Disaster Relief Missions Research Articles

Experiences of Deployed Physicians in Support of Operation Allies Refuge/Operation Allies Welcome: Lessons to Inform Improvements in Training.

Stability operations, including humanitarian assistance and disaster relief missions, are key functions of U.S. Military medicine and the Military Medical Humanitarian Assistance Course (MMHAC) is a 2-day course widely used to prepare military medical personnel for such missions. It focuses on caring for those most vulnerable in the wake of disasters, particularly children. The large-scale humanitarian deployment of military medical providers in support of Operation Allies Welcome/Operation Allies Refuge (OAW/OAR) presents an opportunity to evaluate the preparedness of these providers to care for the needs of the Afghan travelers, so we explored the experiences of military medical providers deployed in support of OAW/OAR to inform improvements in the MMHAC. We conducted a qualitative study of military medical providers who were deployed in support of OAW/OAR using a series of three virtual focus groups. Focus group questions were structured around the main topics covered in the MMHAC (patient care, ethical considerations, logistical concerns, and preventive and public health) and explicitly asked about adaptive leadership challenges faced and strategies used to overcome them. We analyzed transcripts using inductive thematic analysis within a constructivist paradigm, with adaptive leadership as a sensitizing concept. The study was approved by the Institutional Review Board of Uniformed Services University. We constructed 4 themes from participant responses, each addressing challenges that medical providers faced during their mission: (1) Medical providers navigated tension between medical and public health priorities and military mission priorities; (2) Chronic and complex care needs posed unique challenges for medical personnel; (3) Challenges in patient care were compounded by logistical and system-based barriers; and (4) Cultural barriers led to ethical dilemmas that physicians felt inadequately prepared to handle, most notably with respect to gender-related concerns. Within each theme, participants described which aspects of MMHAC training were most helpful and which areas were inadequate. Physicians found the OAR/OAW mission meaningful but also identified challenges related to medical care provision, public health, logistics, and ethical dilemmas that hindered their ability to carry out their medical mission. Lessons learned from OAW/OAR highlight several areas in which the MMHAC training could be augmented and improved to further mitigate these challenges.

A System of Systems Framework for Strategic Cargo Airlift Using Agent-Based Modelling

The effective transport of cargo across the globe by aircraft, termed strategic airlift, is foundational to the success of humanitarian aid/disaster relief (HA/DR) missions and even military operations. Due to the variable extremity of these events, it is essential for aircraft and operations to be designed with a high resilience, factoring in performance in a plethora is scenarios. This work aims to provide a framework that enables the coupling of aircraft, fleet and concepts of operations (CONOPS) design to a mission effectiveness in a strategic cargo airlift. Through agent-based modelling, the complex interaction and emergent behaviors of the different systems in the dynamic airlift environment is better captured and evaluated. Unexpected events, such as cargo requirement reformulation, aircraft servicing and changing airbase accessibility, are employed to emulate the dynamic and spontaneous nature of rapid cargo airlift missions. The impact of these events is stochastically modelled, promoting an analysis of a variety of scenarios. By creating a theoretical disaster relief mission, a trade-space exploration is conducted so that aircraft designs and operational objectives can be evaluated for their mission effect. The framework demonstrates the ability to evaluate aircraft and operational performance holistically, enabling a more robust design procedure for a variety of potential design scenarios and metrics.

401 Global Neurosurgery Advances from Trenches to Bedside: Lessons from Neurosurgical Care in War, Humanitarian Assistance, and Disaster Response

