Occupational exposure to bloodborne pathogens : precautions for emergency responders.

"OSHA 3130."

Occupational exposure to bloodborne pathogens : precautions for emergency responders.

Shipping list no.: 93-0447-P.

Slicing big data - Twitter, gambling and time sensitive information

Big Data presents many challenges related to volume, whether one is interested in studying past datasets or, even more problematically, attempting to work with live streams of data. The most obvious challenge, in a ‘noisy’ environment such as contemporary social media, is to collect the pertinent information; be that information for a specific study, tweets which can inform emergency services or other responders to an ongoing crisis, or give an advantage to those involved in prediction markets. Often, such a process is iterative, with keywords and hashtags changing with the passage of time, and both collection and analytic methodologies need to be continually adapted to respond to this changing information. While many of the data sets collected and analyzed are preformed, that is they are built around a particular keyword, hashtag, or set of authors, they still contain a large volume of information, much of which is unnecessary for the current purpose and/or potentially useful for future projects. Accordingly, this panel considers methods for separating and combining data to optimize big data research and report findings to stakeholders. The first paper considers possible coding mechanisms for incoming tweets during a crisis, taking a large stream of incoming tweets and selecting which of those need to be immediately placed in front of responders, for manual filtering and possible action. The paper suggests two solutions for this, content analysis and user profiling. In the former case, aspects of the tweet are assigned a score to assess its likely relationship to the topic at hand, and the urgency of the information, whilst the latter attempts to identify those users who are either serving as amplifiers of information or are known as an authoritative source. Through these techniques, the information contained in a large dataset could be filtered down to match the expected capacity of emergency responders, and knowledge as to the core keywords or hashtags relating to the current event is constantly refined for future data collection. The second paper is also concerned with identifying significant tweets, but in this case tweets relevant to particular prediction market; tennis betting. As increasing numbers of professional sports men and women create Twitter accounts to communicate with their fans, information is being shared regarding injuries, form and emotions which have the potential to impact on future results. As has already been demonstrated with leading US sports, such information is extremely valuable. Tennis, as with American Football (NFL) and Baseball (MLB) has paid subscription services which manually filter incoming news sources, including tweets, for information valuable to gamblers, gambling operators, and fantasy sports players. However, whilst such services are still niche operations, much of the value of information is lost by the time it reaches one of these services. The paper thus considers how information could be filtered from twitter user lists and hash tag or keyword monitoring, assessing the value of the source, information, and the prediction markets to which it may relate. The third paper examines methods for collecting Twitter data and following changes in an ongoing, dynamic social movement, such as the Occupy Wall Street movement. It involves the development of technical infrastructure to collect and make the tweets available for exploration and analysis. A strategy to respond to changes in the social movement is also required or the resulting tweets will only reflect the discussions and strategies the movement used at the time the keyword list is created — in a way, keyword creation is part strategy and part art. In this paper we describe strategies for the creation of a social media archive, specifically tweets related to the Occupy Wall Street movement, and methods for continuing to adapt data collection strategies as the movement’s presence in Twitter changes over time. We also discuss the opportunities and methods to extract data smaller slices of data from an archive of social media data to support a multitude of research projects in multiple fields of study. The common theme amongst these papers is that of constructing a data set, filtering it for a specific purpose, and then using the resulting information to aid in future data collection. The intention is that through the papers presented, and subsequent discussion, the panel will inform the wider research community not only on the objectives and limitations of data collection, live analytics, and filtering, but also on current and in-development methodologies that could be adopted by those working with such datasets, and how such approaches could be customized depending on the project stakeholders.

Animal stories : flash flood 2011

Flash flood disasters happen suddenly. The Toowoomba Lockyer Valley flash flood in January 2011 was not forecast by the Bureau of Meteorology until after it had occurred. Domestic and wild animals gave the first warning of the disaster in the days leading up to the event and large animals gave warnings on the morning of the disaster. Twenty-three people, including 5 children in the disaster zone died. More than 500 people were listed as missing. Some of those who died, perished because they stayed in the disaster zone to look after their animals while other members of their family escaped to safety. Some people who were in danger refused to be rescued because they could not take their pets with them. During a year spent recording accounts of the survivors of the disaster, animals were often mentioned by survivors. Despite the obvious perils, people risked their lives to save their animals; people saw animals try to save each other; animals rescued people; people rescued animals; animals survived where people died; animals were used to find human victims in the weeks after the disaster; and animals died. The stories of the flood present challenges for pet owners, farmers, counter disaster planners, weather forecasters and emergency responders in preparing for disasters, responding to them and recovering after them.

