are important because they can affect the health and safety of care providers ultimately affecting the number of people available to deliver medical care. The lack of sufficient PPE creates difficult choices for providers between working at increased risk to themselves or denying care to some patients (Fischer et al. 2014). Van Wassenhove outlines several of the challenges humanitarian logisticians face, including complex operating environments, “high levels of uncertainty in terms of demand, supplies and assessment” (emphasis in the original) (2006:477), time pressures, staff turnover, and the disaster environment itself. Humanitarian logisticians

work in an operational environment in which there are multiple interconnected factors at play, some of which may be unknown. The situation is characterized by ambiguity in the consequences and impacts of decisions and interrelationships and as new things arise (Van Wassenhove 2006). Van Wassenhove (2006) talks about these specifically for humanitarian logistics, but this really describes the operating environment for anyone involved in humanitarian or disaster relief. This uncertainty and ambiguity are conditions which the previously summarized research indicated affected decision- making and are those under which sensemaking occurs. Since these challenges characterize the humanitarian relief context, it is important to understand how people involved in humanitarian response address and overcome these challenges. The logistics components of medical response are hugely important for surge capacity. Schultz and Koenig define hospital surge capacity “as the components necessary to care for a sudden, unexpected increase in patient volume that exceeds current capacity” (2006:1154), but this extends beyond physical space and bed availability. Supplies and equipment are important parts of surge capacity, as are personnel. The amount and type of these resources that are already available and can be brought in, where those resources will come from, and how quickly they will arrive are all key (Schultz and Koenig 2006). The medical response to the November 13,

2015 Paris attack offers an example of the role of logistics in facilitating medical response, where it appears to have been an important factor contributing to success in treating the rapid influx of patients. While “the demand for tourniquets was so high that the mobile teams came back without their belts”, generally, medical personnel did not run out of supplies during this response (Hirsch et al. 2015:2536). Hirsch et al. write, “The sterile supply chain was augmented to allow a fluid workflow, and

administrative staff supported the medical work, finding logistics solutions when necessary (eg, patient registration, finding free beds, etc.)” (2015:2538). It is important to learn how these problems and solutions are figured out because “Research has shown that in many incidents within the United States, it is not a lack of resources that has hampered response efforts, but a lack of a management system to match the appropriate resources to the current needs” (Schultz and Koenig 2006:1155). The importance of humanitarian logistics and operations lies not just with their roles in enabling medical responses, but also in their power to shape the decisions that occur within those relief efforts. Medical or treatment decisions are context- dependent. As an example, how triage is performed, that is, how people are sorted and prioritized for treatment, depends on the context in which triage is being carried out. While the physical condition of the patient and injury severity is important in determining where he or she will go for treatment (Mackersie 2006a), and physiologic, anatomic, and mechanism of injury criteria in addition to comorbid factors (Salomone

2006) are central criteria in making these decisions, triage is also linked to contextual factors, such as the ability to transport the patient to the best-suited medical facility for a particular situation, distance to receiving locations, capabilities offered at those locations (Mackersie 2006a), and availability of resources (Mackersie 2006a;

Salomone 2006). Because disaster or crisis conditions can affect these aspects of context, the overall disaster/crisis context is important for understanding medical decisions, especially as some scholars posit that the objectives of triage change under these circumstances (Sasser 2006). As a result, understanding disaster medical decisions and what options are available to those providing medical care, depends on understanding and shaping the environment created around those individuals and in

which those decisions are made. Understanding non-medical decisions is crucial to understanding and improving medical response and relief. Despite its importance for successful response, logistics has not received much attention in either research or practice until relatively recently. In their 2007 work, Kovács and Spens indicate that most work (majority of) on humanitarian logistics at the time of writing was in practitioner journals. There was minimal humanitarian logistics research pre-1990, and it is only within the last decade that we see an increase in attention on this issue and development of a research community (Kovács and Spens 2011), with greater interest in in humanitarian logistics emerging within both academic and practitioner circles after the 2004 Indian Ocean Tsunami (Kovács and Spens 2007; Kovács and Spens 2011). An initial focus on preparedness has shifted toward relief. There was an initial focus on coordination and “application of different logistical concepts, such as postponement and speculation” (Kovács and Spens 2011:36)

Kovács and Spens (2011) claim there is a gap between humanitarian logistics research and practice (and policy and procedure). This is partly because most of the work in this area is either case study or conceptual. There is not much empirical work or analytical work (Kovács and Spens 2011). Citing Thomas and Mizushima (2005),

Kovács and Spens write,

The lack of professionalization of HL [humanitarian logistics] also meant that logisticians were rarely included in the planning stages of a humanitarian response. Thus, the voice of logisticians was often absent. The cumulative result of all these factors was that the logistics function remained isolated from finance, emergency response, information technology, and management, leading to the sub-optimization of operational efficiency and effectiveness. (Kovács and Spens 2011: 34)

Even relatively recently, logisticians and logistics discussions were not a part of larger discussions in planning. This information supports both the need to look at logistics decisions, and to talk to logisticians (however informal that position may be), to see what their level of involvement is now and how they interact with these other actors within their respective groups in shaping what the mission becomes. In sum, research has examined decision-making in the medical context, but has been restricted in its analysis primarily to doctors and patients engaging in diagnosis and treatment decisions. The work examining humanitarian response has been conducted by a different community of researchers, predominantly engineers and logisticians, but has not generally focused on medical humanitarian relief efforts. Further, while research on both decision-making and sensemaking has indicated that these are processes spread out over multiple actors and time, research has typically only focused on few actors and short time periods (usually in the response time frame when talking about relief). What is missing is an investigation into how actors— including a wider range of medical personnel and non-medical actors—construct and operate medical humanitarian relief operations over extended periods of time.

Chapter 3

METHODS

Summary of Methodological Approach This study asks “How do the actors that become involved providing international medical relief to an international crisis event plan and implement that effort?” To answer this question, I examined the processes used in planning and implementing a medical relief effort for a range of groups involved in providing medical or health services to at least one of two events: the Ebola epidemic in West Africa that began in 2014 or the April 25, 2015 Nepal earthquake. I focused on organizations responding internationally to these events. The study relied on interviews with individuals within these organizations who occupied positions enabling them to shape the relief effort and be knowledgeable about the various aspects of the process. This study additionally used document analysis of communications from these groups and observation data.

This study examines the processes guiding behavior related to all three types of convergence identified by Fritz and Mathewson (1957), though it is more heavily focused on the movement of people. The organizations featured in this study themselves contributed to materiel convergence, both in bringing supplies with them when they deployed and by effectively becoming a point(s) of convergence within the affected are as they drew materials (and people) to them. This is also true of informational convergence, as they represented points where information was converging, and shared information conveyed to other points of informational convergence. Thus, this project exists at the intersection of personal, materiel, and informational convergence. The research contributes to our understandings of how the

three occur concurrently, and how they simultaneously work and interact in the development, implementation, and evolution of medical humanitarian relief operations. Essentially, this dissertation examines how convergers figure out their convergence behavior in the context of medical relief.

Sampling Overall, the events, organizations, and individual participants for this study were selected through purposive and snowball sampling approaches. Purposive sampling is a well-supported sampling technique in qualitative research (Martin 2002;

Schultz, Koenig, Auf der Heide, and Olson 2005) and disaster research as well

(Killian 2002; Phillips 2014; Stallings 2002). In purposive sampling, cases are intentionally selected for inclusion based on the ability to address and answer the research question. Likewise, snowball sampling is a frequently useful approach in qualitative research and disaster research as well, particularly when studying a small or hard to access population. As will be discussed individually for the events, organizations, and individuals in the following subsections, they were all selected based on their ability to reveal general patterns associated with the planning and implementation of medical relief efforts and their connections to other individuals within the study.

Sampling: Extreme Events In addition to the demonstrated applied need to examine extreme events, there is theoretical value that comes from studying these kinds of phenomena. Disasters and

other extreme events have long been acknowledged as opportunities to learn about social and organizational behavior (Phillips 2014; Turner and Killian 1957; Klinenberg 2002). Turner and Killian write “Extreme and critical situations, such as those created in war or in peacetime disasters, provide opportunities for the investigation of individual reactions to the sudden and drastic disruption of the social framework of behavior” (1957:41). They go on to explain that the disruption caused by the crisis event creates circumstances in which people may not be able to act as they normally would (Turner and Killian 1957:41). Similarly, in Klinenberg’s 2002 study of the Chicago heat wave in the mid-1990s, he explains that the extreme nature of the event made visible the underlying social characteristics that made people vulnerable. Those characteristics were always present, but only became visible with the extreme heat. He notes “that institutions have a tendency to reveal themselves when they are stressed and in crisis” (Klinenberg 2002:23), indicating that a focus on extreme events will be useful in understanding how organizations (and the people within them) solve problems. This study takes a crisis perspective in its selection of extreme events. Boin,‘t Hart, and McConnell “define crises as events or developments widely perceived by members of relevant communities to constitute urgent threats to core community values and structures” (emphasis in the original) (2009:83-84). A crisis occurs

when a community of people—an organization, a town, or a nation— perceives an urgent threat to core values or life-sustaining functions, which must be dealt with under conditions of uncertainty (Rosenthal, Boin, & Comfort, 2001). A crisis may thus result from a wide variety of threats… (Boin and ‘t Hart 2007:42), and has both uncertainty (about the nature of the event and with regard to its potential consequences), and urgency (Boin and ‘t Hart 2007). Crises are not geographically

bound and can exist over extended periods of time, over which the crisis can change and interact with other issues, and can “disrupt a wide range of social, political, and organizational processes” (Boin and ‘t Hart 2003:545). As Boin and ‘t Hart summarize, “What all these dramatic events have in common is that they create impossible conditions for those who seek to manage the response operation and have to make urgent decisions while essential information about causes and consequences remains unavailable” (2007:43).

This definition of crisis compares to a relatively restricted definition of disaster. There is debate among scholars as to the definition of a disaster, and different definitions have emerged and evolved over time (for a discussion, see Perry 2007 and Quarantelli 2005). In 1961, Charles Fritz offered the following definition of disaster:

an event concentrated in time and space, in which a society, or a relatively self-sufficient subdivision of a society, undergoes severe danger and incurs such losses to its members and physical appearances that the social structure is disrupted and the fulfillment of all or some of the essential functions of the society is prevented. (Fritz 1961:655)

While Fritz’s definition has been very influential, others have expanded this or modified it to include other kinds of phenomena under the disasters umbrella. Dynes and Quarantelli, drawing on Dynes (1970), offer a broader definition, writing “More sociologically, a disaster is an event, located in time and space, which produces the conditions whereby the continuity of structure and processes of social units becomes problematic”, but the specific agent, origin and the temporal elements can vary (Dynes and Quarantelli 1977:1-2). While Samuel Prince’s (1920) study of the Halifax munitions ship explosion is generally considered to mark the beginning of disaster research, traditionally, researchers have conceptualized disasters as comprising natural events (Boin and ‘t Hart 2007; Perry 2007), which Kai Erikson (1976) in Everything in

its Path expanded to encompass technological or man-made events (though retaining the rapid-onset component). Levine (1982) further pushed the boundary in the examination of Love Canal by arguing against the time and space components, claiming that disasters do not have to be defined in those respects, nor do they need to be sudden, and highlighting the uncertainty component. Oliver-Smith (1986) emphasized the effects on people, and Kroll-Smith and Couch (1990) identified chronic technical disasters as an increasingly common type of disaster.

Despite these expansions, these conceptualizations of disaster fall short for this analysis in a number of ways. While Hughes (1993) makes a convincing argument that epidemics should be considered disasters based on collective responses to them that parallel those towards disaster, there is debate within the field as to whether they actually qualify as disasters (Hannigan 2012), especially when operating under Fritz’s “concentrated in time and space” (1961:655) stipulations. Hannigan (2012) discusses some of the academic debate in the field about what constitutes a disaster, particularly in distinctions between traditional disaster events and events like famines, epidemics, and droughts (FED), claiming that work on the latter has typically occupied a different space in the literature than has disaster research. He references differences in opinion between Quarantelli, who was against including FED events under the umbrella of disasters, and Dynes, who used similar reasons to argue for their inclusion. While Quarantelli argues that FEDs are distinct from disasters as they are neither rapid onset nor are the literatures for disasters and FED overlapping, Hannigan (2012) explains,

Dynes (2004) argues that these other kinds of events (conflict based events and slow onset events) warrant examination by disaster researchers. Because of this debate, application of or use of the disaster perspective was problematic for this dissertation,

calling for a different perspective. This discussion suggests that there is value in exploring these events within the disaster research community, but that the crisis framework is better for examining events that are protracted and less geographically confined. While disasters are crises, crises capture a much wider range of events, including events requiring a medical response. Another benefit of this approach is that the wider view of crisis fits well with the range of events covered in the humanitarian logistics literature, which, though often using the word ‘disaster,’ includes some of the previously discussed contested events like famine, drought, and even poverty as a slow-onset disaster, and include, events like refugee and political crises as man-made disaster events (Van Wassenhove 2006). As Boin and ‘t Hart explain, the “crisis approach takes a broader view at types of un-ness” including “unexpected, undesirable, unimaginable, and often unmanageable situations” (2007:42). Thus, while earthquakes have fairly comfortably fit into the disaster perspective, the crisis perspective better captures the protracted nature of the ongoing aftershocks and impending threat of monsoon season and mudslides. Likewise, epidemics, which have not historically been investigated under the disaster perspective, have been examined as crises. Adopting a crisis perspective allows for the comparisons of two types of events that might not be deemed comparable under the disaster framework, to examine the underlying issues of the new, unfamiliar, and disruptive nature of these events. The crisis approach accommodates the focus on convergers this dissertation takes. Neither the crisis approach nor convergence rely on a confined, physical disaster site. The crisis approach considers a wide range of phenomena to be crises, so long as there is a threat, uncertainty, and urgency (Boin and ‘t Hart 2007). Likewise,

having a specific disaster location is not necessarily important for the study of convergence. Fritz and Mathewson (1957) describe a concentric circle model of disaster to describe the physical disaster site with various rings radiating out of it, and use that to describe ideas of internal and external convergence. However, this model and these concepts, Kendra and Wachtendorf (2003) claim, are not useful and are limited in their abilities to explain disaster convergence. They write, “Convergence is more generally a movement toward a point of significance identified as such by those who are converging, rather than a transgression of subjectively defined boundaries” (Kendra and Wachtendorf 2003:102). They add:

We suggest that it is more helpful to view convergence as movement toward the response milieu, which we hold to be the complex of people and places involved in the response, a multilocational field of social activity. It is a shifting, protean entity which is created by participants and would-be participants acting across the variety of spaces and places involved in the response and helping to define those places as well (Kendra and Wachtendorf 2003:102).

Importantly, people as well as physical places are points of convergence—“convergers themselves create places to be converged to” (Kendra and Wachtendorf 2003:102). In the context of this dissertation, as groups decide to come together, to reach out, and to implement a medical response, they as actors, become sites of convergence for other people as well as material and information, and create physical spaces of convergence on the ground as they establish a point from which to operate. Their movements and decisions could further strengthen the importance or significance of other, preexisting points of convergence as well.

Events This study focused on health and medical responses to the Ebola Outbreak starting in 2014 and the April 25 2015 Nepal earthquake.

Ebola Epidemic As of the March 30, 2016 situation report (March 30, 2016), there were a total of 28,646 cases of Ebola in all countries combined, with 11,323 deaths. The majority of these were primarily in Guinea (3,811 cases, 2,543 deaths), Liberia (10,675 cases,

4,809 deaths), and Sierra Leone (14,124 cases, 3,956 deaths) (World Health Organization 2016). Actors came from across the international community including Médecins Sans Frantiéres (MSF), the US Centers for Disease Control and Prevention (CDC), the International Federation of Red Cross and Red Crescent Societies (IFRC), International Medical Corps, International Rescue Committee, International Organization for Migration, United Nations Population Fund (UNFPA), Save the Children, United Kingdom, United Nations Children’s Fund (UNICEF), and World

Health Organization among many others. The kinds of activities these organizations engaged in were often in one respect or another, novel. There were many conditions unique to this particular outbreak that contributed to its severity, including a lack of experience with the disease in this region of Africa, poor infrastructure and limited resources to combat the disease, cultural burial practices, and high mobility among the population, including across country boarders (World Health Organization 2015m). The Ebola outbreak in West Africa began in December of 2013 with the first infection in Guinea, though the illness was thought to be a case of cholera at the time. Incidence of the illness gained more attention in January of 2014, and in February, infections were discovered in Guinea’s capital. By March, the (at that point, still

unidentified) disease was receiving a lot of attention, and it was during this month that the disease was identified as Ebola, specifically the Zaire species, which is the deadliest version (World Health Organization 2015n). In March, 2014, the World Health Organization publicly announced the Ebola outbreak with 49 cases and 29 deaths at the time of the announcement (World Health Organization 2015n). At that point, the outbreak was confined to Guinea, but that changed two months later in May 2014 when the disease was identified in Guinea’s neighboring countries of Liberia and

Sierra Leone (European Centre for Disease Prevention and Control 2016). Seven other countries ultimately reported cases over the course of the event: “Italy, Mali, Nigeria, Senegal, Spain, the United Kingdom, and the United States of America” (World Health Organization 2016:Previously Affected Countries), and the numbers reported in these nations are much lower than in Guinea, Liberia, and Sierra Leone. Ebola spread to Nigeria in July 2014, to Senegal in August, and Mali in October of the same year (World Health Organization 2015o). In addition to the action taken in countries with an Ebola presence, other countries deemed high priority by the WHO, but which had not yet seen an Ebola patient received targeted support (World Health Organization 2016), extending the crisis response to even more locations. The far reach of the response and the virus itself, and in particular its persistent presence in

Guinea, Liberia, and Sierra Leone shows the pandemic/epidemic was not geographically confined. Focusing on the three primary countries affected by the epidemic, there were multiple points at which these countries were declared Ebola-free, only to discover new cases shortly after. Liberia was declared Ebola-free in May of 2015, then again in January of 2016. Sierra Leone was declared free of the disease in November 2015, but

new cases were discovered again in January of 2016. Likewise, Guinea, which was declared Ebola-free in December 2015, has since discovered new cases (European Centre for Disease Prevention and Control 2016). Though there continued to be some cases of Ebola, on March 29, 2016, the Director-General of the WHO, after consulting with the Emergency Committee on Ebola during its ninth meeting, declared “That the Ebola situation in West Africa no longer constitutes a Public Health Emergency of International Concern” (Chan 2016: n.p.). This put the Ebola crisis at approximately two years in duration, with substantial variation in status within and between countries over time, illustrating the protracted nature of this event and the level of change and interruption throughout.

Nepal Earthquake The event in Nepal began on April 25, 2015, with a 7.8 Magnitude earthquake (Guha-Sapir 2015a). Located 9.3 miles deep, the epicenter was located approximately

175 kilometers away from the capital city of Kathmandu in the Gorkha district (Nepal Planning Commission 2015). A 7.3 magnitude aftershock followed on May 12, roughly two and a half weeks after the initial quake (Guha-Sapir 2015a; Nepal Planning Commission 2015). Its epicenter was located on the opposite side of Kathmandu (North and East compared to the first which was North and West of the capital), near Mount Everest (Nepal Planning Commission 2015), located in the Dolakha district (World Health Organization 2015j). More than 30 of Nepal’s 75 districts were affected by the quake, 14 of which were designated as “crisis-hit”

(Nepal Planning Commission 2015). The response and reconstruction efforts were affected by monsoon season (Guha-Sapir 2015a), which is associated with heavy rains in Nepal (Barros and Lang 2003). During our time in the field, many people expressed

concerns about landslides. Landslides occurred as a consequence of the earthquake, and were expected to be made worse by the oncoming monsoon season (Field Notes, 2015). The earthquake both created a medical need and diminished available health resources. The May 8, 2015 situation reports and updates from the International Medical Corps and WHO reported government figures, stating that there were 7,885 deaths and 17,803 injured persons as a result of the first earthquake (International

Medical Corps 2015; World Health Organization 2015k). An International Medical Cops situation report from May 8, 2015, just before the aftershock, reported 269 health facilities were completely and 527 facilities were partially damaged from the initial quake (International Medical Corps 2015). The aftershock, caused additional damage, injuries, and deaths (World Health Organization 2015j). While no aftershocks have occurred on a scale like that of the May 12 tremor, aftershocks continued in the region.

These events fit the definition of crises events. [See Table 1 for a breakdown of how each event fits the characteristics of crises.] These events each posed a threat to the physical wellbeing of people exposed to them and the ability of the existing medical system to meet the health needs caused by these events (the value). That lives and wellbeing were at stake and required rapid response created the sense of urgency. There was uncertainty in the nature of the event. For Nepal, that existed in the extent of damage and injuries and deaths, both in terms of the numbers and the spread. There was uncertainty in the number and severity of future aftershocks, and the start of monsoon season. There was uncertainty in the operational context in terms of the activity of other responders, and the government, given that the country did not have a

Table 1 Table of Events by Crisis Characteristics

Crisis Nepal Earthquake Ebola Epidemic Characteristics Providing sufficient service to meet the health and medical needs of a given population, in particular, to meet those health and Value Threatened medical need created by the crisis Injuries from the earthquake and subsequent aftershocks Compromised health from infection with the Ebola virus The value is threatened by an inability to meet the health and medical need of the affected population because of a crisis- induced insufficient supply of resources and/or an increase in demand Injuries and increase in demand from the earthquake and The increase in people needing intensive medical because of Threat aftershocks and tremor-induced damage to buildings the number of Ebola infections, and the inability of the local health infrastructure to meet those demands in part because of an unfamiliarity with the virus

40 The need to meet medical demands quickly to prevent a worsening of patient medical conditions and a potential increase in the

numbers of people who die or face poor health outcomes Urgency Failure to address earthquake-induced injuries quickly can Failure to identify and treat people with Ebola and do so early lead to death or disability, and depending on sanitary increases likelihood of death and that they spread the disease conditions, could lead to illness if infected to others. Uncertainty in population needs, the number of injured and dead, the locations of the injured, other actors involved in the response, where they are, what they are doing, resources available, legal context Uncertainty about how the absence of a constitution will The characteristics of this particular virus, including how long Uncertainty: Nature affect response, in the number, strength, and location of the someone can still pass on the disease, uncertainty regarding of the Event aftershocks, the safety/structural integrity of the buildings, the West African context (since Ebola was new to this region), accessibility of roads, the effects of landslides, and the start the protective measures needed of monsoon season

Table 1 continued

How the event and response will affect recovery, the local economy, how the event and response will affect local use and perceptions of local medical resources even after the responders leave, how the event affects other health issues for the affected population and the broader community. Uncertainty: Damage to health infrastructure may mean medical service How experiences during the epidemic will affect people's Consequences of the shortage when responders leave, interactions with foreign interactions with the healthcare system in the future for further Event medical teams may change attitudes and usage of remaining Ebola outbreaks and for other medical conditions, long term medical resources in Nepal, and sustainability of treatment effects on local medical resources options

The events are protracted, taking place over extended periods of time Not Temporally While the earthquake itself occurred on April 25, 2015, Approximately two years from announcement of epidemic to Confined aftershocks have continued for months afterwards the announcement by the Director-General of the WHO that it is no longer a Public Health Emergency of International Significance The events are not restricted by geopolitical boundaries, and affects a broad geographical area.

41 Fourteen districts in Nepal were deemed "crisis-hit" and Ebola crossed national boundaries and reached multiple

nearly half of the districts were affected by the earthquake in continents. Even when concentrating on the areas playing host Not Geographically some way. The mobility of affected people within the to the majority of patients, this still represents three countries, Confined country and to other countries also defies geographic with widespread distribution within each country. Further, boundaries. organization worked proactively to prepare countries that never ended up seeing the virus. The mobility of people infected with Ebola means the crisis site consistently has the potential to grow

*Crisis criteria drawn from Boin and ‘t Hart (2003), Boin and ‘t Hart (2007).

constitution at the time of the earthquake. For Ebola, the uncertainty lay in the characteristics of the virus, the location of the virus and infected patients, and how long the virus stays in the human body and can be transmitted to another person. Neither of these events were geographically bound. In Nepal, there were certainly locations of physical destruction, but 14 districts were identified as areas with earthquake damage. Damage varied within each of those districts. As a result, the variability in damage meant that there were actually multiple points of convergence

(and medical responders could create multiple points) within what would be considered a very large disaster area, and those points were geographically dispersed. With the Ebola epidemic, multiple outbreaks spread over a large geographic area and no physical damage directly resulting from the crisis prevented pin-pointing a specific disaster location, and yet clusters of affected people and the care centers and hospitals that were set up in response to the medical needs are clear sites of convergence for people, material, and information. Both of these events can be understood as protracted events. The ongoing aftershocks occurring in Nepal months after the initial earthquake, and the continued presence of new cases of Ebola two years since the outbreak began indicate that these events are not temporally bound. Most of my participants were most familiar with working in the United States context (or at least high-income nation context) with all of the infrastructure, resources, and expectations that implies (though my sample includes individuals who were not based in the United States, and/or they had international response experience). Working in the international context stripped away the taken for granted infrastructure and resources and the familiar operations participants are used to. It forced them to rationalize or be more conscious of their decision-making and to think

things out in ways they might not have had to if responding to a domestic event. This study fundamentally endeavored to understand how responders figured out how to deal with disruption. Examining different kinds of disruption allowed for seeing patterns across event type, and the comparative analysis provided a lens for identifying important differences. Some challenges are disaster type- and location-specific (Kovács and Spens 2009). Looking at two events allowed for discussion of broader patterns by moving away from event-specific details. Looking at two events better enabled a focus on the processes leading up to medical humanitarian relief in general rather than the decisions made for any one event in particular. In addition, there is some literature calling for going beyond the individual case study (Kovács and Spens 2011).

Sampling: Organizations Organizations were purposefully sampled for groups that provided an international medical or public health response to the Ebola outbreak that occurred in West Africa beginning in 2014 and/or to the Nepal earthquake. As Phillips (2014) explains, purposive sampling identifies participants for inclusion based on whether or not they fit particular criteria, often including a range of types. The pre-identified organizations were selected to represent a range of types of organizations that responded to these events, from smaller volunteer groups to international NGOs (INGOs), and government responses. To the extent possible, this study strove to include organizations representing each of these types of groups for both events to enable the best possible comparison. By including not just multiple groups but groups representing different types of organizations, I limited the extent to which my findings reflect the particular characteristics or culture of one organization or even one type of

organization to better reflect the underlying processes of planning and implementation that are shared across these groups, and allowing any differences to this figuring out process between different kinds of groups (or different events) to emerge in the data. This sampling approach is similar to that used in work examining organizations’ decisions to contribute to disaster relief (Nelan 2016; Penta, Nelan, and Wachtendorf 2014; Penta, Nelan and Wachtendorf 2015). In addition, it builds on the work of Gralla and colleagues (Gralla, Goentzel, and Fine 2014; Gralla, Goentzel, and Van de

Walle 2015; Gralla, Goentzel, and Fine 2016). In those studies, participants were from predominantly large NGOs/INGOs. The present study expands on the kinds of groups under analysis. In addition to purposive sampling, I used snowball sampling to supplement group representation in my study, in which current participants recommended other potential participants (Phillips 2014). Sometimes they mentioned a group that I was unaware of playing a role in the response. Other times, their recommendations, rather than bringing a new group to my attention, would reprioritize the groups I considered for inclusion, shifting my emphasis on reaching out to those groups. Kendra and Wachtendorf (2003) noted in their work on 9/11 that, though some of the volunteers arrived in New York City with credentials, some kind of affiliation, and/or with useful skills relevant to the response and needed at the time, many did not. This dissertation focuses specifically on the skilled converger. While their convergence may or may not be problematic, the groups I included offered a specialized service (medical and public health care) that requires specialized training and resources. Even when the individuals I spoke to did not converge themselves or have a specialized medical training, their roles as actors facilitating a medical response

still resulted in a focus on skilled converges and skilled facilitators of convergence. [Table 2 lists the organizations included in this study separated by event.] There were some organizations involved in some ways to relief efforts in both events. They appear in lists for events when I was able to interview at least one person who could speak to the response for that event or I had document data from the organization for that event.

Table 2 Organizations With Interview and/or Document Data by Event

Ebola Epidemic Nepal Earthquake Centers for Disease Control and Prevention America Nepal Medical Foundation (ANMF) (CDC) Assistant Secretary for Preparedness and Massachusetts General Hospital, Global Disaster Response (ASPR) Response Team Public Health Service (PHS) Delaware Medical Relief Team (DMRT) Samaritan’s Purse Samaritan’s Purse French Red Cross French Red Cross Team Rubicon Team Rubicon International Organization for Migration Univ. of Southern California, Keck School of Medicine United Nations Medical Teams International International Health Services* U.S. Urban Search and Rescue Team World Health Organization (WHO) WHO, Health Cluster *This organization is a private company that provides medical services to its clients across the globe during disasters and emergencies. They asked not to be named in the study, so the name listed in the table is a pseudonym.

This table lists the organizations which supported at least some kind of relief effort for the event and for which at least one person was able to speak about the organization’s efforts or for which I have document data. More specifically I have interview data for

all of the organizations in the table except for the World Health Organization for both events.4 I have document data alone for the World Health Organization.

Sampling: Individuals The specific individuals who were interviewed for the study were purposively and snowball sampled. I interviewed people who worked in a decision-making capacity within the operation or who had sufficient perspective within the organization to speak to the decision-making process. While several these individuals had some kind of leadership role in their respective organizations, they are better described in terms of their relation to decision-making and the activities on the ground than just their position within the organization. The individuals I interviewed were in positions which allowed them to shape what the relief effort looks like or offer perspective on the decision-making within the organization. As a result, interviewees ranged in position from senior personnel to lower level personnel who were directly involved in some aspect of decision-making, or who were lower in organizational hierarchy, but assumed important roles in the relief activity. In a similar fashion, this dissertation includes interviewees representing a wide range of backgrounds and occupations, including people working in logistics, communications, and managers and doctors, nurses, and public health practitioners, and other kinds of personnel as well. In doing so, I expanded on the decision-making work of Gralla and colleagues (Gralla et al. 2014; Gralla et al. 2015; Gralla et al. 2016) who focused on logisticians, and most of the medical sociology work focused

4 Team Rubicon did not send an organized response to the Ebola epidemic, but they did facilitate opportunities for their members to participate and one interviewee was able to speak to how that decision was made.

on doctors and patients (Austin et al. 2013; Charles et al. 1999; Haider et al. 2011; Kessler 1990; McKinlay et al. 1996; Rapley 2008; Sabin et al. 2009; Whitney 2003). This approach included a wider array of types of actors than in other studies, and actors whose backgrounds did not always match with the kinds of decisions they need to make (i.e., people accustomed to decision-making with regard to how to provide care with existing resources then had to figure out how to make those resources available).

Like with the sampling of organizations, my sample of individuals derived from a combination of purposive and snowball sampling. While I was able to identify some actors by their positions within the organization, I was unable to rely on this approach alone. In many cases, it was difficult to identify the specific actors who were involved in the relief effort at all, let alone those individuals who occupied decision- making capacities. As a result, I frequently relied on referrals from others in the sampling process. In some cases, I started with individuals external to organizations of interest who knew individuals within them. These external individuals served as gatekeepers who could facilitate introductions with key informants within organizations. My key informants were frequently not in positions to be interviewees themselves, but due to their positions in the organization were able to connect me with others, typically through e-mail introductions. They introduced me to others in their organization who either could participate in an interview, or who were better positioned to identify someone who could, referring or deferring my request to another individual better suited to participate either through position in the organization or time available to participate.

Similarly, I approached some organizations through their general ‘contact us’ e-mail addresses for the organizations, and was able to connect with individuals through ‘cold-e-mailing’ them that way. I asked my participants (not just key informants) to identify other actors within their organizations who I should speak with. I identified these additional actors both through open-ended requests for recommendations at the conclusion of the interview (“Now that you know what I am interested in, is there anyone else you think I should talk to either within your organization or in other organizations?”) and requests to be connected with individuals repeatedly mentioned during participants’ interviews. In sum, while I sometimes approached specific individuals based on their fit with the criteria for inclusion I had identified for my study, more frequently, I interviewed people who were recommended to me by others based on their understanding of my inclusion criteria, who I included based on the degree to which I thought they would facilitate answering my research question and their willingness to participate.

There was another important distinction to make regarding their status as convergers. Within personal convergence, Fritz and Mathewson (1957) identify five types of convergers: returnees, anxious, helpers, curious, and exploiters, to which Kendra and Wachtendorf (2003) in their work after the September 11, 2001 terrorist attacks in New York City add fans/supporters and mourners/memorializers as two additional categories of convergers. This dissertation focused on one type of converger: the helper. Specifically, it focused on helpers in the form of those involved in providing and facilitating a medical relief or response effort to a crisis. It is important to note, however, that not every person I spoke with actually went to the site of relief provision. That is, there were some people who were central to the decision-

making process, organizing the relief effort, and coordinating logistics who never actually arrived in the affected areas. Discussions with these individuals, however, still contributed to understanding convergence for two reasons. First, they worked (for pay or in a volunteer capacity) as a part of an organization that converged, even if the particular person I spoke with is not, and thus facilitated the convergence of other individuals, materials and information. Second, by attending meetings and participating in any other support activity, they converged, just not to the disaster site, extending Kendra and Wachtendorf’s (2003) concept of a response milieu further by including these ‘at home’ activities as relevant sites of convergence.

Data Collection

Interviews The primary source of data for this study was interviews with people involved in organizations providing medical and health services related to the crisis. Interviews were conducted by phone and over Skype and were audio recorded for accuracy. Interviews took place from September 2016 through February 2017. According to Phillips, “Interviewing represents the most used method in qualitative disaster research” (2014:66). The study used semi-structured interviews. While guided by points directed at understanding the processes shaping these relief efforts, the semi- structured nature allowed for some flexibility in the course of the questioning, allowed for interviewee story-telling, and enabled me to pursue points of interest as they arose over the course of the interview. Topics the interview addressed included how the group identified needs and resources, who was involved in the organization’s processes (including professional background), interactions within the group and

between their group and other responding entities, the kinds of interruptions and challenges they faced and how they adapted in response to them [see Appendix A for the interview guide]. In addition to these broader topics, I specifically asked about provision of psychological services and what their exit strategies were. Questioning participants about psychological or psychosocial services was important in two respects. First, the psychological needs of survivors are important in their own right. During the field work in Nepal, we encountered people who variously communicated a need for psychological care or support, particularly after the May 12 aftershock. Understanding if those are needs that are even considered when designing a medical relief effort is an important part of understanding how/if those needs are met. Discussing these issues offered specific points around which to discuss how relief workers conceptualized the problems and the relief efforts, and how issues like personnel and resources affected decision-making.

The primary focus of this dissertation was to answer the question of how participants figure out the process of aid delivery. A secondary area of inquiry was “why”, that is, why participants choose to fix in the way that they do. While the process of figuring out or deciding what a group should do is different from the reasons it uses to explain or justify that decision, the conceptual boundaries between the “how” and the “why” behind the design and implementation of a medical relief effort are blurred, and these aspects are functionally linked. Throughout the interviews, several reasons for taking particular courses of action emerged. These are the characteristics of the decision-making setting, decision makers, and decision recipients.

Interview Sample In total, I had 10 organizations included in the study for the Nepal earthquake response and 10 for the Ebola epidemic, for a total of 15 organizations for which I had at least one interviewee. The sample includes 22 interviews about the Ebola response and 20 about the Nepal response, for a total of 36 interviews (again, because some individuals were involved in both events to some compacity and could speak to both responses in their interviews). This is a sufficient number to have representation of different kinds of groups within the organization sample working in different locations. The numbers of organizations and interviews for each event when added together equal more than the total number of organizations and interviews in the sample, that is because some of these organizations individual interviewees were involved in responses to both events. The French Red Cross interviewee I spoke with was involved in that organization for both events. While having a diverse representation of responding organizations in my sample was important, interviewing personnel involved in different events from the same organization was also of intellectual interest and relevance to the study. An implicit underlying assumption or question in my dissertation relates to the issue of parallels between different kinds of events. That is to say, it implicitly examines the extent to which there are similarities in approaches and relevant theoretical explanations between different kinds of crises.

Having some instances in which a group is represented for multiple or all of the events in this study would facilitate this comparison. That said, diversity of group type was important for my study, so having 15 organizations in my sample, of which three organizations had interviewees samples speaking to both events offers a good balance. With regard to the number of interviewees, I was able to obtain at least two interviewees for most of the organizations, and there are several organizations and

individuals within each organization in my study. It was important to interview multiple people for several reasons. They occupied different positions in the organization, both in terms of roles and responsibilities and in terms of organizational hierarchy. This can affect their perspectives in several ways. Some were only responsible for some kinds of decisions and activities, but not others, meaning that interviewing only one person would have given me an incomplete picture of the organizational figuring out process. Their different locations in the organizational hierarchy may mean that they faced different pressures, or may be more or less aware of certain organizational pressures that shape the figuring out process. They had different occupational and training backgrounds and different histories within their respective organizations. While having multiple interviewees does not completely eliminate these issues, nor do I have complete representation of all important perspectives for any single organization, there is sufficient variation to offer insight on how these factors shape the figuring out processes even under similar organizational contexts. Despite my goal of multiple interviewees for each organization, there were some organizations for which I was only able to interview one person. While these organizations did not have the benefit of multiple perspectives, they still offered valuable comparison in the context of the collection of interviews as a whole and the representation of different roles, backgrounds, and relief efforts, facilitating meaningful comparison between responses.

Documents

In addition to the interview data, this project incorporated documents to the extent they were available. There were 32 documents analyzed for the Nepal earthquake case and 36 documents for the Ebola epidemic, for a total of 67

documents: approximately 422 pages of data. These documents include emails and other written communication between decision-makers and others within or outside of the organization discussing decisions, lists of needs, supplies, packing lists, meeting agendas, and news reports about the organizations’ efforts. The bulk of the documents were produced by the World Health Organization (WHO) and the United Nations Health Cluster (led by the WHO). These include situation reports and status updates, and other documents reporting on the status of the earthquake or epidemic. I only have document data for these organization (no interviews or observations). [See Appendix E for the list of documents analyzed for this study.] I referenced other documents throughout the study to confirm claims and add context. These documents served two purposes. First, these documents helped triangulate the data collected during the interviews. Qualitative researchers, including those specializing in disaster research (Phillips 1997; Phillips 2002; Phillips 2014; Stallings 2007; Stern, Deverell, Fors, and Newlove-Eriksson 2014) advocate efforts to support data collection through triangulation, including through the use of documents. This both helped confirm information in the interviews, and fill gaps that emerged in the interview data, be it from memory loss (an issue discussed in Wachtendorf 2004) or failure to follow up on identifying a point of interest during the interview. Second, I obtained those documents prior to the majority of the interviews. This allowed for establishing important points in time and decisions to bring up during the interviews.