INTRODUCTION: War has influenced the development of neurosurgery. Armed conflict and mass casualty events, including Humanitarian Assistance Disaster Relief (HADR) missions, require military surgeons to innovate to meet extreme demands. Neurosurgeons serving in the military have provided a pragmatic template for global neurosurgeons to emulate in humanitarian disaster responses METHODS: We performed a narrative review of the literature examining the influence of wars and mass casualty disasters on contemporary global neurosurgery practices. RESULTS: Wartime innovations that influenced global neurosurgery include the development of triage systems and modernization with airlifts, implementation of ambulance corps, early operation on cranial injuries in hospital camps near the battlefield, use of combat body armor, and the rise of damage control neurosurgery. Workforce shortages during wars and disasters have promoted task-shifting and task-sharing in low-resource settings that catalyzed the establishment of the physician associate profession in the United States (US). Neurosurgical care has been utilized by the US as a form of "soft power" during natural and humanitarian disasters. Low-and middle-income countries (LMICs) face similar challenges in developing trauma systems and obtaining advanced technology, including neurosurgical equipment like battery-powered computed tomography scanners. These challenges— ubiquitous in low-resource settings— have underpinned innovations in triage and wound care, rapid evacuation to tertiary care centers, and minimizing infection risk. CONCLUSIONS: War and mass casualty disasters have catalyzed significant advancements in neurosurgical care both in the pre-hospital and inpatient settings. Most of these innovations originated in the military with subsequent spread to the civilian sector as military neurosurgeons and civilian neurosurgeons, who are military reservists, returned from the battlefront or other low-resource locations. LMICs have, by necessity, responded to challenges arising from resource shortages by developing innovative, context-specific care paradigms and technologies.

Trusted Autonomous Operations of Distributed Satellite Systems Using Optical Sensors.

Recent developments in Distributed Satellite Systems (DSS) have undoubtedly increased mission value due to the ability to reconfigure the spacecraft cluster/formation and incrementally add new or update older satellites in the formation. These features provide inherent benefits, such as increased mission effectiveness, multi-mission capabilities, design flexibility, and so on. Trusted Autonomous Satellite Operation (TASO) are possible owing to the predictive and reactive integrity features offered by Artificial Intelligence (AI), including both on-board satellites and in the ground control segments. To effectively monitor and manage time-critical events such as disaster relief missions, the DSS must be able to reconfigure autonomously. To achieve TASO, the DSS should have reconfiguration capability within the architecture and spacecraft should communicate with each other through an Inter-Satellite Link (ISL). Recent advances in AI, sensing, and computing technologies have resulted in the development of new promising concepts for the safe and efficient operation of the DSS. The combination of these technologies enables trusted autonomy in intelligent DSS (iDSS) operations, allowing for a more responsive and resilient approach to Space Mission Management (SMM) in terms of data collection and processing, especially when using state-of-the-art optical sensors. This research looks into the potential applications of iDSS by proposing a constellation of satellites in Low Earth Orbit (LEO) for near-real-time wildfire management. For spacecraft to continuously monitor Areas of Interest (AOI) in a dynamically changing environment, satellite missions must have extensive coverage, revisit intervals, and reconfiguration capability that iDSS can offer. Our recent work demonstrated the feasibility of AI-based data processing using state-of-the-art on-board astrionics hardware accelerators. Based on these initial results, AI-based software has been successively developed for wildfire detection on-board iDSS satellites. To demonstrate the applicability of the proposed iDSS architecture, simulation case studies are performed considering different geographic locations.

A Decade of Surgery Aboard the U.S. Naval Ship COMFORT (T-AH 20).

The U.S. Naval Ship COMFORT has performed six humanitarian assistance and disaster relief mission since 2007. This paper describes the surgical volume per surgical specialty for five missions spanning 19 countries. Raw surgical case logs were analyzed for total case volume, total operating days, unanticipated return to operating room, and percentage of pediatric cases (<18 years old) for each country visited. Total surgical volume for the five missions was 5,142. The countries most frequently visited were Columbia and Haiti with seven and five visits, respectively. General surgery, ophthalmology, and plastic surgery have had consistent volume over time. Orthopedic surgery volume has steadily decreased with the exception of the 2018 mission. As volume in military treatment facilities declines, alternative sources of surgical volume for military surgeons are being examined. This paper highlights the historical volume which can inform future personnel planning requirements of U.S. Naval Ship COMFORT missions. With the exception of orthopedic surgery, surgical volume has remained consistent over the last decade. For future best practice, historical case data should be used to determine staffing needs on hospital ships and case logs and operating procedures and follow-up protocols should be standardized.

