This case study investigated the Endoscopy Center of Southern Nevada's crisis communication tactics employed in response to the Hepatitis C outbreak springing from the clinic in 2008. The research sought to evaluate the success of the clinic's crisis PR strategy, as it followed the advice of its lawyers and declined to take responsibility for the patients' exposure or offer an apology. The aim of this study is to illuminate public relations alternatives to apology in instances of corporate transgressions resulting in major harm, to salvage reputation and preserve company viability. Content analysis was used to extract public opinion from reader feedback comments on online news stories regarding the clinic. Benoit's (1995) Image Restoration theory and Coombs and Holladay's (2002) Situational Crisis Communication theory were used to develop the content analysis instrument and evaluate the clinic's crisis communication strategies. Agenda-setting theory was also explored between the news stories and the reader feedback. Analysis yielded overwhelmingly negative public response to the clinic's communications, and revealed some possible reasons for the negativity. A list of five crisis communications "best practices" was developed from these discoveries, highlighting five public relations principles to consider when the lawyers say apology is not an option: 1. Have a rapid initial response; 2. Maintain consistent message strategy, especially when employing Situational Crisis Communication tactis; 3. Compensate victims; 4. Give 'em a "pound of flesh," and 5. Get the situation squared away quickly. Evidence showed agenda-setting effects for the public influencing the "tone" of reporting (positive, neutral or negative), and both the news outlet and the public contributed to determining focal issues of the crisis. This finding underscores the importance of following "best practices" guidelines to devise effective communication strategies for shaping reputation in times of crisis.

No description available.

AN ABSTRACT OF THE DISSERTATION OF Amy L. Mathes, for Doctor of Philosophy degree in HEALTH EDUCATION, presented on May 8, 2013, at Southern Illinois University Carbondale. TITLE: PROMISING PRACTICES: A CASE STUDY ON PUBLIC HEALTH EMERGENCY PREPAREDNESS MAJOR PROFESSOR: Dr. Kathleen Welshimer There is little published literature on operational coordination during a real time disaster regardless of the setting. This study describes a university's emergency management plan and its execution in response to a specific natural disaster, the May 8, 2009 "inland hurricane," which was later classified as a "Super Derecho." The case study design allowed for an in-depth exploration into the intricacy and complexity of an emergency response by interviewing individuals present in the CEOC and others from State Police, local EMA agencies, local health departments, and IEMA, document analysis of the Campus All-Hazards Emergency Preparedness and Violence Prevention Plan (CAHEPVPP), Situation Reports, Illinois Emergency Management Agency (IEMA), Federal Emergency Management Agency (FEMA), and National Incident Management Agency (NIMS) documents. This study will assist public health emergency preparedness officials in higher education to educate students and development of proactive development of planning and response during a real disaster. This study will also provide contributions to universities regarding mitigation, planning, response, and recovery activities. It shows the value of proactive, forward-thinking leadership from day-to-day preparedness activities to response and recovery efforts.

In the aftermath of Hurricane Katrina, Goodman and Mann (2008) found that many locales along the Mississippi Gulf Coast did not have plans that addressed human resources (HR) issues in the aftermath of a disaster, and many vital employees were not included in the emergency planning process. The authors concluded that if involved in planning, HR managers could address typical HR issues such as compensation, retention, recruitment, and task re-orientation that become more difficult following a disaster. The purpose of this study was to examine the level of involvement of HR departments in the emergency planning process as well as the characteristics of cities that include HR personnel in this type of planning. This study highlights some of the common HR issues included in local government emergency plans as well as the characteristics of cities that have addressed these issues. A nationwide study of HR directors revealed that while most local governments include HR departments in emergency planning, the extent of this involvement varies. In addition, many HR professionals stated that some areas, such as compensation, discipline, and termination, need further attention, and that guidelines regarding important human resource issues should be established for local governments nationwide. Because this study is one of the first to examine the role of human resource professionals in local government emergency planning, it serves as a foundation for future research on the impacts of human resource involvement in emergency planning, and also for governments at all levels to consider how areas that are often daily routines may become difficult during times of crisis. Finally, this study provides a starting point for the creation of guidelines for important areas of human resource management that should be considered as local governments continue to build resilient, sustainable communities.