Observation

The final source of data I used is observation data from quick response field work. I was part of a three-person research team engaged in quick response field research following the April 25, 2015 earthquake in Nepal. The first phase of this

research began in the United States approximately two weeks before departure. This work involved participant observation of a group associated with a local hospital. This group organized and performed a medical relief mission in Nepal to response to the earthquake. I was present for four of their meetings. Two of these meetings were ones held at an office meeting space at the hospital the group was affiliated with. These were informational meetings in which organizers provided information to volunteers (and potential volunteers) about what currently deployed teams were doing, and about upcoming deployments. They covered topics like team size and structure, how many people would go per trip, how many deployments they would make, transport and supplies decisions, information from Nepal, and travel requirements. The other two meetings were “packing parties” taking place at a small warehouse storage facility. That is to say, while they did share some updated information, the primary purpose of these meetings was to pack supplies to be utilized by the team in Nepal. I had a notepad with me and documented my observations in field notes during the informational meetings. I engaged in participant observation during these meetings. During the informational meetings, this meant attending and listening to the meeting. There was little other activity that required participation. During the packing parties, I worked alongside group members to sort, pack, and document supplies. I typed up notes from those experiences after the fact. During both meeting types, I pursued opportunities to have informal conversations with a range of volunteers, varying by position within the organization, occupation, and past experience with the organization. I had more opportunities to have these conversations with people during the packing parties given their informal structure. During these conversations and observations, I collected additional information on group decisions, including what

they were and why they were packing certain supplies and how challenges, obstacles, and uncertainties and their expectations of what their relief effort experience might be like. By and large, my presence as a researcher was known among the participants. At least one senior level person was aware of my presence and position as researcher, as he was our initial contact in the organization. Most of the meetings involved self- introductions that included occupation and past experience with the organization. I introduces myself at these times, so everyone in attendance at this time learned who I was. In addition, while I did not initiate every conversation with introducing myself, I was very open with people about who I was and what I was doing there when asked. As a result, while I cannot say that everyone knew who I was at any moment, in general my presence was known. I do not feel that this had an impact on the data. One reason is that many of the decisions, while explained in front of me, happened elsewhere. Second, I was not the only outsider present. Not only were many of the volunteers new to the organization, but there were two members of the media in attendance: a journalist and photographer from the Delaware News Journal. These journalists were present at two of the meetings I attended, and accompanied one of the waves of teams to Nepal, documenting their work. This group was not only prepared to have outsiders present and documenting their behavior, but on the two occasions when I was present and the media were not, I could discern no differences in behavior. While it is possible that the similar behavior was due to the continued presence of an outsider (me), my inability to detect guarded behavior (in fact, the fact that I was helping them in the participation component of observation helped combat outsider

status) I generally believe that they did not care that I was there and it had minimal effect on the data. I conducted field work in Nepal along with two colleagues from the Disaster Research Center and a Nepali graduate student who served at the team’s translator. Details of the methodological approach and areas of focus are outlined in Penta, DeYoung, Yoder-Bontrager, and Suji (2016). We were in the field from May 26 to June 10 of 2015. The purpose of this field deployment was to understand the social impacts of the event and relief efforts, the relief activity taking place days and weeks following the earthquake, and social factors shaping post-earthquake experiences. In particular, we were focused on NGO coordination, the medical response to the event, and the post-disaster needs of new mothers and young children. We focused data collection predominantly in the Kathmandu area, though we did branch out to the communities of Bhotechaur, Sankhu, and Ramkot during one day of data collection. The reasoning behind our decision to focus in the Kathmandu area parallels that of

Wachtendorf, Kendra, Rodríguez, and Trainor (2006) in their quick response study of the Indian Ocean Tsunami in 2004, namely that our connections and the concentration of activity related to our research interests were concentrated in the Kathmandu area, and access concerns combined with limited time available in the field directed us to stay in the capital city. This data will be useful in terms of identifying issues important to the medical response to explore in my data collection.

Human Subjects Considerations

I did not promise confidentiality for my participants or the organizations they represent. I did not make this promise for several reasons. First, given today’s electronic security environment, I determined that that it was unreasonable to make

that promise and expect that their identities could remain confidential under any and all circumstances. Second, while I did ask about a medical response, I did not ask for specific medical information about any patient in particular, only what kinds of services were offered, needed and utilized, therefor there are no privacy concerns in that regard. Third, that many of the organizations I sought out were involved in the response to these crisis is both well-known and well-documented. It is possible that enough information may emerge in my dissertation that participant’s identities could be determined. However, I did not identify by name the individuals I included in the study. Since their positions, responsibilities, and activities within the organizations and relief efforts were all relevant to my study, I sometimes described the positions, backgrounds, and responsibilities of my participants. In this way, I did not identify their specific job titles, but presented sufficient information to understand the data the interviewee presented. These expectations regarding the lack of confidentiality versus exposure were outlined in the informed consent forms participants were required to sign for a recorded interview, enabling them to make an informed decision about participation in the study. At the organizational level, many organization names are recorded in reports generated by international agencies such as the World Health Organization and the

United Nations High Commissioner for Refugees among others. In addition, organizations participating in these relief efforts (both large and small) are frequently identified in media coverage, making their participation publicly available. Further, these organizations typically highlight their involvement through their own communications, including information posted to their websites. As such, it is highly likely that someone reading my dissertation and subsequent publications using this

data could reasonably assume or determine at least some of the organizations in my study. Related to the previous point, the organizations that will be included in my study are public, or as charitable organizations, have similar expectations of transparency in order to maintain credibility with their donors. Any effort undertaken by a government organization funded by tax payer dollars is often available to the public. In a similar way, NGOs and INGOs frequently pursue transparency in their activities because of their reliance on donor dollars, meaning they are expected to be up front about their activity. As such, much, if not all, of the areas I wanted to discuss are already under or available for public scrutiny. In addition, it is not the purpose of the study to evaluate the success of these groups’ efforts. As a result, I anticipate no harm to my participants as a result of their involvement in my study. While situations of a disconnect between a need and service provided did emerge and are of interest to me as events offering opportunities to explore the processes leading to that disconnect, it was not the intent of this dissertation to decide if that activity or the effort as a whole was ‘good’ or ‘bad’. I cannot control how others might use or interpret my dissertation findings, but that my dissertation does not strive to evaluate the quality or effectiveness of these efforts should decrease concerns about any sort of harm coming to the organizations or participants in my study. The benefit of being able to state explicitly what organizations are included in my study is that it allows for the clearest representation of what kinds of organizations the findings I produced reflect, and could offer a clearer outline for future research as myself or others reveal limitations in my sample.

Analysis

Overall Coding Summary I coded the data using Atlas.ti software. I coded for two phenomena: the processes (how) underlying the organization and implementation of a medical relief effort, and the justifications/reasons/influencing factors shaping decision-making though not processes in and of themselves. The latter are the criteria that may be considered or evaluated in the figuring out process. The coding process I used for the analysis of this data will utilize both open coding and deductive coding processes. I will begin my analysis with the use of first cycle coding, relying on process coding, In Vivo coding, subcoding provisional coding, values coding, attribute coding, and open coding in the process of analyzing the data. Both Saldaña (2013) and Miles, Huberman, and Saldaña (2014) explain that these multiple coding techniques can be used simultaneously in the same project and can be combined as appropriate. I followed this with second cycle coding in which built on the first cycle codes to form codes of greater theoretical meaning and significance, ultimately identifying five themes in the data (Miles et al. 2014; Saldaña 2013). In all aspects of the first cycle coding, I utilized provisional codes and open coding. Essentially, I began with parts of an incomplete picture of decision-making and problem solving based on the literature. However, given the limitations in the literature, it was unclear how incomplete a picture this may be. Based on the literature review, I had ideas about the kinds of processes individuals in groups may undertake and what may shape those processes. Because I had reason to expect that they would appear in my data, I anticipated their presence with provisional codes that I deductively applied to the data to the extent that they were useful to capture

phenomena in the data. That said, many of these provisional codes fell short. Some of these codes did not appropriately capture the processes at play in my data. As a result, I remained open to other codes as well. I adapted some of the provisional codes, and used open coding, which allowed me to more fully capture processes I saw emerge in the data. Below, I discuss the coding approaches for the “how” and the “why” components separately.

Analyzing the “How” To understand how the personnel involved in the medical relief mission figured out their approaches to relief, I relied predominantly on process coding. Process coding uses words in gerund form to capture actions and activities (Miles et al. 2014; Saldaña 2013). Specifically, they capture “observable and conceptual action in the data. Processes imply actions intertwined with the dynamics of time, such as things that emerge, change, occur in particular sequences, or become strategically implemented” (Miles et al. 2014:75). Coding in this way helped me to stay focused on what actors (captured in interviews, observations, and documents) did rather than why they did it. Many of these process codes were also open codes, some were In Vivo codes, and some contained provisional codes and subcodes. As an example of how my coding process worked, one of the themes that emerged was developing situational awareness. My coding initially captured activity related to obtaining information. Codes included “exchanging information”, “seeking information”, “identifying need”, “identifying resources”, “sharing information” along with some epidemiological terms in gerund form of “tracing contacts” and “surveilling.” At the same time, I was capturing data about working with the information. These codes include “assessing”, “comparing”, “contextualizing”,

“situating in time”, “vetting”, “reviewing”, “confirming”, and “questioning.” These activities were generally organized around two broader categories of activity: (1) gathering and communicating the activity, and (2) processing that information. Through closer examination, I realized that while obtaining and communicating the information was different from how groups and individuals worked with it, these categories of activities were linked. Both sets of activities were contributing to the same larger process: developing situational awareness.

The data revealed three themes that emerged around processes responders used in planning and implementing the response: developing situational awareness, working with boundaries and definitions, and matching and aligning. These processes were ongoing throughout the response.

Analyzing the “Why” In analyzing the “why” component of the study, I again used a combination of inductive and deductive coding, looking for concepts identified in the literature and open coding to capture aspects that emerged as important in my data, utilizing values, attribute, In Vivo and subcoding with open and provisional codes. I generally open coded for the reasons given for a particular action or decision. Based on literature indicating the importance of values in decision-making and humanitarian/disaster relief (Gralla et al. 2016), I looked for values as they related to why particular approaches or processes were taking place. Based broadly on my literature review, I use provisional codes that reflect the three general components identified as affecting decision-making: “characteristics of the decision-maker”, “characteristics of the recipient”, and “characteristics of the decision-making setting.” Even though change is often captured through process coding (Miles et al. 2014), I want to keep these

characteristics conceptually separate from the processes my participants are engaged in. This final code, CDMS (characteristics of the decision-making setting) is where I captured disruption associated with the ongoing crisis events, including disruption in supplies, needs, in the presence of other groups, policies, legal aspects (such as treaties, deals, and requirements) and changes in the event itself (ex: additional aftershocks). This is also where issues of time and uncertainty came into play. While I used this code to capture a broad array of characteristics, I subcoded specifically for four characteristics in this area. I subcoded for uncertainty, since there is literature indicating that uncertainty in particular is important in shaping decisions making processes (Fox 1980; Rathore et al. 2009; Sabin et al. 2009; Vakey et al. 2009). My decision to do so was further supported by the data as it emerged as an important part of the relief efforts in the data. The final three sub codes are personnel resources, material resources, and information resources. Resources themselves have been shown to be important in decision-making (Fink 2013; Mackersie 2006a; Mackersie 2006b; Salomone 2006). I have distinguished between these three types of resources to correspond with the three types of convergence Fritz and Mathewson (1957) identify, both because this distinction is both well-used and has had staying power in the disaster research community, and because humanitarian response reflects the intersection of these three types, so capturing how processes related to each of these are interconnected was important for understanding the organization and implementation process. Ultimately, the data revealed that these reasons for taking action were all grounded in one larger theme: characteristics of the decision-making context, which included characteristics of the event, social, political, legal, and

cultural environment, the physical environment, and the three forms of convergence (informational, personal, and materiel).

Additional Coding In addition to the information outlined above, I captured characteristics pertaining to the interviewee, including position, experience, what their roles were in the response, the organization they were with, and where they were and what event they responded to. These will further capture the characteristics of the decision-maker (they likely discuss decisions they know about or witnessed but did not make themselves), and are important for understanding what perspective I am getting in the interview. Finally, I used causation coding, used to capture the way participants perceive cause and effect relationships (Saldaña 2013), and “interrelationships, and the complexity of influences and effects on human actions and phenomena” (Miles et al.

2014:79). The causation coding captured relationships between activities with processes and between processes as well. Likewise, as I have indicated the “how” and the “why” are functionally linked, and the causation coding captured those links. The causation coding revealed that the processes of developing situational awareness, defining and bounding, and matching and aligning were all connected. They were linked in a kind of feedback loop in which aspects of the decision-making context, captured in the process of developing situational awareness were then defined and bounded. Those definitions and boundaries guided further development of situational awareness and the matching process through which decisions were made. The outcomes of these decisions became a part of the decision-making context, feeding back into the cycle. These relationships revealed the final theme of decisional inertia.

Chapter 4

CHARACTERISTICS OF THE DECISION-MAKING SETTING: CONDITIONS AFFECTING DECISIONMAKING AND THE RESPONSE

Introduction The characteristics of the context in which people and organizations worked to provide medical relief emerged as important in the design and delivery of those services. Some particular aspects of the decision-making context were more salient in some of the data sources than in others. Likewise, some of these aspects were explicitly mentioned in the documents or by participants in the study, while others were implicit themes in the data that emerged through the course of the analysis. These characteristics emerged not just in the frequency with which they appeared in the interviews, observations, informal conversations in the field, but also in their repeated use in documents. Their importance was emphasized in the structure of the reports and other documents to the extent to which the contents was organized in a way that consistently discussed and highlighted particular information. In all, there emerged a picture of features of the environment that shaped the effort as a whole. Among those themes are features of the physical environment in which relief workers were operating, the infrastructure—medical and otherwise—that existed within the affected countries, the safety and wellbeing of the personnel involved in the response, the uncertainty of the situation and knowledge of it, and a diverse and numerous array of actors. Many of these characteristics can be understood in terms of their relationships to the three types of convergence: personal, materiel, and informational convergence. Many of the factors presented simultaneously and interacted with each other to further complicate the relief environment.

In this chapter, I review these characteristics of the decision-making setting significant for the response as revealed in the data. I begin with discussions of characteristics of the decision-making setting regarding characteristics of the event, the political, legal, social, and cultural context, and the physical environment and nature of the hazard itself. I follow this with discussion of characteristics relating to material resources, personnel, and information. As will be noted in the rest of the manuscript, these factors and conditions influence decision-making by emerging in all three processes, serving as a force that restricted available options, and served as the force that opened up new opportunities, which could enable the relief efforts to shift in new directions.

Characteristics of the Decision-Making Context

Characteristics of the Event Characteristics of the event itself influenced decision-making. One important characteristic was the ongoing nature of both of these responses. The first case of Ebola occurred in December of 2013 (though it was identified after the fact), and cases continued on into 2016 (World Health Organization 2015n). The height of the Ebola epidemic lasted for less than this approximately two-year time frame. However, there was still a prolonged period in which substantial numbers of people continued to be infected. The Nepal earthquake took place on a shorter time scale, but a time scale that still continued beyond the initial earthquake to encompass the series of aftershocks that took place in the days, weeks, and even months following the first earthquake, including the 7.3 magnitude aftershock. The protracted event timelines for the two crises necessitated an extended response, and therefore, demanded human, financial,

and material resources over an extended period of time that could prove challenging for organizations to provide, particularly in the Ebola response. In addition, the Ebola virus has a long incubation period: 21 days. This means there are 21 days between when an individual is infected with Ebola and when they develop symptoms. This period of ambiguity prolonged uncertainty about the status of any particular individual. It further complicated the response by prolonging the amount of time deployed personnel involved in direct patient care would have to be away from work

(since many were quarantined/isolated upon return). Related to the long duration of these events and responses was the dynamic nature of the event. The events were not static. Conditions were changeable. Ebola Virus Disease continued to appear in new patients which opened up new areas for response activity. Further, the discovery of sexual transmission of the virus from a survivor to another individual had serious implications for the response and relief work in that event. Likewise, the aftershocks following the initial earthquake caused damage and expanded the affected region that relief workers needed to operate in. As these conditions changed, relief workers and organizations had to gather and process information. In the same vein, specific characteristics of the populations affected by these events were key features of the operational context shaping decision-making. Data from the interviews, documents and observations indicated that, in Nepal, many of the people most severely affected and in need of help were in the rural areas. The Ebola epidemic took hold in urban areas, and t healthcare workers as a population were infected and at high rates. These characteristics of this epidemic had important implications for the response, as it diverged from previous outbreaks. The other

important component of the affected population in the Ebola epidemic was that significant numbers of healthcare workers were infected due to their roles in providing care for and interacting with infected patients. This last point is linked to another key characteristic of the event that influenced the relief efforts: the way the hazard agent caused harm. In Nepal, this was predominantly due to falling buildings (or landslides in rural areas) from the shaking or, later, as a consequence of structural weakening initially caused by the earthquake. For the epidemic disaster, the disease—Ebola—is spread through close contact with bodily fluids. The scope, level of severity, and level of novelty of these events (Fritz 1961; Levine 1982) were important in shaping the planning and implementation of health and medical relief efforts. Affected populations were spread out over a wide geographic area. This was especially true of Ebola, which ultimately reached far beyond the initially impacted countries of Guinea, Liberia, and Sierra Leone, to affect Nigeria, countries in Europe, and the United States. Several interviewees who participated in the Ebola response commented on the extreme nature and uniqueness of that epidemic and response. One Public Health Service (PHS) member who deployed noted that the scale, scope, and challenges of Liberia were unique. Another interviewee said that the distribution of infection in Monrovia was surprising because it hit all sectors of society, all over the city—even remarkably prominent people became ill. Even the specific strain of the virus—the Zaire strain—was the deadliest strain of the virus.

Conversely, the severity and novelty were not as striking to participants who responded to the Nepal earthquake as they were to the Ebola responders I spoke with. Those who had participated in Nepal relief efforts certainly acknowledged the

hardships that effected individuals were facing and the larger consequences for the country, but in general, they considered the Nepal earthquake as less severe than other disaster events that had occurred or that they had specifically responded to, earthquakes and otherwise. Some indicated that this earthquake was less severe than what the Nepalese government anticipated and planned for, according to some sources. In this way, the 2015 Nepal earthquake presented some conditions that were unanticipated because they were surprisingly favorable when compared to what some responders expected to face. In the interviews, several participants had experience responding to different kinds of crises. By comparing responses to different types of events, they discussed many of the ways that characteristics of the event itself affected relief efforts crafted to address them. The following quote comes from one interviewee involved in the public health response to Ebola. Reflecting on her involvement in natural disasters, epidemics, and peacebuilding responses, she elaborated on several ways these event characteristics are important for response and relief efforts:

The thing that’s closest to epidemics is actually violence. The thing about natural disasters is they happen, and then it’s a single event, I mean as we know, no disaster is purely man-made…there’s inherent vulnerabilities, and most natural disasters now happen in the context of complex emergencies, so yeah, all of that aside, that’s a given, that’s well known, a natural disaster is an event, it happens, and then there’s more linear path forward. The bad thing is over, and now you just have to figure out how to build back from it, and there’s’ not the same pressure of time. You build back as fast as you can, but--the best way that you can, but the bad dark thing is over. It is an event. The thing with both violence and epidemics is that they’re unpredictable. You can think that you’ve quelled them and they pop up somewhere else. They spread.

Violence, just like epidemics, spreads like a contagion, from person to person, area to area, there’s things that you can do to help people

become immune from them, but it’s not always enough, and the fact that people kind of are vectors of—people can be vectors of bad violence and they can be vectors of disease….There’s no human face that caused the disaster, but whether it’s disease or violence, ultimately there is a person that the harm emanates from, whether unwilling with the disease, or willing with violence. It creates whole issues around stigma and distrust and fear, that you do not get in a kind of traditional disaster response., and at the same time you have to work with those people either the people who are affected or the people who are participating in violence, they are still people, and they have...they need to be part of the solution, they’re not just vectors. She went on to say

And that’s the problem, you don’t know where… it’s not a single event, it’s a series of events, and you can’t let your guard down. And that happened [in the Ebola response], we could see people during this one kind of lull in the response, we thought we had it down to one—it was one area… we had extinguished it and we thought it was victory, and everyone was getting relaxed, and it was like “oh this is great”, and then it pops up again in the forest area and everyone has to remobilize and revamp all the engines. That’s not going to happen with a hurricane, it’s not going to happen with an earthquake in the same way. So there’s that sense of making sure that this state of weird vigilance where you don’t want to be paranoid, and you don’t want to burn yourself out, but you can’t ever relax your guard because it’s when you relax your guard that things go wrong. And again, with both of them, it just takes one person to relaunch an entire epidemic. It just takes one person to relaunch a war. The margin of error is so slim. If you are rebuilding houses and you miss one house, it’s horrible for that family that doesn’t get their house, but the lack of that house is not going to cause another earthquake. But with violence and epidemics, if you miss that one person, they can relaunch everything, and everything you’ve worked to can come back to zero.

The advantage of working with epidemics versus working on violence is that with epidemics, even though the disease has a human face, the disease is a disease. The disease, it doesn’t choose to infect people, it doesn’t have an ulterior motive, it doesn’t have a choice. People might facilitate it’s spread through negligence or whatever, but ultimately, it’s a biological thing doing what it’s programmed to do. With violence at some point, there is people are deciding that someone else doesn’t’

deserve to live. And so, emotionally, I found working on Ebola a lot easier than working on issues of violence and conflict. Several other interviewees from both events echoed many of the points this participant articulated above. She concluded by saying that she and her boss agree, “There’s a hierarchy here. Natural disasters are the easiest, then it’s epidemics, and then it’s conflict.” Identifying the events as international events was important as well, since it had implications for the political, legal, social, and cultural context.

Political, Legal, Social, and Cultural Context These crisis events were taking place in political, legal, and social contexts. These contexts shaped experiences of affected populations and responders, and influenced the decision-making behind planning and implementing, including the relief efforts themselves. One important component of this context was the other organizational and individual actors involved. Other organizations’ presence and activities changed over the course of the relief efforts offering potential resources and creating challenges. In addition to organizations, specific individuals rotated in and out of the crisis relief efforts. This meant there were few people who saw the relief activity from the beginning to end, and that personnel sometimes left just as they adjusted to their roles and built relationships. Interview data indicated that this was especially problematic in the Ebola response. As one interviewee said about deployed staff, “they would just begin to have a really strong bond with the Ministry of Health officials and they would leave.” In addition, the disconnect and unfamiliarity between converging personnel and the local context meant they were “not as literate” in the context and were much less likely to see the consequences of their actions.

There were laws and policies in place guiding behavior. These included, for instance, laws within the affected countries regarding what materials, such as medications, could be brought into the country. This legal context was also reflected in lack of legal guidance. As an example, one Centers for Disease Control and Prevention (CDC) interviewee working in the Ebola response noted differences in privacy laws and policies compared to those in the United States. Similarly, another CDC interviewee described how the international nature of the response and the specific nature of the event as an epidemic meant the situation was characterized by a lack of clarity in procedure. Comparing the international public health response to domestic disaster response, he stated that in “Ebola specifically, now Zika, any large infectious disease response is more complicated than the frames of reference that many people in homeland security and the defense department understand,” because “With these large public health infectious disease outbreaks, there’s no Stafford Act.” Whereas in the United States, the Stafford Act offers guidance on disaster response,

(generally natural disasters, he noted), and state and national actors have a general understanding of their roles and activities, those frameworks and that familiarity did not exist for this type of event and at the international level, making the response much more complex

Other international guidelines on procedures comprised this context as well, such as those set by the United Nations (UN) and World Health Organization (WHO). Many groups, mainly those responding to the Nepal earthquake, noted expectations that converging organizations register to participate in the response. This was noted in one of the situation reports for Nepal:

Foreign medical teams have been given clear instructions on the protocols and guidelines for work in Nepal, and have almost

universally registered and been given license to practice in the country. (Sit rep 7 2 May 2015, p 1). Critical to note, however, is that some of the interviewees indicated that not all groups complied. International coordination structures utilized in the Nepal response, such as the UN cluster system and particularly the health cluster, contributed to this context (even though the level of direct engagement varied with each group). It included international treaties and agreements guiding the movement of government personnel from one country to another. Moreover, it could include the policies set within particular organization guiding behavior, such as U.S. State Department policies for government personnel deployments. Some interviewees suggested that there were political motivations guiding relief activity. Interviewees from U.S. government entities that responded to the Ebola epidemic believed that there was a political component to the U.S. involvement. One interviewee, for example, talking about international relief efforts broadly indicated that the purpose of such relief was to win over “hearts and minds.” Another discussed

“the influence of politics.” He believed this was more significant in international responses than domestic ones. Though he was not in a decision-making position when it came to deploying, he speculated that political dynamics played a role in the decision. He explained,

Ebola was there going on for a couple years, and then we send four teams kinda towards the end…. Part of the reason—no one will say this, but there’s an interesting coincidence of agents deploying while those three west African countries… (Guinea, Sierra Leone, and Liberia) was being so heavily impacted by Ebola that it was beginning to destabilize their governments….So when you have destabilization of the government, and [when you have] citizens all over the place—if we had to bring American citizens back from all three of those countries because they had a right to be here and we want them to be safe ‘cause if the government became so destabilized it moves into a civil war,

things like that…how are we bringing like thousands of people back … who are in high risk states? So, I would venture to say it was a better, more strategic and tactical decision to send us there than to bring them back. He added that “…by sending us there, it helped stabilize the government because at least in Liberia the United States is highly regarded, and ‘ok, so the Americans are here. We’re good,’ you know?” Government legitimacy appeared to be a concern in both cases. However, beyond these perceptions, I did not find clear indications of this kind of political influence. That said, these perceptions among participants are still worth noting because, whether or not these political motivations were actually present, these perceptions did shape how participants interpreted and understood the decisions and activities that took place. Characteristics of the locations and communities that relief organizations worked in were another important part of the context that influenced the planning and implementation of the relief efforts as well. According to one interviewee, aspects of the response “needed to be vetted through cultural and historical lens” Facets of the culture and social dynamics in areas where relief organizations operated emerged as important as well. For instance, several interviewees from the Ebola response noted the role local burial practices played in spreading the disease, since traditional practices involved interacting with the body and contacting bodily fluids. One interviewee went further, highlighting how women’s traditional role in dealing with sickness increased their exposure to the virus. Similarly, other cultural influences appeared to emerge as a result of the crises themselves. In Nepal, interviewees noted that as the aftershocks continued, and particularly after the May 12 aftershock, there were severe consequences on survivors’ mental health. This was apparent during our time in the field. In the Ebola epidemic

response, one interviewee from the International Office of Migration (IOM) noted that when she was working in the field (well into the recovery), programs specifically discussing Ebola were poorly received as local populations were both tired of dealing with the epidemic and were angry—feeling that they were only being treated as possible vectors of disease—and, by extension, that their wellbeing was only cared about to the extent that it would help prevent the spread of Ebola. Tensions due to the epidemic were palpable earlier in the Ebola response. Take the following story from one CDC participant who was one of the first CDC responders in Liberia:

We walk into his office, and sit down and eventually open the discussion and literally the first sentence his secretary comes into the room and says, ‘We have to evacuate the building. There’s a fire.’ To cut a long story short, there was indeed a fire, and somebody— rumor has it. I don’t know if this is true. I don’t know whether it’s an urban myth or actually is true. I think it is true—somebody, an angry member of the community, angry at what was happening, and I think one of his relatives had died of Ebola, went into that conference room I described earlier, piled the plastic chairs together, poured kerosene over them, and set it alight. So, this is an arson attack on the Ministry of Health. Really quite severe, and we hurried out of the building and moving down the stairs, there was thick black smoke on the stairwell, and I thought ‘My gosh, this is really getting serious. We gotta get out of here.’ You know, hundreds of people milling around in the car park, who had evacuated the building, we get all our CDC people together, and we leave, and indeed this had been someone trying to set the Ministry of Health on fire. Um, these are not everyday events, obviously.

There were a small number of instances in which interviewees noted security concerns. However, these concerns were generally considered to be isolated incidents, and not reflective of the larger environment. Many interviewees never mentioned any sort of human security concern. Thus, concerns about interpersonal violence, though appearing in the data, were not a substantial concern among the interviewees present here.

Socio-political context related to the recent historical contexts of the affected countries comprised another component of the operational context. Several interviewees noted recent histories of civil conflict in the countries affected by the crisis. Consequences of these histories then shaped the context in which the events and responses took place. Nepal, for example, lacked a constitution at the time of the earthquake. The country was in the process of writing a new constitution and setting up a new government when the earthquake occurred. While there were government entities in existence, the fact that the country was in state of transition came through in planning and implementing the relief efforts. Similarly, one interviewee working in Guinea noted that elections took place while she was there, which affected her organization’s work, affecting mobility and raising concerns that there would be increased infections as the elections drew large crowds of people at a time when the Ebola virus was still present in these communities. The aforementioned examples focus within countries, but past and present social and political dynamics between countries played out in the relief efforts as well. Some of the interviewees thought that the West African nations’ colonial era relationships influenced international support converge patterns, claiming that the British had a stronger presence in Sierra Leone, the French in Guinea, and the

Americans in Liberia (though these boundaries were not hard and fast). One interviewee did offer some nuance to this, indicating that while those colonial relationships were something she expected, she found that in Guinea she could see the legacies of the country’s previous relationship with the Soviet Union in the locations of the schools where many of the local doctors had received their training.

The experience of Team Rubicon in Nepal offered one illustration of how historical relationships between countries could open up resources. Team Rubicon, a veterans-based organization with strong ties to military, began as an American-based group responding to the Haiti earthquake in 2010. Shortly before the Nepal earthquake, a branch of the organization was undergoing establishment in the United Kingdom. When the earthquake took place, members from Team Rubicon UK became involved in the relief effort, alongside members of the American organization.

Historically, the British military had a relationship with the Gurkhas of Nepal. It was because of those historical connections that Team Rubicon UK, and by extension, the larger cohort of Team Rubicon personnel, were able to forge a collaboration between the groups. In a different example, as a land-locked country, everything coming in to Nepal had to go through another country (India and China), even if just through their air space. Relations between Nepal and its neighbors, then, affected how those resources came in. Several interviewees noted that the latter in particular became an issue later on after the earthquake when India implemented an embargo on fuel coming in to Nepal through the India-Nepal boarder. Although the response period was over by that point, and work had transitioned to the recovery, one interviewee noted that this embargo affected their work because fuel (which was needed to transport their building supplies to rebuild health posts among other activities) became more expensive (and harder to get).

Physical Environment

The physical environment was another important condition that relief workers had to consider in planning and implementing the health and medical relief efforts. One feature of this environment that was important for the relief efforts in both cases

was the remoteness of the affected countries, and therefore many of the affected populations. Affected populations for both cases were remote. This remoteness emerged on two levels. First, because this was an international response for the groups I included in the study, the affected country was remote in terms of the sheer distance from the point of origin for many of the relief teams. The majority of interviewees came from organizations based in the United States. For individuals deploying from these groups, getting to the affected area required at minimum a long flight that crossed an entire ocean. One interviewee elaborated on the remoteness of West Africa at length:

Liberia is so remote… It is closer to Rome than it is to Johannesburg, or to Pretoria, or Cape Town. It’s closer to Rome than it is to Nairobi, Kenya. The closest medical care, actually, upgraded medical care, is probably Brazil. It sticks out so far into the Atlantic, it’s almost under Iceland, if you want to go with the uh, I guess it’s longitude. So, it is really remote out there. It’s almost as close to London—It’s almost closer to London than it is to Cape Town. It’s so remote, the HIV disease hasn’t penetrated it, there’s higher rate of HIV disease in Atlanta, Georgia, than there is in Monrovia. People don’t go there. …it is really remote. Even by African standards, it’s remote. It’s ah, for military, when we have military operations going there, it’s probably a three day turn around to get somebody there, to fly a plane directly down there and directly back, to Aviano, Italy, a NATO base near Rome. It’s a long way down there. He added, “It’s hard to get there…. This is probably the most remote place in the world other than Antarctica. It’s just that part of Africa.… And again, the HIV disease is the example I always give. It’s so remote that Africans don’t even get over there.” This distance increased the transportation cost for team, which, in turn, demanded teams have greater confidence they would be needed and—at least for some teams— that those deploying would be available for longer periods of time than what could be acceptable for a local, domestic deployment (my sense was that this was more of an

issue for the some of the NGOs, especially smaller groups). Further, the substantial East-West distance had the consequence of making communications between deployed individuals and their home bases more challenging because of the substantial time differences. One Team Rubicon respondent spoke of how confirming information regarding travel was complicated, as to get the message to Nepal, they had to get in touch with the specific person, who may very well be in a remote location. That person would then have to respond to the message, significantly lengthening the amount of time it took to get information and make decisions. Particularly in the Nepal response, the long travel time resulting from this physical remoteness (a full day and night of travel) further amplified the need for the organizations to work quickly to get people into the affected area in order to meet needs. The challenges of remoteness did not end with simply getting to the affected country. Once in country, the specific areas in need were often remote. Affected populations were located in areas geographically distant from points of entry to the country and the locus of organizational operations. These challenges resulting from physical distances were compounded by the physical terrain. Many of the affected communities in Nepal, for instance, were not just rural areas, but communities in the more mountainous regions of the country. The ability to navigate the terrain was further worsened by the poor transportation infrastructure in much of these areas. Several interviewees who went to Nepal and ultimately ended up working in those more remote regions commented on how difficult those areas were to reach. They had to travel for hours by road. In many cases, those roads were already in poor condition before the earthquake, and their condition worsened with the shaking. Earthquake- induced landslides obstructed some roadways, and made traveling in some of these

areas more dangerous. Once they reached the end of the road, many of these individuals then traveled by foot to reach communities. In West Africa, Ebola relief workers faced similar road infrastructure difficulties, and even some limitations in terms of air transportation. One Samaritan’s Purse interviewee noted that they (that organization) had built most of the airstrips in Liberia, and offered them to others for use in the Ebola response. Of course, another important environmental component shaping the relief efforts were the public health and medical infrastructure. In both cases, the affected countries had medical and public health infrastructures incapable of meeting the regular demand for healthcare. Not only was this true overall, but the distribution of those healthcare services was such that some areas had much worse access to health care than others. In both cases, the crises exacerbated those conditions. In the Ebola epidemic, it did so by infecting and killing healthcare workers. In Nepal, long term consequences were felt throughout the country as the earthquake damaged health care facilities. These facilities ranged from a large hospital in Kathmandu to small health posts located throughout the rural areas. These health posts did not offer the same level of advanced care as the larger Kathmandu hospitals could, but performed an important regular role in supporting the health of the communities they served who may otherwise go unserved. One health post we encountered approximately a two- hour’s drive outside of Kathmandu had offered several services to patients including laboratory services, OBGYN and family planning, among other services, and provided some space for in patient care where patients could spend the night at the facility. After the earthquake, although still standing, the building was unusable, and many of their services were no longer offered.

The climates of the affected areas in both cases influenced the response. Both Nepal and West Africa were very hot while people were engaged in relief work. In the Ebola response, some interviewees noted the impact that working in intense heat and humidity could have on their work force and the jobs they were doing. It could limit the amount of time they engaged in particular tasks (especially when those activities required wearing all of the layers of personal protective equipment, even though the Monrovia Medical Unit (MMU) where the Public Health Service worked was air conditioned). One interviewee even suggested that this played a role in shaping deployment durations (or at least helped to reinforce the deployment durations once the decision was made), suggesting that the length of the deployment took into account not just that personnel would be working long hours, but doing so in intense heat and humidity. In Nepal, monsoon season was a specter on the relief and recovery horizon, which influenced decision-making in multiple aspects of the response, relief, and recovery activity. Its significance for the health and medical response lay in its potential effect on access and health conditions. The monsoon rains would further isolate many communities potentially in need of help. Some of these remote areas are routinely inaccessible during the monsoon season, and some relief workers expected that the earthquake’s effect on the land would increase the mudslides normally experienced during this extended period of heavy rain. In the documents, it was clear that people working to support survivor health were concerned about the consequences negative environmental conditions would have on the health of people living in tent camps. They were concerned because of survivors’ exposure to the rain from poor

housing, and because of the heavy rain’s potential to compromise sanitation in these areas and facilitate disease spread.

Resources

Informational Resources There was a great deal of information that was important in planning and implementing the relief efforts. This information can be broadly categorized as information to inform the services they would provide (information about the affected population), and information necessary to provide the services (information about the response). That is, they needed information about the problem they were trying to address, and then information surrounding how they would figure out how to address it. This information included data on the number and location of affected people and how they were affected (specifically what kinds of health consequences). Interviewees indicated that knowing the rumors circulating in an area were important too. In the words of one interviewee “rumors were everything. Everyone had to know the rumors.” They needed to know about the existing resources available in the affected area, such as existing medical supplies and services and the extent to which they were affected by the crisis. Information about other converging groups, including their capabilities, activities, and locations, were important. Once their personnel were in the affected area, they kept track of how many of their people were in the field, where they were, and what they were doing. This was in addition to acquiring information about potential partners. These groups, and the individuals within them, sought information about what support resources were available for their teams, such as housing options and food availability. As people began to transition roles from some

individuals to others, incoming personnel sought more information about the specific role they were filling. Of course, information about the hazard agent itself was important in the response. For the earthquake, that involved an understanding of the magnitude, depth, and location of the earthquake and aftershock, and the stability of the buildings and land that remained. In the Ebola case, this included information on the particular strain of Ebola, the symptoms associated with the disease (how the disease presents in an infected individual), means of transmission, incubation period, and for how long an individual is contagious. In addition, information about other simultaneous or contextual activity that could influence the response was important. Thus, we can understand relief workers seeking both expert knowledge about the hazard and response, and situational knowledge. There was an emphasis and high value placed upon getting on the ground information, that is, information from the affected area where they would be operating.

