Planning volunteer responses to low-volume mass gatherings: do event characteristics predict patient workload?

INTRODUCTION: Workforce planning for first aid and medical coverage of mass gatherings is hampered by limited research. In particular, the characteristics and likely presentation patterns of low-volume mass gatherings of between several hundred to several thousand people are poorly described in the existing literature. OBJECTIVES: This study was conducted to: 1. Describe key patient and event characteristics of medical presentations at a series of mass gatherings, including events smaller than those previously described in the literature; 2. Determine whether event type and event size affect the mean number of patients presenting for treatment per event, and specifically, whether the 1:2,000 deployment rule used by St John Ambulance Australia is appropriate; and 3. Identify factors that are predictive of injury at mass gatherings. METHODS: A retrospective, observational, case-series design was used to examine all cases treated by two Divisions of St John Ambulance (Queensland) in the greater metropolitan Brisbane region over a three-year period (01 January 2002-31 December 2004). Data were obtained from routinely collected patient treatment forms completed by St John officers at the time of treatment. Event-related data (e.g., weather, event size) were obtained from event forms designed for this study. Outcome measures include: total and average number of patient presentations for each event; event type; and event size category. Descriptive analyses were conducted using chi-square tests, and mean presentations per event and event type were investigated using Kruskal-Wallis tests. Logistic regression analyses were used to identify variables independently associated with injury presentation (compared with non-injury presentations). RESULTS: Over the three-year study period, St John Ambulance officers treated 705 patients over 156 separate events. The mean number of patients who presented with any medical condition at small events (less than or equal to 2,000 attendees) did not differ significantly from that of large (>2,000 attendees) events (4.44 vs. 4.67, F = 0.72, df = 1, 154, p = 0.79). Logistic regression analyses indicated that presentation with an injury compared with non-injury was independently associated with male gender, winter season, and sporting events, even after adjusting for relevant variables. CONCLUSIONS: In this study of low-volume mass gatherings, a similar number of patients sought medical treatment at small (<2,000 patrons) and large (>2,000 patrons) events. This demonstrates that for low-volume mass gatherings, planning based solely on anticipated event size may be flawed, and could lead to inappropriate levels of first-aid coverage. This study also highlights the importance of considering other factors, such as event type and patient characteristics, when determining appropriate first-aid resourcing for low-volume events. Additionally, identification of factors predictive of injury presentations at mass gatherings has the potential to significantly enhance the ability of event coordinators to plan effective prevention strategies and response capability for these events.

Event-related brain potentials dissociate the developmental time-course of automatic numerical magnitude analysis and cognitive control functions during the first three years of primary school

In this study we set out to dissociate the developmental time course of automatic symbolic number processing and cognitive control functions in grade 1-3 British primary school children. Event-related potential (ERP) and behavioral data were collected in a physical size discrimination numerical Stroop task. Task-irrelevant numerical information was processed automatically already in grade 1. Weakening interference and strengthening facilitation indicated the parallel development of general cognitive control and automatic number processing. Relationships among ERP and behavioral effects suggest that control functions play a larger role in younger children and that automaticity of number processing increases from grade 1 to 3.

Application of Geographic Modeling Techniques to Quantify Spatial Access to Health Services Before and After an Acute Cardiac Event: The Cardiac ARIA Project

Background: Access to cardiac services is essential for appropriate implementation of evidence-based therapies to improve outcomes. The Cardiac Accessibility and Remoteness Index for Australia (Cardiac ARIA) aimed to derive an objective, geographic measure reflecting access to cardiac services. Methods: An expert panel defined an evidence-based clinical pathway. Using Geographic Information Systems (GIS), a numeric/alpha index was developed at two points along the continuum of care. The acute category (numeric) measured the time from the emergency call to arrival at an appropriate medical facility via road ambulance. The aftercare category (alpha) measured access to four basic services (family doctor, pharmacy, cardiac rehabilitation, and pathology services) when a patient returned to their community. Results: The numeric index ranged from 1 (access to principle referral center with cardiac catheterization service ≤ 1 hour) to 8 (no ambulance service, > 3 hours to medical facility, air transport required). The alphabetic index ranged from A (all 4 services available within 1 hour drive-time) to E (no services available within 1 hour). 13.9 million (71%) Australians resided within Cardiac ARIA 1A locations (hospital with cardiac catheterization laboratory and all aftercare within 1 hour). Those outside Cardiac 1A were over-represented by people aged over 65 years (32%) and Indigenous people (60%). Conclusion: The Cardiac ARIA index demonstrated substantial inequity in access to cardiac services in Australia. This methodology can be used to inform cardiology health service planning and the methodology could be applied to other common disease states within other regions of the world.