<p> </p> <p>A search and rescue (SAR) operation requires a rapid, accurate, and effective response to provide the missing person the best chance of being rescued. Personnel from the local area are likely to be closest to the location of the missing person, be familiar with the area, but they may not be adequately trained, experienced, or equipped with the best tools to effectively locate, identify, and retrieve the missing person. Thus, most SAR operations rely on a mix of trained personnel and volunteers. Among the trained personnel, there is a wide variance in proficiency, experience, and access to technology, leading to some emergency response agencies being better prepared than others. Volunteers, on the other hand, could be very helpful, but are largely untrained and inexperienced, reducing their inherent likelihood of success. The primary challenge to successful SAR operations is the lack of consistently trained, adequately equipped, and diversely experienced personnel. Despite the lack of desired resources, SAR operations must be completed rapidly and emergency responders often turn to volunteers. In response to this challenge, the use of unmanned aerial systems, UAS, in small volunteer teams was proposed. Available, off-the-shelf UAS technology can be used to simplify training with the help of affordable advanced technology, and thereby enable rapid, accurate, and effective SAR operations.  </p> <p>The following research was executed in the form of three independent, but related, studies. The first study focused on the efficiency of a UAS-equipped SAR operation; the second study focused on the accuracy of a UAS and image analysis software-enabled SAR operation; and the third study tested the ability of novice volunteers to learn and apply the new technologies (UAS plus image analysis) efficiently and effectively. The goal of these studies was to determine whether affordable commercial, off-the-shelf technologies could be used to enhance the efficiency and effectivity of SAR operations. The experimental methodology used specifically designed simulations of SAR operational scenarios. Two operational tactics were tested: (a) Equip the SAR team with UAS and (b) equip the SAR team with UAS and image analysis software. The specific scenarios selected were similar in complexity, but different enough to minimize the transfer of learning from the first study to the second study.  Finally, the reference times for manual SAR operations were compared against UAS and computerized image analysis software-assisted methods. The results of the proposed studies determined whether off-the-shelf UAS and image analysis technologies could be used to enable rapid, accurate, and effective SAR operations. </p>

No description available.

The COVID-19 pandemic has pressured governments to plan and implement policies to protect their citizens and economies. In British Columbia (B.C.), all local governments needed to plan and respond to the pandemic emergency to some degree. However, due to the variations in population, region, and resource capacity, there may be a number of discrepancies between local governments. Using key informant interviews with emergency management staff from local governments across B.C., this thesis aims to identify how local governments in B.C. used pandemic planning documents to develop policies to respond to the COVID-19 pandemic. The analysis revealed that the majority of participants viewed pandemic planning documents as not critical to the successful implementation of policies. The analysis also identified what the participants believed worked well and did not work well when planning and responding to the pandemic with respect to collaboration, communication, staff impacts, digital infrastructure, and financial impacts. The thesis concludes by recommending that local governments develop a flexible plan, establish collaborative networks with target groups, create communication strategies with higher levels of government, and regularly review and update digital infrastructure. / Graduate

Risk assessments in volcanic contexts are complicated by the multi-hazard nature of both unrest and eruption phases, which frequently occur over a wide range of spatial and temporal scales. As an attempt to capture the multi-dimensional and dynamic nature of volcanic risk, we developed an integrAteD VolcanIc risk asSEssment (ADVISE) model that focuses on two temporal dimensions that authorities have to address in a volcanic context: short-term emergency management and long-term risk management. The output of risk assessment in the ADVISE model is expressed in terms of potential physical, functional, and systemic damage, determined by combining the available information on hazard, exposed systems and vulnerability. The ADVISE model permits qualitative, semi-quantitative and quantitative risk assessment depending on the final objective and on the available information. The proposed approach has evolved over a decade of study on the volcanic island of Vulcano (Italy), where recent signs of unrest combined with uncontrolled urban development and significant seasonal variations of exposed population result in highly dynamic volcanic risk. For the sake of illustration of all the steps of the ADVISE model, we focus here on the risk assessment of the transport system in relation to the tephra fallout associated with a long-lasting Vulcanian cycle.

Emergency management coordination in the United States has fallen victim to over a century of strategies to organize, reorganize, consolidate, or decentralize disaster preparedness, planning and response. Regardless of the agency in charge at the federal level, individual citizens have been responsible for their own well-being immediately after any disaster or emergency event for more than 100 years because it takes time to mobilize and deliver aid. The system most often charged with managing that mobilization during an emergency event that exceeds the response capacity of local public safety agencies is the state emergency management network. Many entities in a state emergency management network have different responsibilities during disaster states vs. non-disaster states. Regardless of their role and function, entities need to be able to exchange resources and information with each other, often under time, economic, or other constraints during disasters. This resource exchange generates trust, an essential element of a resilient network. Resilient networks suffer fewer negative impacts from disaster related loss and are more likely to retain collective capacity to respond and help communities recover. The purpose of this study is to explore the ability of individual and state level attributes to explain variability in perception of network resilience. One-hundred fifty one state emergency management agency employees were surveyed regarding their perception of 5 constructs of network resilience (rapidity, redundancy, relationships, resourcefulness, and robustness) and individual level attributes. State level indicators from FEMA, NEMA, American Human Development Index, and Social Vulnerability Index were also analyzed. Overall, it was found that the individual attribute of perception of network integrity had the most influence on perception of network resilience, followed by perception of community resilience and state level attributes including disaster experience, state well-being, and number of full time state emergency management agency employees. These findings can improve network resilience by informing state emergency management network development activity. Networks that increase member opportunities to develop relationships of resource and information exchange will increase their resilience. That increased network resilience impacts community resilience because, as Winston Churchill's wise words during World War II reconstruction advise, "We shape our communities and then they shape us".