Uncertainty Uncertainty was a frequent feature of the response context. Relief workers and the organizations they were affiliated with consistently dealt with challenges of insufficient information during the responses, though the way this challenge emerged varied over time. This uncertainty took two forms: an absence of or lack of clarity in needed information, and a constantly evolving understanding of the operational environment.

Looking more closely at the first form, responders frequently faced a shortage of information they required, or at least would have liked to have had in guiding their decision-making in the implementation and response. For example, personnel faced

unfamiliarity with the working environment. This included information about the countries and the specific conditions or spaces in which personnel were working and procedural uncertainty. One Public Health Service (PHS) participant who deployed to West Africa noted that PHS personnel never worked in Expeditionary Medical Support (EMEDs) facilities (the U.S. military medical structures that were used for the Ebola treatment units). This person claimed that many in the organization did not even know what they were and required orientations to working in that space. Another claimed that questions of what to do if an expat gets infected had not been fully considered by many of the responding organizations (especially the American government organizations) before the epidemic. They had assumed the individual would stay where they were, but that meant that many aspects of the process had not been systematically thought out before the epidemic. Several interviewees deploying to Nepal stated that they had a general idea of what they would do and where they would go once in the field, but that many of the specific details were unknown and flexible. In the Nepal response, there was a lack of knowledge about the existence and location of all organizations involved in the health and medical response. There was additional uncertainty around the extent to which the health problems presented to the healthcare workers operating in these two contexts were actually due to the crisis to which that the group was responding. One Ebola response Public Health Service interviewee noted uncertainty regarding the evolution of the disease and the difficulty in diagnosing Ebola. He noted that there were different ways it may present, and that it looked like malaria. Another interviewee from a private organization similarly noted the symptom similarities between Ebola and other diseases endemic/prevalent in the region that, in other circumstances, health providers

would have seen as most likely causes and which could complicate diagnosis. In Nepal, the uncertainty in this area arose because relief workers were operating in an area in which medical care was hard to come by normally, so it became difficult to discern if the health issue was earthquake related or another issue due to lack of routine health care. The uncertainty associated with the lack of information changed over time as people and organizations were able to gather and vet more and more information about the situation. One CDC interviewee noted he deployed to West Africa very early on in the epidemic, when it was first emerging. When he returned later, not only was there increased capacity for laboratory work, more CDC personnel, and greater numbers and capacity within Ebola Treatment Units (ETUs), but health providers “had a better understanding of what was really going on.” The second source of uncertainty lay in the nature of the information relief organizations were able to obtain, constantly changing over the course of the response.

The nature of this kind of uncertainty itself had two origins. The first was a reflection of the fluidity of the response context and event itself. One way in which this appeared in both cases was in the locations of survivors and injured or sick individuals. In both events, affected populations were mobile. Consider the population in West Africa affected by Ebola. Data revealed that boundaries between countries were porous, meaning sick individuals or infected individuals who were not yet presenting with symptoms could move about the country, creating new locations of outbreaks. Porous borders allowed easy movement between countries. In Nepal, people left damaged areas for areas where they heard medical care would be provided. One Team Rubicon noted this pattern and the challenges it posed for decision-making and planning their

operations in Nepal. He explained that they would sometimes go to a location and prepare for one level of service provision based on their initial assessment of population and needs. However, they found that after a couple of days, word had gotten out to the surrounding communities that there was a medical team providing care, and people would converge on the site. This presented relief workers with a different scenario than they had prepared for. Several people encountered in the field observations noted the mobility of earthquake-affected populations. One program officer we spoke with in the field commented on the difficulty this mobility presented in providing follow up care for new mothers after the earthquake. Because of damage to some medical facilities, in particular the medical hospital, new mothers—according to this respondent—were allowed only minimal time in the hospital before being released. The respondent explained that, if a new mother’s home was destroyed in the earthquake, it was very difficult for the members of this organization to identify where this displaced woman in need of their services would go in order for them to follow up with her. In the immediate aftermath of the earthquake, when there were only a small number of tent camps, tracking these women for follow up consultations was, though difficult, still possible, as there were few options for the providers to check. However, as time went on and more official and unofficial tent camps formed across the city, the ability to track down those new mothers became decreasingly feasible. This meant they could not provide follow up care, and were often limited to one visit with the mother in the hospital. In other words, the need was known and the population with that need was known, but the location was unknown because of the population’s mobility. The mobility of the new mothers after giving birth combined with the number of possible

locations for them to go meant uncertainty in the location of the population targeted for service (which changed with time), affecting how people in this organization provided their service. The second origin was grounded in questions over the quality of the data or state of data analysis that was being used at any given point. There were times when data was collected, but it was somehow incomplete. This was especially evident in the Ebola epidemic. One interviewee who responded to the event offered the following description of the challenges associated with the available information. In a discussion comparing a plane crash or bomb type scenario to Ebola:

There’s a difference in countries which can image the heck out of people, you know, ultrasounds, CPs, MRIs, really work them up reliably so that you know you’re not missing anything, there’s countries that can’t do that, and so you’re going to move the patient for diagnosis. With Ebola, um…big problem. There were some countries which couldn’t test—period. Then there were some countries which said that they could test, but you know from years of dealing with those countries—and I’m very sorry to be so blunt—that their lab capability’s low, and their lab quality control is just about nonexistent. So, do you then trust a new Ebola test if it’s administered in this country? And if you don’t trust it, what do you do? Rhetorical question. And if it’s negative, can you afford to trust it? And if it’s positive, is it truly positive? So, um, you know, in some respects, it was the worst possible combination because you had a test which was incredibly important for everybody managing that case or that group of people, and it was being administered by staff in places where the laboratory quality control is normally very, very poor. Decisions were being made on the basis of that single test that probably shouldn’t have been, um, and unlike say Malaria, it wasn’t the parasite’s there, the parasite’s not. So if you wait to see what happens clinically, oops, if you don’t [identify] that patient, you are going to infect others. If you move the patient before you have a test result, and they become positive after you land, you’ve got a whole different set of circumstances to deal with, so yeah, the test issues was major.

In the documents produced in the Ebola epidemic response, they made frequent notice of the changeability of the data. For instance, in the World Health Organization produced documents regarding Ebola, some of the data presented is followed by the following statement: "The numbers of cases remain subject to change due to reclassification and consolidation of cases and laboratory data, enhanced surveillance and contact tracing activities. Introduction of Ebola virus serology to test PCR-negative clinical cases is also likely to change the final number of laboratory- confirmed cases" (World Health Organization 2014d:205). Throughout the Ebola documents, similar statements appear as well. Interestingly, documents for both events include references to the changeability of information, but it appears to be much more systematic and consistent within the Ebola documents. Documents for both cases do seem to indicate the changeable nature of information (more data being collected or combined, people moving, just discovering more, the effects of changes in the crisis itself), however, it only seems to be explicitly highlighted in the Ebola related documents. They mention that the numbers of EVD deaths, cases, and suspected cases may change with time and mention the number of reasons. How people in organizations dealt with this uncertain and evolving information resource context will be addressed in subsequent chapters. The salient point here is that this uncertainty did exist, it was something that had to be addressed or contended with in the design and implementation of the relief effort, and it was present in the response environment of both events.

Personnel Resources Personnel resources were a frequent point of conversation during the interviews and even appeared as important points in the documents and observation

data. Specifically, a few issues related to personnel resources emerged. In planning and implementing their relief efforts. Organizations were concerned with personnel availability. Organizations needed increased numbers of people to handle the demand. This was complicated by a number of factors. The organizations often needed people who were available on short notice. While this was a little more pronounced in the Nepal response than for the Ebola epidemic, some interviewees who worked in West Africa had only a few days’ notice before they deployed. Organizations needed personnel who were available for comparatively long periods of time. Deployments were a substantial time commitment, lasting several days to several weeks depending on the effort. The availability of staff was partially linked to the time demands of the field. The Ebola relief efforts were long enough that, at least when looking at deployed personnel, the same individuals could not be deployed for the entirety of the response. Because these were international responses, they required longer deployment times, both to justify larger time and financial cost associated with getting to the affected areas and to accommodate adjusting to the new locations. The international nature of these responses exacerbated these personnel challenges for groups, as deploying became more challenging for individuals with the increased time demands. The international nature of the deployments leant themselves to longer periods of time in the field. Some of these factors encouraging longer deployments were directly stated, while others could be implied. It took a long time to get to these locations. Getting to Nepal, for example was an approximately 24-hour process (which is consistent with my own experience in traveling to Nepal for the quick response deployment). This does not include the time it might take to get people from the airport to the areas in which they needed to work, which were sometimes in

remote areas that were both far away and difficult to access, increasing time spent traveling in country as well. Personnel arriving in a new national context sometimes needed to adjust to the culture, time change, and climate/physical environment of the deployment area. Flights abroad are more expensive than domestic flights. All of these factors generally required a longer deployment (thought there are some exceptions). By comparison, the PHS deployments are typically domestic deployments and are last up to about two weeks in duration. The extended time away from work required participating individuals identify even more people to pick up shifts they could not fill themselves because of their participation in the relief efforts. It required that responders take more leave than they would have to for a shorter deployment. Particularly in the PHS case, the longer deployment extended the period of time in which responding individuals were not filling their non-disaster roles, resulting in a longer period of time in which the service(s) those individuals normally provided were unavailable. As one PHS interviewee explained, with the quarantine, it really became a 90-day deployment for them. This meant not just an absence of a valuable service, but a potential mountain of backlogged work awaiting the responder when he or she returned. In sum, the prolonged time occupying the responder role contributed to strain or difficulties in maintaining the demands of their normal roles/functions.

An important factor determining availability was that for many, if not the majority of people ,who became involved in the relief efforts for both events, their deployment role was voluntary. They typically had primary time commitments to other employers or other job responsibilities. Serving as deployment personnel was a temporary, optional role that conflicted with other permanent and often dominant roles. This meant: (1) time spent working in the relief effort was time not spent

working on tasks associated with their primary commitment; and (2), they often had to get permission or approval from someone above them to participate or at least have a job that allowed for last minute schedule change. Several interviewees noted the voluntary nature of their workforce and the consequences that had for meeting their personnel needs. Especially among the volunteer based groups deploying to Nepal, the volunteer base meant that those individuals often had to get permission to leave from a paid employer, in many cases taking personal leave in order to get the time off. The international nature of the event, which required longer time commitments exacerbated this issue. This could discourage some people from participating, and some interviewees indicated that it could mean relying on the same few people over and over again for international response. A couple individuals suggested that they took a position with or valued their current employment because it offers the flexibility required to participate in these kinds of efforts). Of course, relief effort organizers were not just worried about staff in general, but the availability of particular kinds of staff. Organizations were concerned about the background of personnel they had at their disposal: the professional background, technical skills, interpersonal skills, and if they met other requirements for participation, namely for deployment. The relief efforts needed skilled personnel. Skilled medical or public health staff they were interested in included doctors, nurses, epidemiologists, and other health and medical personnel. One interviewee from a Nepal response event said that more nurses than doctors are necessary for disaster medical relief efforts. Another respondent identified trauma surgeons, anesthesia providers, trauma emergency specialist, intensive care unit (ICU) nurse as members of the team. The Ebola epidemic in particular required

specific skill sets. Team composition extended beyond medical personnel, though medical personnel dominated the staff. Personnel included individuals focused on communications, command or administrative positions, and people responsible for supplies and logistics. Administrators included figures such as a university dean and his assistant as well as people serving in supervisory capacities in the field. Position titles included: operations section chief, logistics manager, national technology manger, doctors, nurses, paramedics, and emergency medical technicians. When looking within the category of medical personnel, a diversity of positions were listed. They reflected different types of medicine and different roles in medical response, from anesthesia, to nursing, paramedics, and first aid. One interviewee summarized the consequences of all these constraints, saying:

especially for the international operations, it requires so much more of a time commitment away from work on little to no notice. We end up having to rely on a very small pool of people who not only have the skill sets that we need, that not only have the experience we need, that not only have the personality and those other intangibles that we really need on those operations, but also have the type of employment and employers that are gonna let them do this stuff. Even though there was interest in participating in these efforts, for volunteer-based organizations, there were still several challenges associated with personnel resources. However, this also occurred among government employees for whom deploying for disaster response was part of their responsibility. This latter scenario came up in interviews about the Ebola response when discussing the role of the Public Health Service in the U.S. response. Once the United States government determined that it would support the international response to Ebola in West Africa, the United States Public Health service was tapped to provide the personnel to staff the U.S. efforts. The PHS encompasses a large number of individuals engaged in a range of

public health activities located in numerous and diverse agencies, including not just the Centers for Disease Control and Prevention and the Office of the Assistant Secretary for Preparedness and Response within the U.S. Department of Health and Human Services, but in agencies such as the Department of Corrections, and branches of the American military. The PHS personnel fill a regular function and service within the agencies within which they are housed. However, it is part of their responsibility as PHS employees that they will deploy to disaster response. The host agencies agree to this as a condition of getting the PHS employee. As a result, participating in a deployment to support a disaster/crisis response is an explicit part of their professional role, yet it takes these individuals away from the services they provide the host agency, presenting a degree of internal and role conflict. Relief effort organizers considered the merits of one individual in relation to other individuals, looking at team composition as a whole. Data from both cases demonstrated relief organizations’ desires to include individuals with different skills on their teams, including individuals with different medical specializations. It was clear that non-medical actors were important members of these teams. Diversity of skill sets and backgrounds among members within a team made the team as a whole more flexible and capable of adjusting to changes. Personnel resources were not just considered in terms of their individual value, but their value as a part of a team. In the interviews, issues of personnel wellbeing emerged. Participating in the relief efforts in both responses was taxing in a number of ways. Some of these concerns contended with the physical wellbeing of the responders from the hazard. In the Ebola epidemic, participants revealed major concerns within the responding organizations about the possibility of Ebola responders (doctors, nurses, community

health workers, etc.) becoming infected with Ebola through their involvement in the response. The risks posed by aftershocks threatened staff safety in Nepal. Unstable built structures and subsequent aftershocks could bring down weakened structures. Moreover, they could trigger landslides in the rural areas. In addition to these consequences that were direct results of the earthquake, secondary conditions could affect responder wellbeing. One Team Rubicon interviewee revealed that multiple members of their field personnel fell ill with conditions like gastrointestinal illnesses.

But there were still other concerns about the consequences of participating in the response for providers and their families. Data revealed a recognition that emotional, psychological, and social consequences needed consideration. Several interviewees mentioned the emotional toll the response could take. One interviewee from the Nepal response got emotional during the interview when talking about the response. In the Ebola response, there were efforts to monitor responders’ mental health while in the field. However, a few interviewees noted the need for support services when returning home after deployment. Some of these services were to support the individual responders with processing their deployments. Some interviewees indicated that their families faced social consequences of their deployments. One responder revealed that while he was deployed, his neighbors found out that he was in West Africa responding to Ebola and then refused to let their children play with his. Others noted that there were school districts that were concerned about the children of men and women who had returned from a deployment in West Africa attending school. At least within CDC and the Public Health Service, resources, such as more extensive debriefings and support services for returning

personnel, were developed to address these issues over time as problems and resources were identified. Though not frequently mentioned, a few interviewees suggested that participating in the response could take an emotional toll even when they were not involved in direct patient care. For example, one Team Rubicon participant talked about feeling like she was not helping. Talking about the time once she arrived in Nepal, she revealed that on top of the exhaustion from the sleep deprivation, altitude, and being sick with a chest infection, there was stress associated with working in the disaster environment. She explained,

[T]hat stress affects everyone differently of like the devastation that you see. I struggled with it because I was sitting at my laptop inside an office building in Kathmandu, and I was not out in the street or in the field helping anyone, and I actually found that really hard to deal with. Because you get over there, and you want to do something, right? Like you want to feel like you’re having an impact, and whatever value my role or everything that I did while I was there had, it doesn’t feel like you’re accomplishing anything when you’re sitting inside a temperature-controlled office at your laptop. Even if you’re working 15 hours a day, even if you haven’t slept, even if you’re doing something that’s vital to the operation, it certainly takes a toll on you to be sitting at your laptop, you know, in its own way. Because you feel like you’re not—you don’t feel like you’re doing anything to help. I think what I learned from that was the ability to say, to be able to look at the teams that are out in the field and say ‘hey, those guys are doing the real heavy lifting, and it matters and it is important that I make sure that they don’t have to do all the rest of this, that they have a hot meal and a place to sleep, and they have a flight home. But no matter how many times I say that, I think when you factor in the exhaustion and just having to look around you when you walk out of that office building and see what’s happened to all these people, it takes a toll on you emotionally for sure. It’s kind of hard to deal with. Even though she knew that she was filling a valuable role in the response, she still felt a negative emotional response because she was not directly involved in patient care. A

participant from Samaritan’s Purse indicated a similar feeling. Around the same time one of their personnel became sick with Ebola, this interviewee began taking on more and more administrative functions and was less involved in direct patient care. Again, with the removal from direct patient care, came a sense of guilt or of not helping. The more they moved into administrative positions, the more they felt they were not helping enough. This seemed to be an issue only for individuals serving in more administrative role in the affected area, not in the home country operations. Under those circumstances, they could see the harm and need on the ground, but their roles were preventing them from directly engaging with the affected populations or filling that direct service provider role.

Materiel Resources Materiel resources emerged in the data as important aspects of the relief efforts requiring attention. Some of the needed materiel resources directly related to the provision of medical services, including medical supplies and medical equipment. These items most frequently included medications, bandages, and other wound care items for the Nepal earthquake, though specific items varied depending on what kinds of health issues they expected to face. In relief efforts for the Ebola epidemic, materiel resources similarly included the items required to provide supportive care for infected patients and personal protective equipment required to perform that care. Interviewees for a few organizations (primarily working in Nepal) noted bringing or sending other relief items as well, such as water filtration devices and medicals supplies intended for donation rather than for their specific use in the field. They also included other material that, while not strictly medical, was important for the response. Materiel resources important to the response included operational spaces where relief workers

provided their services, transportation resources, housing and food for relief workers, communications equipment, and range of items individual relief workers deploying to affected areas were expected to bring to support themselves in the field. Interviewees revealed a range of resources they needed or brought with them to support themselves and their operations. These items varied from food items to medications to deal with personal ailments that might arise over the course of their deployment, such as over the counter treatments for gastro-intestinal issues. Deploying personnel obtained vaccines and other important medical supplies they would need to stay healthy abroad. Personnel deploying to the affected areas needed to bring appropriate clothing. Appropriateness included clothing items that accommodated the climate (especially rain and heat), but the specific kind of clothing items varied with the person’s role in the response. For groups like Team Rubicon and others going into very remote, rural, and hard to access locations, they needed clothing and gear that would support them in austere environments. For others, such as one CDC respondent who was working primarily with senior members of the Ministry of Health in Liberia, more professional clothing one would associate with an office environment better suited the demands of the job. Several other items emerged in the data, including documentation of professional licensure, food supplies, and water purification tablets.

In addition to identifying the material resources they needed, organizations had to identify where to get those materials. The limited resources available in the host country not only meant that members of converging organizations felt they had to bring the supplies they needed with them in order to perform their tasks, but pushed many of the people I spoke with and observed to conclude that they needed to bring their own supplies so as not to be a burden for the community which they intended to

serve. In other words, to not take resources away from the community that community members might need (including medications, food and water, and shelter resources). On the other hand, some individuals noted the importance of supporting the local economy. One organization, for instance, emphasized the importance of buying things locally. By purchasing items in Nepal, it would support the recovery of the economy, and therefore contribute to the overall wellbeing of the country Organizations obtained material resources from a variety of sources. With regard to the supplies to support the individual responders, some organizations did have some resources available for their staff. CDC employees deploying from the U.S., for instance, had a contact within the agency that would actually provide them with many of the resources they needed, which one CDC interviewee noted using. Similarly, the group affiliated with Massachusetts General Hospital had a supply closet that volunteers deploying on medical missions could pull from if they need to. However, for many of the deploying interviewees, items required to support themselves in the field were procured by them at their own expense. While this was especially the case for the volunteer-based organizations, evidence suggests that this was also true for some of the government-affiliated responders. One Public Health Service member who deployed revealed that he had to purchase many of the supplies he needed on his own, and another indicated that his history of previous deployments meant that he had some supplies he needed already, suggesting that these were his personal items, not items belonging to the organization available for his use.

In terms of the supplies organizations used to fulfill their goals, most of the organizations did not have all the supplies they needed on hand within their organizations at the time of the deployment. In many cases, they worked with another

organization to acquire what they need. Some organizations ordered the medical supplies they needed from suppliers. Others sought and received donations of medical supplies from hospitals. Some of the organizations affiliated with hospitals received supply donations from those affiliated hospitals. The latter occurred in the Nepal earthquake response, but not among the organizations in this study that participated in the Ebola response. Others relied on partnerships with other organizations to procure these resources. For some, these partnerships were already established. This was the case with the Massachusetts General Hospital affiliated group, which partners with International Medical Corps for all of their logistics support required to perform medical services in disaster-affected areas. Others forged new relationships. This occurred when establishing the Monrovia Medical Unit (MMU). In establishing the MMU, PHS filled the need for personal resources, but PHS does not have the material resources or logistics footprint required for such an operation. For that, they turned to the U.S. Department of Defense (DoD). DoD had a logistics base near the airport and supported the equipment requirements of the MMU. For example, the tent hospitals that served as the spaces to care for Ebola patients were existing United States Air Force resources, adapted to meet the needs of the Ebola response. The Office of the Assistant Secretary for Preparedness and Response (ASPR), along with Department of

Defense further facilitated the movement of those supplies. In addition to simply not having the resources themselves, other challenges associated with materiel resources emerged in the data. One such challenge was competition for resources. The clearest example comes from the Ebola epidemic. Not only was there an absence of either a vaccine or a cure for the disease, but there was competition to obtain the personal protective equipment (PPE) resources necessary for

healthcare workers to care for infected patients safely. One CDC interviewee explained:

[O]ne of the more complex issues was around personal protective equipment, PPE. And so, DoD was trying to procure personal protective equipment, CDC was trying to Procure PPE, other entities domestic and international, they were trying to procure PPE, and you know, everybody was trying to buy this different personal protective equipment stuff from the same small set of vendors that manufactured them.

In other words, the kind of PPE necessary for the Ebola response was suddenly in high demand, but only a few vendors produced and sold these products, making their acquisition challenging. In a similar way, transportation resources for both events could be difficult to secure as there was suddenly increased demand. This was especially the case when looking for available aircraft that were capable of and willing to transport individuals infected with Ebola. To make matters worse, transporting materials in a way that would ensure their availability in the field was challenging, as people faced concerns about customs payments and potential seizure of supplies at the borders.

Summary The characteristics of the decision-making setting reflected the wide range of important issues that providers of medical relief had to contend with and that ultimately shaped the relief efforts. Particularly within the discussion of information and personnel resources, there emerged two additional categories of factors shaping the planning of the health and medical relief efforts: characteristics of the decision- maker and characteristics of the decision-recipient. At the organizational level, these characteristics included the origins of the organizations, how long they had been in

existence, their organizational mission or purpose, resources and structure, and the type of organization. Characteristics of individual people involved in planning and implementing these efforts affected decision-making through the processes outlined in this dissertation. In particular, an individual’s previous experiences, training, professional background, and role or position within the organization and relief effort shaped how they engaged in the three processes presented here. There were two categories of characteristics of the decision recipients that were important in this study. The first refers to the affected population that the relief effort intended to help. In this way, the decision recipient is similar to that of the patient in the medical decision-making literature. The characteristics of the recipient that had the most sway were the needs of the patient. Other characteristics like gender or race and ethnicity did not emerge as important in the data. However, in looking at the decision-making for the relief effort as a whole rather than just the delivery of care, another group of decision recipients emerged: that of members of the relief effort. These individuals became decision recipients through role and task allocation, where the characteristics of the recipient like skill sets such as language skills came in to play. That the characteristics of the decision maker and recipient emerged as important in the response is consistent with the general patterns documented by other scholars of decision-making (Bodenhausen’s 1988; Haider et al. 2011; McKinlay et al. 1996; Reyna 2008; Sabin et al. 2009). Much of this research has focused on the influence of race, but race did not emerge as an important factor shaping decision- making in these interviews, documents, or observation data. Race was only mentioned once as a potentially influential characteristic of the recipient in the context of having

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the public faces of the relief effort (meaning those working directly with the affected population) reflecting the population based on the belief that the messaging and programs would be better received by those individuals. Yet, this comment was grounded in a larger discussion of including people from affected communities in their relief delivery personnel, with relief worker race being just one component of that. Similarly, several groups responding to Nepal valued working with or being advised by local Nepalis, but that seemed to be less specifically about their race than their familiarity with the local area (be it geography, language, culture, etc.). Through the processes of developing situational awareness, defining and bounding, and matching and aligning, features of the response context were incorporated into decision-making for the relief efforts. The outcomes of the decisions produced by the three processes became part of the decision-making context. The result of this feedback loop created a condition of decisional inertia, which increasingly limited the options available to organizations for participating the crisis relief.

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Chapter 5

DEVELOPING SITUATIONAL AWARENESS

The 2015 Nepal earthquake and the 2014-2016 Ebola epidemic in West Africa generated substantial health and medical needs within the affected countries. Governmental and nongovernmental organizations responded to help address the crisis-induced medical needs. Organizing and implementing those relief efforts required responding groups to grapple with the complex operational contexts created by these crises, and which evolved throughout the life of the relief effort, including uncertainty and changing needs and resources in the affected areas. To gain the requisite understanding to undertake such endeavors, people in organizations engaged in a process of developing situational awareness. This process was comprised of two components: (1) gathering and communicating information and (2) processing that information. Using a variety of channels and sources, they gathered and communicated information both internally within the group, and between groups.

Once collected, groups processed the information by assessing the content and quality of the information, and then deriving meaning from it. This process began early in the response, often the first thing organizations did once they heard about the event, and continued throughout the implementation of the relief effort. This process is visually depicted in Figure 1 below.

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Within Group Gathering and Communicating Between Groups Developing Situational Awareness Information Content Assessing Information Processing Quality Deriving or Making Meaning

Figure 1 Process of Developing Situational Awareness

Gathering and Communicating Information Organizations began gathering and communicating information very early on in the response, and this activity continued throughout the relief efforts. People and organizations sought out and received information relevant to the response and pushed information back out to others. Information flowed both between individuals within the same organization and between different organizations. Organizations and individuals used multiple means to communicate this information and the information came from multiple sources. The data revealed multiple communication channels. Organization members shared this information in person or verbally, and through a number of text-based communication methods. Among some of the means most frequently mentioned were meetings, phone calls, emails, reports, and surveillance activity, but they included social media and more specialized means of collecting information such as Global Positioning Systems (GPS) trackers and unmanned aerial vehicles (UAVs).

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Sometimes they sought out information, as when they scoured media and the internet for information about the event and area or reaching out to partner organizations in the crisis-affected areas for information. Other times they received information, but the other party was the one initiating the interaction. Under some circumstances, such as during organization meetings or in meetings as a part of the cluster system, organizations actively exchanged information. Information exchange between and within groups could occur simultaneously, as it did when people in Team Rubicon heard about the Nepal Earthquake from the news while notified through organizational channels about the event and potential deployment (including the specific unit dedicated to following reports regarding potential deployable events). Part of using and transmitting information involved management. A few interviewees discussed the importance of information management in this process. For instance, an interviewee described his role as communications liaison with the Centers for Disease Control and Prevention (CDC) in the Ebola epidemic, saying “It was all about information management. It was keeping DoD as up to date as possible on CDC’s activities so they could gauge their own activities on the continent.” There were a few other mentions of the importance of managing as opposed to specifically communicating information, but in general, these discussions indicated that this was a part of the process of developing situational awareness rather than something altogether separate from gathering and processing information. As the discussion of communication channels suggests, the information participants in these relief efforts gathered came from a range of information sources, both formal and informal. The number and type of sources people and organizations relied upon varied, though most did consult more than one source. Many people I

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interviewed first heard about the crisis they responded to through the news media. Some groups, primarily the nongovernmental ones, relied on media reports in the early stages to get information about the situation on the ground. Members of their own organization were another important source, as they communicated internally through in-person and online meetings, phone calls, and e-mails. This type of communication was particularly employed for sharing information regarding ongoing tasks from one wave of personnel to was replaced with a subsequent wave. Here, training (pre- deployment or on-the-job) was a valuable means of sharing information. In addition to information from their colleagues within their organization, relief workers got information from people within other organizations. These other organizations included other responding organizations that planned to (or had already) converged on the affected area, and partner organizations in the affected locations, whether or not that organization was a new or pre-existing partner or if it had a disaster focus. In the Ebola response and relief effort, the CDC and WHO were particularly important sources of information for interviewees. The CDC was especially important for the American respondents working in ASPR and PHS. MSF was a key source of information for Ebola as well, though that information may have been filtered through the two aforementioned sources. Groups and individuals consulted connections to the affected area, for instance identified and tapped through social media. These local contacts were a source to the extent they could provide insight on conditions on the ground, though this was the case much more so for the non-governmental groups and the less established groups than the well-established government organizations. No matter what the source, respondents valued on-the- ground information sources.

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This gathering and sharing of information continued as personnel began arriving in the areas affected by the crises, and occurred in tandem with or as a part of activities aimed at connecting with relevant contacts on the ground. One CDC respondent involved in the early epidemiological work for the Ebola response described his team’s initial activity as looking around at the situation and introducing themselves to relevant government or ministry of health personnel. Even after they were on the ground, information gathering and sharing often occurred alongside response activity or was part of the response activity itself. Some interviewees with epidemiological backgrounds or experience working with infectious diseases indicated that contact tracing is a standard part of an epidemiological response, and its use was consistently noted by interviewees speaking about the Ebola response and in the World Health Organization situation reports and status updates. By following up with individuals who may have had contact with someone known to be infected with Ebola, they were inherently responding to the epidemic by identifying additional individuals who were possibly infected, monitoring them, identifying those who were sick themselves and connecting them to the appropriate health services. Doing so addressed the medical needs of newly identified sick persons and helped to contain the spread of the disease. However, this activity was inherently information gathering. It afforded them an updated, clearer picture of the status of the epidemic, including numbers of suspected and confirmed Ebola Virus Disease (EVD) cases and the locations of those cases. Going to a remote location outside of the Kathmandu Valley in order to provide care to isolated communities involved additional information gathering upon arrival. In the case of Team Rubicon, information gathering was a simultaneous objective alongside the delivery of medical services in these remote

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environments. While working in these remote communities, they conducted damage assessments and reported that information back to their main base of operations in Kathmandu, which then pushed that information into the Health Cluster meetings and meetings for Foreign Medical Teams. Examination of the channels and sources of communication revealed that, along with the formal communication mechanisms and sources these groups used, informal communication channels and sources were often of great value in developing situational awareness. Resources on social media offered valuable insight on the crisis context. Personal contacts in an affected area or Facebook groups like Kathmandu Living Labs, which performed substantial needs mapping in Nepal, sometimes yielded important information about the situation in-country, as could a quick call to a knowledgeable friend or colleague involved in another response effort. Information gathering was sometimes as simple as being observant while participating in other response activities. Interviewees from one university hospital- based group demonstrated this in their time at a Kathmandu hospital. As they helped provide care in that facility, some members noticed that there was a high-tech piece of anesthesia equipment going unused. That observation prompted further investigation. They discovered that another organization had donated the equipment, but did not offer training, so none of the staff knew how to use it. Similarly, another interviewee from this organization noted that observation of the local hospital staff providing care revealed that they were not aware of some infection reducing techniques. In neither case were the interviewees explicitly and purposefully trying to gather information, nor did they stop their existing work to engage in additional information collection. Rather, it was an ongoing process concurrent with other relief activity.

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In another example, locations of non-communication-related relief activity became hubs for information sharing. The Kathmandu airport was one example. A few interviewees noted some challenges in getting baggage through the Kathmandu airport, as did several people I encountered in Nepal during the field work (including both people focused on medical work and those who were not). One interviewee explained that at one point, luggage was just piled on the floor, and people looking for their luggage had to keep digging through the pile until they found what was theirs.

This was a cumbersome process, but one interviewee described the ways it was a useful opportunity for information gathering about group activity. He explained,

But it was also a great place to go get intel … because I would be there with the logistics guy from like, Backpacker Medics out of Australia and you could [just say] ‘Hey, where are you staying?’, and well ‘Where are you deploying to?’ So, you are able to exchange sort of this informal situational updates amongst folks that are just sitting there just diving through this pile of luggage. The convergence of material items related to the earthquake response made that location important for the response and lead to a convergence of people to that area. This personal convergence, in turn, led to an informal exchange of information. Similarly, casual conversations with recently returned trekkers in the bars or restaurants of the Thamel tourist district of Kathmandu within the first few days after the earthquake could yield valuable information about earthquake effects in the more remote areas of the country. Many of them had been in the remote areas trekking at the time of the earthquake, and in the first couple of days after the initial earthquake had only recently made it back to the capital. Brief conversations with these individuals encountered at restaurants could help responders learn about the locations and status

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of remote villages that was unavailable by other mechanisms. This was information useful in guiding deployment decisions. In this study, informal resources appeared to play a bigger role for groups that were involved in the Nepal response than it did for those groups I examined for the Ebola response, though this could be due to a difference in sample composition. There were more non-governmental groups included in the sample for the Nepal earthquake than for Ebola, and therefore this difference could have resulted from the type of responding organization than the event itself.

Previous Experience Previous experience was another important source of information. This experiential knowledge was sometimes drawn from the organization’s previous experience, from the individual’s previous experience and, in some cases, from research. The use of experiential knowledge became especially (though not exclusively) apparent under conditions of informational uncertainty. As noted in the previous chapter, the information context was challenging in its uncertainty, both in its variability and in the lack of information available particularly early on the response. There were often information gaps or uncertainties. People used previous experience to fill those information gaps.

Multiple participants referenced previous experience (or indicated doing so) in deepening their understanding of the situation and what they should do to address the array of needs for patients and responders. Sometimes this information came from an individual level, others times it was the organization’s previous experience. In many cases, knowledge was based in previous deployment experience. Members of DMRT referred to the organization’s experience in Haiti to fill in gaps about what they would

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see while working in Nepal or what they would need to compliment the information they were getting from traditional and social media, organizations in the country they reached out to, and even their advance team. Several individuals speaking about the Ebola epidemic indicated reflection on information generated from previous Ebola epidemics, and some even referenced experiences during the severe acute respiratory syndrome (SARS) or H1N1 Influenza outbreaks. People and organizations supplemented the information they received about the current situation with previous experience at the individual and organizational levels. One of the most common areas where the use of previous experience to supplement current knowledge was apparent was in anticipating the crisis-induced medical needs. When there was limited information about the situation on the ground, such as during the onset of the deployment, people would look to the injury patterns for similar events to anticipate what they might see upon arrival. Research was a way to draw on the previous experience of others to inform that group’s preparation for their Nepal Earthquake response. Related to identifying medical need, people consulted previous experience to identify what supplies to bring, both to support the relief effort and regarding necessary personal supplies. The Suggested Traveler Supplies List for Nepal Relief

Effort distributed to members for one deploying organization identified a range of items deploying volunteers might need, from credentials (such as a medical license or nursing license), insurance information, clothing appropriate for the environment - such as rain gear and sneakers or steel toed boots, a tent, hygiene products and medications, as well as suggested foods to bring and other potential items like a cell phone or batteries.

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Information from previous experience was not always from previous deployments. Sometimes non-disaster experiences could offer useful information about the operational context. An interviewee from one organization used the knowledge she gained from her time working for an airline in an airport to inform her work in trying to fly the Team Rubicon volunteers and supplies to Nepal. Another interviewee from an organization responding to the Nepal earthquake revealed familiarity with running fundraisers, in general, and with the web format for previous fundraising efforts, even though neither he nor the organization had previously engaged in disaster relief efforts. People frequently used multiple forms of this previous experience to develop provisional expectations. One interviewee revealed how members of her organization used different forms of previous experience during their planning to anticipate what they might encounter once they arrived in the affected area, explaining,

However, we recognized in the situation with Nepal that the whole— the plan was very fluid. We weren’t exactly sure what we were gonna find when we got there, so there was an outlined idea of what we knew from previous response and what we knew from research of previous earthquake response that sort of guided, what sort of medications we were gonna pack, what we’re gonna prepare for, what sort of people we are going to vet on the team. Though we didn’t necessarily fly in there knowing where we were gonna go or what patients we were gonna be treating or what we were gonna find when we got there. This example highlights the importance of gathering information from previous experience to inform decisions and actions when there is little information on the current situation available to guide them. However, it also illustrates a behavior among some groups to delay the information processes or meaning making activity. While previous experience was important, some interviewees did indicate hesitance to develop too concrete an idea of what they were going to see and how they would

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respond before they arrived on the ground. The previous experience helped to fill in the gaps they seemed unable to accurately fill at the time, but did not supplant the on- the-ground information they valued and prioritized so much in their decision-making. In sum, people involved in the response for both events consulted multiple sources of information through multiple channels, with the importance or degree of use of each source varying over time. There are particular crisis events that seemed key points of reference for most of the interviewees. The 2010 earthquake in Haiti was the most frequently evoked case, mentioned by a large portion of the interviewees for both events, and among those occupying positions in the U.S. government and non-governmental organizations. Many of the hospital groups that went to Nepal sent teams to Haiti in 2010, and a number of interviewees participated in both relief efforts. The Haiti earthquake was often a group’s or individual’s first foray into international disaster relief, as a baseline for understanding complications of international relief efforts or expectations of damage, and an experience underlining how the process worked. For some individuals from the Office of the Assistant Secretary for Preparedness and Response within Health and Human services and the Public Health Service, their agencies’ involvement in that event served as important reference point for understanding the organization’s role in international response and insight on how to perform their specific, individual roles within the response effort. In addition to the prominent place the Haiti earthquake held as a reference event, interviewees referred to some other events as well. Recent typhoons in the Philippines served as a point of reference, particularly for Team Rubicon Participants. SARS and H1N1 were reference points, especially for people with the more clinical or epidemiological

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background or working with Ebola. As people drew upon this information derived from previous events and combined it with the information collected about the present situation, they processed the information in order to find meaning in the increasing body of data they possessed.