Mapping Services to Support a Patient's Journey through Evidence-Based Care Pathways After a Cardiac Event

Background: There are inequalities in geographical access and delivery of health care services in Australia, particularly for cardiovascular disease (CVD), Australia's major cause of death. Analyses and models that can inform and positively influence strategies to augment services and preventative measures are needed. The Cardiac-ARIA project is using geographical spatial technology (GIS) to develop a national index for each of Australia's 13,000 population centres. The index will describe the spatial distribution of CVD health care services available to support populations at risk, in a timely manner, after a major cardiac event. Methods: In the initial phase of the project, an expert panel of cardiologists and an emergency physician have identified key elements of national and international guidelines for management of acute coronary syndromes, cardiac arrest, life-threatening arrhythmias and acute heart failure, from the time of onset (potentially dial 000) to return from the hospital to the community (cardiac rehabilitation). Results: A systematic search has been undertaken to identify the geographical location of, and type of, cardiac services currently available. This has enabled derivation of a master dataset of necessary services, e.g. telephone networks, ambulance, RFDS, helicopter retrieval services, road networks, hospitals, general practitioners, medical community centres, pathology services, CCUs, catheterisation laboratories, cardio-thoracic surgery units and cardiac rehabilitation services. Conclusion: This unique and innovative project has the potential to deliver a powerful tool to both highlight and combat the burden of disease of CVD in urban and regional Australia.

Reconstructing the event stratigraphy from the complex structural - stratigraphic architecture of an Archaean volcanic – intrusive – sedimentary succession : the Boorara Domain, Eastern Goldfields Superterrane, Western Australia

Two main deformational phases are recognised in the Archaean Boorara Domain of the Kalgoorlie Terrane, Eastern Goldfields Superterrane, Yilgarn Craton, Western Australia, primarily involving southover- north thrust faulting that repeated and thickened the stratigraphy, followed by east northeast – west-southwest shortening that resulted in macroscale folding of the greenstone lithologies. The domain preserves mid-greenschist facies metamorphic grade, with an increase to lower amphibolite metamorphic grade towards the north of the region. As a result of the deformation and metamorphism, individual stratigraphic horizons are difficult to trace continuously throughout the entire domain. Volcanological and sedimentological textures and structures, primary lithological contacts, petrography and geochemistry have been used to correlate lithofacies between faultbounded structural blocks. The correlated stratigraphic sequence for the Boorara Domain comprises quartzo-feldspathic turbidite packages, overlain by high-Mg tholeiitic basalt (lower basalt), coherent and clastic dacite facies, intrusive and extrusive komatiite units, an overlying komatiitic basalt unit (upper basalt), and at the stratigraphic top of the sequence, volcaniclastic quartz-rich turbidites. Reconstruction of the stratigraphy and consideration of emplacement dynamics has allowed reconstruction of the emplacement history and setting of the preserved sequence. This involves a felsic, mafic and ultramafic magmatic system emplaced as high-level intrusions, with localised emergent volcanic centres, into a submarine basin in which active sedimentation was occurring.

Predicting deadline tansgressions using event logs

Effective risk management is crucial for any organisation. One of its key steps is risk identification, but few tools exist to support this process. Here we present a method for the automatic discovery of a particular type of process-related risk, the danger of deadline transgressions or overruns, based on the analysis of event logs. We define a set of time-related process risk indicators, i.e., patterns observable in event logs that highlight the likelihood of an overrun, and then show how instances of these patterns can be identified automatically using statistical principles. To demonstrate its feasibility, the approach has been implemented as a plug-in module to the process mining framework ProM and tested using an event log from a Dutch financial institution.

