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Community Responses to Mass Casualty Events: A Mixed Method Approach
Title
Community Responses to Mass Casualty Events: A Mixed Method Approach.
Creator
Payne, Jeffrey, Handberg, Roger, Dolan, Thomas, Kang, Kyungkook, Knox, Claire, University of Central Florida
Abstract / Description
This dissertation explores how traits of a mass casualty event and community institutionalization affect how a community demonstrates solidarity after a mass casualty event. A systematic examination of mass casualty events along these lines has not been conducted before. Theoretically, individual helping behaviors like altruism help explain individual involvement in demonstrations of solidarity while solidarity and resilience help in explaining group behaviors. A typology is proposed that...
Show moreThis dissertation explores how traits of a mass casualty event and community institutionalization affect how a community demonstrates solidarity after a mass casualty event. A systematic examination of mass casualty events along these lines has not been conducted before. Theoretically, individual helping behaviors like altruism help explain individual involvement in demonstrations of solidarity while solidarity and resilience help in explaining group behaviors. A typology is proposed that breaks up mass casualty events into four different types: terrorism, criminal, weather and accidents. These types of events make up the majority of non-war mass casualty events. Experimentally a sample of students is used to assess how individuals are likely to respond to mass casualty events by gauging how they would respond using five different types of demonstrations of solidarity. Findings suggest that victim type positively influences demonstrations of solidarity while casualty number and event type are only selectively influential. Two cases (Orlando, FL 2016 and San Bernardino, CA 2015) are used to test three hypotheses that are related to how a community demonstrates solidarity after a mass casualty event. Results indicate that victim type positively influences demonstrations of solidarity, particularly through the specific institutions within vulnerable communities that increased access to demonstrations. Additionally, increased institutionalization within the victim community also positively influences demonstrations of solidarity. Furthermore, results suggest that event specific traits do influence demonstrations of solidarity under certain circumstances. However, more empirical research is needed to examine how individuals respond and the exact processes available to communities that would aid in their recovery from such an event.
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Date Issued
2019
Identifier
CFE0007850, ucf:52778
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0007850
An Index to Measure Efficiency of Hospital Networks for Mass Casualty Disasters
Title
An Index to Measure Efficiency of Hospital Networks for Mass Casualty Disasters.
Creator
Bull Torres, Maria, Sepulveda, Jose, Sala-Diakanda, Serge, Geiger, Christopher, Kapucu, Naim, University of Central Florida
Abstract / Description
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....
Show moreDisaster 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 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 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.
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Date Issued
2012
Identifier
CFE0004524, ucf:49290
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0004524
A FRAMEWORK FOR THE ASSESSMENT AND ANALYSIS OF MULTI-HAZARDSINDUCED RISK RESULTING FROM SPACE VEHICLES OPERATIONS
Title
A FRAMEWORK FOR THE ASSESSMENT AND ANALYSIS OF MULTI-HAZARDSINDUCED RISK RESULTING FROM SPACE VEHICLES OPERATIONS.
Creator
Sala-Diakanda, Serge, Rabelo, Luis, University of Central Florida
Abstract / Description
With the foreseeable increase in traffic frequency to and from orbit, the safe operation of current and future space vehicles at designated spaceports has become a serious concern. Due to their high explosive energy potential, operating those launch vehicles presents a real risk to: (1) the spaceport infrastructure and personnel, (2) the communities surrounding the spaceport and (3) the flying aircrafts whose routes could be relatively close to spaceport launch and reentry routes. Several...
Show moreWith the foreseeable increase in traffic frequency to and from orbit, the safe operation of current and future space vehicles at designated spaceports has become a serious concern. Due to their high explosive energy potential, operating those launch vehicles presents a real risk to: (1) the spaceport infrastructure and personnel, (2) the communities surrounding the spaceport and (3) the flying aircrafts whose routes could be relatively close to spaceport launch and reentry routes. Several computer models aimed at modeling the effects of the different hazards generated by the breakup of such vehicles (e.g., fragmentation of debris, release of toxic gases, propagation of blast waves, etc.) have been developed, and are used to assist in Go-No Go launch decisions. They can simulate a total failure scenario of the vehicle and, estimate a number of casualties to be expected as a result of such failure. However, as all of these models – which can be very elaborate and complex – consider only one specific explosion hazard in their simulations, the decision of whether or not a launch should occur is currently based on the evaluation of several estimates of an expected number of casualties. As such, current practices ignore the complex, nonlinear interactions between the different hazards as well as the interdependencies between the estimates. In this study, we developed a new framework which makes use of information fusion theory, hazards' dispersion modeling and, geographical statistical analysis and visualization capabilities of geographical information systems to assess the risk generated by the operation of space launch vehicles. A new risk metric, which effectively addresses the lack of a common risk metric with current methods, is also proposed. A case study, based on a proposed spaceport in the state of Oklahoma showed that the estimates we generate through our framework consistently outperform estimates provided by any individual hazard, or by the independent combination of those hazards. Furthermore, the study revealed that using anything else than fusion could provide seriously misleading results, with potentially catastrophic consequences.
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Date Issued
2007
Identifier
CFE0001606, ucf:47178
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0001606
THE EFFECT OF UNEMPLOYMENT ON DEMOCRATIC WARFARE
Title
THE EFFECT OF UNEMPLOYMENT ON DEMOCRATIC WARFARE.
Creator
Rakower, Andres, Vasquez, Joseph Paul, Kang, Kyungkook, University of Central Florida
Abstract / Description
This study was done to see the effects of a war on the economy and the internal politics of the United States. In selecting the engagement, we would study we agreed the Iraq War would be aided by a large amount of sampling of public opinion that was more nuanced than in previous wars. The Iraq War was a very complicated war, as it was controversial from the beginning and became a political issue while continuing to be a war fought by Americans abroad. Based on the literature, there were many...
Show moreThis study was done to see the effects of a war on the economy and the internal politics of the United States. In selecting the engagement, we would study we agreed the Iraq War would be aided by a large amount of sampling of public opinion that was more nuanced than in previous wars. The Iraq War was a very complicated war, as it was controversial from the beginning and became a political issue while continuing to be a war fought by Americans abroad. Based on the literature, there were many starting effects and assumptions that were accounted for such as the 'rally round the flag effect.' As a historical landmark, the Iraq War is important for being a significant conflict after the Vietnam War, another very controversial conflict in the eyes of the American public. The hypothesis that I presented were not supported by the data. The impact of the war on the economy was not strong enough that it would create pressure for the sort of model I created to apply. In this model the economic problems faced domestically could lead to more unemployment and therefore to higher military recruitment rates. While this was partially true in 2008, the consequence was not a significantly higher amount of people in the military. Ultimately, this project requires to be done in a more thorough setting where effects may be compared with those of other similar countries in similar scenarios.
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Date Issued
2018
Identifier
CFH2000435, ucf:45816
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFH2000435