On the Ground Information and Sources Regardless of whether the source was internal or external to the organization, there was value on sources that were ‘on the ground’ providing information directly from the affected area. People valued their proximity to the affected populations for the clear, unfiltered understanding of needs and opportunities in the crisis area that people presumed these sources offered. These on the ground sources included individuals and groups present in the affected area, whether or not the organizations’ work was disaster focused. The Delaware Medical Relief Team reached out to hospitals in Kathmandu as they prepared to deploy. The team from the University of

Southern California was in contact with an individual at a hospital in Kathmandu who provided them with information on needs and connected them with other partners in country. Members of the American Nepal Medical Foundation (ANMF) reached out to several groups in Nepal in various stages of their relief work, including POSSIBLE— an organization providing healthcare services in a rural area of Nepal—and ANMF’s sister organization in Nepal. Samaritan’s Purse consulted hospitals in Nepal with which they were already connected. Similar patterns were apparent in the Ebola response, with several groups including Samaritan’s Purse, The Assistant Secretary for

Preparedness and Response (ASPR), and U.S. Public Health Service (PHS) looking to the CDC and MSF (which had people in Ebola-affected areas) especially for information about evolving state of the epidemic.

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Early on, some groups sent advance teams (though they were not always called that) into the field to engage in some initial response activity and to gather important information to inform subsequent response activity. As more staff arrived in the field, they continued to serve as an important source of information. One Public Health Service interviewee who deployed on one of the later waves of personnel revealed that once there were people who had served in Liberia who had returned, PHS made efforts to include them in some of the training experiences for subsequent waves of volunteers preparing to deploy. Others communicated with currently deployed individuals who they were replacing. One CDC participant reported reaching out to the person who she was to replace in the Ebola response and getting information about the situation, schedule, and living in Liberia. These were sources whom decision- makers perceived to have more direct access to information about conditions and needs than other sources were perceived to offer. The importance of this information was apparent in multiple ways. The value of sources located in the affected area and the information they provided was apparent in when they developed their perceptions of the situation. Several interviewees who deployed to the affected areas revealed that they delayed drawing too many conclusions about the conditions they would face before they arrived on-site. They wanted to hold off finalizing their impressions of the context until they could directly see and experience it. Even then, they valued information that was provided to individuals sent in subsequent deployments once the first waves of personnel in the relief teams were actually on the ground. Several individuals delayed sensemaking until they themselves set foot in the disaster area. Respondents from USC noted reserving judgment and decisions until they arrived in Nepal, similar to comments

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from some Team Rubicon interviewees who similarly hesitated to form too firm a set of expectations before arrival. This purposeful delay in developing situational awareness that multiple interviewees referenced in their conversations with me revealed the value they placed in information direct from the affected area and population in guiding their situational awareness. Discussions with some interviewees involved in the Ebola response emphasized the importance of Tom Friedan’s visit to West Africa as important in shaping his understanding of the situation, risk, and the need for involvement from American agencies in dealing with the epidemic in West Africa. While they did not reveal a direct delay of sensemaking on Dr. Friedan’s part, that the decision to become involved occurred only after his visit to West Africa suggested the importance of seeing and experiencing affected conditions to fully and accurately understand the situation on the ground. Their seemingly constant efforts to obtain this kind of information from these kinds of sources further illustrates its importance.

Processing that Information (Assessing) There were two components of information processing: assessing the information and finding meaning in that information. In the documents in particular, developing situational awareness appeared as assessing activity and evaluation of the status of a population or service provision source (be it the physical structure and supplies or the personnel providing the care). When people in organizations assessed information, they assessed the information content and the information quality.

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Content The information content was the substance of what was conveyed. This would include, but was certainly not limited to, the numbers and locations of people injured and killed as a result of the crisis, what their needs were, who else was responding in the field and what they were doing. The data revealed different approaches used to assess the information they gathered and received.

Comparing

One technique used in the relief efforts was comparing information. These comparisons took many forms. Participants and the documents frequently compared different geographic regions. In the Ebola response, different countries with Ebola cases were compared to each other. In particular, there were many comparisons of Guinea, Liberia, and Sierra Leone, the three countries where the Ebola epidemic had the strongest hold. Smaller geographic units within each of those countries were also compared. The following excerpt from one of the Ebola Response Roadmap Situation

Reports from October of 2014 demonstrates the use of this approach:

EVD [Ebola Virus Disease] transmission in Guinea remains intense. By contrast with Liberia and Sierra Leone, however, several areas of Guinea are still to report a single case of EVD, whilst seven have now been free of cases for over 21 days after an initial case or cases of EVD. (World Health Organization 2014k:3). This quote illustrates how those involved in the Ebola response used comparisons of large and small geographic zones defined by political boundaries to develop a comprehensive understanding of the overall situation and variation within the affected area. Situational awareness in the Ebola response involved not just understanding the numbers in a particular country. Contrasting that information with the other major countries affected by the epidemic was important for understanding the situation

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within a country (or the epidemic as a whole) as the situation ebbed and flowed. In other words, one of the means of processing the information was through comparison with other situations deemed as relevant reference points in some way. This technique was apparent in the Nepal earthquake. There were 14 crisis- affected districts (Nepal Planning Commission 2015), the state of which were compared to each other and the state of other districts more broadly. Many people compared the state of Kathmandu to the rural districts more generally. Several participants noted the preexisting differences between the capital city and rural areas, and how those differences translated to the post disaster context. In planning meetings for DMRT, for instance, organization leaders noted the differing conditions in the rural areas versus Kathmandu, and identified the rural areas as generally having a greater need for their services. Within the documents, sometimes these comparisons were implicit, such as the following statement from the May1, 2016 situation report from WHO:

Treatment of the injured in the remote areas remains a challenge due to access problems as most of the remote villages are not linked with the road networks. Even air lifting is difficult due to weather. (World Health Organization 2015e:1) Here, the indication of special challenges to accessing these rural areas notes an implicit comparison that distinguishes the infrastructure conditions and ability to provide care in these areas from the conditions and ability to provide care in the capital city.

In addition to comparing different areas affected by the event they were responding to, data revealed the use of comparisons with other events as a means for understanding the situation they faced. Several interviewees referred to responses to other events they were involved in as a point of comparison to put their responses in a

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context or demonstrate how the Nepal earthquake or Ebola epidemic were unique. In interviews about the Ebola epidemic, respondents compared this epidemic with previous Ebola epidemics and epidemics of other infectious diseases. Respondents from the Ebola case sometimes compared what they did for the Ebola response to what occurred in H1N1 or SARS. Sometimes they made even broader comparisons. For instance, some respondents indicated that Ebola was unlike anything they had dealt with before, particularly in scale. Statements like these are evidence of implicit comparing Ebola to all previous responses. Similarly, multiple personnel from Team Rubicon referred to their responses to typhoons in the Philippines to convey meaning within the interviews. Comparisons allowed participants to understand and convey the severity, complexity, and scale of the event and the response to it. Many interviewees made reference to the 2010 earthquake as a way of demonstrating that, while still a serious event for Nepal, the Nepal earthquake and its response were not as severe as previous international disasters.

Contextualizing Information pertaining to the earthquake was contextualized in order to ascribe appropriate meaning to the information. Frequently, disaster consequences, the post- disaster conditions, and relief operations were described in relation to what conditions were like in pre-disaster times and larger cultural and political context. For example, the state of the transportation and health care infrastructures in both West Africa and in Nepal were highlighted to better understand operating conditions during the event and response/relief. The poor state of roads in the affected regions of both crises were emphasized in order to convey the difficulty in getting to some locations, the length of time it took to get to them, and the importance of accessing those regions.

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Likewise, information about culture informed how they understood previous recommendations and how they understood conflicts as they arose. For instance, interviewees stated that understanding the role of women in caring for the sick for many communities in West Africa and the importance of burial practices were important for understanding how aspects of the response were received by residents in local communities. One interviewee discussed the importance of situating messaging in cultural (and temporal context). She explained that, while in the 2014-2016 epidemic in West Africa, the intent of messaging was to explain Ebola to the affected population in scientific terms, it was

ironic because the messages that were effective in the initial outbreaks of Ebola in DRC [Democratic Republic of Congo] were actually predicated on the fact that this was bad witchcraft and you wanted to avoid it so you needed to report it. So it’s interesting in the difference in a generation in terms of what we want to tell people and desire to be transparent, trying to explain what is in many ways a very western medicine concept and one that’s not widely understood in some of these more—especially some of the rural areas of Western Africa. So this is I think a real constant challenge during the response. In that example, she not only situated the messaging in the cultural context of the affected population, but of the organization as well. In both the earthquake and the epidemic, the relationship between local communities and the national governments were another important lens for understanding the operational context. Sometimes this (historical, political, cultural) contextual information only emerged in the interviews when specifically asked about it, but other interviewees highlighted these issues on their own. Regardless of how cultural and political contextualization arose in the interviews, it did consistently emerge as important in the data. Another important means of contextualizing the information was to situate the information in time. Situating the information in time took several forms. Sometimes,

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this meant indicating the chronological time point of the information, like the time after the event occurred, or in discussions of how old the information was, and if it was recent and timely information. Interviewees demonstrated this kind of contextualization when they discussed the types of injuries they expected. While information from previous events and early reports on injuries was something responders sought, this information was understood in the temporal context in which it was relevant compared to the time that the responders would be arriving and the expected effect that would have on the relevance of that information on the relief activities. More specifically, several of the interviewees who went to Nepal noted that most of the immediate lifesaving activity would take place in the first 24-48 hours, before the majority of the interviewees would converge on the area. The time helped them understand what kind of earthquake-induced health and medical needs were relevant to them. Other times, it meant locating the information in relation to concurrent and anticipated events and conditions. This occurred, for instance, when interviewees acknowledged that the Nepal Earthquake occurred at a time when Nepal was without a constitution—still trying to draft a constitution after years of civil conflict when the earthquake happened. In the same vein, at one point, the public health response in

Guinea that IOM was involved in coincided with elections in the country. Knowing that the elections would lead to large groups of people at the same time that there were still individuals infected with the Ebola in the country shifted their perceptions of the risk of disease spread. Some CDC interviewees indicated that activities within their organization concurrent with the Ebola response, such as multiple emergency

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operations center (EOC) activations and some organizational changes were important in understanding CDC’s activity and experience in the event. An excerpt from the Nepal Earthquake Health Cluster Bulletin illustrates these different markers of time. The Bulletin states:

As the emergency response transitions into the recovery phase, the health cluster priority activities target to revitalize health service delivery with focus on restoration of Primary Health Care Services through the Provision of Medical supplies, tents and rehabilitation support ensuring that priorities such as reproductive health, mental health, and child health are coordinated and addressed. Strengthening the communicable disease control and surveillance system particularly in view of approaching monsoon season remains they key priority for the immediate future. (Health Cluster 2015c:2). In this excerpt, the information is situated in the current time and projected in the future. At the same time, it is located in relation to phases of the disaster cycle, specifically the transition from response to recovery, and in terms of the seasonal time marker of monsoon season, which itself represents a point of significance for the relief effort. Priorities and goals are all linked to these time points and in relation to each other. The conditions present and organizational activity changed with time. Consequently, linking that information to its appropriate timeframe was important for deriving meaning from the information.

Assessing Quality (Evaluating and Vetting) The data indicated that responders did not just assess the information content. They also assessed the quality of the information. A number of factors were considered when evaluating information quality. Participants and documents revealed a focus on the completeness and accuracy of the information. They had to consider how well the information they received genuinely reflected the conditions on the

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ground, and how the level of detail provided could affect their understanding. This not only pertained to conveying needs in the affected area, but to understanding the presence and activities of other responders as well. One Team Rubicon participant described unregistered teams (teams that failed to register with the government as required) as the biggest challenge, describing how it taxed responders’ resources.

There [were] a lot of teams who were not operating in the cluster. So you would get tasked to go to a village which was 60 kilometers away, and it would take almost a whole day to go on the roads and you know traveling on foot, and then when you get there, there was already two large teams [who] had been there having a medical clinic for three days. You’d have to turn around and go all the way back. Inaccurate information had real consequences for responders and relief activity. As a result, they had to consider the potential inaccuracy of their information regarding the locations and activities of other response groups, and integrate the new information into the larger understanding of the relief operation. One means of vetting reports was to assess information specificity. The information was vetted or evaluated based on the number of sources that were providing this information. Similar reports coming from multiple sources were generally seen as more solid foundations on which to make decisions than were claims based on only one or two reports. They triangulated reports, piecing together or connecting information from different sources with other information in order to develop and understanding of the situation. One interviewee from a group responding to Nepal detailed the way these two points were weighted in the Nepal response:

We’re getting formation from quite a few different sites, if you will. We’re getting information, again, a lot of it is coming from local connections. Some of that is coming from governmental organizations and kind of their desires. Some of it is coming from the cluster and is really that amalgamated information that’s being shared around. We’re getting information from a lot of different places, and at some point,

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that comes down to a command and general staff looking at ‘alright what hot spots do we have? Where are they? What do we know about it? What’s the strength of the information that we have?’ You know, if you get one, completely unconfirmed, unverified report that there’s a little village in the middle of nowhere that somebody’s worried about but can’t give you any specifics, and in another part of the country, you know, there are three dozen villages up through this valley system, and the road has been cut off, we know that people are trying to make their way out of there, they’ve carried people out to areas that vehicles can get to, and they’re all saying the same story that, you know all the houses fell down, lots of people are dead, lots of people are sick and injured, we can’t get them all out. Ok well let’s get there, and actually get eyes on ground and start trying to quantify these anecdotal stories that are coming out versus the unknown. Somebody needs to get there, but let’s prioritize the one where we know that there is a situation that we need to get a better handle on. The larger number of sources, consistency, and specificity of the information all contributed to the information assessments. Whether information needed to be vetted depended on the perceived trustworthiness in the source from which the information came. They considered the credibility of thetype of sources used, (government, NGO, partner organization, news) and within these categories, they considered the credibility of the specific source. For instance, some participants involved in the Ebola response indicated that information provided by the World Health Organization and Centers for Disease Control and Prevention in the Ebola epidemic was not further vetted because the source marked it as good quality information. The timeliness and fluidity of the information and the situation it represented were other factors to consider in weighing the quality of information. In the complex communication environment in which quickly sharing information was difficult to achieve and a constantly changing operational context, it was possible for information to be accurate at the time it was collected, but no longer reflected the reality on the

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ground by the time an organization received it or by the time their actions took effect. In addition, sometimes the information itself was unclear and needed to be clarified for comprehension. All of these aspects of quality influenced the how they viewed the information, and consequently how they understood and used it. In sum, as individuals and groups engaged in information seeking, sharing, and exchanging activity to develop and understanding of the situation, they were also evaluating the quality of that information. As a result, the assessment of the quality of that information prompted further action and informed their decision-making and activity alongside the information content. In many cases, the quality of the information led responders and relief workers to act to specifically address that particular problem and act to improve the quality of the information. The documents produced for both the earthquake and the epidemic note efforts to improve the data collection. For instance, in the seventh situation report the World Health Organization issued in the Nepal earthquake response, WHO was identified as

“Providing support to strengthen disease surveillance system for epidemic-prone diseases” and “Providing logistic and technical support to the Information Analysis and Management Unit in the Health Emergency Operation Center to collate and analyze information and surveillance data from districts.” (World Health Organization

2015g:2). Both of these tasks indicate efforts to improve the information responders had about the post-earthquake environment. This activity was even more pronounced in the documents for the Ebola epidemic. The first Ebola Response Roadmap Situation Report 1 published on August 29, 2014 noted,

The data contained in this report are based on the best information currently available. Substantial efforts are being made to improve the

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availability and accuracy of information about both the epidemiological situation and the response implementation. (World Health Organization 2014e:1) This refrain was repeated in many of the subsequent reports produced in the weeks that followed. A couple weeks later, another WHO: Ebola Response Roadmap Situation Report revealed more specific details about activity to improve data in Liberia.

In the past few months, staff from WHO, US CDC and other partners have been working closely with the Liberian Ministry of Health to improve data collection and to integrate sources of data to provide the best possible picture of this rapidly evolving outbreak. Some of this work includes consolidating several different databases and cross- checking numbers of cases reported by the Government of Liberia against cases from laboratory test results. During this process, many cases previously classified as probable and suspected are being reclassified, while at the same time approximately 100 previously unreported cases have been found. These new figures will be published soon, and will reflect significant improvements in data collection, and therefore provide a more accurate understanding of the situation. Liberia remains the country worst affected by the epidemic. (World Health Organization 2014g:3)

These efforts and their consequences for the response were echoed by one CDC interviewee who explained that “We tried to improve the quality of the data and help the ministry of health to make sense of the information coming in.” Later in the interview, he added:

By this time, the cases were down, there were more people--everything was slightly better, I mean I think in November we were finally able to get a much better handle on the data and actually know that, you know, this laboratory result came from this particular person, this is the true number of proven positives that we have today, and whereas, you know, in July, [I was thinking] ”oh my lord, how big is this?” In November and into December, we were sort of saying “how small is this?”

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Developing situational awareness clearly involved not collecting data, but working to improve the quality of the data itself so that they better understand the crisis and derive more accurate meaning from that information.

Deriving or Making Meaning The information content, once assessed and interpreted in light of the information quality, was the basis on which responders made or derived meaning and developed their situational awareness. The following excerpt from one of the WHO Ebola Response Roadmap Situation Reports in October of 2014 illustrates this relationship between information content and quality and how that could be combined to develop an understanding of the Ebola epidemic status:

A large number of suspected new cases (and deaths among suspected cases) have been reported from Liberia over the past week. It is very likely that a substantial proportion of these suspected cases are genuine cases of EVD, and that the reported fall in confirmed cases reflects delays in matching laboratory results with clinical surveillance data. Efforts are being made to urgently address this problem, and it is likely that the figures will be revised upwards in due course. At the present time, the numbers of probable and suspected cases, together with those confirmed, may be a more accurate reflection of case numbers in Liberia. The counties of Bong, Grand Bassa, Margibi and Nimba continue to report high numbers of new cases. There has been little change in the number of new cases reported in Lofa, which borders Gueckedou in Guinea, for the past three weeks, with 38 confirmed and probable cases reported this week. (World Health Organization 2014h:3) Here, the authors of the report highlight the distinction between confirmed and suspected cases, limitations or obstacles preventing a more complete understanding of the cases (inability to link laboratory and surveillance data), and making predictions on the likely change in understanding of the event that will come from improved data

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integration (an increase in the number of confirmed cases) compared with the current documented status of the epidemic in Liberia. This example highlights one of the common forms meaning making took. The meanings people and organizations derived from the information they received and assessed sometimes emerged as assertions or predictions of what the situation or needs would be in the future. They would anticipate what the situation would be like or what they would need to do or have in the future based on the information they had about the past and the present. The following week’s Ebola Situation Report offers another example, stating,

…the reported fall in confirmed cases over the past three weeks reflects delays in matching laboratory results with clinical surveillance data. Efforts continue to urgently address problems with data acquisition in what is an extremely challenging environment, and it is likely that the figures will be revised upwards in due course. (World Health Organization 2014i:3). The authors predict an increase in confirmed cases in the future based on what they know about the limitations of the current data. This was also apparent in the data from the Nepal earthquake response. In my observations of one of the “packing parties” DMRT held to prepare for its deployment, leaders identified some of the items they would bring and activities they would need to do to prepared based in part on their

Haiti deployment, making predictions about the future conditions they would be facing in Nepal based on the information they could obtain about the present and their information from the past deployment.

Sometimes the meaning derived was an increase in clarity regarding the situation or policy rather than a prediction or assertion about the future. One interviewee from CDC occupied multiple roles in the Ebola response. One of them

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was as a liaison to the Department of Defense, a role that generally focused on information exchange and developing situational awareness. In describing this role, he explained that part of this function meant clarifying information and guidelines as they came out. He explained,

And really, it was clarifying too. So, it’s one thing to kinda pass the message or let them know –taking guidance that was getting ready to come out of CDC or whatever the issue was, but often it was helping them get clarity on what the guidance meant.

In this case and cases like it, making meaning of the information meant coming to understand the core message the information conveyed. In this case, doing so meant making sure that the meaning that recipients of the message derived was the same meaning from the information that the message creator (CDC) intended, so that everyone was operating with the same meaning. Regardless of whether people making sense of the information they processed were looking at current circumstances or future ones, they were ultimately developing an understanding of what was happening in the event and response and how that related to them and their activities.

Content and Objective of Developing Situational Awareness The information that was processed covered an array of issues about the decision-making context (see chapter 4 for a more detailed discussion of the information content). This information fell into two general categories of information that were processed: information about the needs (including the intended recipients target area), and information on how to address those need (information regarding the response effort itself, including available resources and existing strategies they could draw upon). As they developed situational awareness, they gathered and processed the

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information about the characteristics of the decision-making setting.5 The Objective of developing situational awareness was to achieve two broad goals: to identify things that that could affect the response and needed to be addressed (needs) and to identify things that could address those items (including resources and strategies). This is information that is key to developing a baseline understanding of what is going on and then in determining what needs to be done.

Different Perspectives in Developing Situational Awareness Although having a shared understanding of the situation among at least some members of the groups was important, situational awareness was not uniform across all parties involved in the relief efforts. Differences in professional background and roles in the relief efforts led to differences in situational awareness. Two factors contributed to these differences. First, by virtue of their backgrounds and training, relief effort participants and their different baseline knowledge going into the relief efforts. Second, due to these different backgrounds and their roles in the relief efforts, people were implicitly and/or explicitly focused on different issues, which lead them to develop different understandings of the needs, context, and relief effort itself.

5 To the extent that crisis relief workers could be harmed by the event, the distinction between survivor needs and response needs was sometimes blurry. Evidence from the relief efforts in both cases revealed that the individuals participating in the response could experience physical and potentially psychological or emotional health consequences. However, rather than negating the existence of these two categories or their utility, this finding emphasizes the importance of continually developing awareness of both categories of individuals in planning and implementing the relief effort.

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Diverse Backgrounds and Roles The professional backgrounds and occupational roles among the interviewees varied. Some had medical training (most of these were doctors, but the sampleincluded representatives from nursing, paramedics, and with general first aid and psychology). Several respondents had previous experience in the military. There were people with backgrounds in logistics while others’ training was in communication. The diversity of experiences and roles affected the development of situational awareness in two ways. First, at the level of individual responders, different people had different knowledge bases depending on their backgrounds, experiences, and positions or roles both within the organizations and the response effort. Second, their roles in the organization narrowed their fields of view so that they were only focused on certain information.

Differences in Knowledge In the data, and particularly in the interviews, it became increasingly clear that knowledge and perspective were not uniform within or across these responding groups. These differences in knowledge and perspective were most clearly apparent in the interviews. Some interviewees would directly state that they were unfamiliar with some of the information informing the relief efforts or how that information was used, and were clear about the limitations of their perspectives for the purpose of this study. When multiple interviews within the same organization were available, differences in content knowledge and focus were apparent in their positions and roles within the organizations. Sometimes one participant was able to speak at length about a topic and provide extensive detail or multiple examples, while another from that organization did not. These differences were present in organizations of all sizes, but appeared to be

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especially the case for interviewees who belonged to large organizations that undertook large and prolonged relief efforts. The responders’ individual backgrounds and experiences endowed them with different sets of knowledge. The military background of many of the Team Rubicon responders meant they knew the demands of working in an austere environment and transportation in that context. Doctors were able to identify medical supplies needed for different medical care and the best science in doing so. Likewise, exposure to or participation in multiple disaster responses allowed individual and organizations to accumulate knowledge through experience. The legal requirements and policies guiding international crisis reliefs, and medical relief in particular, offered another example of how knowledge of the operating environment and the identification of needs varied among members of an organization and could necessitate pulling together the knowledge bases and foci of different members of the team. Throughout the data, interviewees mentioned several policies, procedures, and laws governing international medical relief. Some stated that international groups converging on Nepal were expected to register with the government (as they are expected to do in international response to other types of events in other locations). Others described the presence of laws regarding what medical supplies could be brought in, customs issues for relief supplies in general, and policies for bringing items (specifically controlled medications) back to the United States. Still other participants who provided medical care following the Nepal

Earthquake mentioned having to provide in advance or bring with them copies of their licenses. The Delaware Medical Relief Team, for instance, instructed their deploying members to bring copies of various forms indicating their licensure and training such

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as certificates and copies of licenses, a recommendation reinforced in the packing lists disseminated to (potential) volunteers in a preparation and planning meeting. However, no single person I spoke with appeared to have all of the necessary information regarding these policies. The extent to which different responders knew what these policies and laws were varied not only across the respondents, but within teams as well. An interview with one member of the medical team that deployed to Nepal from the University of

Southern California Keck School of Medicine revealed that though she knew there were policies of registering and proving licensure, another individual with the school (specifically the assistant to the Dean) was responsible for identifying and guiding the group through these policies. With regard to registering the group’s presence in Nepal, there was evidence from multiple groups included in the study that indicated at least leadership in those organizations knew to do so, though it was clear from one interviewee involved in the Team Rubicon Nepal response that not all responding organizations did. While it is possible that some of those unregistered groups simply refused to do so, it is also possible that this reflects different levels of procedural knowledge across responding groups. Similarly, some, but not all participants from groups deploying to Nepal after the earthquake mentioned issues with paying customs on relief supplies. An interviewee from Public Health Service illustrated the disciplinary-specific nature of some knowledge, and as a result, the importance of communicating across these disciplines. He noted that there were several laws and policies guiding how they handle these situations, such as those from the Occupational Safety and Health Administration (OSHA) within the United States, and others international, and a body

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of knowledge under the disciplinary umbrella of a certified industrial hygienist. Working with a certified industrial hygienist in the Ebola responses, as with other responses, was important in making sure they were aware of and appropriately adhering to those laws and policies. This is just one of several examples in which people involved in relief efforts incorporated the knowledge of more experienced individuals or knowledgeable others and individuals with specialized knowledge or expertise to enable a more complete situational awareness.

Differences in Foci and Approaches Not only did responders come in with different information or knowledge bases, but their different backgrounds and positions could focus their attention— consciously or unconsciously—on some components of the response or environment more than other components, queuing them in to some response needs or resources/capabilities more so than others. In a formalized capacity, there were some individuals or units within an organization who were specifically tasked with information gathering and developing situational awareness for the relief effort as a whole, providing the information and even creating a big-picture vision of the situation that members of the organization used in decision-making. A situation from Team Rubicon’s experience highlights the way people’s disciplinary backgrounds and roles (in the absence of experience) could lead them to focus on identifying some needs rather than others, with potential implications for the response. This interviewee was one of the individuals involved in handling logistics for the organization’s response effort, including logistics operations in the crisis- affected areas. Nepali doctors from another medical group had joined up with Team Rubicon to support the provision of medical services (the doctors were originally from

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Nepal, but were living and working in the United States at the time of the earthquake). This interviewee described one day when the team was getting ready to go in to some very remote areas, the doctors

…they showed up in like windbreakers and day packs and you know, for me I’m like, ‘are you serious?’ because if you go out there like that, you’re going to become part of the disaster. So I would say that often times, the medical field in-in responses like this forgets how important logistics is, because—and its’ no fault of their own. They just want to get out there and help, but that—that safety net, that lifeline quickly becomes [taught and] breakable the further they stay out, and if they don’t recognize the fact that they need logistical support, they’ll end up becoming part of that disaster…. He went on to explain, “…once we got them outfitted, they performed remarkably, but it wasn’t on their mind. They were thinking of like, ‘what do I need in my pack to go help those people’, and they’d forget, like, what do they need to help themselves to be able to help those people.” That disciplines and some organizational roles could narrow one’s focus was further illustrated by the degree to which perspectives had to be shifted or expanded to fulfill other kinds of roles. One participant who was involved in the Ebola response highlighted this, discussing how her perspective necessarily shifted from a narrower perspective to taking on a larger view of the response once she transitioned into a position much higher in her organization’s response hierarchy, adopting more of a senior leadership role. The power of organizational role to shift foci in information seeking and sharing was apparent in observations of DMRT. The vast majority of the people involved in the group have some kind of medical background (doctors, nurses, or some other medical position), but the leaders of the group gathered and processed information that went beyond information about medical needs.

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There was some evidence that this may have occurred at the organizational level as well. Some interviewees noted language differences in how different agencies or organizations talked about or saw aspects of the response. One CDC interviewee talked about “learning the culture of how to speak DoD language, and them learning how to speak public health language” as the agency learned what information DoD needed and how that needed to be communicated. Another interviewee from CDC who was involved in the agency’s early epidemiological work in Liberia explained the communication situation during his first deployment to Monrovia:

I think we underestimated early on the need—and actually this is interesting—because, I’ve—I’ve’ now realized this in other areas of my work as well, I think we underestimated the need for much greater investment in data management. When I say data management, I don’t mean epidemiology, I mean basic infrastructure and people to manage data, make sure—just all the logistics, the computers, the reporting,…reports are coming into the ministry on scraps of paper, by cell phone, sometimes by email, but you know very disorganized, and uh trying to make sense of this and make sure there aren’t duplicates and linking it to the laboratory results and stuff like that, and how to disseminate laboratory results to where they had to go…it just was…our investment in that at the beginning and actually throughout the whole exercise, in my opinion in retrospect was grossly under, under emphasized. Here, it appears that the organization and even this individual were very focused on the task of epidemiological investigation, the information needs, and on the importance of communicating the information about the epidemic, but were less focused on the logistical needs required to support the collection and communication of that information.

It is important to note that these differences were more frequently, though not exclusively, mentioned by interviewees who were not medical personnel and were not in a medical role in the response. Sometimes the importance of the interdisciplinary

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composition of teams emerged though a discussion of a problem or disconnect in developing this situational awareness, such as the example from Team Rubicon. Other times, interviewees highlighted the importance or value of interdisciplinary teams in opening up new perspectives or addressing the issues more broadly. For example, a participant who provided relief to the Nepal Earthquake with a group from Massachusetts General Hospital had this to say about the importance of differing perspectives and diverse backgrounds in teams:

To me, that’s one of the best things about bringing a multidisciplinary team. Because, I might not be able to problem solve it with the way I look at it, but if I have somebody who has a completely different perspective, and I listen to them, and certainly I’ll tell you this is something I learned. I didn’t come to this--I had to learn it the hard way, but if I sit back in my uncomfortableness at being not able to solve or problem or listen to somebody and talk about something in a way I’m not used to, and really listen, often times they’re proposing solutions or ideas that improve the function of the team or how we provide care, and it may not have been how I wanted to do it, but, you know what? Half the time or more it ends up better. So you know I’ve learned that over the years that I actually think it’s a huge advantage.

In this case, the different perspectives and approaches that came with diverse team composition were not a problem because through previous experience, she had identified the value of these perspectives and learned how to include and incorporate these perspectives in her process of developing situational awareness as she and her team sought to identify solutions to the problems they faced. These perspectives informed the resources or strategies selected to address them. This interviewee indicated that the contribution of different perspectives was evident in setting up site with clinic spaces when they did not have a structure to operate in. She followed her statement on the value of diverse teams with an example

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of how listening to one of her Nepal team colleagues whose perspective came from a different area of medicine improved their operations.

At one point the OB [obstetrician] said, ‘how about we keep one of the tents up and use it as a private room for OB exams?’…At first I was like ‘well those are our private tents.’ You know you kind of keep this mental separation, and then after, I paused and said ‘no that’s really actually a fabulous idea, and I can’t believe we didn’t think of it until now!’ That’s a great idea, why didn’t we think of that? Yes, we should do that, and we should do that from now forward for when we’re not working in a structure.

In this situation, the colleague’s perspective allowed for the identification of a need and a resource unnoticed by the other team members. Being able to fully hear, consider, and use these perspectives in identifying problems, resources, and other issues was a learned skill as this interviewee emphasized. For some interviewees, learning about these different perspectives and how to identifying sources of information and solutions and the role different backgrounds played in doing so came with experience.

In a similar way, one participant from the American Nepal Medical Foundation, a group predominantly composed of medical personnel, explained that he has a background in both medicine and IT, and it was this IT role he currently occupied. When asked if there were disciplinary-based divisions within the group or issues associated with an emphasis on one set of concerns over another, he believed that these dual perspectives helped to prevent those kinds of cross-disciplinary focus issues. These kinds of statements suggest that the diverse makeup of teams and responders’ ability to communicate across those disciplines or roles facilitated avoiding the kinds of problems or incidents other interviewees raised.

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Chapter Summary The data reveal a process of developing situational awareness in which people and organizations gather and share information through a variety of means, from sources both formal and informal to understand the characteristics of the decision- making context. The specific points of interest they obtain information on are numerous and wide-ranging, but generally center on two areas: (1) information about the event and those affected by it, and (2) information about the response. That information is processed by assessing the content of the information as well as the information quality. The objectives of this process are twofold: to identify things that need to be addressed and to identify resources and activities to address them. While it was more often the case that when there were disciplinary challenges that they more often brought up by non-medical personnel than medical ones, there were certainly interviewees from medical backgrounds who saw these differences and identified the problems and benefits that came from that diversity of backgrounds.

Through the process of developing situational awareness, relief workers learned about the characteristics of the decision-making setting and incorporated these details into their decision-making. This process shares some characteristics with sensemaking theory (Weick 1988, 1993, 1995), including the ongoing nature of the process. Developing situational awareness is similar to sensemaking just as sensemaking is enactive, activity is an important part of the process. Relief workers learned more about their environments and the relief efforts by participating in them. Like sensemaking, developing situational awareness is social in that it involves multiple people and is often dependent on interactions with others. However, researchers typically conceptualize sensemaking as something that occurs in short time periods. Conversely, developing situational awareness takes place long after the

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initial days of the response. This process is ongoing throughout the response. While sensemaking as traditionally defined is not taking place over such an extended time period, elements like those central to the sensemaking process took place long after the hazard event. This process parallels the search process described by Gralla et al. (2016) and the information exchange phase of decision-making talked about in the decision-making literature (Charles et al. 1999). That people engaging in this process did so with others through collaboration and conversation or by gathering information from multiple sources and multiple actors participating in this process at the same time echoes literature on sensemaking (Kendra and Wachtendorf 2016) and decision- making (Charles et al. 1999; Rapley 2008; Goodwin 2014) noting the shared or distributed involvement of multiple people in these processes.

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Chapter 6

DEFINING AND BOUNDING

Both the Nepal earthquake and Ebola epidemic generated increased demands on and disruption to the health systems in the affected areas. The Ebola epidemic severely affected the countries of Guinea, Liberia, and Sierra Leone (though it affected several other countries as well), with 28, 646 cases and 11,323 deaths total as of March 30, 2016 (the World Health Organization 2016). The Director-General of the

World Health Organization declared the Ebola epidemic was no longer a public health emergency of international concern on March 29, 2016 (Chan 2016). The initial earthquake in Nepal occurred on April 25, 2015, with a recorded magnitude of 7.8. Aftershocks followed, including a 7.3 magnitude aftershock on May 12 (Guha-Sapir 2015a). Collectively, the earthquake and aftershocks affected almost half of the 75 districts in Nepal, with 14 labeled as “crisis-hit” (Nepal Planning Commission 2015). As organizations created relief efforts in response to these events, analysis of the interviews, observations, and documents revealed the key role creating and using definitions and boundaries played in guiding and shaping how the relief efforts were designed and implemented. Definitions and boundaries emerged around multiple aspects of the relief efforts for the earthquake and epidemic. As organizations worked to address the health consequences of these two crises, creating and using definitions were an important part of planning and implementing the relief efforts. Definitions appeared in the data for a range of subjects. They defined the event itself, the target areas and recipient(s), the problem(s), goals and objectives, the temporal boundaries of the event and response, and the responders. Many of these definitions were created prior to the onset

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of the crisis, and were sometimes adapted over the course of the response. Others were created during the relief effort. Consequently, these definitions and boundaries were the products of multiple individuals and organizations over time. Through applying and altering existing definitions and creating new ones, these definitions created a framework of operations which used the situational awareness developed, guided further information gathering activity, and guided decision-making.

What they Defined Definitions and boundaries provided frames for responders to understand the events and response and for them to work within, guiding their activity. While many definitions and boundaries appeared in the data, they fell into a few boundary and definition types: definitions of what the event is, of the target area and recipient, of the problem or need, the goals and objectives of the relief effort, temporal boundaries of the relief effort and event itself, and definitions of the responders. Some concentrated on bounding aspects of the crisis itself, while others defined aspects of the relief effort. Sometimes these definitions and boundaries were explicitly stated. Other times these distinctions were more implicit in discussions about the crisis and the response to it.

What the Event Is Defining the event itself shaped how people and organizations responded to the crisis. People defined the type of crisis they responded to. This definition extended beyond defining the event as a disaster (Nepal) or epidemic (Ebola) to defining specific hazard types. The disaster in Nepal was specifically an earthquake (as opposed to a hurricane, tornado, etc.). In West Africa, the event was a public health emergency. More precisely, the public health emergency was an epidemic, which was

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specifically an epidemic of Ebola (as opposed to Cholera, Yellow Fever, etc.). Some data even pointed to further nuancing. Within the Nepal response, some distinctions were made between the earthquake and the subsequent aftershocks, particularly the 7.3 magnitude aftershock on May 12, 2015. In the Ebola response, this nuance appeared in efforts to determine the specific strain of Ebola affecting the region in West Africa (In March of 2014, it was identified the Zaire species, the deadliest of the strains [World Health Organization 2015a]). These distinctions were implicit in discussions with the interviewees, in the observations, and in the majority of the documents. The second component of the event definition involved defining the scale of the event, more specifically as of sufficient severity to demand an international response. Multiple entities made their own determinations about whether these events warranted international response. Some of them had an important official role in defining and labeling the crisis as such. Many interviewees indicated that it was important for the governments of affected nations to determine (and publicly indicate) that their crisis was one that needed an international response, because a request from the affected country is key in both receiving and allowing international support. Some interviewees from U.S. government entities like the Centers for Disease Control and Prevention (CDC), United States Public Health Service (PHS), and the Office of the

Assistant Secretary for Preparedness and Response (ASPR) discussed the role that recipient governments played in defining the event for international governmental responders. It was their understanding that the local government defining the crisis as requiring international support and requesting that support was central for the involvement of their respective organizations. Dahl et al. report that a small team of CDC staff arrived in Liberia “after a request for assistance from Liberia’s Ministry of

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Health and Social Welfare” (Dahl et al. 2016:16). Similarly, United Nations resolutions, while emphasizing the importance of responding to human needs generated by disasters, siultaneously emphasizes “the sovereignty of affected states and their ‘primary role in the initiation, organization, co-ordination and implementation of humanitarian assistance within their respective territories’” (Fisher 2007:54). Other interviewees indicated that this was increasingly important for NGOs as well. As one Team Rubicon participant explained,

A key factor in there of course is whether or not the country in question has requested international assistance. There’s been a very active movement towards formalizing the inclusion of international response resources in domestic responses among the international community over the last three years. So it’s not as acceptable especially for large organizations to be cavalier in just saying ‘we’re coming’ and then go there and spontaneously respond without coordinating with national resources. That is nowadays one of the biggest triggers outside of population need and outstanding risk.