Suspended sediment properties and suspended sediment flux estimates in an inundated urban environment during a major flood event

During a major flood event, the inundation of urban environments leads to some complicated flow motion most often associated with significant sediment fluxes. In the present study, a series of field measurements were conducted in an inundated section of the City of Brisbane (Australia) about the peak of a major flood in January 2011. Some experiments were performed to use ADV backscatter amplitude as a surrogate estimate of the suspended sediment concentration (SSC) during the flood event. The flood water deposit samples were predominantly silty material with a median particle size about 25 μm and they exhibited a non-Newtonian behavior under rheological testing. In the inundated urban environment during the flood, estimates of suspended sediment concentration presented a general trend with increasing SSC for decreasing water depth. The suspended sediment flux data showed some substantial sediment flux amplitudes consistent with the murky appearance of floodwaters. Altogether the results highlighted the large suspended sediment loads and fluctuations in the inundated urban setting associated possibly with a non-Newtonian behavior. During the receding flood, some unusual long-period oscillations were observed (periods about 18 min), although the cause of these oscillations remains unknown. The field deployment was conducted in challenging conditions highlighting a number of practical issues during a natural disaster.

Using information communication technologies to develop dynamic curriculum frameworks for diverse cohorts: a case study from event management

This article investigates the role of information communication technologies (ICTs) in establishing a well-aligned, authentic learning environment for a diverse cohort of non-cognate and cognate students studying event management in a higher education context. Based on a case study which examined the way ICTs assisted in accommodating diverse learning needs, styles and stages in an event management subject offered in the Creative Industries Faculty at Queensland University of Technology in Brisbane, Australia, the article uses an action research approach to generate grounded, empirical data on the effectiveness of the dynamic, individualised curriculum frameworks that the use of ICTs makes possible. The study provides insights into the way non-cognate and cognate students respond to different learning tools. It finds that whilst non-cognate and cognate students do respond to learning tools differently, due to a differing degree of emphasis on technical, task or theoretical competencies, the use of ICTs allows all students to improve their performance by providing multiple points of entry into the content. In this respect, whilst the article focuses on the way ICTs can be used to develop an authentic, well-aligned curriculum model that meets the needs of event management students in a higher education context, with findings relevant for event educators in Business, Hospitality, Tourism and Creative Industries, the strategies outlined may also be useful for educators in other fields who are faced with similar challenges when designing and developing curriculum for diverse cohorts.

Reconceptualising mega project success in Australian Defence : recognising the importance of value co-creation

Recent literature in project management has urged a re-conceptualisation of projects as a value co-creation process. Contrary to the traditional output-focused project methodology, the value creation perspective argues for the importance of creating new knowledge, processes, and systems for suppliers and customers. Stakeholder involvement is important in this new perspective, as the balancing of competing needs of stakeholders in mega projects becomes a major challenge in managing the value co-creation process. In this study we present interview data from three Australian defence mega projects to demonstrate that senior executives have a more complex understanding of project success than traditional iron triangle measures. In these mega defence projects, customers and other stakeholders actively engage in the value creation process, and over time both content and process value are created to increase defence and national capability. Value created and captured during and post projects are the key to true success.

Anomalous event detection using a semi-two dimensional hidden Markov model

The rapid increase in the deployment of CCTV systems has led to a greater demand for algorithms that are able to process incoming video feeds. These algorithms are designed to extract information of interest for human operators. During the past several years, there has been a large effort to detect abnormal activities through computer vision techniques. Typically, the problem is formulated as a novelty detection task where the system is trained on normal data and is required to detect events which do not fit the learned `normal' model. Many researchers have tried various sets of features to train different learning models to detect abnormal behaviour in video footage. In this work we propose using a Semi-2D Hidden Markov Model (HMM) to model the normal activities of people. The outliers of the model with insufficient likelihood are identified as abnormal activities. Our Semi-2D HMM is designed to model both the temporal and spatial causalities of the crowd behaviour by assuming the current state of the Hidden Markov Model depends not only on the previous state in the temporal direction, but also on the previous states of the adjacent spatial locations. Two different HMMs are trained to model both the vertical and horizontal spatial causal information. Location features, flow features and optical flow textures are used as the features for the model. The proposed approach is evaluated using the publicly available UCSD datasets and we demonstrate improved performance compared to other state of the art methods.

