Emergency management

This study addressed gaps in research on understanding the preparedness status of emergency management programs within Florida College System (FCS) and State University System (SUS) institutions. The quantitative assessment involved 21 institutions (51% response rate).
A survey instrument was developed from prior studies and measured programmatic factors. These questions explored the current preparedness level regarding emergency management programs within Florida’s FCS and SUS institutions, the involvement of stakeholders in these programs, the perceived preparedness to respond to various hazards, the extent of institutional investment in emergency management efforts, and the organizational frameworks characterizing the emergency management departments or units within these institutions.
Findings revealed that FCS institutions generally have needs, particularly in exercises and financial resources, suggesting foundational elements are present but highlighting opportunities to advance their preparedness. In contrast, SUS institutions report needs in planning and financial support, emphasizing the necessity of comprehensive and updated emergency strategies and plans and sufficient funding as programs advance. Both systems displayed strong leadership commitment that supported their levels of preparedness.

Natural disasters often result in large-scale power outages. Real-time tracking of the extent, distribution, and timelines of electrical service loss and recovery can play an important role in minimizing disaster impacts. Using NASA's Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB), the extent and duration of disrupted electric utility infrastructure in the Florida Panhandle following Hurricane Michael were estimated. The percent loss of electrical service was downscaled to a neighborhood level using the 2013-2017 American Community Survey (ACS) data at the block group level. Two ordinary least square models were estimated to examine the association between socioeconomic characteristics and the extent and duration of the power outages as well as recovery rates. The study found that block groups with higher percent minorities, multi-family housing units, rural areas, and a higher percentage of households receiving public assistance were experiencing slower power restoration rates than urban and more affluent neighborhoods. The findings have implications for disaster preparedness and recovery planning.

The transportation system is particularly vulnerable to disruptive events, while at the same time it is the primary sector for preparedness management and mitigation. The objective of this research is to quantify the changes in vehicle movement during non-recurrent events (Hurricane Irma 2017, Hurricane Michael 2018, and the COVID-19 pandemic in 2020) by comparing with recurrent period for different categories of vehicles, with an emphasis on freight vehicles. This research sought to identify where and when different classes of vehicles were traveling leading up to hurricane landfall and post-storm re-entry. Moreover, this study aims to understand the impact of the pandemic based on different decision made by government and how this decision was affected by the changes in the daily number of cases. The most significant findings showed that the transportation system is very exposed to disruptive events and needs considerable time to recover and adapt. In addition, it was found that freight vehicle transport experience significant changes after the evacuation and the last phases of the pandemic. The less impacted vehicles are those who belong to vehicle category 9 . This category did not have many days with significant changes. On the other hand, the most affected categories were vehicles in category 5 for evacuations and vehicles in categories 5 and 8 for the pandemic. These findings indicate the vehicle category is a parameter that should be taken into consideration in various emergency event management. The guidance of each vehicle group should have a unique design in order to increase management success by the competent authorities.

Emergency Management Information Systems (EMIS) are defined as a set of tools that aid decision-makers in risk assessment and response for significant multi-hazard threats and disasters. Over the past three decades, EMIS have grown in importance as a major component for understanding, managing, and governing transportation-related systems. To increase resilience against potential threats, the main goal of EMIS is to timely utilize spatial and network datasets about (1) locations of hazard areas (2) shelters and resources, (3) and how to respond to emergencies. The main concern about these datasets has always been the very large size, variety, and update rate required to ensure the timely delivery of useful emergency information and response for disastrous events. Another key issue is that the information should be concise and easy to understand, but at the same time very descriptive and useful in the case of emergency or disaster. Advancement in EMIS is urgently needed to develop fundamental data processing components for advanced spatial network queries that clearly and succinctly deliver critical information in emergencies. To address these challenges, we investigate Spatial Network Database Systems and study three challenging Transportation Resilience problems: producing large scale evacuation plans, identifying major traffic patterns during emergency evacuations, and identifying the highest areas in need of resources.