Thus, the definition developed by the host nation was important in shaping the relief effort by simply identifying a need for international aid. That said, there was evidence indicating that, while there may be increasing pressure to do so, waiting for a request from the host country was not as firm a requirement for NGOs as it was for government responders. One Public Health Service interviewee speaking about the response generally suggested as much. Evidence from the health cluster situation reports for the Nepal earthquake reveal increasing numbers of foreign medical teams arriving in country at the same time those documents reported Ministry of Health requests that no more foreign medical teams arrive, further supporting this claim.

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Definition of the Target Area and Recipient Another important definition for the relief efforts was the definition of the target area and aid recipient. In both cases, the populations of the affected areas were quite large. Planning and implementing the response involved specification of the people organization aimed to help. Looking at the first, in both cases, multiple geographic areas were affected by the crisis. Organizations defined which areas were and were not affected by the crisis event. For example, situation reports produced throughout both responses noted specific affected areas and the severity of the event impact, sometimes depicting these features graphically though the use of maps. In addition to defining affected areas in terms of size and severity, organizations defined the specific areas in which they would operate. Both within organizations and in interactions between organizations, people placed boundaries around areas in which they intended to or were already working. Fairly early on in the Nepal earthquake response, groups began claiming areas for particular initiatives, and undertook efforts to map these claims. The Nepal Health Cluster Situation Reports capture this combination of defining activities, explaining in the April 30, 2015 situation report that,

WHO [World Health Organization] is establishing a surveillance system for epidemic-prone diseases, mapping the locations and activities of Health Cluster partners, and assessing overall health needs and gaps. WHO has prepared maps showing the location of destroyed and damaged health care facilities and the distribution of field hospitals and foreign medical teams. (World Health Organization 2015e:2). This quote shows that at the same time they were developing situational awareness, they were translating that information into definitions through the graphical display of areas of impact, types of impact, and locations of operation for foreign medical teams and Health Cluster partners. This implicitly defined areas that needed to be targeted

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with relief resources and areas in which some of those needs were being addressed through a group(s) efforts. Interviewees similarly noted this transition. “Already the information switched from who has need or who needs immediate need, to who’s rebuilding, who’s going to be providing long term coverage, who has what territory, and what isn’t covered right now?” explained one Nepal earthquake responder from Team Rubicon who participated in this mapping process. This documenting process transitioned from needs assessments to, in his words, “a little more political geography with boundaries and capabilities measurements than it was about the points of need and specific emergencies in these locations.” This geographic bounding also occurred in the Ebola response. Speaking about the public health response in Guinea months into the Ebola Epidemic, an interviewee who worked with the International Office of Migration noted the designation of organizations to specific regions in the country. One group was assigned per region. Occasionally, two groups were assigned to some areas when an organization was unable to implement the program on its own. She said, “We did the 4W mapping. IOM was responsible for, was in charge of that, the mapping. We made pretty maps with who was going to be where and who had commitments where, and who was potentially going to go where.” An organization’s scope of activity was geographically bound to particular areas through their own decision-making or from others. These kinds of boundaries were useful to ensure areas were adequately and relatively equally covered. They helped avoid duplication of effort and guided decision making. Because there ended up being fewer actors involved in the early stages of the Ebola epidemic, this didn’t happen on quite the same scale early on as it did with the Nepal earthquake.

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While the two aforementioned examples illustrate very deliberate efforts to define and bound, more implicit defining and bounding processes emerged as well, such as Samaritan’s Purse’s focus on Liberia in the Ebola Epidemic. Samaritan’s Purse’s involvement in the provision of medical care was confined to the country of Liberia. This was because they already had medical operations and infrastructure in that area. Defining Liberia as their area of operation was less a conscious effort to carve out the country as their own territory, than it was the use of their existing geographic operational boundaries applied to this epidemic-related activity. Organizations had to determine who they were going to target their relief efforts on. Sometimes target populations overlapped with geographic boundaries, such as when an organization focused on a particular community. However, target populations were defined in other ways as well, identifying a subset of the affected population based on other characteristics. An example of this kind of distinction is the target population for the Monrovia Medical Unit (MMU) set up near Monrovia in

Liberia. The MMU was established specifically to care for healthcare providers infected with Ebola. Rather than caring for anyone with Ebola Virus Disease, the MMU restricted its attention people who had gotten infected as a consequence of their participation in the Ebola response. The target population was a subset of the larger group of Ebola patients defined around their role in the healthcare response. Defining these target populations was sometimes challenging. Challenges emerged, for instance, when trying to target relief efforts on individuals with certain health consequences. In the Nepal earthquake case, defining a specific target population could be challenging as they tried (or did not try) to distinguish between individuals who were directly injured in the earthquake from other individuals in need

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of assistance. Several interviewees noted that many people had health consequences as secondary effects of the earthquake. For instance, some people had chronic conditions before the earthquake that they were able to manage successfully with the help of whatever health resources were available to them. When those health resources were destroyed in the earthquake, it affected their ability to meet their health needs. These needs would not be apparent in the immediate aftermath of the earthquake. Instead, they would gradually emerge as injuries directly related to the earthquake were addressed and the consequences of the lapse in management of these chronic conditions increased in severity. Groups maintaining a focus on earthquake-affected populations needed to define those secondary health consequences as earthquake- related in order to define the target population as earthquake-affected. As a result, definitions of the target population were closely related to the problem definitions relief agencies constructed.

Definition of the Problem Organizations defined and bounded the problems with the crisis and the response to it. This differs from the identification of needs as described in the previous chapter in that the definitions offer a more comprehensive understanding of the problem, such as the problem being defined as a medical problem or an issue of public health rather than specific needs of not enough of X resource in Y location. Central to the relief efforts were definitions of the type of health or medical problem the organization addressed. In both cases, data revealed conceptualizations of the problem as medical. Many interviewees defined the type of injuries they anticipated to see. In the Nepal earthquake case, these were generally crush injuries, and the type of wounds associated with falling structures. In the Ebola epidemic, this

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was the palliative and isolation needs associated with infected Ebola patients. Within that, problems could be defined as a shortage of medical personnel or supplies required to address those health problems.

Defining in Public Health and General Wellbeing Terms As time went on, these problem definitions shifted or expanded beyond the presence of direct crisis-inflicted health consequences. The data indicates that the problem was identified as one of broader health needs, concerns over general wellbeing (or broader definition of health), and especially towards making the health response in terms of public health problems (and solutions) rather than medical ones. This was evident in both cases. One way this was apparent was in the definitions of the kinds of patients and health consequences organizations would see. Participants in the Nepal earthquake relief efforts talked about different categories survivors based on the severity of their injuries. Many of them noted that the type of patient and medical need they faced (or expected to face) depended on how long after the earthquake they arrived. One interviewee, for instance, arrived in Nepal three or four days after the earthquake, and he revealed that “the vast majority of cases had already been kind of identified and stabilized, which was not super surprising to me.” He elaborated on this point, explaining

Any kind of mass trauma situation, basically if you survive the first 24 hours, you’re probably going to survive [a given] length of time. At 48 hours, you know you’re probably getting to people that are going to just survive in general, but medical intervention would certainly be appreciated for fractures and that kind of stuff.

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What this statement illustrates is the appearance of problem definitions around needs, which based on the changing needs associated with different time periods after the response. It demonstrates a shift away from problems being broadened. These evolving problem definitions also appeared in changes in the activities. Soon after Medical Teams International started delivering earthquake relief in Nepal, they very quickly identified hygiene as a larger, more important issue. They subsequently shifted their work to focus on Hygiene practices (like handwashing).

There was a general trend among the efforts included in this study for problems and needs to be defined around public health terms. For the most part, these broader wellbeing and public health definitions were developed or applied later in the relief effort. The America Nepal Medical Foundation (ANMF) offers an interesting counter example. The ANMF is an organization of medical professionals (primarily doctors) in the United States from or connected with Nepal. Their goal is to support and improve healthcare and medicine in Nepal. They did not consider themselves a disaster relief organization, and only became involved in the earthquake relief effort because it affected the country on which they concentrate their efforts. Immediately after the earthquake occurred, ANMF leaders in the relief effort defined the problems as immediate needs related to shelter, food, and water supply. They defined problems around medical need later. This is particularly interesting because they are specifically a medical group. Most of the other medical groups immediately defined a medical need, only moving on to broader wellbeing needs with time. The America Nepal

Medical Foundation is an exception from this pattern. These approaches reflect a problem definition that extended beyond setting broken bones and treating crush injuries from the earthquake. Some of the

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interviewees from one group discussed their provision of routine medical care and concern for meeting basic needs (shelter, replacing damaged food supply and clean water, especially with the onset of rainy season coming. They delivered food, bags of rice and lentils, and shelter (tarps, and tents) and to a lesser extent supported clean water. They explained that a lot of disaster response is restoring access to basic resources, including health care. In the words of one interviewee, “unless we can restore these things, there’s no point in just doing trauma care and then leaving. That’s not going to be helpful in the long term.” They saw these other activities as supporting the overall health/medical mission. Another member of the group echoed these sentiments, saying from the development side “I’ll make a note here just in saying that, we say development, but [at the end of the day]…it can all be related to public health.” This individual went on to explain the challenges inherent in constructing clear boundaries around these broader need definitions when services to these communities that are generally underserved independent of the post-earthquake context.

the separation too in issues that are specifically incident-related, and then the incident issues that are chronic based or simply exacerbated by the incident at hand that were chronic to begin with. There’s a lot of pressure in these communities where they haven’t got a lot of regular medical care to begin with, to naturally take advantage of the resources that have suddenly appeared to get care for issues that have been outstanding and aid organizations run into trouble of when do we turn people away, when do we shut down operations, because there are going to be plenty of people that need distinct care to western standards, and organizations are often driven to provide to western standards, but when we walk away, those standards won’t be maintained. That continuation of treatment won’t be there, and we may actually be causing more harm. It’s a conundrum that we have to deal with of where do we draw the line in general treatment as we’re treating people, and where do we draw the line in terms of operations with when we choose to shut things down. There’s immense pressure

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for mission creep, to increase what we’re treating, or to increase the length of time that we stay there, because of that desire to do good and the requirement often for medical care to be provided to western standards. In another example, a university hospital-affiliated team distributed supplies throughout their time in Nepal, “We distributed a lot of medications wherever we went….” In addition, they “brought over a hundred water filtration systems with us, and each one of those water filtration systems was capable of filtering a million gallons of water. So that was, you know, in the long run, probably our biggest contribution, was the distribution of supplies as well as the water filtration systems.” This kind of definition, which was incredibly visible in the data from the Nepal response, was apparent in data from the Ebola epidemic. One interviewee from IOM noted that at the point she was involved in the public health response for Ebola (much later in the Ebola timeline than many of the other Ebola interviewees), the importance of the public health response for the medical response to mean anything was generally recognized. Similarly, another interviewee responding to Ebola noted that it was really important early on to meet general wellbeing needs (and public health needs). Speaking more broadly about crisis medical response in general, he noted that there is a tendency to want to get surgical teams on the ground quickly, but that is not necessarily the biggest or most impactful response. Providing clean drinking water can go a long way in supporting people’s health, summarizing by saying that “the big thing is water, food, shelter.” This problem definition shift resulted in similar problem definitions for both events, and similar activities around those definitions. For example, defining infectious disease spread as a problem which was addressed through handwashing campaigns and messaging were developed for both events. Collectively, this evidence

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suggests medical response and relief efforts adopt definitions of health needs that embrace a more holistic view of needs the entire way of the response. This is important because it happened with both Ebola and Nepal. The foci in Nepal once this occurred made it very similar to Ebola (Public health campaigns), and for the participants themselves, accepting this wider definition of health problems that they could address better enabled or better ensured that they would be able to contribute to the response in some way.

One of the many critical gaps in the response was that communities were not identifying their sick people. Without community members identifying themselves/members of suspected cases, “the whole rest of that medical machinery that was put in place would serve for nothing.” This issue was apparent in the shifts in messaging. One interviewee working in the public health response in Guinea after the peak of infections described how the messaging changed to reflect broadened perspectives (in this case to make affected populations more receptive to the messaging):

As much as possible, we tried to change the dialogue, to not being about Ebola, but to be about health in general. People were tired of hearing about Ebola, they were sick of hearing about Ebola. They felt like people didn’t really care about their health. They felt that people just saw them as potential vectors of a disease, and that really, really pissed people off, and understandably so. Because of all the concentration on containing the disease, many Guineans—I can’t speak for Guineans in general—but many of the Guineans our team encountered and spoke with felt they were only valued or seen or cared about insofar as they were potential vectors for Ebola. And that was not a fun position for them to be in. So, we altered our messaging based on that to really talk about more just general health and epidemic diseases…these other things that people have lived with for much longer, and to be honest affected them much more than Ebola was, and that they cared more about. So the more that we broadened our message, the more people were receptive to it.

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She went on to explain:

If anything, organizational mandates and priorities probably took precedence over the more personal background issues…. In public health training, you always talk about the divide, right, the medical- public health divide, medical people see patients, and public health people see populations, but Ebola pushed everyone to see the same thing, in some ways. Doctors had to reconcile themselves with the fact that there was huge cultural and social dimensions behind people accessing care and us public health people had to recognize that we had no idea, you know, the technicalities of this actual virus, right? And [once you get the person in] the clinic door, you couldn’t not be in awe of the doctors who were treating these patients, and nurses of course, and everyone else who was part of that effort. This interviewee’s statements demonstrate the general shift in problem definition that took place among individuals participating in the relief efforts. As the response went on, members of different disciplines came to define the overall problem less in terms of their discipline towards a more comprehensive definition of the problem and solution. Similarly, the problem definition moved from being specifically about Ebola to encompass other related health issues and broader health and wellbeing themes.

Goals and Objectives Linked with problem definitions, organizations defined their relief effort goals and objectives. For instance, one senior CDC interviewee explained that “the goal of the response was to stop transmission in West Africa and to prevent spread of disease out to other countries.” Another interviewee who was involved in the public health response in Ebola revealed that the work she was involved in had three goals, including encouraging people to voluntarily share information of sick individuals, creating a network of community health volunteers who both recognized Ebola symptoms and were equipped to notify appropriate entities of a new case at any time,

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and to train health posts on what to do if they received notification of a new Ebola case. One of the organizations deploying to provide medical care in Nepal, in addition to their goal of treating people injured in the earthquake, identified additional goals for helping the communities they encountered, including providing more basic health care and supporting the local economy. Interviews with Public Health Service personnel revealed several goals to be achieved with the establishment of the Monrovia Medical Unit. Its purpose was to treat sick healthcare workers and those who had become ill through the course of their involvement in the epidemic. However, an interviewee suggested that another goal was to support the overall supply of healthcare workers. The MMU did this not only by caring for sick health care workers who could presumably return to work once they were better, but by demonstrating to healthcare workers that if they got sick, they would be taken care of. The thought was that if people knew that they would be taken care of if they were sick, more people would be willing to volunteer or work in the

Ebola clinics, thus increasing the number of personnel. As one PHS interviewee explained, “The psychological benefit of having a facility that could care for medical providers was huge, in terms of…folks willing to continue the fight against it in the general population,” (though he noted that he only heard evidence of this anecdotally).

Another PHS interviewee noted the political goals or objectives underlying any government initiated relief effort.

Temporal Boundaries of the Event and Response

People and organizations involved in relief efforts created and applied temporal boundaries to their work, the relief as a whole, and even the events themselves. Temporal boundaries were linked with many of these goals and

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objectives. Associating goals and objectives with deadlines limited the time frame in which certain activities took place. For instance, the following statement appeared in the WHO Ebola Response Roadmap Situation reports from both 15 October and 22 October, 2014:

In accordance with the WHO Ebola Response Roadmap, the 90-day Ebola Response plan requires that at least 50% of major inputs in five crucial domains be put in place by 1 November, with 100% of inputs in place by 1 December. Progress towards putting these inputs in place and the attainment of each target will be assessed through a comprehensive response-monitoring system, and will be reported in due course. (World Health Organization 2014j:5-6; World Health Organization 2014k:7) In this example, the goals do not just pertain to an amount of inputs in particular domains, but that those inputs be complete by a certain time frame. Data revealed important boundaries in time for other aspects of the relief operation. Organizations defined deployment durations, defined by the numbers of days or weeks spend working in the field. Within or in addition to these deployment time frames were other deployment-associated time frames, such as defining how much time was spend in transit (and not in their actual relief role) or in quarantine. People defined the phases of the crisis relief. Some talked about phases of the disaster cycle, locating their activity in the response phase or the transition from response to recovery. One interviewee in the Ebola response described her involvement as spanning three phases. She described one as focused on building Ebola treatment centers and conducting safe burials (from approximately July-November of 2014). The next phase focused on bending the curve, stopping exponential growth of disease spread and getting basic epidemiology back online by supporting contact tracing and supporting other epidemiological tools. She described third phrase as “getting to zero.”

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This phase was characterized by much of the detailed contact tracing, the incidence sexual transition, and was getting in place as she transitioned out of her role in the spring of 2015. By describing the phases in terms of the activities taking place in them, she linked temporal boundaries and activities. In another Ebola example, in the Ebola response, 21 days was an important marker because that was the incubation period. If a person was infected with Ebola virus, they would begin to develop symptoms within 21 days. Forty-two days without an Ebola case was another important threshold. According to the World Health Organization, 42 days without a case of Ebola (double the 21-day incubation period) marked the threshold for considering a country Ebola free. This period was followed by a 90-day window of intense surveillance, a time period informed by concerns about reemergence of the disease by transmission from animals, travel of infected individuals, and possible sexual transmission from survivors to their partners (World Health Organization 2015a). Not only were these time frames important in their own right, but they served as important criteria for defining areas as Ebola free, and by extension marking a new phase of relief operations.

Responders People defined the responders both at the organizational and individual levels.

Sometimes these definitions were clear in the organizations’ missions and origin stories. Other times they emerged in the explanations of what the group was that participants provided in the interviews and observation. Still other times these definitions were less obvious, but emerged as implicit understandings of what the group was, and when multiple people from the same organization were interviewed, were understandings that were shared by multiple group members. These implicit and

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explicit definitions described who the groups and individuals were, including their purpose, mission, identity, and composition. There were several traits raised as defining features of the organizations. They were defined by their term of involvement (short term, long term, response or recovery), as providing medical relief or public health response services, and by the way they provided relief (mobile versus stationary, bringing in their own supplies to set up their own clinic or partnering with an existing facility). Groups were defined by their origin story, composition, and organizational base. Samaritan’s Purse is a Christian organization, and its activity grounded in the Biblical parable of the Good Samaritan. One interviewee explained:

Our organization is formed out of the parable of the Good Samaritan in the bible….There was a Samaritan who was sort of a social outcast of the day, and he’s going down the road and this guy’s beat up, he’s laying over in a ditch, he’s naked, and he’s been left for dead. Left for dead. And the religious people of the day walked around the guy, but when the Samaritan came to him, if you read the scripture in the tenth chapter of Luke, he went to him, that was the first thing he did, he went to him. And if you’re anybody who’s going to be involved in disaster response, I don’t care if it is Ebola, or if it’s measles, or if it’s cholera…or if it’s earthquake, or food, or famine, whatever it is, go to them. You must go to them, and I think that’s probably the single greatest piece of advice that I could give. Being a Christian organization was a central feature defining the organization, what they responded to, and how they responded to it. Similarly, members of the America Nepal Medical Foundation who I spoke with described themselves as a medical organization generally focused on healthcare and medical care in Nepal, but not a disaster relief organization. A number of other categories emerged as well. Beyond the specifics of CDC’s mission, CDC was defined as broadly a science organization. The title of foreign

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medical team (FMT) distinguished the converging medical relief from local medical resources. Specifically, the World Health organization defines FMTs as “groups of health professionals and supporting staff outside their country of origin, aiming to provided health care specifically to disaster affected populations”, including nongovernmental groups and civilian or military governmental ones (Norton et al. 2013:27), and that FMTs have “staff to provide basic and/or advanced healthcare based on international classification levels and minimum standards during a limited time period in existing or temporary structures, with or without field hospitals” (Norton et al. 2013:27). Even within FMTs, there were distinctions between different types, distinguished by their mobility, resource, and the kind of care they provided. For instance, Team Rubicon’s special distinction as a Type I mobile medical team. According to the World Health Organization, a Type I team provides “[o]utpatient initial emergency care of injuries and other significant health care needs” (Norton et al. 2013:28). Several Team Rubicon interviewees told me that being distinguished as a mobile medical team, meant they can be self-reliant for up to 72 hours. This was a distinction and recognition the group pushed for within the World Health Organization to capture the kind of work they do, work that they felt was valuable, but believed was not reflected in the existing WHO framework. Once these definitions were established, they can be used as a guide for organizational activity. Team Rubicon offers another example of several of these defining characteristics. Team Rubicon emerged out of the Haiti earthquake when former members of the U.S. Armed Forces converged on the country to help in complex aftermath of the crisis, believing that their military skills, including their ability to mobilize quickly and function well in austere environments fit well with the demands

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of the post-disaster environment. Approximately five years later when the Nepal Earthquake occurred, the organization had grown in size, but still defined itself by many of the characteristics valued in that initial group. While not exclusively comprised of former military personnel, interviewees defined the organization as a veterans-based organization that draws on “kick ass civilians.” Because of this background, they see themselves as having unique skills to offer in terms of mobilization, ability to access remote areas, and ability to function in austere environments, among other traits. Consequently, they define the organization as one that gets into the field quickly and is particularly focused on the response time period and performing ‘gap-filling’ activity. Another distinction is the one which one member of Team Rubicon said the organization makes between response and relief. While relief was seen to consume longer term efforts, they define response as filling the gap between the creation or identification of those needs and the ability of groups launching those longer term, larger scale relief effort to stand up and meet their needs. This distinction is informed by the backgrounds of the group of individuals who founded and largely comprise the organization. The distinction is important for this group because they only see themselves as participating in one of those activities (response). They view their role this way specifically because of the gap they identified (the gap between event and the onset of relief services) and the skills they believe they can bring (rapid mobility and functionality in austere environments based on the military background of many volunteers), which they believe aligns more clearly with the rapid movement required in response activity.

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Within these organizations, groups or communities of individuals were categorically defined as well. Some interviewees categorized members of organizations as emergency managers compared to scientists, or more specifically, as medical personnel and doctors. Within ASPR, definitions of some personnel as PHS identified a subset within their ranks that was an important definition/distinction during role allocation. One CDC participant distinguished between individuals in communications who worked in risk communication compared to those trained to work with the media. For many organizations, the definition of their personnel as volunteers compared to paid employees was a meaningful distinction with significance for the response. The definition of responders is partially informed by previous experience. Samaritan’s Purse seeks volunteers to identify personnel for its missions, but once they volunteer, they are paid. The purpose of doing so is so that everyone involved is designated as an employee, which reduces the complications that could arise in some situations, thinking especially of issues pertaining to insurance.

Connections Between Definitions As is evident in the descriptions of the kinds of definitions and boundaries important to the response, many of these definitions are connected/linked to each other. Changes in one definition could be linked to changes in another. For instance, changes in the definitions of needs and problems could shape the definitions of goals and objectives as well as what the group does. Likewise, the temporal boundaries of the event or especially of a group’s involvement could shape the objectives defined for their involvement. The opposite could also be true: resources permitting, the stated objectives defined for the group could shape the temporal boundaries of their time in the field. One interviewee indicated this occurred when they stayed in the field a little

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longer than the organization typically does in order to support some communities they were working with in preparing for the oncoming monsoon season. These connections appear in how organizations worked with and used definitions in planning and implementing their relief efforts.

How Responders Worked with Definitions and Boundaries

Development and Change: Selective Bridging, Breaching, and Alteration

These definitions and boundaries were created over time and evolved with the relief efforts. Defining the event as warranting international response and as fitting within the group’s mission or their measure of relevance occurred after each crisis began. Defining the Ebola epidemic as a public health emergency of international significance, for instance, relied on the WHO’s existing definitions of such an event. They continued to define problems and goals as they learned more about the situation, became more engaged in the response, and conditions changed in the areas affected by the crisis, as occurred with the development of plans like the Ebola response roadmaps, which often involved multiple individuals and groups connected with the response. However, many of these definitions and boundaries relief workers relied on developed before the crisis event. Some individuals from organizations with ample experience in this field claimed that, because of their experience, they already know what the problems are and what activities are required to address those problems, indicating predefinition of needs and aid delivery before any given event. In some cases, they emerged in a previous event. In others, they were produced during planning processes taking place independent of any crisis response. Thus, having more previous experience or simply being an older organization, in many cases, meant

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having more of these definitions and criteria in place than their newer, less experienced counterparts. The creation of these boundaries and definitions was took place over time and involved multiple people to a greater extent within older, experienced organizations compared to newer, less experienced ones. Even when relief workers and organizations used pre-existing definitions, they did not always use them in their original form. They either altered (even if temporarily), their definition(s) or justified breaching or bridging across boundaries that were previously determined. They often reframed the breach to fit in their mission, definition, or obligation. The changing definitions of team membership or partners can occur through event-specific partnerships and participation in the cluster system, where boundaries between groups may temporarily be suspended to facilitate sharing of information or collaboration. The U.S. Public Health Service response offers an example of the bridging or selective breaching that occurred simultaneously with the sectioning activity. Inherently, they were working with USAID and DoD, though each of these entities were responsible for distinct aspects of the response (USAID funding among other things, DoD logistics, and PHS staffing and providing care in the facility). Boundaries between organizations were selectively breached when responders from one group were sent to another organization for training. A group from the Nepal earthquake case offers another example of selective breach. One hospital-affiliated organization has extensive requirements for participating in their response efforts that includes substantial training which must be documented. However, they allowed a doctor to join their medical relief effort without having gone through most of that credentialing. They made this exception because this

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doctor was originally from Nepal, and therefore could contribute to the cultural competence and translation capability of the team, and provide local knowledge and general familiarity with the country. The group included him on the team with some the requirements expedited and some waved (but maintaining the ones critical for participant safety). Here, the criteria (definition) required to become a deployable team member was temporarily breached when doing so facilitated the success of the overall mission.

Definitions at Odds As is clear from this discussion, multiple groups engaged in creating and adapting these definitions. Sometimes they co-created the same definition, but other times, they were simultaneously creating separate definitions of the same issues. While sometimes multiple groups came to define the event or an issue the same way, there was evidence of instances in which different parties appeared to create divergent definitions. The continued arrival of foreign medical teams (FMTs) in Nepal despite reports from Nepal suggesting that no FMTs were needed there serves as one example suggesting different definitions and their consequences for the response. In the Nepal earthquake, several local hospitals in Kathmandu determined that they did not need personnel support from Foreign Medical Teams (FMTs) and there were requests from the Ministry of Health for additional outside medical groups to not come, yet FMTs continued to arrive, numbering over 100 registered teams at peak numbers (World

Health Organization 2015i; World Health Organization 2015j). As early as the first Health Cluster Situation Report for the Nepal Earthquake dated April 26, just one day after the earthquake, there was limited need for FMTs in Kathmandu hospitals based

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on the first needs assessment organized between the Health Minister and Kathmandu valley hospital directors. Specifically, the report states “Directors informed to the Minister that they do not need foreign medical team to support them in their respective hospitals” (World Health Organization 2015b:2). This statement was the only point in the two-page document in bolded text, adding to the emphasis behind this claim. Two days later, some FMTs arrived, but “MoHP request that further medical teams coming to Nepal be on standby as FMTs continue to be deployed” (World Health Organization

2015c:1). This pattern continued over subsequent days, with the arrival of more FMTs occurring simultaneously with requests from the Ministry of Health and Population for no further groups to arrive. The next day, “The MOHP has thanked all countries who deployed foreign medical teams, and announced that it does not require additional teams. All foreign medical teams on standby are therefore kindly requested to stand down” (World Health Organization 2015d:1), and by April 30, 2015, there were over 60 FMTs in Nepal (World Health Organization 2015e:1). On May 1, there were more than 75 FMT’s in the country, and the situation report nuanced the needs report to state “No further teams are required, but medical tents and supplies are still required for the national effort” (World Health Organization 2015f:1). This situation documented in the Health Cluster situation reports reflects what were likely conflicting definitions of the need or the place of FMTs in the response. While it would appear that people representing multiple converging medical groups from outside Nepal independently (but simultaneously) defined the situation as requiring international aid and as something they should respond too, local health and medical entities defined existing personnel resources as sufficient. Ultimately, these definitions changed over time, becoming more location specific as the Ministry of

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Health directed organizations to the more rural areas, and the organizations themselves came to define the rural areas as the specific locations in need. That multiple groups were able to construct their own definitions presented opportunities and challenges for the organizations. The ability to create their own definitions allowed organizations to develop and use the definitions that best supported the organization’s desired goals. However, this freedom for groups to create their own definitions presented problems for the recipient nation to the extent that it limited their ability to control the response within their country. That different groups could come up with their own definitions was true in the Ebola epidemic. Conversation with some interviewees involved in the Ebola comments suggest that the early months of the Ebola response were marked by differing definitions of the severity of the epidemic, the relevance to the international community and the role of outside actors in the response. Groups like Médecins Sans Frontières (MSF) and Samaritan’s Purse clearly defined the event as serious and necessitating the involvement of the international community, and then actively campaigned for those points. In both an op-ed in the New York Times (Isaacs 2014a), and in testimony before the House Committee on Foreign Affairs; Subcommittee on Africa, Global health, Global Human Rights, and International Organizations (Isaacs

2014b), Ken Isaacs, the Vice President of International Programs and Government of Samaritan’s Purse at the time of the Ebola epidemic, pushed to the international community to share that definition and get them to participate in the response. The lack of involvement of other international entities suggests that they did not share this definition, at least not defining it as something requiring their involvement if not the seriousness of the event itself.

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Use: Connections to Other Processes The process of working with definitions and boundaries is linked with both developing situational awareness and the process of matching and aligning.

Developing Situational Awareness The situational awareness that people who participated in the provision of crisis medical relief developed informed the creation, application, and adaptation of definitions. Changes in circumstances were reflected in changed information and interpretations of the environment, changed definitions used to label the crisis and response, and changes in the boundaries they worked within. This is clearly the case in the shifting definitions of problems and needs from a more focused idea of medical needs to an expanded definition that includes issues of public health and broader health and wellbeing needs. In other words, the information gathered and situational awareness developed could inform and even drive changes in boundaries guiding the decision-making and activities of the relief efforts.

Likewise, the data suggest that definitions can inform the process of developing situational awareness. Definitions and boundaries sometimes (re)focused attention and (re)framed communication efforts that affect information seeking and sharing as well as how people made sense of that information. Definitionssometimes narrowed what kinds of information people looked for, what kinds of needs they tried to identify, and how they ultimately defined the problems. For instance, as mentioned earlier in the chapter, one senior CDC interviewee explained that “the goal of the response was to stop transmission in West Africa and to prevent spread of disease out to other countries.” She went on to explain that from there, they then identified the things they needed to accomplish that goal, identifying several needs including

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surveys to collect data and teams to identify cases. In other words, based on the defined goal, they then focused part of their information seeking and situational awareness activity on a field of issues related to that goal. Groups that defined themselves as being health and medical relief groups concentrated on identifying needs falling under that health and medical needs umbrella. This was the case for groups like the Public Health Service in the Ebola epidemic, and the hospital based groups like those hailing from USC Keck School of Medicine and Massachusetts

General Hospital. Other groups with somewhat broader organizational definitions captured somewhat wider ranges of information, such as Team Rubicon, which also conducted damage assessments. The definitions that are developed here may ultimately serve or create some of the categories that get compared to each other in the assessment portion of developing situational awareness. One example is the definitions of which areas are crisis affected in Nepal and which countries have epidemics versus which are Ebola free. These definitions created categories which were compared to each other as a means of understanding the status of each area and the overall crisis situation.

Matching and Aligning The definitions and boundaries created have an important connection to the matching and aligning process as well. Definitions and boundaries guided the matching process. Definitions themselves were also be matched. One of the CDC interviewees described this connection between creating definitions and matching.

Talking about the incident management system that CDC used to structure its Ebola response (and other responses), this individual stated that “The point of an incident management system is really to… define what the problems are, what your goals are,

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and then to organize in such a way that you can accomplish and break things down into finite tasks, so it’s not an overwhelming problem, and that you [sort of] break down those tasks and assign people to those tasks.” In this example, the definitions of the goals and problems clearly served as the overarching guide for what the organization should do, but as members of this organization defined individual tasks, people were matched with those definitions. Different services or activities, for instance, were matched to definitions, and changes in the definitions could yield new sets of matches. In the Ebola epidemic, as the response was coming to be redefined as recovery and relief workers began defining needs in public health or broader health need terms, personnel, including those from CDC, began matching and aligning activity to meet those new definitions, including setting up disease surveillance systems that would identifying and track diseases beyond Ebola. Around the same time, they began identifying diseases that would be automatically reportable to the ministry of health (thus, the new definition of public health needs facilitated matching of new reporting systems, which in turn lead to the development of new definitions to match the priorities and protocols of the new system). Organizations matched messaging to the new definition of need. IOM did this when it broadened its public health messaging to address multiple health concerns. In this case, the broadened definition of health concerns matched the changed attitudes regarding Ebola and the Ebola response among the affected population. Similarly, continuing to promote hand washing was beneficial because it not only limited the spread of Ebola, but could limit the spread of several other illnesses and diseases. As one CDC respondent explained, “It’s kind of like using a lot of the structures and other

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things that we set up to go into a broader [range of] outbreaks or general, like, public health initiatives.” She further explained that this was using this epidemic as an opportunity and considering the lessons learned and their transferability to other epidemics and public health issues, taking advantage of the networks and “window of opportunity.” In other words, there was a shifting definition of the problem to broader health needs, which then triggered a matching of the Ebola health systems and structures to these larger public health agendas. In sum, the definitions and boundaries used in the relief efforts themselves reflected and shaped the relief efforts over time.

Chapter Summary The actors involved in these relief efforts used definitions and boundaries throughout the relief efforts. These definitions and boundaries covered a wide range of issues important to the response, from problems, to goals and objectives, to group definitions. Sometimes, they used definitions that pre-existing the crisis they responded to. When existing definitions and boundaries were insufficient, they adapted those boundaries or they created new ones altogether. Among the definitions that emerged, it is particularly interesting that relief workers and organizations shifted to conceptualizing the problems they were trying to address in broader wellbeing terms, often more reflective of public health perspectives. This echoes similar statements by Van Rooyen who noted based on his years of experience in medical relief to a range of crisis that “Humanitarian crises like the Ethiopian famine and the Kurdish refugee crisis were increasingly recognized as acute, massive public health emergencies” (2016:38). These definitions were important in the response. They placed limits on different elements of the relief efforts and guided decision-making through their

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influence on the other processes. Definitions framed and focused developing situational awareness activity, increasing emphasis on some topics over others. They affected the matching process by guiding matching activity and by being used and applied in the matching process. The influence of definitions and boundaries on decision-making functions similarly to goals in Gralla et al.’s (2016) work on decision-making, where participants often consulted the goals in while making their decisions. The findings from the current study expand on the work by demonstrating that a wide range of definitions (not just goals, which represent just one type of definition) influenced decision-making.

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Chapter 7

MATCHING AND ALIGNING

When an earthquake struck Nepal in 2015 and the Ebola epidemic unfolded in West Africa over the course of two years from 2014 to 2016, these crises created substantial health and medical needs among the affected population. At the same time, these events compromised the abilities of existing health and medical resources to meet those needs, further taxing already limited medical resources in these areas.

Relief efforts organized by the international community arose to help address those needs. As people in these organizations planned and implemented the relief efforts for these crises, they had to address not only the needs generated by the events themselves, but contend with a whole host of characteristics of the context in which they were working, including the social, political, and physical environment. Members of these organizations crafted their relief efforts through a process of matching and aligning. Linked with the processes of developing situational awareness, and defining and bounding, multiple individuals were involved in this process, and matching took place over time. Evidence indicated that how individuals approached or engaged in matching and aligning processes differed based on professional background.

Resources and Activities

As people in organizations engaged in the processes of developing situational awareness and defining and bounding, they identified and defined an array of constraints. These constraints ranged from needs and problems to policies and regulations. To plan and implement the relief efforts, relief workers matched resources and activities to these constraints. One area in which this was apparent involved deployment lengths. There were constraints on personnel resources, both in the

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limitations on what they could physically handle and in training for long deployments. These constraints shaped decision-making regarding deployed personnel: it meant deployments, especially early ones were shorter. It also led them to decide to encourage those people returning to take the training and redeploy. Several excerpts from the World Health Organization (WHO) documents show instances of matching at both the organizational and individual levels. Here, the scale of the activity is being increased in order to match the scale of the need:

Interagency coordination is being strengthened in order to review strategies and align them with increasing needs at all levels. The World Food Programme (WFP) continues to scale-up its Ebola response through the provision of food, common services and logistical assistance to support the treatment of Ebola patients and mitigate the risk of the virus moving into new areas. (World Health Organization 2014f:5) In this example, the scale of the response and specific response activities were implemented in accordance with the scale of the Ebola crisis and the needs it generated. Similarly, this except from one of the Nepal Earthquake Health Cluster situation reports shows how hospitals were paired with partner organizations by matching hospital needs with other organizational resources.

Four major district hospitals require long-term (3-6 month) support by foreign medical teams with full field hospitals (Bidur, Chautara, Dhunche and Ramechhap). Partners have been identified for all four facilities with provision of surgical and obstetric services, outpatients and inpatient care. All have begun building of their facilities, or are in advanced stages of planning. (World Health Organization 2015g:1) Again, resources, in this case, foreign medical teams (FMTs) capable of supporting field hospitals, were matched with facilities requiring that level of support, pairing one organization with another.