Disaster events have emphasized the importance of healthcare response activities due to the large number of victims. For instance, Hurricane Katrina in New Orleans, in 2005, and the terrorist attacks in New York City and Washington, D.C., on September 11, 2001, left thousands of wounded people. In those disasters, although hospitals had disaster plans established for more than a decade, their plans were not efficient enough to handle the chaos produced by the hurricane and terrorist attacks. Thus, the Joint Commission on Accreditation of Healthcare Organizations (JCAHO) suggested collaborative planning among hospitals that provide services to a contiguous geographic area during mass casualty disasters. However, the JCAHO does not specify a methodology to determine which hospitals should be included into these cooperative plans. As a result, the problem of selecting the right hospitals to include in exercises and drills at the county level is a common topic in the current preparedness stages. This study proposes an efficiency index to determine the efficient response of cooperative-networks among hospitals before an occurrence of mass casualty disaster. The index built in this research combines operations research techniques, and the prediction of this index used statistical analysis. The consecutive application of three different techniques: network optimization, data envelopment analysis (DEA), and regression analysis allowed to obtain a regression equation to predict efficiency in predefined hospital networks for mass casualty disasters. In order to apply the proposed methodology for creating an efficiency index, we selected the Orlando area, and we defined three disaster sizes. Then, we designed networks considering two perspectives, hub-hospital and hub-disaster networks. In both optimization network models the objective function pursued to: reduce the iii travel distance and the emergency department (ED) waiting time in hospitals, increase the number of services offered by hospitals in the network, and offer specialized assistance to children. The hospital network optimization generated information for 75 hospital networks in Orlando. The DEA analyzed these 75 hospital networks, or decision making units (DMU's), to estimate their comparative efficiency. Two DEAs were performed in this study. As an output variable for each DMU, the DEA-1 considered the number of survivors allocated in less than a 40 miles range. As the input variables, the DEA-1 included: (i) The number of beds available in the network; (ii) The number of hospitals available in the network; and (iii) The number of services offered by hospitals in the network. This DEA-1 allowed the assignment of an efficiency value to each of the 75 hospital networks. As output variables for each DMU, the DEA-2 considered the number of survivors allocated in less than a 40 miles range and an index for ED waiting time in the network. The input variables included in DEA-2 are (i) The number of beds available in the network; (ii) The number of hospitals available in the network; and (iii) The number of services offered by hospitals in the network. These DEA allowed the assignment of an efficiency value to each of the 75 hospital networks. This efficiency index should allow emergency planners and hospital managers to assess which hospitals should be associated in a cooperative network in order to transfer survivors. Furthermore, JCAHO could use this index to evaluate the cooperating emergency hospitals’ plans. However, DEA is a complex methodology that requires significant data gathering and handling. Thus, we studied whether a simpler regression analysis would substantially yield the same results. DEA-1 can be predicted using two regression analyses, which concluded that the average distances between hospitals and the disaster locations, and the size of the disaster iv explain the efficiency of the hospital network. DEA-2 can be predicted using three regressions, which included size of the disaster, number of hospitals, average distance, and average ED waiting time, as predictors of hospital network efficiency. The models generated for DEA-1 and DEA-2 had a mean absolute percent error (MAPE) around 10%. Thus, the indexes developed through the regression analysis make easier the estimation of the efficiency in predefined hospital networks, generating suitable predictors of the efficiency as determined by the DEA analysis. In conclusion, network optimization, DEA, and regressions analyses can be combined to create an index of efficiency to measure the performance of predefined-hospital networks in a mass casualty disaster, validating the hypothesis of this research. Although the methodology can be applied to any county or city, the regressions proposed for predicting the efficiency of hospital network estimated by DEA can be applied only if the city studied has the same characteristics of the Orlando area. These conditions include the following: (i) networks must have a rate of services lager than 0.76; (ii) the number of survivors must be less than 47% of the bed capacity EDs of the area studied; (iii) all hospitals in the network must have ED and they must be located in less than 48 miles range from the disaster sites, and (iv) EDs should not have more than 60 minutes of waiting time. The proposed methodology, in special the efficiency index, support the operational objectives of the 2012 ESF#8 for Florida State to handle risk and response capabilities conducting and participating in training and exercises to test and improve plans and procedures in the health response.