Naval humanitarian assistance and disaster relief (HA/DR) operations in the Indo-Pacific region: need for fresh thinking

ABSTRACT Natural disasters are increasing globally. Geographically, the Indo-Pacific region is the world’s most vulnerable region and navies here have been called upon frequently to provide humanitarian assistance. Thus, humanitarian assistance and disaster relief (HA/DR) missions have emerged as a key role for the regional navies. However, recent studies in disaster management indicate that disaster risk mitigation needs a greater focus on development issues and preparedness than post-disaster humanitarian response. This paper posits that navies too must expand their focus beyond HA/DR to contribute to other aspects of disaster management and promote collaboration with other stakeholders which could help overall to mitigate risks from natural disasters.

Pediatric Surgical Care During Humanitarian and Disaster Relief Missions

Pediatric Surgical Care During Humanitarian and Disaster Relief Missions

FALCON: A Networked Drone System for Sensing, Localizing, and Approaching RF Targets

We present FALCON, a novel autonomous drone network system for sensing, localizing, and approaching RF targets/sources such as smartphone devices. Potential applications of our system include disaster relief missions in which networked drones sense the Wi-Fi signal emitted from a victim’s smartphone and dynamically navigate to accurately localize and quickly approach the victim, for instance, to deliver the time-critical first-aid kits. For that we exploit Wi-Fi’s recent fine time measurement (FTM) protocol to realize the first on-drone FTM sensor network that enables accurate and dynamic ranging of targets in a mission. We propose a flight planning strategy that adapts the trajectory of the drones to concurrently favor localizing and approaching the target. Namely, our approach jointly optimizes the drones’ diversity of observations and the target approaching process, while flexibly trading off the intensities of the potentially conflicting objectives. We implement FALCON via a custom-designed multidrone platform and demonstrate up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2\times $ </tex-math></inline-formula> localization accuracy compared to a baseline flocking approach, while spending 30% less time localizing targets.

Deep learning with RGB and thermal images onboard a drone for monitoring operations

AbstractThis article describes the artificial intelligence (AI) component of a drone for monitoring and patrolling tasks associated with disaster relief missions in specific restricted disaster scenarios, as specified by the Advanced Robotics Foundation in Japan. The AI component uses deep learning models for environment recognition and object detection. For environment recognition, we use semantic segmentation, or pixel‐wise labeling, based on RGB images. Object detection is key for detecting and locating people in need. Since people are relatively small objects from the drone perspective, we use both RGB and thermal images. To train our models, we created a novel multispectral and publicly available data set of people. We used a geo‐location method to locate people on the ground. The semantic segmentation models were extensively tested using different feature extractors. We created two dedicated data sets, which we have made publicly available. Compared with the baseline model, the best‐performing model could increase the mean intersection over union (IoU) by 1.3%. Furthermore, we compared two types of person detection models. The first one is an ensemble model that combines RGB and thermal information via “late fusion”; the second one is a 4‐channel model that combines these two types of information in an “early fusion” manner. The results suggest that the 4‐channel model had a 40.6% increase of average precision for stricter IoU values (0.75) compared with the ensemble model and a 5.8% increase in the average precision compared with the thermal model. All models were deployed and tested on the NVIDIA AGX Xavier platform. To the best of our knowledge, this study was the first to use both RGB and thermal data from the perspective of a drone for monitoring tasks.

The Role of Military Diplomacy in Nepal’s Foreign Policy

Military diplomacy is the exploitation of a range of military resources, both bilaterally and multilaterally, to create favorable and cooperative ties with foreign nations in a pacific manner. Mutual security pacts, defense assistance, intelligence sharing, anti-piracy missions, joint military drills, communications assistance, disaster-relief missions, and high-level engagements between senior military hierarchies comprise military diplomacy. Military diplomacy aims to fill in the gaps, when needed, to help its parent nation respond to the challenges and complexity of disruptive, fast changing, strife-torn geopolitical circumstances while working in tandem with other state instruments. Nepal Army’s intense experiences in jungle and mountain warfare’s, tactical operations, and its redoubtable military training exercises have been employed to develop vibrant bilateral relations. The compelling military diplomacy of Nepal Army with foreign nations led to unstinting support and assistance in garnering essentials during the devastating earthquake and COVID-19 situation. Peacekeeping force should be prioritized to enhance foreign policy and seek to direct Foreign Direct Investment to Nepal. Appointment of military attaché to the nations having bilateral relations with Nepal, hosting of cultural and sports meet, high altitude training etc. would strengthen bilateral military relation along with improved foreign policies. The first part of this paper explores the role of Nepalese military diplomacy in Nepal’s foreign policy with Britain, India, China and United Nation in various time periods followed by second part focusing on SWOT analysis, possible counsels for better diplomacy and future prospects. This paper is framed with doctrinal methodology wherein primary data were collected from statues, seminar brochures, research and review papers, interview of current and ex-Nepal Army officer and Ministry of defense reports whereas secondary data sources used for the study are legal prodigals, treaties, encyclopedia, newspaper, reports, and bona fide information&#x0D; &#x0D;