Northeastern and mid-Atlantic United States are understudied from the perspective of hurricane vulnerability. In an attempt to fill this gap in research, this dissertation attempted to assess the hurricane vulnerability of the northeastern and mid- Atlantic United States through the construction of a Composite Hurricane Vulnerability Index (CHVI) for 184 counties extending from Maine to Virginia. The CHVI was computed by incorporating indicators of human vulnerability and physical exposure. Human vulnerability was derived from demographic, social and economic characteristics whereas physical exposure was based on attributes of the natural and built up environments. The spatial distribution of the CHVI and its component indices were examined and analyzed to meet the research goals, which were a) to develop indices of human vulnerability, physical exposure and composite hurricane vulnerability for all counties; b) to assess vulnerability distribution in terms of population size, metropolitan status (metropolitan versus non metropolitan counties) and location (coastal versus inland counties); c) to identify the specific underlying causes of vulnerability; d) to identify the significant clusters and outliers of high vulnerability; and e) to examine overlaps between high human vulnerability and high physical exposure in the region. Results indicated high overall vulnerability for counties that were metropolitan and / or coastal. Vulnerability clusters and intersections pointed towards high vulnerability in the major cities along the northeastern megalopolis, in the Hampton Roads section of Virginia and in parts of Delmarva Peninsula. Evidence of relationship of population size, metropolitan status and location with vulnerability levels provides a new perspective to vulnerability assessment.

The trauma and devastation that resulted from Hurricane Katrina's landfall on August 29, 2005, produced a wide spread public perception of government neglect and ineptitude. Subsequently, a period of nationwide shame and concern for those most affected by the disaster elicited a wave of financial generosity from all social sectors. Yet, by late 2005 the media declared that the majority of Americans had become desensitized to the tragedy and its consequences, coining this shift in public perception as "Katrina fatigue." Thousands of volunteers contradicted this phenomenon, however, by performing service in the devastated city of New Orleans. Long-term volunteers defied "Katrina fatigue" by redirecting the trajectory of their lives so they could provide service. Conventionally accepted volunteer theory predicts that volunteers provide service and that their labor operates in conjunction with institutionally supported mechanisms of security and services.

Catastrophic event emergency planning has emerged as one of the most important operations management areas. Much of the successes of a response plan rely on the ability to maintain an operating transportation infrastructure. In recent years urban areas have become susceptible to biological terrorist attacks due to their size and demographics. To mitigate the devastating effects of an attack, a comprehensive catastrophic event response plan is devised. The characteristics of the disease (dormant periods, signs/symptoms), daily traffic operations and trip distributions, patient-choice hospital modeling and emergency center corridor optimization are all elements of an effective response plan. Simulation and optimization modeling of this plan becomes a faster-than-real-time tool in replicating urban area degradation. Therefore, allowing planners to identify "worst case scenarios" within the network and implement Dynamic Traffic Assignment (DTA) techniques and a non-linear departure time slot allocation mathematical model ensuring infected populations receive treatment and/or vaccinations efficiently.

Catastrophic events in the past revealed the need for more research in the field of emergency evacuation. During such a procedure, different problems such as congestion at the related traffic networks because of the large number of the evacuating vehicles can occur. Current best practices, in order to deal with such problems, suggest the further involvement of buses in evacuation operations. On the first part of this study after the accurate development of the related simulation model, the optimization of a selected bus system characteristics focusing on the vehicle routing parameter will follow through the development and the application of a non-linear cost minimization problem. On the second part, the potential use of the regular-everyday bus routes in a no-notice emergency evacuation in order to save time comparing to the time needed so as to assign the actual evacuation routes to the evacuation bus vehicles will be analyzed.

Disasters are unavoidable. The United States separates the phases of addressing a disaster into Response and Recovery. There are systems in place for Response; but Recovery, a fundamental process for countries to rebound from disasters, is a topic that is left aside. Recently the U.S. released a framework regarding this topic and it is the intention of this work to further explore recovery by starting a modeling process for disaster management systems by developing a Disaster Recovery Roles Pattern based on the framework and creating flowcharts using the Business Process Modeling Notation for use in future development of systems for the recovery process.

The use of wireless sensor networks for a myriad of applications is increasing. They can be used in healthcare for emergency management. In Florida, hurricanes are the main source of natural disasters. There has been a high incidence of hurricanes over the past decade. When a hurricane warning is issued it is important that people who live in potentially dangerous areas, such as along the coast, evacuate for their safety. Nursing homes and other care facilities for elderly or disabled people experience difficulty with the evacuation as their residents require additional assistance. The characteristics and challenges of a hurricane evacuation are investigated. A patient-centric hurricane evacuation management system is proposed to allow healthcare providers the ability to continuously monitor and track patients. During a hurricane there are usually scarce energy resources and a loss of basic communication services such as cellular service and Internet access. We propose the architecture of the system that allows it to operate in the absence of these services. The hardware and software architectures are also presented along with the main phases of operation. The system was then validated and the performance evaluated via simulation using the OPNET Modeler.