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Organizations and facilities were matched with individuals. In the following three excerpts, the needs of specific individual patients were matched with facilities with the capabilities to meet each patient’s needs. Relief workers categorized patients and facilities. They then matched patients to facilities based on these categories to make allocation decisions:

Injury Rehabilitation sub-cluster is working on a simple flow chart to help tertiary hospitals identify an appropriate facility for each patient based on his/her needs. (Health Cluster 2015b:14; World Health Organization 2015l:3)

The sub-cluster has been advancing on plans from its first meeting on 10 May to map partners and match capacity against the needs, and to establish step down transit shelter for the post rehab care. Already, it has identified a number of large step down facilities with rehabilitation and nursing services in the Kathmandu Valley, as well as several smaller locally led facilities. The main centres include: Cuban FMT at Kirtipur, Anandaban Hospital (Lalitpur) and Spinal Injury Rehabilitation Center (Bhaktapur). Green Pastures in Pokhara will accept complex rehabilitation patients from the West of the country, including spinal cord injury patients. (Health Cluster 2015a:14)

IOM assisted discharge and referrals of 45 patients from hospitals and temporary field hospitals to a step down care facility and/or their home. It is noteworthy that IOM was able to assist a temporary field hospital to find a placement for their patients, with only one day’s notice of their closure. (Health Cluster 2015a:14) All of these excerpts how individuals were matched to the health care facilities. Several interviewees discussed the matching of needs and constraints with resources and capabilities as well. Members of one team included in the study not only provided medical care, but brought and distributed relief supplies. First, they matched the supplies they brought to the needs of earthquake survivors as a broad category that they identified in the process of developing situational awareness. As one interviewee explained, “the type of disaster that you’re responding to will dictate the type and

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quantity of the medical equipment that you plan to bring in and the relief supplies that you plan to bring in.” She elaborated on that statement, saying that “Given the disaster we were responding to, i.e. earthquake, [we brought] lots of orthopedic supplies, casting material, surgical instruments….” Once they arrived in Nepal, they distributed the supplies at different locations by further matching the supplies they had with the specific needs at each location. In one health facility they worked at, there were no antibiotics remaining, but they had treated several patients with lower extremity injuries and were concerned about their for infections, so the team donated their remaining antibiotic supplies to this facility. They left the remainder of their anesthesia supplies at another facility because the team felt that there was both a need for those supplies in that location, and felt the recipients could use the supplies safely. These decisions were made in discussion with each other and with the intended recipient, though in some cases the group deferred to the most knowledgeable individual.

Many of the groups in this study matched their preparation activities and what they brought to the uncertainty inherent in the context. Reflecting on new or unfamiliar diseases in general, one participant said, “I just think the whole novel aspect of emerging infectious diseases always means you have to build uncertainty into your communication because we don’t know all the science on what’s going on.” In Nepal, some interviewees mentioned bringing tents because they were unsure about building safety and if they would be able to find other places acceptable to stay. They planned to be self-sustaining, bringing personal supplies including food and water, anticipating that they would be unable to acquire anything to fill those needs once they were in the field. In other words, because they did not know what

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they were going to face once they got there, they imagined the most extreme version of the situation they would face and designed the relief effort to match that potential situation. They incorporated flexibility in their plans and team composition, for instance, bringing people who could fill multiple roles and who were comfortable with transitioning in the field.

Structures

Sometimes, the matching process assigned some decision-making activity to actors within the organization most appropriate to handle those decisions. Other times, people adapted the organizational structure to match the demands of running the relief effort. The America Nepal Medical Foundation did this early on in their relief effort. While there were a couple of individuals who took the lead, the decisions were run by the entire America Nepal Medical Foundation (ANMF) board, a fairly large body. Interviewees from this organization explained that this was a very time-consuming approach because many of the board members would have questions or feedback, prolonging the back and forth discussion before making the decision. At this point in the first few hours and days after the initial earthquake, time was precious, and decisions needed to be made quickly. To address this decision-making need, they created a committee within the organization to handle the relief effort and speed up decision-making. This committee was much smaller than the full board and was tasked with doing much of the initial work to develop plans of approach. They would then present their plans to the board for approval. The purpose was not to evade the board’s decisional authority, but rather to speed up the process by focusing their attention on a particular phase. In other words, they matched the time-sensitive nature of the relief

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effort decisions with a smaller organization and decision-making procedure that would facilitate meeting those needs. Similar activity among other organizations appeared elsewhere in the data as well. Delaware Medical Relief Team did not necessarily create subcommittees, but it did task specific individuals (or a couple individuals) with particular response needs, allowing individuals to concentrate their time in one area while allowing the group as a whole to tackle decisions in multiple areas of response needs at once. This was reflected in the response as a whole. At various points in the response, particularly as the response activity began to transition into recovery work, sub clusters were created within the United Nations Health cluster to target specific issues. For example, in one of the Nepal health bulletins produced by the Health Cluster, they report that “In addition to the two previously organized health sub-clusters on Mental Health and Reproductive Health, Nepal a third sub-cluster on injury rehabilitation has been established” (Nepal Earthquake Health Cluster Bulletin May 4-10 2015 page 8).

Essentially, members of the Health Cluster identified a need for focused decision- making and attention on particular groups and issues, and altered structure of the overall UN Nepal response to match that need. Matching structure to response needs also occurred in the Ebola response. One

Centers for Disease Control and Prevention (CDC) interviewee involved in the very early days of the Ebola response discussed structure in Liberia. After assessing the response situation and discussing it with a colleague, they determined that the Ebola response needed to be restructured to resemble the way CDC runs an Emergency operations center. They wanted (and successfully pushed for) an incident command system with an incident manager, clear lines of authority, and meetings that were

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smaller in size and included only essential participants. This participant felt this was very important for the response. Here, they created a new structure for this response modeled off of a familiar existing structure from another organization. Other times, people relied on existing organizational structures, matching a decision based on its characteristics to the most appropriate person or individual to meet them. Continuing with the incident manager example, that same interviewee noted that the purpose of the incident management system changed as it grew, shifting its purpose towards broader information sharing. This resulted in the creation of another, smaller group to handle decision-making. A member of a team responding to Nepal similarly noted the shifting locus of decision-making depending on the context and needs of the decisions. She revealed “We had a designated, you know a de jure team leader, but I ended up being the de facto team leader because I had more experience than anybody on the team,” but added that “we did have a very nice, collegial group,” and that “decision-making was definitely shared on the Nepal trip…collegial type group decision-making process.” This same logic guided determining who was involved in CDC’s Ebola decision-making. As one interviewee explained, “I mean, it depended on the decision....” He added,

As far as process goes, there are there are things that are appropriate to discuss with 50 people and there's a time and place for that, and then there's things that are appropriate to discuss with 5 people. Um, you know, the five people who have the most influence, or have the most knowledge, or that are subject matter experts, or whatever, so a lot of the big decisions would be discussed and with very senior leaders from , you know, the White House, the National Security Council, Dr. Friedan, the Incident Manager Dr. Damon, and so, you know, a lot of the really big, complex, you know, decisions with political impact, and economic impact , and social impacts, you know a lot of those were

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hammered out with subject matter experts in smaller forms than the daily, than the daily update. An interviewee from one of the groups deploying to Nepal agreed with this sentiment, saying “there are times when you must have an in charge, dictating team captain, and there are times that allow for a more collaboration and putting all the heads together.” Different decisions were made by different units of the organization depending on the characteristics of the decision being made. While some of these decisions were pushed up the organizational hierarchy, others were pushed down. The Public Health Service was responsible for running the Monrovia Medical Unit. Deploying personnel received training on, among other things, documenting patient condition information in the hot zone, but each wave of Public Health Service (PHS) personnel modified these techniques in order to find better techniques (or at least approaches that worked better for them). Just as organizational structure was selected or created depending on the needs of the decision, structures were also selected or created based on the requirements of the objective or task the unit was undertaking. The clearest examples of this kind of match related to team size and mobility. Team Rubicon, for instance, kept its team size small when sending groups into the remote, mountainous regions of earthquake- affected Nepal, to facilitate their mobility in the field and the organization’s agility. Even when looking at the entire group they sent over as a whole, a relatively small team with a small “logistics footprint”, in their view, enabled them to respond more quickly than larger teams (under circumstances in which responding quickly was key in providing gap-filling services) and allowed them to be nimbler in the field to changing needs. Other organizations responding to the Nepal earthquake similarly created smaller units to work in the field. In the Ebola response, responders eventually

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implement the RITE strategy (Rapid Isolation and Treatment of Ebola). With this strategy, as they become aware of a case their rapidly deployable team would be able to help perform contact tracing. The program started in Nov 2014, and was considered by at least one interviewee to be successful and an important part of reducing the number of infections. This was apparent when taking a macro view of these two relief efforts. The Outbreak Bulletin produced by the WHO Regional Office for Africa on October 31,

2014 reported that,

In order to stop the transmission of EVD in the affected countries and prevent the spread within and outside the African Region, national authorities, with the support of WHO and other partners are taking necessary measures in line with the IHR (2005). These include: activation of the presidential, national, provincial and district emergency management committees to coordinate response; deployment of additional multi-disciplinary experts; provision of outbreak logistics support; capacity building of healthcare workers and community; and provision of financial support. (World Health Organization 2014b:para 9).

Similarly, in the Nepal health response, efforts were made to align the new earthquake-related health campaigns with existing health initiatives in the country:

Before the earthquake, Nepal authorities had already planned to conduct a polio campaign in 27 high risk districts. This polio campaign will be conducted in 22 of the 27 districts starting 6 June. The campaign in the other five districts, which are also earthquake affected districts (Kathmandu, Lalitpur, Bhaktapur, Makwanpur and Sinduli) will be combined with the measles and rubella campaign, on a date to be finalized. (Health Cluster 2015a:14)

In sum, whether looking at actions within organizations or the responses to these crises as a whole, actors in the relief efforts matched activities with structures capable of carrying them out.

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Procedures to Goals and Objectives People matched, procedures, to tasks, goals, and objectives. In many cases, these procedures were already established or familiar to the individuals prior to the event. For instance, one individual in the Office of the Assistant Secretary for Preparedness and Response (ASPR) focused on gathering and disseminating information about the epidemic utilized existing operational procedures to address the challenges of rising demands on his and his colleagues for information requests. He explained,

I got the different agencies, or departments in some cases, I would make them go through their operations center. That way their operations center could collect the information, or collect requests I should say, and a lot of times, they would be able to filter those requests. In this case, he was able to shift the sorting and organizing of requests to the operations centers and channel those requests through the existing procedures. Similarly, about four months in, they developed a frequently asked questions list.

While he did not say if ASPR has used that approach for previous responses, frequently asked questions lists are a widely recognized, used, and familiar approach to providing regularly requested information. The America Nepal Medical Foundation turned to an approach familiar to at least one of their members in their initial relief efforts: running an online fundraiser.

This member had previous experience running an online fundraiser for another organization and was familiar with what was required of these initiatives. Here, the approach to relief and the tools used matched the level of familiarity with them while simultaneously meeting the need (to start raising money quickly in order to meet needs, doing something they already knew how to do sped up that process). An

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interviewee from another organization who was responsible for moving people who were participating in the organization’s Nepal response, had a background working in the airline industry. Her experiences in that previous role, influenced the approaches she used in the organization’s response, transplanting procedures and approaches from one context to another based on their ability to fill needs. In the Ebola epidemic, one respondent from CDC described the activity for a response to any epidemic as “textbook”, identifying three key steps to the process. When relying on these standardized practices (however formal or informal they may be), they are engaging in the process of matching. Based on the information they have about the present scenario and the needs present, response participants match their existing repertoire of practices and strategies to the needs present. Even when faced with unfamiliar circumstances or tasks, people tried to relate those items to familiar strategies or processes, aligning what they did know to what they did not, or what they knew to do under one set of circumstances to the task at hand in other circumstance. Another CDC interviewee involved in communications aspects of the Ebola response offers a clear example of matching familiar processes to unfamiliar tasks. When she arrived in Liberia for her first deployment, the country was in its first 21 days without a case, and all the information she had been provided leading up to her response and when she first arrived indicated that their work and messaging were all going to be organized around recovery and the end of the epidemic. However, shortly after she arrived, a new case appeared. Though they did not know it at first, this was the first documented cases of sexual transmission of Ebola in the epidemic. She explained:

I remember sitting in one of my first meetings by myself and the IM turned to me and said ‘we have a communication expert from the CDC

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here, right?’ And so, I raised my hand, said ‘yes’. And he said, ‘you can write me up some talking points about what we need to say at this next press conference, right?’ I was like ‘Sure, I can do that.’ [laughter] And again, I don’t have any press background, so I’m like, I’ve never written talking points. She was both faced with a situation she had not anticipated facing and was presented with a task that, at first, she felt she was unfamiliar with. Her initial impressions appeared to be that her background and skills did not match sufficiently with what she was tasked to do. However, upon further reflection, she was able to find parallels between the task before her and the work she was more familiar with doing. She realized that while she was not necessarily familiar with writing talking points,

…I know the principles of crisis and emergency risk communication, and I know the science behind things, and so, so all I have to do is put that into a format of talking points, so even if I’ve never written up a press thing, and then you know, then help them to be able to deliver those messages. So, it’s things, like, you know, tell people what you know, this is what we know right now about the situation. We know this person—at that time, when we did the first press conference, we didn’t know it was sexually transmitted. We didn’t’ know how they got it because the person hadn’t been out of the country. They hadn’t been taking care of someone who was sick… so, that’s what I told them, I said ‘that’s what you tell them, you say, ‘the normal transmission means, you know we don’t know, because it seems like the normal transmission means are not here, but we don’t know. We’re exploring it further to see if there was a way that you know, if we’re wrong, or if there’s something else and here’s what we’re doing to try to find out more.’ And I said ok, and then now let’s apply the principles of Uncertainty Reduction Theory, ‘cause we know that , you know, people are going to be very anxious, especially when you don’t know what the transmission is, and they had thought that they were on the tail end of being successful and all of a sudden they were thrown back into this response where there’s been lots of lives lost, and lots of misery, and lots of illness, and so you want to make sure in order—so their anxiety is going to be high, which is part of uncertainty reduction theory, but then, how do you reduce that uncertainty? You do it by A) giving people information, or B) giving them a sense of control over things, so

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that whole concept of self-efficacy. So I made sure to build those things also into the talking points. So I said, you know, like, ‘so we can’t tell them a lot of information, but we can tell them, you know what you don’t know and what you’re doing to find out more,’ and then, but then also…I put in there specifically, ‘but the actions that we’ve been telling you to take to protect yourselves still apply in these cases, and so, all you have to do is just keep doing those things’...so we reinforced the you know washing your hands and um you know protecting yourself and staying away from people who are sick or you know taking protective you know gear if you have it to be able to do so, so um, you know, notifying people if there is a dead body, do not touch or wash dead bodies, those types of things, so we reinforced those messages as well. In other words, she was unfamiliar with the format of talking points, but she was able to match the content needed or these points with the content of the message she was more familiar with: crisis and emergency risk communication. She further matched the circumstances she was writing about (namely the uncertainty) with the appropriate theory to inform her message content, structure, along with the specific information to meet the components of the theory. Under conditions of procedural and situational uncertainty, she matched established procedures and knowledge from previous research and experience to the needs of the situation at hand.

Characteristics to Criteria Another form of matching that occurred in the relief efforts to both events was to match the characteristics of an individual, organization, or the event to characteristics outlined in some kind of decision-making criteria. For instance, Medical Teams International (MTI) has different categories of disasters marking different levels of severity. Each category is associated with response activities appropriate for that level of event. Thus, individuals at MTI used the early information they gathered about the event, matched that information to the corresponding category,

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and then used that match to guide how they would proceed in the response, in this case, to the Nepal Earthquake adapting these activities to the needs of the response as necessary. Other organizations similarly had a series of pre-defined criteria which they matched against information about the crisis that informed their decisions to engage and escalate the response and to deescalate and transition out of response activity. CDC has criteria for activation and deactivation, with activation occurring when the work associated with responding exceeds the ability of one center within CDC to handle it. De-escalation depends on the characteristics of the decision-making setting. However, deactivation was not just about characteristics of the epidemic itself. There were political characteristics for deactivating (though one CDC interviewee felt that the de-escalation criteria were not or were less clearly outlined in the Ebola response than they typically are for other responses). Criteria were matched to information about individuals. For instance, one PHS officer described quarantine criteria for returning personnel. This guidance from CDC considered the risk of the person based (at least in part) on their level of exposure to Ebola patients to determine if they would be quarantined or just monitored once they returned to the United States. Another interviewee from ASPR indicated one factor for prioritizing requests for information was based on the rank of the person making the request. There was discussion in both the documents and interviews about the use of criteria to sort patients. For instance, in one of the Health Cluster bulletins, it was revealed that a Casualty Triage Desk was set up at the Kathmandu airport,

MoHP has set up a Casualty Triage Desk at the Airport to triage critical patients brought by the air route, perform basic initial symptomatic management, and refer them to the public hospitals or the temporary hospitals operated by foreign medical teams (FMT) as appropriate.

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Sindhupalchowk is the district with the highest number of patients processed by the desk – 281 of the 443 casualties triaged and referred from the desk up to 26 May 2015. (Health Cluster 2015b:4). At this desk, personnel used triage criteria to match patients to a triage category, which they then matched to healthcare facilities. Not only would patient condition be matched to a category of patient which was in turn matched to facilities categorized as being able to provide the level of care corresponding with the patient need, but the matching that occurred in these patient triage systems also prioritized which patients received care first. For instance, one participant indicated MMU patients were prioritized based on when they presented at the facility. While the content of the criteria may have differed between organizations, the point here is that these criteria (definitions) were used by being matched with characteristics of an organization, individual, or the event to determine the course of action. This type of match highlights the way that matching and aligning is connected to the other processes: the criteria are effectively definitions and the conditions of the individual, organization, and event would all be gathered in the process of developing situational awareness.

Distribution of the Matching Process Multiple people participated in the matching processing that took place over the course of the relief efforts. Previous research examining medical decision-making noted that decision-making involves multiple people and over time (Charles et al. 1999; Rapley 2008; Goodwin 2014). In particular, Rapley (2008) discusses the concept of distributed decision-making over people and time. This distribution characterized much of the matching and aligning processes captured in this study as well. This was evident in the connection between the three processes. In some cases,

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some individuals’ sole focus was in one of the processes. For instance, the people concentrating on collecting information in developing situational awareness were not always directly involved in matching that information to decision-making criteria. Instead, they solely provided that information to the people primarily responsible for making decisions based on that information. However, by collecting the information, they still contributed to the matching process as they assessed, processed, and filtered the information they shared.

In other cases, there were some decisions appropriate for one body to make, while other decisions lay with another group. For instance, it was the receiving government who determined if groups could come to the country. One responder indicated the Liberian government (co-)determined the people who were admitted into the MMU by contributing to defining the category of person admitted. Similarly, the government of Guinea who had the ultimate decision-making authority in the public health response IOM along with many other organizations participated in.

In many cases, matching involved the direct involvement of multiple individuals. For example, Tom Friedan (the director of CDC) is the individual who activates the CDC’s emergency operations center, but that activation can be done upon an activation request. In the case of the Ebola activation, “It was a discussion.” The involvement of multiple individuals was further apparent in the way interviewees talked about disagreement. Interviewees did not identify a problematic degree of disagreement. When asked directly, people seemed hesitant to say that there was disagreement. While this could be due to negative perceptions of disagreement that these interviewees may hold, their responses appeared to be linked to how they conceptualized decision-making. In some cases, there was no disagreement because

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there was a clear authority, and/or clear information. When disagreement did occur, people in the organizations in this study resolved disagreement by relying on the mission, decision-making criteria, and recommendations from some kind of authority figure. The authority figure was defined by their role in the organization or response (or by their clear superiority in knowledge and technical skill related to the issue at hand). This occurred in the Ebola crisis where Médecins Sans Frontières (MSF) was widely considered to be the expert on supporting Ebola patients and providing Ebola care. Especially among U.S. government responders, the CDC was also considered the authority in the response, both in its position in the response, and its technical background in its area (some of which was at least assumed to be coming from MSF). One participant indicated that there was no disagreement because people looked to CDC for guidance. When there was a clear authority or trusted source, then that would reduce the extent of disagreement. However, disagreement did not seem to be a significant concern to the participants because the expression of different opinions and perspectives was seen as (and was as far as I was able to ascertain) a part of the decision-making process. In the Nepal response, participants from Team Rubicon and USC described elements of discussion in decisions once in the field. A USC participant described the decision making as collegial and incorporating discussion. This appeared to be true in at least some aspects of the Ebola response. One CDC participant described it as debate rather than disagreement. Another CDC interviewee described CDC as participative and collaborative in nature. When there was time, discussion would occur as a decision was being made in a transparent and open manner. Even if people disagreed, some respondents indicated, they knew the rationale for decisions. Because differences in

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decision making emerged during the decision-making process they did not have disagreements later. That CDC and its stakeholders are data driven, meant that data was a useful tool in building consensus. In general, interviewees did not view disagreement as problematic. This discussion of disagreement reveals another feature of the matching process, which is that it took place over time. These opportunities for debate and discussion, the degree to which it involved multiple individuals, sometimes sequentially, and the extent to which the information and definitions they used changed indicates that these matches take place not as a single moment, but over an extended period of time.

Role Allocation Role and task allocation is one area which demonstrates the different kind of matching activity that took place and the distribution of that matching and aligning activity. Status and role are key sociological concepts used in understanding behavior. According to Bosworth and Kreps, “Status is a socially recognized category of actors. As such it serves as a constraint on individual behavior. To some degree, therefore, social expectations shape the actions of and toward positionally labeled individuals. These expectations are referred to as roles” (1986:705). Drawing on Merton 1957, they explain the relationship between status and role, explaining, “A status is a social position with behavioral expectations, which are referred to as roles, attached to it.” (Kreps and Bosworth 1993:434). They define disaster roles as “what people are actually doing during a disaster such as search and rescue workers as opposed to a search and rescue leader” (Kreps and Bosworth 2007:308). In their work on organizing behavior, they focus on the concept of role enactment. Though the exact

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terms they used evolved over the years, they define role enactment as comprised of (1) the status/role nexus (also referred to as role allocation), (2) role relationships (or links), and (3) role behavior (Bosworth and Kreps 1986; Kreps and Bosworth 1993; Kreps and Bosworth 2007). Role allocation is measured by the degree to which a person’s disaster role is “consistent or inconsistent with predisaster occupations” (Kreps and Bosworth 2007:308). Role relationships reflect the extent to which the relationships between these disaster roles are continuous or discontinuous with the relationships associated with their predisaster roles. Role behavior reflects “Whether roles are performed in a conventional as opposed to an improvised manner” (Kreps and Bosworth 2007:309). These aspects of role enactment emerged in the data as individuals (and organizations) were matched to roles in the relief efforts. The data suggest that when matching individuals and groups to roles, the match makers strove for pairings that best facilitated more consistent role/status nexus, more continuous role relationships, and more conventional role behavior.

In the relief efforts to the Nepal earthquake and Ebola epidemic, this allocation occurred at the organizational and individual level. Multiple factors were considered when matching organizations or individuals to these roles and tasks, ranging from their regular roles and functions, and characteristics of the organization (resources and capabilities). Some role allocation was based on the person’s pre-existing role in the organization, appearing to occur relatively automatically, but a lot was volunteer (and thus self-identified) or requested rather than an assignment per se. Because the individual self-identifies their ability to fill the role or perform the task, it means multiple people participate in the role allocation decision.

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Organizational Level Organizations could be matched to particular functions or responsibilities within the (medical) response and relief effort. The selection of the Public Health Service as the arm of the U.S. Government that would provide direct clinical care to infected patients in the Monrovia Medical Unit is one clear example of task and role allocation at the organizational level. Once it had been determined that the United States government would dramatically increase its involvement in the Ebola response and relief effort though standing up and operating the Monrovia Medical Unit, they had to determine who would be responsible for providing the direct clinical care to patients in the facility. As one senior PHS interviewee described, there were two possible candidates for this role: the U.S. Public Health Service, and the National Disaster Medical System (NDMS). Both of these organizations bring in personnel to support disaster medical services, and both had personnel capable of providing that direct medical care. Here, the resources and capabilities of the organizations (skilled medical personnel) and the structure (ability to provide a surge capacity for medical care) matched the need in West Africa, specifically Liberia. However, according to this interviewee, legal frameworks shaped the decision as to which of the two entities was ultimately assigned the task. This participant explained that there are treaties which guide the deployment of government personnel internationally. One pertains to the deployment of State Department employees and personnel from the CDC. Another pertains to the armed forces on issues such as handing of military personnel who commit crimes in another country. To the knowledge of this individual, there was no treaty guiding the international deployment of non-State Department or non-CDC civilian government personnel. This was important in weighing the two groups going. NDMS is comprised of civilians. In this

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legal context, there was no pre-determined legal framework to guide their deployment. One would have needed to be hammered out. The Public Health Service, while not military, is a uniformed service, meaning that it could technically fall under the terms established in the Status of Forces Agreement. In short, in making the decision as to which group would provide medical care to patients in the MMU, decision-makers not only matched available and appropriate resources to the healthcare need, but matched the characteristics of the potential candidate organizations to the legal framework guiding government international relief.6

Individual Level Role and task allocation clearly occurred at the individual level as well, and the data showed numerous ways in which individuals were matched to particular roles and tasks. To some extent, role and task allocation at the individual level was connected to the organization. The selection of an organization for involvement could be the first step in role or task allocation at the individual level by presenting opportunities or requirements to become involved in the organization’s effort. An individual’s language skills, technical ability, availability, and previous experience could be matched to a role or task. One interviewee from the French Red Cross was involved in the very early part of the Ebola response effort, going to Guinea to perform a needs assessment there that would help guide subsequent Red Cross activity. She indicated that she was selected because of her medical background and because, being French, she spoke French, which was spoken in Guinea. Similarly, the interviewee who was involved in the International Office of Migration’s Ebola public

6 This interviewee did not make this decision, but they did have insight into how the decision was made.

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health response explained that her former boss reached out to her about joining the effort because of her previous experience doing similar kinds of work with him following the 2010 Haiti earthquake. In addition, she speaks some French, an asset since she too worked in Guinea. Some of the CDC personnel I interviewed who deployed to West Africa were already involved in the Ebola response in some capacity. However, they were approached about deploying for several reasons. One individual was sent to Germany as a communications liaison to the Department of Defense before being sent to West Africa. He explained,

The person who was running the EOC at the time knew of my background and actually sending me to Europe to be the liaison there, they sent me back to the exact office I had worked in years before. And so, they knew I had a history of working in—when I was there it was just European Command, after I left they split it up into the European Command and the Africa Command, but I still had contacts there, I still knew people in the local area, and they knew that about my background. That’s, that’s how I was chosen to be the initial liaison officer to DoD. Similarly, another CDC interviewee, deployed to West Africa twice, was selected for slightly different reasons. Her academic and professional background in crisis risk communication and her rank as a more senior person aligned with the needs for a communications person in the country who was high ranking enough to interact with senior local government officials. While she was initially supposed to go to Guinea, she was reassigned to Liberia, primarily because the need for her was greater there, though she added that she does not speak French, suggesting that that may have been a factor as well. The reasons behind her selection for a second deployment were different. In that case, she was a last-minute selection. The person who was supposed to go became unavailable at the last minute. They needed someone who was familiar

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with the response and the players in the field, and this interviewee’s previous deployment experience indicated she could meet those needs. Likewise, background and previous experience were important in individual role allocation in the Nepal response. For example, one interviewee speculated on the reasons for her selection to the USC team, believing that

I was probably specifically selected for the team because I had been deployed to um the Haiti disaster immediately after the quake, and um, so I was known to the dean as well as the trauma surgeon…for basically my expertise in anesthesia, and I have a background in trauma, many years of trauma care, and so I have a relationship with the trauma surgeons, I have worked with them for many years…. In this case, her disaster relief experience, familiarity with decision-makers and other actors in the response, and her technical experience facilitated her match.

Distribution and Volunteering These role and task allocation decisions involved multiple individuals, in that multiple people had to recognized the match between the selected individual and the role or task. Sometimes, these matches required permission from a third party, and often required the individual being matched to see and agree to the match as well. Many of the organizations in this study that provided health and medical relief to the Nepal earthquake relied predominantly if not exclusively on volunteers. Even if they were paid employees of the organization (such as doctors working for the hospital that sent a team), their roles/capacities within the team were typically voluntary. For example, one of the USC participants explained,

The chairman of the department of anesthesiology asked for volunteers, and I volunteered to go again, um, although I fully expected someone else to go in my stead, since I had already had a very rewarding experience, I was hoping [that] somebody else would get the chance to go and have that experience, but after two or three days went by and no

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one had, no one else had offered, it looked like it was going to be me, so I put a rush in on my passport, which was actually expired at the time. And so, it was basically just a, you know, the team knew me, and the team was looking for volunteers. Similarly, Samaritan’s Purse has paid personnel and the people it sends on its responses are paid, but many of those individuals still volunteered to participate in the mission first. In these cases, not only could the role or task be assigned only with the recipient’s approval, but since these individuals often had a primary commitment to their employer, they often had to get permission to go from a supervisor, an employer, or have a job that allowed for short notice schedule change. The distribution and voluntary nature of role and task allocation was even apparent within the governmental organizations that responded to the Ebola epidemic. While not all of the role and task allocation had a voluntary component, there were some aspects that were, namely the decision to deploy to West Africa. When PHS was looking for people to deploy, they sent out several mass emails to all PHS officers letting them know they were looking for volunteers. According to the individuals I spoke with, they were able to obtain sufficient numbers of personnel by seeking volunteers. One interviewee suggested that there was some nuance to this, however: if PHS truly needed people or someone, to go, they had the power to require that person to deploy, but as one participant put it, “It was voluntary 95% of the way.” Similar dynamics emerged within the CDC. Some of the individuals who deployed to West Africa did so after agreeing to the requests to do so. In one of those cases, the individual had to get approval for the deployment from her supervisor.

Disciplinary Differences Some interviewees revealed differences in how this decision-making occurred, claiming that these differences fell along disciplinary lines. One participant from CDC

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highlighted what appeared to be disciplinary differences in the amount of information required to make a decision. This person explained,

We’re a data driven agency, and there is a tendency to want to have more information than…there’s a tendency to want more information before you’re willing to make a decision than either you have time or information for. And so, there are people here at CDC that are professional emergency managers and there are people here at CDC that are professional scientists, and so in emergency response, it’s finding the balance and the blend of those two different communities that that come together to make an effective response.

While he did not discuss a specific example, his comment seemed to reflect a general observation about how people coming from different professional backgrounds approach decision-making in the response differently. Another interviewee from ASPR who was involved in information provision identified this issue in his experiences within his organization as well, narrowing down the ‘scientist’ category to medical personnel. Reflecting on his interactions with some of these colleagues with medical backgrounds, he explained:

You also have to remember that I’m not a doctor by trade, ok? And- and I’m about as non-medical as you can get. So I was trained that if I only had 50% of the information and I had to make a decision, I could make a decision. Some of the people, well--Most of the people are medical professionals, and … docs like to have 100% of the information before they make a decision, and that was sometimes challenging. You know, you ask for a decision and they flippin’ refused, because they didn’t have 100% of the information. It took some time to get across to them that there was no way you’re gonna get of the information. You know, and to be honest sometimes you would get so many requests for information, that you would have to ask people ‘here’s what I got, now, which ones of these are priority information requirements?’ That would help. That would help us out a great deal. You know, because if everything is a priority, then nothing is a priority. So it was, to get people to understand that.

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Here, it seems that the consequences of these differences in decision making extended beyond that particular decision. Waiting for more information could not only delay this decision, but could potentially affect other decisions as well. Further, the individuals who were responsible for gathering the information were heavily burdened with information requests from multiple sections and agencies, and from individuals at multiple levels of the organization. Pushing back with requests for more information when there was no more to be found could leave marks on the priorities the information gathering group had, and add to the workload of those individuals, either in attempts to find more information or in the conversations trying to convince others that they would be unable to further fill any of the information gaps. This indicates that not just background, but a person’s role in the organization or response influenced this dynamic as well. Other interviewees noted disciplinary differences, though instead of talking about this issue in terms of challenges or limitations experienced, they highlighted the value of or benefit to having interdisciplinary teams. In general, this point was raised or discussed by individuals with non-medical backgrounds or in non-medical roles much more frequently that it was raised by medical personnel performing medical functions in the response. When medical personnel did highlight the value of an interdisciplinary team, it seemed to be coming from those individuals with more response experience and who could note witnessing the benefits of having a diverse set of perspectives.

Chapter Summary Matching is the mechanism by which decisions were actually made. Though matching, medical relief workers connected parts of the response that needed to be

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addressed with the things best suited to address them. These matches produced diverse pairings of problems, resources, activities, definitions, etc. The discussion of role allocation builds on the work of Kreps and Bosworth (Bosworth and Kreps 1986; Kreps and Bosworth 1993; Kreps and Bosworth 2007). Essentially, when matching individuals to roles in the response, their aim was to create role match that made role allocation and the status/role nexus as consistent, role relationships/links as continuous, and role behavior as conventional as possible (Bosworth and Kreps 1986;

Kreps and Bosworth 1993; Kreps and Bosworth 2007). Multiple individuals participated in these matches, echoing the literature indicating that decision-making is distributed (Rapley 2008) or shared (Charles et al. 1999; Goodwin 2014). The data also offer evidence suggesting that how people approached or engaged in this matching process varied based on the person’s professional background, position, and experience, paralleling work by Hall (2005) noting disciplinary differences in interprofessional teamwork. The outcomes of these decisions became a part of the decision-making context, affecting future decision-making as relief workers captured these changes in the process of developing situational awareness.

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Chapter 8

DECISIONAL LEGACIES AND INERTIA

Connections Across Processes When the Nepal earthquake (2015) and Ebola epidemic in West Africa (2014- 2016) occurred, international organizations took part in the medical and public health relief efforts to those two events. To plan and implement those relief efforts, they engaged in three processes: developing situational awareness, defining and bounding, and matching and aligning. As demonstrated in the previous chapters, the three processes people in organizations went through to plan and implement their medical relief efforts were connected to each other in multiple ways. These processes were generally sequential, operating in a feedback loop. The data suggest that people and organizations began by developing situational awareness. They generally moved to defining and bounding next. They then moved on to matching and aligning, the outcomes of which became part of the decision-making context, and were subsequently fed back into the cycle with further development of situational awareness. The data offers some evidence that there was some feedback in the opposite direction as well. For instance, in the matching and aligning process, people and organizations could match the need for information gathering and decision- making around a particular subgroup of people or problems, and in matching that need, created and defined a subcommittee on that task. They once they completed the match, they reengaged in the other two processes. This indicates the match kicked back to the defining and bounding phase by triggering new definition, which could then inform further development of situational awareness and subsequent matches and alignment activity. The information about the decision-making context and other

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influencing factors was collected and processed through the process of developing situational awareness. This information helped inform definitions during the defining and bounding process and then informed the matching process. The definitions, in turn, focused information gathering and processing activity, targeting the development of situational awareness on particular topics. Definitions and boundaries created in that process both guided the matching process and themselves served as something that was matched. Beyond the evidence that these feedback loops exist, this dissertation was unable to reveal the exact nature of those feedback loops between the processes, and further investigation is necessary to more precisely tease out those relationships. Part of the reason for this difficulty is because these three processes occur simultaneously, feed into each other and are ongoing. These processes occurred simultaneously with each other and were ongoing throughout the relief efforts. The people in this study and the organizations included as a whole did not cease engaging with any one of these processes. They occurred over time, extending across and even beyond the temporal boundaries of the event itself. The development of situational awareness continued throughout the response and relief efforts. Even actively creating new (or changing) boundaries of definitions, they were working with the boundaries and definitions they created at some point in time.

Since matching is the mechanism through which they come to make the decisions, matching and aligning activity occurs throughout the response as well. In other words, these processes do not occur during a finite point in time, but instead continue throughout the response. Multiple individuals and organizations were involved in these processes. In many of the groups, individuals were assigned roles or tasks in the relief efforts that

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had them working primarily in one of these processes. Since decision-making behavior engages all three, it inherently involves multiple people. Similarly, multiple people were often involved in each of these processes (and often times people and the organizational units they were in would be engaged in all three process), further involving more people. The numbers of different people involved were a reflection of change over time Because of the turnover within some parts of the organization (particularly among those individuals deployed in the field), the duration of the responses increased the number of different individuals involved. As a result, the decisions each actor made left consequences for the other actors and decisions who followed later in the relief efforts. This was apparent when people matched tasks to be done with standardized procedures or the existing mission of the organization. Matching was the process by which the legacies of previous decisions were carried forward and connected with the subsequent relief activity. The following discussion of how the

Centers for Disease Control and Prevention (CDC) became involved in the Ebola response illustrates how decisions were distributed over both time and multiple actors. Talking about the different actors involved in the decision to become engaged in Ebola relief, he explained that

It was a conversation between that center, the director, and then my center which is the Office of Public Health Preparedness and Response (OPHPR). And so typically it’s a conversation…. When we activate, it’s when we believe or when we’re told that that the local capacity to handle the event or respond to the event has become overwhelmed. And so in this particular case, it started in the country of Guinea, and in conversations with the World Health Organization and others, it became apparent over time starting in March of 2014, it became apparent over those few months after that this was not a normal Ebola outbreak. There was something different about this, and then the fact that it made its way into a very densely populated urban area led us to

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believe that this was something that local authorities would not be able to handle on their own, that we were going to be asked to help respond and that’s when we activated our EOC. Here, there were not only multiple people from several groups within CDC in conversation with one another, but they were also in communication with people from other organizations important for the Ebola response, including the World Health Organization (WHO) and the government of Guinea. His comment that “it became apparent over those few months” demonstrates that these discussions were built over time. What is clear here is that the decision was neither made by one decision-maker, nor was it made in a single moment. Multiple parties were engaged in developing situational awareness over time, used that information to define and redefine the situation and match the appropriate actions to those definitions. Looking at decision-making within organizations as well, the legacies of previous decisions made by other decision-makers were evident. Reflecting on one of his roles in the CDC Ebola response, one interviewee revealed that during this activity,

“I had to assume that if we were doing a certain process a certain way, that somebody before me had a really good reason for doing it that way…it really made me very deliberate about changes that I made to the division’s structure and operating procedures.” Due to the time demands of the event circumstances, he had limited time available to study why a process was executed a certain way. When he was considering a change, he explained that, “I relied on the division’s senior leadership…to let me know, if we were getting ready to change something”, seeking their opinion before making a change. This deference to others with more experience and careful consideration of existing procedure is one reflection of the ways in which decisions were spread out over people and time.

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As this discussion shows, multiple people were involved because different people were involved at different time points in the response. Not every individual involved was involved at the same time. This was particularly salient when considering personnel who deployed to the crisis-affected areas. Most of the personnel in this study who went to Nepal and all who went to West Africa were not present in the field for the entire duration of their organization’s response. They were most frequently members of waves of personnel, taking tasks and responsibilities on from some personnel and transferring them to others at the end of their terms. As a result, these processes (and by extension, decision-making) were distributed over time and over people as well. Consequently, decisions were not made by individual decision- makers acting alone, and the decision-making in general did not take place in finite, clearly-defined moments.