The Climate Justice Implications of Co-Locating FEMA and ICE within DHS

For the past two decades, the Department of Homeland Security has housed both the Federal Emergency Management Agency (FEMA) and U.S. Immigration and Customs Enforcement (ICE). This article discusses two ways that DHS’s structure has impaired FEMA’s ability to equitably provide disaster aid: the historical refusal to guarantee undocumented people that FEMA would not share their information within DHS for removal purposes, and DHS’s reprogramming of appropriated funds from FEMA to ICE. This article frames these issues in the context of climate change, arguing for legislative solutions to ensure that ICE’s immigration enforcement functions do not overwhelm FEMA’s disaster relief mission.

On Controlling Drones for Disaster Relief

Drones or unmanned aerial vehicles (UAVs) are increasingly deployed for disaster relief, from aiding in drug or supply delivery to search and rescue victims. For a large-scale mission, the more drones are used, the more difficult they are to control and manage in a timely manner. Automated control is one of the central techniques used in knowledge-based drone management systems to enhance the quality and efficiency of the disaster relief mission. Although many drone management systems have been developed, automatic control of these systems remains a difficult problem. Many approaches have "human in the loop" that trades the degree of autonomy with the efficiency and perhaps accuracy. Our goal is not to fully automate the system but to reduce user interactions where intelligible (e.g., selecting appropriate drones/actions based on prioritized needs) by means of significant advances in control mechanisms. This paper presents a knowledge-based framework for intelligent drone management by explicitly representing control knowledge for use in selecting appropriate task-specific actions. The paper describes how control decisions are derived using domain knowledge relevant to drones and disaster relief. By employing a blackboard control architecture, our framework provides adaptability for dynamic control behaviors and flexibility to handle unanticipated situations during the drone mission activities. The paper illustrates the use of the framework on specific scenarios.

Challenges in Oncologic Preparedness: A Retrospective Review of Incident Surgical Cancers During Pacific Partnership Missions, 2008-2016.

For over 30 years, the USNS Mercy hospital ship has provided surgical care on multiple humanitarian aid and disaster relief missions. During these missions, surgical support varies according to host nation needs, and the operative treatment of cancer patients remains controversial. We report the number of incidentally discovered surgical oncologic cases treated aboard the USNS Mercy on four missions and discuss challenges regarding oncologic care on these missions. Between 2008 and 2016, operative cases and surgical pathology results from four multinational humanitarian missions were analyzed according to organ system, patient's geographic location, and diagnosis. Primary outcomes were total number and proportion of malignant cases, analyzed yearly and over all four missions. Secondary outcomes were malignant diagnoses by organ system and host nation health capacities (based on indicators from the WHO). A total of 2,767 operations were performed during 18 port visits in 8 countries in Southeast Asia. In total, 1,193 pathology specimens (surgical biopsies, fine needle aspirations, etc.) were obtained. Overall malignancy rate across all organ systems was 9%. Yearly malignancy rates ranged from 2% to 13%. The highest malignancy rates were found in thyroid (33%), breast (20%), and parotid and salivary gland cases (19%). All host nations had operational strategies for cancer in place (n = 8, 100%), but few had national infrastructures to treat noncommunicable diseases (n = 2, 25%). Despite current policies to screen out cancer patients on USNS Mercy missions, 9% of surgical biopsies were malignant. Cancer management during these missions presents a unique challenge because of limited resources for surgery, chemoradiotherapy, and follow-up care. Contingency plans must be considered to provide completion of care for these patients whose cancers are discovered incidentally. Furthermore, an understanding of host nation capabilities in relation to medical and surgical care is crucial to providing treatment in resource-limited areas.