A Comprehensive Benchmarking Framework (CoBeFra) for conformance analysis between procedural process models and event logs in ProM

Process mining encompasses the research area which is concerned with knowledge discovery from information system event logs. Within the process mining research area, two prominent tasks can be discerned. First of all, process discovery deals with the automatic construction of a process model out of an event log. Secondly, conformance checking focuses on the assessment of the quality of a discovered or designed process model in respect to the actual behavior as captured in event logs. Hereto, multiple techniques and metrics have been developed and described in the literature. However, the process mining domain still lacks a comprehensive framework for assessing the goodness of a process model from a quantitative perspective. In this study, we describe the architecture of an extensible framework within ProM, allowing for the consistent, comparative and repeatable calculation of conformance metrics. For the development and assessment of both process discovery as well as conformance techniques, such a framework is considered greatly valuable.

How activation, entanglement, and searching a semantic network contribute to event memory

Free association norms indicate that words are organized into semantic/associative neighborhoods within a larger network of words and links that bind the net together. We present evidence indicating that memory for a recent word event can depend on implicitly and simultaneously activating related words in its neighborhood. Processing a word during encoding primes its network representation as a function of the density of the links in its neighborhood. Such priming increases recall and recognition and can have long lasting effects when the word is processed in working memory. Evidence for this phenomenon is reviewed in extralist cuing, primed free association, intralist cuing, and single-item recognition tasks. The findings also show that when a related word is presented to cue the recall of a studied word, the cue activates it in an array of related words that distract and reduce the probability of its selection. The activation of the semantic network produces priming benefits during encoding and search costs during retrieval. In extralist cuing recall is a negative function of cue-to-distracter strength and a positive function of neighborhood density, cue-to-target strength, and target-to cue strength. We show how four measures derived from the network can be combined and used to predict memory performance. These measures play different roles in different tasks indicating that the contribution of the semantic network varies with the context provided by the task. We evaluate spreading activation and quantum-like entanglement explanations for the priming effect produced by neighborhood density.

SAIVT-QUT@TRECVid 2012 : interactive surveillance event detection

In this paper, we propose an approach which attempts to solve the problem of surveillance event detection, assuming that we know the definition of the events. To facilitate the discussion, we first define two concepts. The event of interest refers to the event that the user requests the system to detect; and the background activities are any other events in the video corpus. This is an unsolved problem due to many factors as listed below: 1) Occlusions and clustering: The surveillance scenes which are of significant interest at locations such as airports, railway stations, shopping centers are often crowded, where occlusions and clustering of people are frequently encountered. This significantly affects the feature extraction step, and for instance, trajectories generated by object tracking algorithms are usually not robust under such a situation. 2) The requirement for real time detection: The system should process the video fast enough in both of the feature extraction and the detection step to facilitate real time operation. 3) Massive size of the training data set: Suppose there is an event that lasts for 1 minute in a video with a frame rate of 25fps, the number of frames for this events is 60X25 = 1500. If we want to have a training data set with many positive instances of the event, the video is likely to be very large in size (i.e. hundreds of thousands of frames or more). How to handle such a large data set is a problem frequently encountered in this application. 4) Difficulty in separating the event of interest from background activities: The events of interest often co-exist with a set of background activities. Temporal groundtruth typically very ambiguous, as it does not distinguish the event of interest from a wide range of co-existing background activities. However, it is not practical to annotate the locations of the events in large amounts of video data. This problem becomes more serious in the detection of multi-agent interactions, since the location of these events can often not be constrained to within a bounding box. 5) Challenges in determining the temporal boundaries of the events: An event can occur at any arbitrary time with an arbitrary duration. The temporal segmentation of events is difficult and ambiguous, and also affected by other factors such as occlusions.