Legacies

These actors are connected across time and space through decisional legacies. Decisional legacies are the outcomes of decisions. Each decision left a legacy that affected subsequent decision-making. These legacies were felt in additional decision- making in the same area of work, but were sometimes connected to decision-making in other areas. These outcomes informed subsequent activity in a number of ways.

One of the most clearly noticeable ways these legacies were carried forward was through their effects on the decision-making context and on the characteristics of the organizations themselves. Information about the context and organization was captured and processed by developing situational awareness. Since this information informed the defining and the matching processes (and ultimately the decisions that come out of these three processes), changes in the context of the decision-making

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setting or operational context were picked up while developing situational awareness and consequently shaped subsequent decisions. For instance, the interview with an individual focused on information gathering in the Office of the Assistant Secretary for Preparedness and Response (ASPR) revealed that once U.S. government personnel were deployed to West Africa to support the epidemic response, the number of U.S. (government) personnel who were deployed both became part of the operational context and became important information that was collected and incorporated into situational awareness which collectively informed further decisions. Another way these legacies continued was through the use of definitions once they were created (or once they were adapted or breached). These definitions and boundaries framed the discussions, matching activity, and partnerships of these organizations, and framed what organizations did or did not do. Consequently, these definitions could and did shape decision-making throughout the response. One example is the triage and facility allocation criteria documented in the situation reports created to sort earthquake survivors in the days and weeks following the event. Another example are the definitions of suspected versus confirmed Ebola cases that were important categories used throughout the response to understand the status of the epidemic and inform activity. Similarly, the relief goals and objectives laid out early in the relief efforts (and the extent to which they were adjusted) focused and guided relief activity throughout the relief efforts. In all of these examples, the definitions created for some purpose were used throughout the response, affecting decision- making beyond the times of their creation. The experience of one of the Team Rubicon teams highlights not just the interconnectedness of the processes, but how the decisions that emerged from previous

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iterations of these processes (and sometimes involving different actors) left legacies that influenced processes that followed and affected the decisions that came out of that engagement. One Team Rubicon interviewee described an incident that occurred while one of their mobile teams was working in a remote community in Sindhupalchowk. By this point, Team Rubicon had already partnered with the Gurkhas, and Gurkhas were present among the Team Rubicon personnel who were operating in this area. The interviewee explained:

In the middle of the night, there was a domestic violence incident where a lady got lit on fire. So, the circumstances are unclear to me, but essentially this lady ended up with significant second degree burns from having hot, burning kerosene poured on her. And so, we, as medical providers, had the prerogative to provide immediate lifesaving care and to make a determination as to what the right action to take would be for ensuring that this person survived and, and could have a good life despite these injuries and hopefully have the best chance of recovery. So, our paramedics and doctors do provide initial treatment and care and they make the determination that she needs to be evacuated. The only option for evacuation at that time was to call the army. And so, we called the nearby army base on sat[ellite] phone and said ok, we need a helicopter pick up to take this person to a hospital.

Well, because it involved a domestic abuse incident, the national police were sent up the next morning to arrest the person involved—to arrest the husband. And that put us in a very tricky situation, because the village, being very far away from central government, was very intent on dealing with its own problems internally, and they had already set up their own little uh, council to deal with it, the entire village got together to deal with this problem. The injection of the police caused a conflict and a lot of the villagers then accused us of calling the police, who were then interfering with village justice. And so with-- the village ire was up, the police were arguing about how to get things done. The army was sending people in, it just turned into a mess, and if we had not had good relations with the village otherwise and the Gurkha translators with us, that may have turned out very differently. I don’t expect, like, physical harm or anything, but certainly we may have not been welcome if there weren’t people able to represent us. And there was a very distinct, um show in the difference between like ‘OK, we’re

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a very peaceful culture, we all get along,’ and, and they have this outward image of-of they want the care…like, but when it comes down to where emergent care and public health kind of intersect, those local, cultural norms just take over very distinctly and we had to work through them. Ultimately, the situation was resolved:

[T]he guy was, was run out of the village for a period of time to be allowed in later and the police took him and eventually were allowed to helicopter this poor lady out. But, all in the midst of this we are trying to provide our care and trying to manage the situation and not get thrown out because we have an active patient that’s in need of very distinct care. Several processes were at play here. They were continually developing situational awareness, first in identifying and assessing the medical need of the woman, then in identifying available resources (namely transportation resources with the military helicopters and social resources in their Gurkha colleagues), and in assessing the deteriorating situation after the arrival of the police. They defined the medical problem of the woman as serious, as something under their purview to address, and as needs beyond what they would be able to sufficiently meet on their own. They in turn defined a transportation problem of being able to get this woman to the facilities most appropriate to meet her needs. They matched the transportation problem to the only available resource: the military and their helicopter capabilities. They also matched their Gurkha colleagues to the needs for not just literal translation, but to navigating a

(tense) social and cultural environment and to serve as their cultural representatives. The legacies of the decisions made during this experience and even before this particular situation arose are apparent in each of the processes. The presence of the Gurkhas among their group, for instance, is a legacy from previous decisions to partner with them. Earlier in the response, the Gurkhas were identified as a resource during the process of developing situational awareness, just as the need for translators

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and cultural ambassadors were identified as a need. They were matched, and the team boundaries expanded to include Gurkhas. Their presence then affected all subsequent processes and the decisions that emerged out of them, including the ones highlighted in this situation. When the group members decided to reach out to the military for transport, one legacy of the decision was the connection between Team Rubicon and the action that ultimately triggered the involvement of police and the immediate reaction to their arrival, which was a tense environment that affected their ability to continue providing care in that community. However, their early efforts to develop a positive relationship with the community they were working in was another legacy. The positive relationship they had fostered before this incident was a resource in the operational context that helped them to successfully navigate the tense situation that precipitated with the arrival of the police. The consequence of these decisional legacies was that each decision was made in a context that was created or shaped by the decisions that came before it. Each new decision, in turn, left a decisional legacy behind which influenced subsequent decisions made after it in intentional and unintentional ways. This legacy could be a focus in a particular area, in changes in resource availability based on allocation decisions, or other changes on the operational context that result from the decisions

(matches) that were made. These decisional legacies were the connections between these different decisions over time.

Decisional Inertia

Collectively, the connections between processes and the decisional legacies they left behind created a condition I refer to as decisional inertia within the relief efforts. In physics, Newton’s law of inertia is the tendency for an object in motion to

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stay in motion or an object at rest to stay at rest unless acted upon by an outside force (see Seaborn 1998 for an overview of the law of inertia). Inertia is generally viewed as a reflection of an object’s mass. The greater the mass of the object, generally the more inertia it has, meaning the harder it is (the greater outside force required) to cease or start the motion. When looking at the context of international crisis medical relief and the social process of decision-making in humanitarian relief, this ‘mass’ has two components.

First, the mass of the relief effort is measured in part by the actual size or number of tangible and intangible resources that are associated with it. This includes commitments of the three types of resources that Fritz and Mathewson (1957) note converge in association with extreme events. The mass includes the commitment of personnel, something can be reflected in the numbers of personnel directed towards the effort and reflected in the overall organizational structure. Likewise, the ‘mass’ includes the commitment of materiel resources to the relief effort, with an increase in the material goods increasing the mass. Likewise, increases in information resources constitute an increase in relief effort mass, even though information itself is not tangible. There is another aspect of this mass important in directing the relief efforts: the content. What kind of resources were being committed and the amount of those resources are important. In the decision-making context of the relief effort, it was not solely about the amount of these tangible and intangible resources that matters. The mass would also reflect the (content) area in which those resources are focused. In other words, the specializations of the resources being committed (or the purposeful

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commitment of broad, flexible resources) points the organizations and their relief efforts in a direction, further committing to a particular kind of relief effort. The second component of this mass is the number of decisions themselves which guide the relief effort, demonstrating increased engagement with the situation. The more resources and decisions there were, the more difficult it was for the organization to change whatever it is doing, the more force is required to change the motion or bring it out of rest.

Forces Similar to physics, in which object in motion will stay in motion and an object at rest will stay at rest unless acted upon by an outside force, the decisional inertia produced a similar effect in the relief efforts. Relief efforts continued in a consistent line of (in)action unless something occurred to upset that activity. This force took a couple of different forms in the data. The forces that could act upon the relief effort as object came from both outside and inside the relief effort/organization and could help shift the direction of the relief effort.

Change in the Event (Hazard) The clearest examples of outside forces that pushed against these relief efforts were the instances in which there were changes in the event itself. In the Ebola epidemic, these changes sometimes took the form of new infection locations. On a smaller scale, these included outbreaks in new areas in a country where the disease was already present. Events such as these could shift or widen the geographic focus of response activity and resources. On a larger scale, these included new cases in other countries, especially if they were the results of transmission within the new country as

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opposed to a person who was already infected crossing the border. Similarly, the infection of American healthcare workers in Liberia shifted American attention to West Africa (Isaacs 2014b). The following excerpts taken from WHO-produced documents on the Ebola epidemic show how the discovery of more cases in new locations resulted in a shift in attention:

“Sierra Leone has enhanced its surveillance and prevention activities for viral hemorrhagic fevers following the death of 2 probable cases of EVD in one family who died in Guinea and their bodies repatriated to Sierra Leone. Mali had previously reported a cumulative total of 8 suspected cases, all of whom have tested negative for EVD.” (World Health Organization 2014c:para 3)

“In Nigeria, IHR focal person report confirms that the probable case notified was symptomatic at the time of arrival in Nigeria and that 59 contacts (15 from among the airport staff and 44 from the hospital) have been identified so far. The report also confirms that the patient travelled by air and arrived in Lagos, Nigeria, on 20th July via Lomé, Togo and Accra, Ghana.” (World Health Organization 2014a:para 4) In both examples, new cases prompted changes in activity in the respective locations.

Similarly, the declaration of a country as Ebola free, and especially the discovery of new cases after a country that had been declared Ebola free functioned as an ‘outside force’ that could completely shift the focus of attention and even way of thinking about the epidemic and their activity in relation to it. One CDC interviewee described how the discovery of a new case in Liberia shifted the direction of the relief activity going on in Liberia. When she arrived in the country, it was in its first 21 days without a case of Ebola. As a result, all of the information she received in preparation for her deployment and meetings she attended were focused on the recovery phase,

“so really talking about memorializing things, talking about recovery, you know, or longer term, like how do we protect ourselves long term…how we were going to transition some of the communications stuff either back to the ministries or other organizations that were going

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to be there long term, that sort of thing. But then a week into my being there, a case came and it turned out to be the first sexually transmitted case ever of Ebola that was documented. So that kind of turned us way back into the response mode again.” In this case, the discovery of a new Ebola case completely transitioned them into the response phase of the disaster cycle. She explained that this was “…something that was totally unexpected and it wasn’t because somebody didn’t tell me, it’s that the situation completely changed at the time I got there,” adding,

“we talk about phases of a disaster, and although if you look in the literature, it talks about how—they do make a note that you know you can go back to earlier phases of a disaster depending on what’s going on, I think there’s still a tendency to see it as a linear type of a process. So, I think that getting people to understand who are working a response that that you can go from being, like, in a sustained or towards the recovery phase, because there are so many unknowns, you can go back to a response phase…at any moment and you need to have a plan and be prepared for how you’re going to transition quickly into that or to communicate about that and all the other stuff” She did not consider this characteristic to be unique to epidemics, adding:

“It could still happen with a disaster I think too. you think about Hurricane Katrina, where everybody is expecting it to be a hurricane situation but it then turned out to be a flooding disaster, or, or like Japan earthquake, which you think of as earthquake, but then it became much more about flooding and then about the nuclear disaster event than it ever was about the earthquake. So, I think that these complex disasters is also the other thing that I think is—we’re learning more about and we need to be prepared for those types of things that happen.” This example raises another kind of outside force: a change in the virus, or at least a discovery of previously unknown information about the virus. The interviewee explained this new case in Liberia was believed to be the first documented case of

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sexual transmission of Ebola from a survivor to another person.7 The effect on the direction of the response was three-fold. First, as mentioned, this case required a shift back into response activity. However, it also triggered not just contact tracing, but a new line of scientific inquiry to discover how this person had gotten infected when none of the other means of transmission which response and health communities were familiar with were present. This required a shift in their messaging, and ultimately their safety/precaution recommendations that shared with the public. A semen testing program was initiated after this discovery, aligning both with the need for additional research on this issue and with a community service need to identify if Ebola was still present in men’s semen. In the Nepal earthquake case, changes in the event took the form of aftershocks in the days, weeks, and months after the April 25 earthquake, in particular the May 12 aftershock which was measured at a 7.3 magnitude (compared to the initial earthquake which was documented at 7.8 magnitude). Similar to the new outbreaks of Ebola, these aftershocks refocused or widened the geographic areas of attention and response resources to different areas within the earthquake affected regions of Nepal. Further, they had the ability to kick the relief efforts back into immediate response type

7 A report published in the Morbidity and Mortality Weekly Report on May 8, 2015 notes that previous evidence indicated that the Ebola virus can remain in semen for several weeks after infection. It also noted a possible (though inconclusive) infection via sexual transmission by sexual intercourse from a previous outbreak and possible sexual transmission of a similar disease, Marburg (Christie et al. 2015). Thus, previous research suggested the possibility of sexual transmission, but was not confirmed at the time of the 2014-2016 Ebola epidemic. Talking about the 2014-2016 event, the authors note that “It is not possible to definitively ascribe Ebola infection in patient A to transmission from survivor A, and another sexual partner or other source cannot be excluded”, but note that the evidence “suggest possible sexual transmission” (Christie et al. 2015:480).

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activity, especially the provision of first aid care and urban search and rescue activity. This event additionally shows how a change in the event itself could interact with other forces, in this case, the presence or absence of other organizations.

Change from other organizational actors Another external force was the change (or changes in direction) from individuals and other organizational actors. Organizational actors included domestic organizations (governmental and nongovernmental) and international ones converging on the area. It was in this way that those local organizations could interact with and ultimately shape the medical relief efforts of the groups converging in the country. Returning to the example of the discovery of new cases in Nigeria, the efforts to test samples from the affected cases shows how the actions of one organization could affect another’s activity. Once the sample had been taken, it appears from the documents that they had difficulty getting this sample tested. The document reads:

The sample from this case is yet to be sent to the WHO Collaborating Centre at the Institute Pasteur in Dakar, Senegal, due to refusal by courier companies to transport this sample. Though only one probable case has been detected so far in Nigeria, Ebola virus infection in this country represents a significant development in the course of this outbreak. (World Health Organization 2014a:para 5) The inability to get anyone to deliver the sample to testing facilities obstructed and delayed the testing of the sample. Likewise, organizations converging on Nepal to provide medical relief were affected by opening or closing opportunities to partner with local organizations. Organizations looking to partner with Kathmandu hospitals, for instance, could only do so if the hospital agreed. Multiple groups included in the study, including Samaritan’s Purse, the Delaware Medical Relief Team, the America Nepal Medical Foundation, and the team from University of Southern California,

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Keck School of Medicine all reached out to local health providers (often hospitals), however their successes in doing so varied. The frequent claim from hospital directors and the Ministry of Health in Nepal that they did not need the assistance of foreign medical teams that were documented in the health cluster situation reports suggests that those facilities’ doors were closed to converging organizations, and that some organizations that may have been interested in working with Kathmandu hospitals may have been prevented from doing so.

As more time went on since the beginning of the event, more and more groups became involved, staking claims to particular tasks and regions to work in. The number of converging organizations increased over time (recall, for instance, how the number of foreign medical teams in Nepal continued to increase in the early days and weeks of the earthquake response). At the same time, local organizations became firmer in their decisions as to if and with whom they would partner. As these international and local groups solidified their plans for response activity, they limited the types of activity other groups could engage in. One interviewee from a hospital- affiliated organization that responded to the Nepal earthquake explained how the activities of other organizations and existing resources in the affected area could influence the decision-making of converging groups.

Specifically where the need was, where the need for resources were because …obviously when you’re responding to a disaster situation and if you’re going to a place that there are multiple other resources flooding into the country from around the world, and already um—in a place like Nepal which already had a lot of outside interests because of the, you know, natural beauty and geographic desirability of the location and the cultural history, this is a place that already had a lot of world interest, and so there were a lot of very well established nongovernmental organizations already in situ. So, you know, you can imagine there are lots of resources—more resources say than for example a place like Haiti. Lots of resources already in place, and lots

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of other resources flooding into the country, you, you don’t want to add to the congestion and not be as effective as you could be if your location that you’ve selected, or has been selected for you to respond to is already saturated with other you know resources or volunteers. In a separate interview, her relief effort colleague added,

I think that people or organizations that want to be part of international medical relief basically need to have a team that is organized and ready to go within 12 hours of incident. To provide the most kind of impact of medical care, it’s that 24-48 hour window. After that, I think that you certainly can find your place, but it’s much harder.

As groups already in the affected area became increasingly committed to a particular course of action in a particular area, they influenced the activity of other, less established organizations by limiting the participation options available to them. Another example of an outside force is the sudden availability of new resources. This happened to the America Nepal Medical foundation. In the immediate aftermath of the earthquake, they set up an online fundraiser in the hopes of raising a few thousand dollars to support the overall response. According to the people I spoke with, they ended up receiving well over one million dollars. This radically changed the course of their action. This massive increase in monetary resources at their disposal shifted their direction in two important ways. First, it allowed them to support more projects (in terms of the raw number of different projects) and more expensive projects than they had initially planned. Second, and related to the point about more expensive projects, the increased resources allowed them to take on projects with longer timelines, ultimately involving them in recovery work. For instance, they were able to take on supporting the rebuild of multiple government health posts. I identify this increase in funds as an ‘outside’ force because the money was coming from outside donors rather than a reallocation of existing funds already existing within the organization, but in some respects, the changing resource base within the organization

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highlights the potential for forces to work inside the organizations and within the relief efforts to shift activity.

Internal Forces Clearly there were factors outside of the organization(s) that shaped their relief efforts, acting as an outside force to stop or change the motion of the relief effort. However, relief efforts and the organizations behind them are not solid, uniform, lifeless masses. Within each organization, there were individuals, and sometimes layers or subunits of those organizations. This study indicates that these actors within the organization too could and did act as a ‘force’ against the motion or rest of the organization’s relief effort. Similarly, there were characteristics about these organizations and the individuals that could facilitate these changes or resist them, allowing them to keep going on a particular track and not get halted by spreading themselves too thin, or to keep going in terms of overall involvement in the response

Time Early in time (both in the organizational life history of a group and in terms of the event) was when there was the greatest number of possibilities available for pursuing particular goals or objectives and the number of different ways to pursue them. In this case, early in time there were a greater number of and variety of ways to participate in humanitarian relief. Even when only looking specifically at medical relief, there were several possibilities available. Focus on one kind of health or medical service versus more general services, long versus short term possibilities, partnership opportunities with other international and local organizations, the potential to focus on a particular sub group (i.e. women, children, people in a particular

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category), or in a geographic location: these are just a few of the potential areas of variability available. However, as time went on, the avenues available to participate in the relief effort decreased, and individuals and groups became increasingly committed to a particular course of action. This occurred both within and between groups. Within an organization, the commitment of increasing amounts of resources to a particular form of participation in an international relief effort narrows the field of possibilities and made deviation from the chosen means of participation increasingly unlikely. The influence of other organizations appeared through the effects they had on the decision- making context, which in turn affected what any individual organization did. All of the organizations operating in the relief context were going through these processes over time and at similar times, meaning they too were becoming increasingly committed to particular courses of action. In so doing, they pushed other organizations to become increasingly committed to their respective choices. This is because by committing to a certain approach, they were effectively taking those options off the table, making them options that other organizations either could not pursue or had to be more careful about pursuing. For example, the Delaware Medical Relief Team (DMRT) had determined that it was going to go to Nepal to help with the response. They transitioned what they focused on over time, but as time went on, if the group was going became more and more certain. The main uncertainty lie in which members were going (for instance, individuals who could only serve in a surgical capacity were only going if they could connect with a hospital to provide surgery). Member availability served as the main

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determinant of participation in that they only created an additional wave if they had enough people to populate it.

The concept of decisional momentum is mapped out in Figure 2. In the figure, the x- axis represents time. The beginning of the x-axis represents ‘the beginning’, of the relief effort, the event itself, or the beginning of the organization’s life history. The

Figure 2 Conceptual Diagram of Decisional Inertia

y-axis represents the number of different possibilities available. Early on in time, there are several options of participating available. As time goes on, an organization commits more resources and makes more decisions that hone in on fewer and fewer options. At the same time, other organizations are going through the same process. Collectively, this process narrows the options available to participating organizations, directing them to particular approaches to relief (reflected in the figure by the downward slope of the curve). This graph represents a conceptual depiction of this

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theory. There are no units on the x or y axes, and they do not necessarily exactly reflect the timeline of a particular organization’s relief experience. Goals are definitions that can give direction to the relief effort. In thinking of direction of movement of relief efforts, it is not that the organization will keep doing what it is doing in perpetuity. Rather, this decisional inertia means that the group will continue to do what it set out to do. If the group determined that it would provide aid for one week regardless of need level and did so, then there was no change in the inertia. A group deciding that it would provide aid until their relief services were no longer needed is also not a change in inertia if that is what the group actually did. If the group changed the type of care or relief it was providing or the activity it was engaging in because of a change in the need, or changed how long it planned to be in the field, then that is a change in direction.

Important Time Points

This theory of decisional inertia allows for identification of important time points in the response. Based on this theory, the times at which a relief effort is most likely to change or is at least most susceptible to change is immediately following one of the forces. The data suggests that these changes are more likely to be larger in scale earlier in the response when fewer resources have been committed. In addition, when looking at the organizations separately from the relief efforts they organize, the data and theory from this study suggest that organizational change is more likely early in an organization’s existence. What this further suggests is a relationship between organizations and relief effort age and the ability of individual actors to directly influence their development.

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This point was illustrated by one of the Team Rubicon interviewees, and was implicitly raised in the interview itself. At the time of the Nepal earthquake, Team Rubicon as an organization was only about five years old. As a result, it was still in the process of formalizing and developing standardized procedures for its responses. This one participant had previous experience working in the airline industry, and therefore had a lot of useful background information about moving people (and things) by plane. She ended up leading that component of the response. She told me during the interview that at the time we spoke she was in the process of documenting those procedures. Specifically, she said

So in some ways, like, a lot of the decision-making that happens as I move people, Nepal was really the first time in some ways that the personnel movement happened in the way that it did. We had always moved as a team, but because of my background…there were certain things that I did differently, and so now those became part of the process, and they’re not right or wrong, or better or worse, they’re just different, and it’s allowed us to sort of make that part of the process…you don’t have to reinvent the wheel every time…it doesn’t have to look different every time. Here’s a process and some certain things that you can follow that will help you be consistent. Her statements suggest that the approaches and methods she used may not necessarily be the right way (suggesting that there may not be a single correct way to do that kind of work), but the approaches she took were what she did and was familiar with. Because she was the one establishing these procedures, that was what was becoming the standardized approach. What this indicates is that her ability to dramatically influence how the organization operates was due in part because of when she was becoming involved: at a time before established procedures were in place for the task she was performing and around the time there was an effort to document them. This created a greater space for her specific background and expertise, and ultimately her

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approach to come through in the response. While this organization as a whole is not particularly rigid, that these approaches are being documented and made the standard suggests that subsequent individuals who will occupy this person’s status and fill this role will have a somewhat smaller ability to personally shape the approach (and indicates that this interviewee’s decision-making will be carried through to other responses). Other, older organizations in the study, by contrast, appeared in the data to offer fewer opportunities for individuals to have a large-scale impact in how those organizations approached relief.

Things Affecting Inertia, Opening Possibilities, and Facilitating Change Just as these forces can push groups to adjust to changing characteristics of the decision-making setting, characteristics of the organizations themselves and the people who comprise them shaped how these groups and the relief efforts they created adjusted to these forces and changed circumstances. In particular, flexibility was an underlying characteristic important in shaping reactions to changing environments. The importance of flexibility was evident both implicitly in the data and in the explicit claims from some interviewees. This flexibility could be linked to how they defined the problem early on, their willingness to change the definition of problems and needs over the course of the response, and in the composition of their teams (such as including people who could fill multiple roles and/or having diverse teams). Some groups had developed situational awareness and defined need as medical and relevant to them and started mobilizing the resources to go there, but then in the time it took them to mobilize, the needs started changing to conditions different than the medical needs they were originally planning to fill. Some groups that had already committed enough resources that deciding to not deploy seemed to no longer be an

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option. Those groups changed the objectives of their relief effort to reflect changing circumstancing, redefining the problem and what the organization plans to do. This happened, for instance, within DMRT. As time went on, they found difficulty in partnering with local hospitals and they came to realize that the needs were less directly connected to the earthquake and more to the large underlying health need that may have been exasperated by the disaster. The organization as a whole may not have changed, but individual members opted out (or in) depending on their new found

(ir)relevance.

Chapter Summary Decisional inertia was the consequence of the combination of developing situational awareness, defining and bounding, and matching and aligning processes. As relief workers engaged in those three processes, they made decisions about the relief effort that became a part of the decision-making context, leaving legacies that influenced subsequent decision-making. As time went on and groups accumulated more ‘mass’ and made more decisions, activity became increasingly focused in a particular direction as fewer and fewer options for participating in the relief effort remained available. However, this direction could change when ‘forces’ acted upon the relief efforts, including changes in the event and other organizational actors, presenting new or previously unavailable options for involvement. Other scholars have used the concept of inertia in explaining organizations. In particular, Hannan and Freeman (1984) present structural inertia as a theory of understanding structural change, a theory which Kelly and Amburgey (1991) among others have refined and built upon through additional studies. Though Kelly and Amburgey (1991) find mixed support for components of the theory, the theory

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indicates that older organizations (among other characteristics) are more likely to experience structural change. The theory itself is meant to explain selection of organizations from an ecological perspective (Hannan and Freeman (1984), but Kelly and Amburgey complement the theory by adding the concept of momentum, writing

These organizations were significantly more likely to repeat changes that they had experienced in the past. We suggest that the concept of momentum is complementary to inertia theory and that a useful way to think about inertia is that it is high when organizations continue to extrapolate past trends in the face of environmental change (1991:608- 609). This concept clearly links structural change in the present with structural changes that occurred in the past, in a similar way that decisional inertia links present and past decision-making. In addition, that the structural change occurs under circumstances of environmental change is similar in concept to the circumstances under which decisional inertia emerged in this study. However, there are some important differences in the theory. The clearest of these is the focus of what each is trying to explain: structural inertia explains change in structure whereas decisional inertia explains decision-making (of which changes to organizational structure reflect just one type of decision). While the authors do no expressly say that the theory is relevant only to corporations, that is the implicitly focus of their work, in contrast to the governmental and non-governmental organizations examined in this study. Decisional inertia contributes to this theory by revealing the mechanisms behind that inertia. Further, the initial analysis suggests that the concept of decisional inertia is relevant at the level of individual decision-making in addition to decision-making at the organizational level. Because decisional inertia inherently reflects connections across time, it offers support for other scholars claims

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that decision making is spread out across actors and time (Charles et al. 1999; Körner et al. 2013; Rapley 2008; Whitney 2003).

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Chapter 9

DISCUSSION AND CONCLUSIONS

Theory and Conclusions The data revealed three processes that responders used in planning and implementing the response: developing situational awareness, working with boundaries and definitions, and matching and aligning. Informed by its context and its own characteristics, through the developing situational awareness process, relief workers obtained information on and came to understand situation and relief efforts as a part of the decision-making context. Through working with definitions and boundaries, they defined who they were, the problems, and their relationship to them. It is through the third process of matching and aligning that they made decisions by making connections between aspects of the decision-making context they have developed situational awareness of and defined in defining and bounding process. The outcomes of these decisions became part of the decision-making context which was incorporated into subsequent iterations of these processes. The collective outcomes of these three processes left decisional legacies. These legacies contributed to the development of decisional inertia within the organization, in which an organization gradually gained more ‘mass” through the commitment of more resources and the commitment of more decisions, making the organization increasingly committed to a particular course of action. These three processes generally occurred in a cyclical process, beginning with developing situational awareness and ‘concluding’ in matching and aligning. Because this was a cyclical process, the matching process could and did trigger further development of situational awareness. These processes were ongoing throughout the response and occurred

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simultaneously. In fact, the processes that occurred during the relief effort began or were influenced by the processes engaged in prior to participating in the crisis effort. There was some evidence that these processes might be connected outside of this pattern (for instance, from defining based to situational awareness or matching back to defining), though future work is required to elaborate on these patterns. Because these processes (especially developing situational awareness) were ongoing and consistently considered information from the (constantly changing) environment, as other organizations went through this process, they too pushed the organization in a particular direction. Because of this inertia, organizations continued in this direction and found it increasingly difficult to change course. They continued to follow this plan of action until acted upon by a force from outside or within the organization. This sometimes disrupted the ‘motion’ (or initiated new motion, and therefore disrupted the rest) by opening up new opportunities while potentially disrupting existing opportunities. This can happen multiple times to varying degrees through the relief effort.

Implications for Theory Other scholars have used the concept of inertia to understand and explain organizations from a social science perspective. Hannan and Freeman, for example, talk about structural inertia in their discussion of organizational change. Taking an ecological perspective, they define inertia as “a correspondence between the behavioral capabilities of a class of organizations and their environments” (Hannan and Freeman 1984:151). Their focus is on structural change and organizational selection and survival. The inertia derives from organizations’ abilities to reproduce

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themselves, and structural inertia of an organization increases as size increases. They summarize their claims, stating,

“We have argued that selection pressures in modern societies favor organizations that can reliably produce collective action and can account rationally for their activities. A prerequisite for reliable and accountable performance is the capacity to reproduce a structure with high fidelity. The price paid for high-fidelity reproduction is structural inertia. Thus if selection favors reliable, accountable organizations, it also favors organizations with high levels of inertia. In this sense, inertia can be considered to be a by-product of selection. Our argument on this point may be considered an instance of the more general evolutionary argument that selection tends to favor stable systems (see Simon, 1862)” (Hannan and Freeman 1984:164). They note that there is less inertia in younger organizations than is present in older organizations, a point that appears to be consistent with inertia as it emerged in this study. Further, that “[h]igh levels of inertia may produce serious mis-matches between organizational outcomes and the intentions of members and clients in situations in changing environments” (Hannan and Freeman 1984:155) is similar to concerns present in this study, where an inability to adjust relief operations to changing needs in the affected area. Kelly and Amburgey (1991) test and build on this theory in their analysis of organizational change in the American air carrier industry. While their findings offered mixed support for the theory, failing to support expected relationships in environmental and organizational change and organizational size with change, they do find support for the size relationship. They add to the theory by incorporating the concept of momentum, conceptualized as repeating changes they previously experienced, citing Miller and Friesen (1984). Specifically, they write that “managers remain constrained by organizational history” and that “prior organizational actions have a powerful effect on both the probability and content of strategic change” (Kelly and Amburgey 1991:610). This integration of momentum in which the past guides and

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restricts later change parallels the concept of inertia proposed here, where previous decision guides and direct subsequent decision-making. The present research diverges from and builds on this research in important ways. While these theories share a focus on change in relation to the environment, a relationship to size, and potential consequences of inertia, there are some differences. Hannan and Freeman (1984) are writing about selection of organizations, not decision- making in and by organizations per se. They describe inertia as a rate of change compared to environmental change, whereas inertia is used in this dissertation more in terms of the strength of a tendency to work towards a set out goal or an organization’s intent. In other words, the present study focuses on what organizations did, with structure comprising only a small portion of that, whereas structural change is the primary focus of Hannan and Freeman. Further, though they do not say that their theory is exclusively relevant to corporations, much of their writing seems to reflect an implicit focus on corporations, and many (though not all) of their examples focus on them. Likewise, Kelly and Amburgey’s (1991) test of the theory similarly looks at corporations. In the context of crisis medical relief, organizations did not necessarily strive to achieve indefinite existence in the response context, but they did want to protect their presence in the relief context long enough to fulfill their plans and goals for participating in the crisis relief as they set out to. The decisional inertia presented in this dissertation is distinct from Weber’s (1978) concept of traditional action. In Weber’s typology of social action, he describes traditional action as that action done simply because it was done that way in the past. Decisional inertia does not necessarily reduce the entire relief effort to traditional

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(habitual) action.8 Decisional inertia is a reflection of the legacies those decisions have in the decision-making context. While precedent set by previous decisions has the potential for subsequent decision-makers to lose the reasoning behind the initial decision, the extent to which the organization as a whole engages in continual development of situational awareness and members incorporate that information in their decision-making determines to what degree this is in fact habitual versus consciously thought out action. Likewise, many of the precedents emerge in the form of definitions and boundaries which shape but do not always determine decision- making.

Convergence This study contributes to our understanding of convergence behavior in several broad ways. First, it explains convergence behavior by revealing the processes that fuel and direct its occurrence. This research demonstrates the interconnectedness of the personal, materiel, and informational convergence. From the discussions particularly of the interviewees, medical and public health relief efforts generally involved all three types. The mobilization and allocation of appropriate personnel was dependent upon the receipt of quality information, and on the mobilization of appropriate materials. Similarly, the distribution of material medical resources was dependent on the convergence of information and people. From their discussions, it appeared that the success of an effort organized around one type of convergence was even dependent on successful convergence of the other two resource types. Thus, not

8 For some individuals and even at the group level, however, some decisions could be made out of habit, or the distribution of decision-making could make a particular decision an example of traditional action.

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only do the processes revealed in this study help precipitate convergence in general, they also connect the three types of convergence together, and are the means by which one form of convergence may become emphasized over others, or how engagement in or request for one type of convergence can trigger processes that ultimately result in the engagement of all three. The convergence of information shapes material and personnel resources and convergence, but the personal and materiel convergence could, in turn, facilitate information resources.

This study aligns with Kendra and Wachtendorf’s (2003) concept of the response milieu. Several of the interviewees included in this study never deployed to the affected areas themselves, yet they were important parts of the response. Further, even among the people who did travel to affected areas to provide services, they generally still met at some point outside of the affected area (somewhere in the United States for the vast majority of the interviewees). Even if the event was happening in one area, the response activity occurred in multiple, some of which at great distance from the event location itself. These substantial distances between important locations of response activity and the event location (which itself was another area of response location) demonstrate both the limited utility in conceptualizing the response area as only being the crisis affected area, and the existence and importance of convergence in those various response locations. All of this aligns Kendra and Wachtendorf’s (2003) argument for a response milieu rather than the concentric circle model put forth by Fritz and Mathewson (1957).

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Models and Theories

Decision-Making and Sensemaking (figuring out) Many of the patterns and characteristics of decision-making discussed in previous research were evident in the findings from the present study. To the extent that there were multiple organizational actors involved in the response to both the Ebola epidemic and the Nepal earthquake, and that organizations (re)acted at least in part based on the actions of other groups indicates consistency with and support for (at least some of) the premises of Game Theory as discussed by Muggy and Heier Stamm (2014), though the present study clearly indicates that group level interactions are not the only external factor shaping activity, and simultaneously recognizes the importance of factors and dynamics internal to each of the individual organizations. This study demonstrates some parallels between sensemaking theory described by Weick (1995) and the process of developing situational awareness outlined here. Weick (1995) identified seven characteristics of sensemaking, many of which appear to be true of developing situational awareness and its links to the processes of working with definitions and boundaries and matching and aligning. That sensemaking is ongoing is one of the clearest parallels between Weick’s theory and the processes presented here, especially that of developing situational awareness. In the present study, groups continued to refine and develop further situational awareness as they and others began to act (often with each other) in the environment, both learning more about the environment and further creating the context within which they were operating. This is similar to the “enactive of sensible environments”, “social”, and “focused on and by extracted cues” characteristics of sensemaking (Weick 1995:17). That people and groups in the study often had to act in advance of complete

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information or full understanding of the situation appears to make it similarly retrospective and potentially “driven by plausibility rather than accuracy” (Weick 1995:17). Finally, that the professional backgrounds of individuals and the definitions of groups influenced what information was collected, focused on, and how that information was processed indicates that, like sensemaking, these processes are “grounded in identify construction” (Weick 1995:17). Sensemaking as a process has generally been conceptualized in the literature as taking place over a short period of time—minutes, hours, or a couple days at the longest. People and organizations in this study did appear to engage in similar types of activity in the process of developing situational awareness and the other processes. Given the temporal specificity to sensemaking in the literature, I am hesitant to say that the process of developing situational awareness is a sensemaking process given that it extends beyond hours and days (though it could be viewed as continual sensemaking to a series of small scale interruptions). Rather, it is a sensemaking-like process at work rather than sensemaking specifically. That said, this research builds on the sensemaking literature by indicating that the elements of sensemaking are at play throughout extended relief efforts, much longer than has been typically viewed. There are similarities to the theory of problem solving put forth by Gralla et al.

2016 a well. Both their work and the theory developed in this study indicate that problem solving is an ongoing and iterative process, and acknowledge that the problem itself changes over time. They diverge in that Gralla et al. indicate problem solving occurs in a back and forth between defining and solving the problem, while the present research indicates it is the result from continual engagement with the three processes put forth here. The previously discussed parallels between the present study

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and sensemaking offer another similarity between this work and that of Gralla et al. (2016). That said, the theory discussed in this dissertation does not explicitly use sensemaking. It also diverges by building on and expanding many of the points in Gralla et al.’s theory. In this study, like in Gralla et al., goals do help define choices. However, in this study, goals represent just one of several types of definitions and boundaries that shape the relief efforts. Similarly, constraints are just another kind of definition or boundary or a component of the decision-making context.