Developing military environmental literacy in the South African Army through a dedicated military environmental management course

It is important for soldiers to be military environmentally literate to prevent unacceptable behaviour in the environment in which they conduct their missions. This is especially true during peacekeeping and disaster relief mission, but holds equally true for combat situations. Military environmental literacy is the nature and level of the attitude toward, knowledge about, and behaviour in and toward the environment in which the military operates. The construct of military environmental literacy (MEL) consists of three components, military environmental attitude (a general feeling of favour or disfavour toward the military environment, i.e. the environment in which the military operates), military environmental knowledge (the ability to identify a number of concepts and behaviour patterns related to the military environment, i.e. the environment in which the military operates), and military environmental behaviour (a demonstration of how one acts toward or in the military environment in which the military operates). The MEL of South African Army soldiers were measured in a study reported on in 2017, as well as in a test-retest survey in 2018. A specially developed valid and reliable questionnaire to test military environmental literacy was used in both surveys. This article argues that exposing soldiers to a dedicated military environmental management course can positively influence their military environmental literacy.

An Autonomous Spectrum Management Scheme for Unmanned Aerial Vehicle Networks in Disaster Relief Operations

This paper studies the problem of spectrum shortage in an unmanned aerial vehicle (UAV) network during critical missions such as wildfire monitoring, search and rescue, and disaster monitoring. Such applications involve a high demand for high-throughput data transmissions such as real-time video-, image-, and voice- streaming where the assigned spectrum to the UAV network may not be adequate to provide the desired Quality of Service (QoS). In these scenarios, the aerial network can borrow an additional spectrum from the available terrestrial networks in trade of a relaying service for them. We propose a spectrum sharing model in which the UAVs are grouped into two classes of relaying UAVs that service the spectrum owner and the sensing UAVs that perform the disaster relief mission using the obtained spectrum. The operation of the UAV network is managed by a hierarchical mechanism in which a central controller assigns the tasks of the UAVs based on their resources and determine their operation region based on the level of priority of impacted areas and then the UAVs autonomously fine-tune their position using a model-free reinforcement learning algorithm to maximize the individual throughput and prolong their lifetime. We analyze the performance and the convergence for the proposed method analytically and with extensive simulations in different scenarios.

Rationale for Military Involvement in Humanitarian Assistance and Disaster Relief.

Good relations and trust are the foundation of soft power diplomacy and are essential for the accomplishment of domestic interventions and any bilateral or multilateral endeavor. Military use for assistance and relief is not a novel concept, but it has increased since the early 1990s with many governments choosing to provide greater numbers of forces and assets to assist domestically and internationally. The increase is due to the growing lack of capacity in global humanitarian networks and increasingly inadequate resources available to undertake United Nations humanitarian assistance and disaster relief (HADR) missions. In response, the military has been more proactive in pursuing the improvement of military-to-military and military-to-civilian integration. This trend reflects a move towards more advanced and comprehensive approaches to security cooperation and requires increased support from the civilian humanitarian sector to help meet the needs of the most vulnerable. Military assistance is progressing beyond traditional methods to place a higher value on issues relating to civil cooperation, restoring public health infrastructure, protection, and human rights, all of which are ensuring a permanent diplomatic role for this soft power approach.

Patch Similarity Convolutional Neural Network for Urban Flood Extent Mapping Using Bi-Temporal Satellite Multispectral Imagery

Urban flooding is a major natural disaster that poses a serious threat to the urban environment. It is highly demanded that the flood extent can be mapped in near real-time for disaster rescue and relief missions, reconstruction efforts, and financial loss evaluation. Many efforts have been taken to identify the flooding zones with remote sensing data and image processing techniques. Unfortunately, the near real-time production of accurate flood maps over impacted urban areas has not been well investigated due to three major issues. (1) Satellite imagery with high spatial resolution over urban areas usually has nonhomogeneous background due to different types of objects such as buildings, moving vehicles, and road networks. As such, classical machine learning approaches hardly can model the spatial relationship between sample pixels in the flooding area. (2) Handcrafted features associated with the data are usually required as input for conventional flood mapping models, which may not be able to fully utilize the underlying patterns of a large number of available data. (3) High-resolution optical imagery often has varied pixel digital numbers (DNs) for the same ground objects as a result of highly inconsistent illumination conditions during a flood. Accordingly, traditional methods of flood mapping have major limitations in generalization based on testing data. To address the aforementioned issues in urban flood mapping, we developed a patch similarity convolutional neural network (PSNet) using satellite multispectral surface reflectance imagery before and after flooding with a spatial resolution of 3 meters. We used spectral reflectance instead of raw pixel DNs so that the influence of inconsistent illumination caused by varied weather conditions at the time of data collection can be greatly reduced. Such consistent spectral reflectance data also enhance the generalization capability of the proposed model. Experiments on the high resolution imagery before and after the urban flooding events (i.e., the 2017 Hurricane Harvey and the 2018 Hurricane Florence) showed that the developed PSNet can produce urban flood maps with consistently high precision, recall, F1 score, and overall accuracy compared with baseline classification models including support vector machine, decision tree, random forest, and AdaBoost, which were often poor in either precision or recall. The study paves the way to fuse bi-temporal remote sensing images for near real-time precision damage mapping associated with other types of natural hazards (e.g., wildfires and earthquakes).

Psychological Effects of Military Service: Applying Research to Civilian &amp; Academic Environments

Active duty, Reserve, and National Guard nurses participate in wartime, humanitarian, and disaster relief missions. Exposure to trauma, death, violence, threats to personal safety, and ethical dilemmas places military nurses at risk for untoward psychological effects. Compassion fatigue, burnout, and post-traumatic stress disorder (PTSD) are common despite robust efforts to better prepare nurses through realistic training and ongoing assessments of the psychological impacts of military service. Resilience and spirituality as psychological protective factors and post-traumatic growth are discussed. However, the results and implications of military nurse research maintains usefulness beyond the confines of the military context. This review of literature seeks to describe the psychological effects of military service on nurses, highlight similarities with civilian nursing practice, and explore the transferability of research findings and recommendations to civilian and academic environments. The article explores solutions, and offers implications for civilian nursing practice and civilian and academic nurse leaders.

Numerical investigation on the hydrodynamic performance of amphibious wheeled armored vehicles

ABSTRACTWheeled armored vehicles (WAVs) are designed for military applications, but they are frequently used in special disaster relief missions during floods caused by severe global climate change. To tackle threats arising from environmental change, developing WAVs with amphibious functions will inevitably become a trend in the future. The purpose of this study is to investigate the hydrodynamic performance of WAVs. An existing WAV model is adopted as a starting point, and computational fluid dynamic (CFD) techniques are used for performing analyses. This study analyzes the relationship between the configuration of a WAV and the sailing resistance. Two computation modes are associated with CFD used for flow simulation around the vehicles: the relative motion and absolute motion computation modes. The results of the simulations obtained through these two modes have been discussed and compared to develop an efficient tool for performing hydrodynamic performance analysis of amphibious wheeled armored vehicles (AWAV).

Secondary trauma and posttraumatic growth among mental health clinicians involved in disaster relief activities following the 2011 Tohoku earthquake and tsunami in Japan

ABSTRACT Following the Tohoku earthquake and tsunami disaster, 230 mental health clinicians participated in a disaster relief mission and then responded to an online survey assessing their posttraumatic growth (PTG), as well as other variables and outcomes related to their work. Findings revealed that post-mission intrusion severity significantly predicted total PTG at 2 months following the relief activities. Previous knowledge/skill was also an important variable, positively predicting CS and negatively predicting burnout. One-fifth of clinicians reported clinically significant trauma symptoms immediately following their work but few respondents reported clinically significant symptoms two months following their relief work. However, severe intrusion and avoidance symptomatology immediately following of the relief mission was associated with greater levels of compassion fatigue. The implications of this study are that adequate preparation of clinicians and social/professional support play important roles in promoting satisfaction with disaster-relief work, and training/knowledge reducing burnout reactions and promoting satisfaction with disaster-relief work. In addition, disaster-related intrusion symptoms may be part of a normative, adaptive process after disaster relief activities and can co-exist with or promote PTG.