The closest parallel to dynamic perception in my study is the concept of decisional inertia. Gralla et al. described dynamic perception, writing that the participants in their study “perceived a more limited set of choices, determined by their dynamic perception” (2016:32). They further explain that “[d]ynamic perception limited the perceived set of possible moves and thus restricted choices to a ‘sub-space’ of the full problem space. It also functioned as a direct connection between sensemaking and solving, in that new dynamic perception prompted dispatch decisions” (Gralla et al. 2016:32). Decisional inertia similarly reflects both the consequences previous decision have for limiting the availability of options in subsequent decisions, but goes further in talking about the appearance of new options. Gralla et al.’s theory as a whole implies a general reduction of overall options over time, even if a particular option may become available or grow in priority. The concept of decisional inertia more clearly articulates how other decision-makers can take options off the table with a range of decision and more clearly addresses the possibility of options increases as well as changes in the event occur. In addition, the present work expands decision type and temporal boundaries of Gralla and colleague’s work (Gralla, Goentzel, and Fine 2014; Gralla, Goentzel, and Van de Walle 2015;

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Gralla, Goentzel, and Fine 2016) by looking at a broader range of decisions and at the medical and health relief context rather than logisticians making transportation decisions (Gralla et al. 2016). Elements of Fuzzy Trace Theory (Reyna 2008) emerged in the data. This pattern appeared in the definitions of needs relief workers produced and the matches they made in response to those needs. The increasing tendency to rely on gists with increased experience and expertise which Fuzzy Trace Theory highlights was evident in the extent to which organizations with long histories of providing international crisis medical relief had pre-defined notions of what would or would not be needed (shortening the length of time developing situational awareness and defining and bounding). While I do not necessarily see these definitions as “gists” in the way Reyna (2008) describes, there is a parallel in that people with more exposure to this kind of response effort and operational environment were more comfortable making decisions in contexts of uncertainty, but not necessarily condensing information. The data suggests that this may vary by field In sum, while the specific components of the theory may not have been clearly present, the tendency to rely on some kind of generalized information was evident in the data. Further, this study builds on the premise of Fuzzy Trace Theory by indicating that aspects of this pattern may occur at an organizational level rather than just at the individual level of analysis. This was apparent when considering the implications of decisional legacies and distribution. People may ‘forget’ the reasoning or miss cues as to why a certain approach or way of thinking fit at a particular point in time and why it may not fit now. This emphasizes the importance of continued use of the developing

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situational awareness process throughout the response, reflexivity, and flexibility to change things over the course of the effort. The connections between developing situational awareness and defining and bounding, and their collective effects in shaping decision-making behavior are both similar to and build upon the Theory of Relief Need Framing put forth by Wachtendorf, Penta, and Nelan (2015). They write that the media attention generated after a disaster brings attention to the event and frames need, which leads to the contribution of disaster relief, created “relief channels” (2015:246). Even after the media attention fades, relief follows a long these now powerful channels, noting that “it is easier to maintain patterns and increasingly more challenging to re-channel efforts” (Wachtendorf et al. 2015:246). Eventually, spillover occurs in directing relief to new unmet areas of need. The present work extends this theory by indicating that these patterns of attention and framing are relevant beyond just survivor need to be important for response needs as well and for the overall problem definition. It indicates that other individuals and groups beyond the media engage in this defining process as well, both on their own and in tandem with and informed by the media (given the importance of media as an initial source of information for many organizations in the earliest phases of developing situational awareness). Finally, the present research explains how these channels came to be carved in a particular way and why it can be so difficult to rechannel them through the concept of decisional inertia.

An important finding that emerged in this study regarding definitions is that, though the two crises were due to different types of events (earthquake and epidemic), relief workers increasingly came to define the problems in terms of public health and

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broader wellbeing needs. This became increasingly so over time. Whether it was concerns for hygiene and disease spread in camps of displaced earthquake survivors and chronic conditions exacerbated by disruptions to healthcare, or issues of stigma for Ebola survivors or links between Ebola spread and other infectious diseases, the health and medical issues came to be perceived of in broader terms. As a result, the definitions of the problems and the resources and activities required to address them became increasingly similar between the relief work for both events. This finding parallels observations from other scholars, such as Van Rooyen who similarly notes the shared definitions that can emerge, writing “[h]umanitarian crises like the Ethiopian famine and the Kurdish refugee crisis were increasingly recognized as acute, massive public health emergencies” (2016:38). Many of the specific crisis needs identified in all three data types echo needs identified in the literature. Specifically, that the crises - especially the earthquake - exacerbated pre-existing, chronic conditions matches with McCann’s (2015) claim that disaster can exacerbate chronic disease through a number of mechanisms including lack of food and clean water, temperature extremes from loss of electricity, injury, infection, physical and mental stress, and a lack of medication and medical care available (McCann 2015:16).

Characteristics: Distributed Over time, People, and Decisions/Processes

This study supports research arguing that decision-making can be distributed across groups, within groups across units and individuals, across inanimate objects, geographically, and over time (Charles et al. 1999; Körner et al. 2013; Rapley 2008;

Whitney 2003). The distribution present in this study parallels the concept of diffuse sensemaking Kendra and Wachtendorf (2016) propose in their study of the waterborne evacuation of Manhattan immediately following the September 11, 2001 terrorist

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attack. Important here is that the various boat operators who spontaneously organized into an impromptu flotilla that carried people out of Manhattan each began working on their own component of the response, independently making sense of the situation and working toward a common goal. This is similar to much of the early stages of developing situational awareness in the present study, where people and organizations began identifying needs the affected area, doing so more or less independently of other organizations’ activity.

The distribution of the three processes highlighted here is consistent with the models of shared decision-making (Charles et al. 1999; Rapley 2008) and distributed decision-making (Rapley 2008) in the medical decision-making literature, these processes were spread across individuals and organizations. That the number involved varied depending on the decision further offers support for Whitney’s (2003) claim in medical decision-making that different models of decision-making can be appropriate at different times depending on the circumstances. There was even some evidence to support Rapley’s claim that the decision-making is distributed across non-human actors/objects when considering the role of diagnostic tests in the Ebola epidemic and in Nepal as they became concerned with disease outbreaks in the tent camps. The duration over which these processes took place support Rapley’s claim that decision- making is distributed over time, and the more general reflection of others (Charles et al. 1999; Rapley 2008; Goodwin 2014) indicating that decision making is not a single moment.

That decision-making was spread across multiple actors both within organizations providing medical relief and across the relief effort as a whole was important in both conducting the responses to these crises and understanding them.

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Decisions had ripple effects which were felt in other organizations and subsequent decisions, even affecting seemingly unrelated aspects of the relief effort. Which services groups offered partially depended on which areas they operated in. The group’s composition, in turn, was affected by what services the group intended to provide. The team composition sometimes affected a group’s ability to shift tasks to meet evolving needs and pursue new opportunities while they were operating in the field. Further, that a group’s location of operation was influenced by other organizations working in the crisis context suggests that other actors may indirectly affected a group’s nimbleness in adapting to evolving post-disaster needs. This research suggests managing a large-scale response would benefit by using approaches that work to direct converging organizations’ efforts by highlighting productive and meaningful opportunities for groups to participate in the relief effort rather than relying solely on more restrictive measures aimed at preventing participation altogether.

The role of other organizational actors and policy in shaping decision-making has been raised by other scholars, who note the role of the UN and WHO along with others in creating policies, agendas, or response structures for international relief, such as the health cluster system (Van Rooyen 2016), and relief donation recommendations and instructions (Boulet-Desbareau 2013). These findings from other work align with the findings from this study that the greatest potential for relief effort change exists: (1) right at the beginning or shortly after the start (of the relief effort), (2) right after a force acts upon the relief effort (i.e. a change in the event), and (3) the first few years of organization life history.

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Medical Decision-Making—Influencing Factors It is clear in this study that the characteristics of the decision-making setting were important in shaping the response to both events. These characteristics featured a wide assortment of characteristics, including the quantity and quality of information, personnel, and material resources. It includes features of the culture and physical environment of the affected location and features in the hazard itself. Another important characteristic of the decision-making setting was the uncertainty inherent in aspects of both events. This uncertainty was both due to: 1) a lack of information; and 2) the ever-changing nature of resource availability, operational setting, needs, and even the hazard itself. The locations and severity of aftershocks, the interactions between the consequences of earthquake with monsoon season, or the discovery of new ways Ebola could spread from person to person: events such as these presented relief workers with a constantly evolving response context. These characteristics of the decision-making setting were the points of interest about which people sought information in the Developing Situational Awareness process, and, in some cases, served as the force that could lead to change in relief activity based on the new needs that manifested because of the previously mentioned factors. Many of these characteristics of the decision-making setting noted that shaped decision-making in these cases are consistent with conditions other research, including uncertainty (Boin and ‘t Hart 2007; Van Wassenhove 2006) and the convergence of material, people, and information resources (Argothy 2003; Fritz and Mathewson 1957; Holguin-Veras et al. 2014; Kendra and Wachtendorf 2001; Kendra and

Wachtendorf 2016; Larson, Metzger, and Cahn 2006; Scanlon and Osborne 1992; Scanlon et al. 2009). This both reflects the continued presence of these features of the crisis setting and supports the relevance of this work to other contexts.

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This study did offer some limited evidence of the influence of characteristics of the decision-maker and recipient (McKinley et al. 1996; Lincoln 2006; Charles et al. 1999; Bodenhausen 1988; Sabin et al. 2009; Haider et al. 2011). This occurred primarily in consideration of the influence of the individual’s previous experiences and training as well as their role or status in the organizations and relief effort. In this regard, the study aligns with the literature on sensemaking (Kendra and Wachtendorf 2016; Weick 1988; Weick 1993; Weick 1995), and in the importance of previous experience in decision-making (Rapley 2008; Reyna 2008) and would therefore suggest that other characteristics may be relevant. With regard to the characteristics of the recipient, the increased reliance on previous experience in the data perhaps supported or facilitated, the use of stereotypes or bias in medical decision making, but it was unclear from the data collected in this if this was the case. In other words, the conditions outlined by Rathore et al. (2009), Varkey et al. (2009), and Sabin et al. (2009) (namely uncertainty, though they refer to medical uncertainty, not uncertainty in overall context) as increasing the likelihood of implicit bias and stereotypes influencing decision-making were present in the cases included in the study. However, I did not have the right data to adequately assess if they were present and active in the decision-making examined in this study. Therefore, this research is inconclusive on this point. There were some parallels to the argument in Goodwin’s (2014) work on medical treatment decisions that decisions are experiments rather than solutions to problems. Participants did not explicitly take action to test the effectiveness of that action, but there was a see-what-happens element to some of the relief activity. The ongoing process of developing situational awareness meant that organizations were

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constantly assessing and evaluating the consequences of their actions and adjusting accordingly. The areas of focus that were created and fostered decision-making are both internal and external. That means both need to be considered in attempts to redirect behavior. In sum, the findings presented here supported the findings of previous research, which has found that people obtain information and use that to understand their environment; that interactions at the organizational and individual level are important in decision-making; and that characteristics of individuals, decision recipients, the context and the decision itself appear in both previous research and the present study. However, this research expands these findings in important ways, highlighting their relevance to wider groups, over longer periods of time, and across disciplines.

Implications for Practice

There are a number of implications for practice. The findings presented here offer suggestions as to the best ‘time’ to introduce science into decision-making and emergency management practice. Understanding how these efforts evolve, then, can perhaps lead to better understandings of how to influence relief efforts by knowing the points in time when relief efforts are most susceptible to change and what sources are most important in directing their activity. The greatest potential for altering a relief effort is in its initial phase and right after a force acts upon it. As a result, any attempts to alter the activities of these relief efforts (towards new approaches, underserved populations, etc.) should be targeted at these points in time. By extension, the people who are involved at these points in time are in the best position to influence them. Findings from this study echo findings from other

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studies that note differences in approaches between disciplines. In particular, the point that professional background and training shaped how people moved through these processes and engaged in them not only supports the ‘based on identify construction’ component of sensemaking (Weick 1995; Kendra and Wachtendorf 2016), it also connects with concerns raised in both emergency management and medical sociology literatures on professional differences. The way people of different disciplines and professional backgrounds appeared to be focused in on some needs and information more than others is similar to the patterns that appear in Caruson and MacManus’ (2011) article which indicated differences in vulnerability assessments for emergency management based on disciplinary specialty (management generalist, first responders, financial officers, human services specialists, and infrastructure specialists), particularly regarding issues of social vulnerability. Likewise, scholars in medical sociology have noted differences in (management styles; problem solving strategies?) between different professions in the medical field. Hall (2005), for instance, notes difficulties in interprofessional teamwork rooted in cultural differences in health professions. These findings are consistent with the notes some interviewees in this study made about different professional languages and perspectives among their relief colleagues that seemed to affect not only what information and issue they focused on, but how they approached decision-making in general. While only mentioned by a few interviewees, there is enough evidence to suggest that (1) this is an important issue in crisis relief work, (2) that even when looking at health and medical care, these disciplinary differences extend beyond the differences between different kinds of healthcare workers, expanding Hall’s (2005) work on interprofessional education in health care to a broader collection of

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professions important for running and providing healthcare services. This finding reinforces Hall’s (2005) claims regarding the importance of interprofessional training which would at least ensure relief workers are aware of profession-based differences in perspectives, and ideally would train relief workers to work with people from a variety of disciplines. Second, the tendency for different fields to have different foci and approaches to problem-solving emphasizes the importance of having disciplinarily diverse teams in order to sufficiently meet organizational goals and provide needed and appropriate health services in a challenging environment. This includes having individuals who have been trained in, occupy, or have occupied diverse positions. In other words, if approaches to relief vary with discipline, and the representation of those perspectives is necessary for a successful response, then diverse team composition is especially important at the times when relief efforts are most susceptible to influence and change. Third, many of these interdisciplinary differences in the study were suggested by individuals with non-medical backgrounds or had a non-medical role in the relief efforts. The medical personnel who did speak to disciplinary differences tended to have more experience in this kind of work. This pattern suggests a need for diverse teams when evaluating these efforts, and potentially in developing and delivering that interprofessional training. Some issues may be clearly apparent to individuals with some perspectives while remain unnoticed by others. This point echoes concerns highlighted in previous research that the involvement of multiple individuals complicates accountability measures (Goodwin 2014). This study reveals implications for how we deliver care in crisis medical relief efforts. Planning for these medical missions began before teams ever arrived in the

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affected countries. While they collect information from multiple sources, relief effort organizers are still essentially diagnosing an entire population before they ever interact with an individual patient. They use those conclusions to inform the materials and personnel they send into the field. The kinds of materials and personnel that are in the field affect what the organizations can do and how quickly and easily they can transition to new activities based on the updated information on the ground. This means that their abilities to address the needs of any individual patient while in the field are dependent on the quality of the assessment of the needs of a large body of people in the early hours of planning.

Implications: Trends Across Events Arguably more important than identifying these processes, the concept of decisional inertia and the commentary on other theory, is that I identified these processes and decisional inertia in both events. There is debate in both research and practice communities regarding applicability of research and practice between epidemics and traditional disasters (Hannigan 2012; Robinson 2016; Penta, Marlowe, Gill, and Kendra2017). Echoing Hannigan (2012), Robinson (2016) notes the separation of public health and emergency management in practice and research. Within the practice communities, different agencies are responsible for these two areas. In education and research, public health and public administration programs in academic settings occupy separate locations in both organizational structure and often in physical space. The result is separate and distinct literatures, and a “noticeable gap between public health work on disasters and work in emergency management (Robinson 2016:368). He notes that the literature and findings in these fields should “crossover” into the other fields (Robinson 2016:372). My research answers his call in

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both combining the literatures from these fields as well as pursuing a topic of research that necessarily engages both academic and practice communities. Similarly, Robinson points to emergency management field’s lack of attention to international disasters and the interconnection of emergency management, public health, and development studies, again echoing Hannigan (2012). This research, too, answers that call in contributing to our knowledge within these fields in an international context. Penta et al. (2017) comment that there is a need for specific comparison of epidemics and disasters, specifically highlighting personal and material convergence, risk communication, and delivery of medical care. This study does just that. In doing so, it identifies several similarities between the two. Disasters and epidemics shared characteristics of the decision-making setting. At the most surface level, some of the specific issues differed. However, at one level up of abstraction, they are categorially the same for both events. For example, in the Ebola epidemic, the danger to healthcare workers came from the patient and the potential for infection when providing when providing care. In Nepal, it came from the damaged buildings and compromised terrain in the location of providing care and further damage from future aftershocks. That said, while the specific mechanisms through which harm could come to the healthcare workers and others supporting those initiatives differed, ongoing threats to the safety and well-being of relief workers were an important part of both cases. Similarly, even when interviewees noted differences in the nature of the events, they were able to identify lessons learned from previous events and apply to both the Ebola epidemic and the Nepal earthquake. Even if characteristics of the event differed, important aspects of the response paralleled across crisis types. Hazards can be different and yet have some similar components

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either in the nature of the hazard or in the responses to them. These similar kinds of demands were met or resolved with similar processes. This finding has implications for the kinds of questions that we ask and transfer of knowledge gained in one event to another. Are epidemics disasters? Are disasters and epidemics similar? These are questions that are not actually very useful.

Study Strengths, Limitations, and Future Work

Methods and Application

Area of focus This study simultaneously considers the influence of individuals, organizations, characteristics of the actors involved and of the decision-making context as a whole and the influence of time at the same time. It does so by considering their influences independently and the way these factors intersect and interact to influence how people in organizations planned and implemented the medical relief efforts to the Ebola epidemic and the Nepal Earthquake. In considering these multiple interactions and dynamics, this study goes beyond the scope of much of other decision-making studies which often focus on one or a very small number of these dynamics, such as only focusing on organizational level interactions without considering the dynamics within organizations and vice versa, or focusing on individuals making decisions on their own or with others, but not simultaneously with the changing conditions of the decision-making context and the flow of organizational level interactions. This study further advances the decision-making literature by examining multiple decisions at once. Taking a more macro view of the entire relief effort rather

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than just one aspect of the relief effort offers insight into how one decision has the potential to affect other decisions over time. This approach extends much of the other work on decision-making, including much of the medical decision-making work which typically focuses on either a diagnosis decision or treatment decisions (e.g. Charles et al. 1999; Kessler 1990; Rathore et al. 2009; Whitney 2003), and the work by Gralla et al. (2016), which does look at multiple decisions over time, but focuses on a single type of decision (transportation allocation decisions). The perspective of this study consequently facilitates connections between findings from a number of scholars focusing on different areas.

Comparison between events Another methodological strength of this study is the examination of decision- making behavior in relief efforts for two events. The incorporation of two cases helps to distinguish between event-specific responses required for a particular type of hazards or even a specific event within a hazard type, suggesting that the processes identified in this study are relevant to other types of crisis events. However, there is an issue of scale. While Ebola was regarded by most of the interviewees as the largest response of its kind and new, Nepal, while considered severe, was an ‘ordinary disaster’. Both events clearly fit the crisis definition criteria, but the two events differ in their severity and novelty. Several respondents involved in the Ebola response noted the uniquely extreme quality of the experience. This outbreak was described as the largest known Ebola outbreak and the first to occur primarily in cities. Several respondents noted that this response was the largest (particularly CDC respondents noted that it was the largest CDC response), and individuals from multiple of the participating organizations indicated that their response activity was, in many respects,

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unlike anything they had done before. The Nepal earthquake, on the other hand, was not viewed in the same light. The people who responded to it definitely acknowledged the severe impact it had on the people who lived through it (and the impact of those who did not survive), yet in many respects it was considered a ‘run of the mill’ or ‘average’ disaster. Response demands did not appear to be unique from other events. In fact, several noted that the event was less severe than what they were anticipating on arrival, and some even noted (especially in the field data) that this was a less severe earthquake in magnitude and consequences than Nepal had been preparing for. In this sense, these are two different kinds of events. In some respects, with regard to the severity of the event and extent of the international response, the 2010 Haiti earthquake which so many interviewees referenced, may be more comparable to the Ebola epidemic than the Nepal earthquake is. That acknowledged, it does not appear that the differences between these events compromised the findings. First, the fact that the same processes and decision- making consequences emerged in the data for both events itself demonstrates consistent patterns of behavior independent of the scale of the events. Second, that the post-earthquake environment in Nepal was less severe than anticipated based on early attempts to develop situational awareness from afar reflects just another form of uncertainty and fluidity in the decision-making context that people participating in the relief efforts had to deal with. In some ways, this difference makes the theory developed here more robust by considering positive surprises as well as negative ones and their impacts on how they planned and implemented their efforts. In other words, while they both may not have had the same kind of or level of uncertainty present in

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the event contexts, they both had uncertainty, and the different kinds of uncertainty may have supported the theory development. Third, just as people in organizations contextualize the information they receive as they develop and understanding of the situation, interviewees contextualized the information they provided me during the interviews. They would often compare their experiences in other events, demonstrating how aspects of the Nepal responses stood in comparison to those other events. The 2010 Haiti earthquake served as an important reference point for interviewees from both events. Future work could take advantage of the research opportunities presented by another event more comparable in scale or novelty to either of the events and responses in this study. The level of conflict present in the operational context is another potential limitation of this study. Recent work notes an increased threat to humanitarian workers, including healthcare workers, involved in international crisis relief, indicating an important point of concern (Van Rooyen 2016). Van Rooyen (2016) notes the increasing risk that humanitarian workers face as they are increasingly under attack, which he claims was demonstrated in cases like the Sudan and Syria. Areas affected by the events in each case did have recent history of civil conflict, and safety concerns related to interpersonal conflict did emerge in the data. However, conflict or safety from conflict were not substantial concerns expressed by anyone in this study. While participants identified some safety concerns, these individuals were operating in areas with fairly recent histories of civil conflict. A small number mentioned some security concerns for themselves or others in their extended response networks, but comments from participants in this study suggest they had a greater focus on hazard- related threats than interpersonal ones.

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Consequently, it is unclear how these processes might be effected by security concerns both for epidemics and disasters occurring in conflict zones, and for understanding medical humanitarian crisis that are themselves caused by or the result of conflict situations, such as provision of medical services in Syria and for Syrian refugees. While it is not immediately apparent that the processes outlined in this study would function differently in decision-making settings with heightened security concerns, it is possible that the context would influence responses. The ways conflict- based crisis, including terrorist events, may foster a different engagement of these processes or may produce unique kinds of relief efforts is an important area of further inquiry.

Type of Relief Effort The distributed nature of the relief efforts to the Nepal earthquake and Ebola epidemic and the implications of that distribution for decision-making revealed in this study are likely analogous to those apparent in other kinds of lief effortsre, such as those focused on providing disaster donations. Given the specialized and technical nature of providing medical treatment, the precise ways in which decisions are made may differ compared to decision-making approaches used in planning and implementing relief activity requiring less technical expertise, and should be explored further in future work. Similarly, though the cases examined in this study and the responses to them were predominantly located in low-income nations, the findings presented here are likely relevant to understanding medical responses within high- income countries, such as the United States. While high-income nations may not experience the same volume of international groups converging on the disaster area as the affected areas in this study did, they may still experience convergence of non-local

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groups to the affected area(s). Additional investigation should explore issues of legitimacy and power dynamics in this process. At the time of the earthquake, Nepal was without a constitution. The earthquake and associated relief efforts did not appear to strengthen power or authority of the national government. The ability of organizations, particularly international groups, to continue to act more or less independent of other actors, most notably against the requests of Nepal’s government, raises important questions about balancing legitimacy with having a diversity of perspectives on the needs of disaster-effected populations. Power dynamics among the governmental and nongovernmental actors involved and the ability of government actors to restrict the activity of others may be different in countries with a stronger or more stable pre-event governmental authority and which are less compromised by the disaster itself, an issue that should be examined further in future work.

Sample

One of the strengths of this study is the sample. The inclusion of different kinds of groups makes the findings in this study more robust because they indicate that these are patterns not restricted to a particular group’s approach, suggesting generalizability. Further, most of the groups had more than one interviewee, offering multiple perspectives within organizations as well. Unfortunately, the sample compositions are not identical for both cases, with limited presence of government personnel in the Nepal data. Likewise, the majority of the Ebola interviewees came from government. While the overall diversity of positions and organizations in the study, combined with the similarities across the interviewees, indicate that this sample was adequate to identify general trends, a better sample would have included governmental and nongovernmental diversity within each event. However, the event-

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based differences in sample composition are reflective of the actors that were involved. Future work should look at how individuals in the medical fields are trained going into this field. Researchers pursuing this line of inquiry, for example, could examine trends in terminology used in training materials or could look at the different models and approaches to training (i.e. looking at who they take classes with, if students are trained to work with others).

Strengths Limitations of the Theory There are some other areas in need of further examination. At face value, it appears that the theory developed here is scalable, meaning that I believe that it could be applied to the behavior of individuals to understand decision-making at an individual, or could be scaled up to understand patterns of the larger relief effort as a whole. However, the present study cannot demonstrate this scalability conclusively. Future research is required to determine at what level of analysis this theory is most appropriate for use. In addition, further research is needed to more fully tease out the relationships between these three processes. This theory does have explanatory power. At a conceptual level, it does appear to be predictive. More research is necessary, however, to determine its predictive power. This is hampered by another issue associated with this theory: the individual components that comprise the relief effort “mass” are difficult to operationalize in quantitative terms. Determining a unit of measurement for personnel when some are working multiple positions, determining an appropriate unit of information, counting resources dedicated to an effort within organizations that have those resources on standby, and the issue of how to quantify the number of decisions, for instance, all present challenges to refinement of the theory through quantitative analysis. While

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ostensibly these would be numerically measurable, as already discussed, these decisions are rarely if ever succinct, precise moments, but rather stretched out over time. Determining when to mark the beginning and end of decision could prove immensely difficult. Similarly, time becomes an issue, particularly in cases where the matching component of decision making predates the crisis, identifying precise ‘start’ time points of the event and the response will be hard to define.

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Appendix A

INTERVIEW GUIDE

INTERVIEW GUIDE CRISIS HEALTH AND MEDICAL RELIEF EFFORTS

Introduction: Thank you so much for meeting with me and talking with me today. Just to reiterate, this is for my dissertation, in which I am trying to learn about how people in organizations create and run humanitarian relief efforts focused on providing health and medical services. Specifically, I am interested in how people make decisions in groups in organizations. For this interview, I would like you to talk about your experiences in the relief effort to [EVENT NAME].

I would like to start by first getting a little bit of background information on you, the organization you worked with, and the relief effort you participated in. 1. Tell me a little bit about your background and what you do here [with this organization]. a. What is the organization are you affiliated with? Is it embedded in a larger organization? b. What other groups were/are you working with? c. What is the main purpose or mission of this organization? Can you describe what your organization is/does? d. What is the extent of this organization’s experience with disaster or crisis relief? e. With disasters/epidemics/refugees [pick based on which event they were involved in]? f. With the country you ended up operating in? Could you provide a brief, one minute summary of your organization’s efforts related to [NAME EVENT] g. What is your position or role within that organization? h. How long have you been involved in this organization? In your current role? i. Have you had previous experience do you have in disaster or crisis relief? j. If yes, then what were your roles in that work? k. What is the composition of the team you worked with for this relief effort?

For these next few questions, I would like you to think back to the beginning/initial stages of the effort and to talk about how the effort began. These questions will focus

269 on the decisions and activities involved in the planning and organization of health and medical relief efforts. For these questions, I would like you to think about the time period beginning with when you first heard of [EVENT NAME] up to the point when your organization began to implement the effort. 2. How did you and the organization decide to get involved humanitarian relief for [EVENT NAME]? Within the organization who was involved in that decision? a. Were these individuals the ones who would usually make the decisions, or were there others brought in not normally involved? 3. Who decided what the organization was going to do? How did they make that decision? a. Were you consulted to provide information before this person or group made the decision? b. Were there people or groups who influenced the planning of the relief effort that you did not anticipate having a role? From the community you were operating in? 4. Can you talk about what kinds of activities you engaged in during the process of planning and getting ready to implement the relief effort? a. [How] Did these evolve over time? Could you describe any ways that the things you were doing changed over the course of your response? b. Was there a point at which your effort became less susceptible to change/when the mission and tasks of the effort were set in stone? c. [If talking about standard operating procedures] How much did you rely on standard operating procures? At what point did you transition out of them? How long have those procedures been in place? Who developed them? 5. What were some of the issues, concerns, or other points of significance that you needed to address in planning the relief effort? a. [Examples in case they need guidance on what I am looking for}: personnel availability, personnel skill set, resources available on the ground, requirements/needs for particular types of care, connections in the country, security concerns on sight, partner organizations, other initiatives in the country, etc. b. How did you identify these? c. Were any of your (organization’s or your individual) decisions or activities held up for some reason? Were there some decisions or actions dependent on other decisions happening first? d. How do you see the work of your organization overlapping with other humanitarian relief initiatives for this event?

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6. Can you talk about how you prioritized these issues, decisions, and tasks (as an organization, as an individual)? a. How much did you think about the delivery of care itself when you were planning and getting ready for this relief effort? 7. I know from looking at past disasters that this is a tough process and sometimes it can be challenging to get everyone on the same page. Were there different approaches to relief considered at any point in the design or planning of this effort? a. Was there any disagreement among your coworkers at any point in the design or planning of this effort? 8. IF YES: About what? Who? What role/position did they occupy? How was disagreement considered or dealt with? How did the idea you all went with win out? IF NO: How did the group build consensus? 9. About how long did this planning period last (from the decision to go to when the group arrived on sight)? 10. Still thinking about the time before your organization left for deployment, what were you expecting when you arrived on sight? a. [Examples to bring up only if they need guidance as to what I’m looking for]: operating conditions, timelines to start up, needs on the ground, the influence of governmental and non-governmental actors, etc. OK great, thank you so much. Now for the next set of questions, I would like to transition to thinking about the implementation of the relief effort. For these questions, think about the time from when the organization started to implement its work, then transitioning to thinking about how the effort and your activity changed over the course of the effort. 11. What did you do upon arrival? (NEED PREVIOUS OF INFO GORUP?) 12. Once the organization started the effort, how did the situation compare or mesh with your expectations? How did it differ? In what way was this event unique (from previous events)? a. Where were you getting information from? How did you gather and assess information? b. Who was involved in assessing information? c. How was information communicated amongst team members? With and between teams? 13. What unexpected things happened along the way and how did you change as a result? a. What interruptions or changes occurred over the course of this phase of the effort?

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b. Did your organization at any point reconsider any of the previously rejected approaches to relief? c. Were there people or groups who influenced your relief effort that you had not anticipated would play a role? Specifically among the local population? 14. How did your individual responsibilities or roles change? 15. [If they have not mentioned psychological or psychosocial services at this point] At any point, did your organization consider offering psychological or psychosocial services to affected persons? Tell me about how you came to that decision? For this final section, I would like you to talk about the conclusion of this relief effort. 16. Tell me about how your organization [will] approach[ed] concluding the relief effort? a. When did/when will your relief effort end? b. How was this approach developed? What factors and issues made you decide to end your work? c. When did your organization develop this plan? How was involved? What did you consider when coming up with this approach? Has it changed? d. [If they do not know] When did you find out about the exit strategy? How did you feel about it? How would you evaluate the exit strategy as it was implemented? Were there any changes? 17. Is there anything else you think is important for me to know in understanding how you and your organization designed and implemented this relief effort? 18. Now that you know what I am interested in learning about, who else in your organization should I talk to? What about from other organizations you know were involved? 19. Would it be alright if I followed up with you in a brief conversation after I have completed more interviews if something arises in those conversations that did not emerge here?

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Appendix B

NEPAL QUICK RESPONSE APPROVAL LETTER

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Appendix C

NEPAL QUICK RESPONSE RENEWAL LETTER

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Appendix D

APPROVAL LETTER—UNDERSTANDING CRISIS MEDICAL RELIEF EFFORTS

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Appendix E

TABLE OF DOCUMENTS

Document Name Organization Emergency and Humanitarian Action, WHO Nepal, Nepal Earthquake Health Health Update, SITUATION REPORT No. 1: 26 April 2015 Cluster/ WHO Emergency and Humanitarian Action, WHO Nepal, Nepal Earthquake Health Health Update, SITUATION REPORT No. 2: 27 April 2015 Cluster/ WHO Emergency and Humanitarian Action, WHO Nepal, Nepal Earthquake Health Health Update, SITUATION REPORT No. 3: 28 April 2015 Cluster/ WHO Emergency and Humanitarian Action, WHO Nepal, Nepal Earthquake Health Health Update, SITUATION REPORT No. 4: 29 April 2015 Cluster/ WHO Emergency and Humanitarian Action, WHO Nepal, Nepal Earthquake Health Health Update, SITUATION REPORT No. 5: 30 April 2015 Cluster/ WHO Emergency and Humanitarian Action, WHO Nepal, Nepal Earthquake Health Health Update, SITUATION REPORT No. 6:1 May 2015 Cluster/ WHO Emergency and Humanitarian Action, WHO Nepal, Nepal Earthquake Health Health Update, SITUATION REPORT No. 7: 2 May 2015 Cluster/ WHO Emergency and Humanitarian Action, WHO Nepal, Nepal Earthquake Health Health Update, SITUATION REPORT No. 8: 3 May 2015 Cluster/ WHO Emergency and Humanitarian Action, WHO Nepal, Nepal Earthquake Health Health Update, SITUATION REPORT No. 9: 4 May 2015 Cluster/ WHO Emergency and Humanitarian Action, WHO Nepal, Nepal Earthquake Health Health Update, SITUATION REPORT No. 10: 5 May 2015 Cluster/ WHO Emergency and Humanitarian Action, WHO Nepal, Nepal Earthquake Health Health Update, SITUATION REPORT No. 11: 6 May 2015 Cluster/ WHO Emergency and Humanitarian Action, WHO Nepal, Nepal Earthquake Health Health Update, SITUATION REPORT No. 12: 7 May 2015 Cluster/ WHO Emergency and Humanitarian Action, WHO Nepal, Nepal Earthquake Health Health Update, SITUATION REPORT No. 13: 8 May 2015 Cluster/ WHO World health Organization Country Office for Nepal Nepal Health Earthquake Situation Report No. 14:11 May 2015 Cluster/ WHO World health Organization Country Office for Nepal Nepal Health Earthquake Situation Report No. 15:13 May 2015 Cluster/ WHO World health Organization Country Office for Nepal Nepal Health Earthquake Situation Report No. 16:15 May 2015 Cluster/ WHO World health Organization Country Office for Nepal Nepal Health Earthquake Situation Report No. 17:19 May 2015 Cluster/ WHO

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World health Organization Country Office for Nepal Nepal Health Earthquake Situation Report No. 18: 22 May 2015 Cluster/ WHO World health Organization Country Office for Nepal Nepal Health Earthquake Situation Report No. 19: 26 May 2016 Cluster/ WHO Health Cluster Bulletin #1 May 2015, Nepal Earthquake 25 April to 3 Health May 2015 Cluster/ WHO Health Cluster Bulletin #2 May 2015, Nepal Earthquake 04-10 May Health 2015 Cluster/ WHO Nepal Earthquake, Health Cluster Bulletin No. 3 May 2015 11-17 May Health 2015 Cluster/ WHO Nepal Earthquake, Health Cluster Bulletin No. 4 May 2015 18-26 May Health 2015 Cluster/ WHO Nepal Earthquake, Health Cluster Bulletin No. 5 May 2015 28 May-3 Health June 2015 Cluster/ WHO Nepal Earthquake 2015, Health Cluster Bulletin #6 16 June 2015 Health Reporting period May 2015 4-18 June 2015 Cluster/ WHO Guinea: situation Report 1 Ebola Virus Disease, Guinea, 28 March 2014 WHO Guinea: situation Report 2 Ebola Virus Disease, Guinea, 14 April 2014 WHO SIREP 2 Ebola Virus Disease, West Africa Date of issue:17 April 2014 WHO World Health Organization, Health emergency Highlights, Emergency Risk Management and Humanitarian Response Issue#14 WHO World Health Organization, Regional Office for Africa, Outbreak Bulletin Vol. 4 Issue 3, 23 May 2014 WHO World Health Organization, Weekly epidemiological record No. 20, 2014, 89, 205-220. 16 May 2014 WHO Guinea: Ebola virus disease, West Africa--update 10 July 2014 WHO Guinea: Ebola virus disease, West Africa--update 14 July 2014 WHO Guinea: Ebola virus disease, West Africa--update 29 July 2014 WHO Guinea: Ebola virus disease, West Africa--update 31 July 2014 WHO World Health Organization, Health Emergency Highlights, Emergency Risk Management and Humanitarian Response Issue#17; August 2014 WHO WHO: Ebola Response Roadmap Situation Report 1, 29 August 2014 WHO WHO: Ebola Response Roadmap Situation Report 2, 5 September 2014 WHO

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World Health Organization, Regional Office for Africa, Outbreak Bulletin Vol. 4 Issue 4, 31 October 2014 WHO WHO: Ebola Response Roadmap Update 8 September 2014 WHO Outbreak Summary, WHO/AFRO Response to the Ebola Virus Disease (EVD) outbreak, and update by the Regional Director 12 September 2014 WHO WHO: Ebola Response Roadmap Situation Report 3, 12 September 2014 WHO WHO: Ebola Response Roadmap Update 16 September 2014 WHO WHO: Ebola Response Roadmap Situation Report 18 September 2014 WHO WHO: Ebola Response Roadmap Update 22 September 2014 WHO WHO: Ebola Response Roadmap Situation Report 24 September 2014 WHO WHO: Ebola Response Roadmap Update 26 September 2014 WHO WHO: Ebola Response Roadmap Update 1 October 2014 WHO WHO: Ebola Response Roadmap Update 3 October 2014 WHO WHO: Ebola Response Roadmap Situation Report 8 October 2014 WHO WHO: Ebola Response Roadmap Update 10 October 2014 WHO WHO: Ebola Response Roadmap Situation Report 15 October 2014 WHO WHO: Ebola Response Roadmap Update 17 October 2014 WHO World Health Organization: Ebola Response Roadmap Situation Report 22 October 2014 WHO World Health Organization: Ebola Response Roadmap Situation Report Update 25 October 2014 WHO World Health Organization: Ebola Response Roadmap Situation Report 29 October 2014 WHO World Health Organization: Ebola Response Roadmap Situation Report 31 October 2014 WHO World Health Organization: Ebola Response Roadmap Situation Report 5 November 2014 WHO World Health Organization: Ebola Response Roadmap Situation Report Update 7 November 2014 WHO Agenda: Volunteer Meeting: Debriefing & Planning DMRT Suggested Traveller Supplies List for Nepal Relief Effort DMRT Post Meeting Message DMRT Agenda: Volunteer Meeting: Debriefing & Planning DMRT Delaware Medical Relief Team (DMRT) - FAQ DMRT

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Suggested Traveller Supplies List for Nepal Relief Effort (Updated) DMRT Ken Isaacs, Testimony, House Committee of Foreign Affairs: Subcommittee on Africa, Global Health, Global Human Rights, and International Organizations, Combating the Ebola Threat, August 7, Samaritan's 2014 Purse

"Why Are We Ignoring a New Ebola Outbreak?" The New York Times Samaritan's by Ken Isaacs, July 24, 2014 Purse

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