Heat-related morbidity in Brisbane, Australia : spatial variation and area-level predictors

Background: Extreme heat is a leading weather-related cause of illness and death in many locations across the globe, including subtropical Australia. The possibility of increasingly frequent and severe heat waves warrants continued efforts to reduce this health burden, which could be accomplished by targeting intervention measures toward the most vulnerable communities. Objectives: We sought to quantify spatial variability in heat-related morbidity in Brisbane, Australia, to highlight regions of the city with the greatest risk. We also aimed to find area-level social and environmental determinants of high risk within Brisbane. Methods: We used a series of hierarchical Bayesian models to examine city-wide and intracity associations between temperature and morbidity using a 2007–2011 time series of geographically referenced hospital admissions data. The models accounted for long-term time trends, seasonality, and day of week and holiday effects. Results: On average, a 10°C increase in daily maximum temperature during the summer was associated with a 7.2% increase in hospital admissions (95% CI: 4.7, 9.8%) on the following day. Positive statistically significant relationships between admissions and temperature were found for 16 of the city’s 158 areas; negative relationships were found for 5 areas. High-risk areas were associated with a lack of high income earners and higher population density. Conclusions: Geographically targeted public health strategies for extreme heat may be effective in Brisbane, because morbidity risk was found to be spatially variable. Emergency responders, health officials, and city planners could focus on short- and long-term intervention measures that reach communities in the city with lower incomes and higher population densities, including reduction of urban heat island effects.

Automated Detection of Concrete Columns from Visual Data

After earthquakes, licensed inspectors use the established codes to assess the impact of damage on structural elements. It always takes them days to weeks. However, emergency responders (e.g. firefighters) must act within hours of a disaster event to enter damaged structures to save lives, and therefore cannot wait till an official assessment completes. This is a risk that firefighters have to take. Although Search and Rescue Organizations offer training seminars to familiarize firefighters with structural damage assessment, its effectiveness is hard to guarantee when firefighters perform life rescue and damage assessment operations together. Also, the training is not available to every firefighter. The authors therefore proposed a novel framework that can provide firefighters with a quick but crude assessment of damaged buildings through evaluating the visible damage on their critical structural elements (i.e. concrete columns in the study). This paper presents the first step of the framework. It aims to automate the detection of concrete columns from visual data. To achieve this, the typical shape of columns (long vertical lines) is recognized using edge detection and the Hough transform. The bounding rectangle for each pair of long vertical lines is then formed. When the resulting rectangle resembles a column and the material contained in the region of two long vertical lines is recognized as concrete, the region is marked as a concrete column surface. Real video/image data are used to test the method. The preliminary results indicate that concrete columns can be detected when they are not distant and have at least one surface visible.

Cultura de segurança em proteção civil

This work aims to stress the concept of a security culture in the sense that each one of us is an emergency responder, the first one to respond, and the more prepared we are, with better training and awareness, the better we will perform, this applies even to the relationship between us and the Emergency Responders. All this will lead to a better probability of surviving an accident. If there is an accident, anywhere at any time, each one of us is alone. And the bigger the accident is the longer we stay alone. There is no firefighter, no policeman, no doctor, so it is very important to be competent, in other words, knowing how to react, wanting to react and being able to react. This is a basic requirement to understand the phenomenon, to know the consequences arising from the way we act and that we have to perform according to the situation: before, during and after it occurred. In brief, let’s not make resilience be just a word, let’s make it a concept that belongs to the higher definition of the Security Culture.

L’agent d’intervention au Centre jeunesse de Montréal – Institut universitaire : étude sur le travail d’un acteur fondamental en centre de réadaptation, mais largement méconnu

Le présent mémoire de maîtrise constitue une recherche qualitative qui porte sur le rôle des agents d’intervention œuvrant au sein des centres jeunesse, dans le processus de réadaptation des jeunes. Peu des études et chercheurs se sont consacrés au rôle des agents d’intervention. Pourtant ils travaillent quotidiennement auprès des jeunes placés en CJM-IU et collaborent avec les éducateurs. Les pages suivantes s’attardent au rôle de l’agent d’intervention ainsi qu’à la manière dont ce rôle est situé dans un contexte de centre de réadaptation comme le Centre jeunesse de Montréal – Institut universitaire (CJM-IU). Le rôle et les pratiques de l’agent d’intervention sont expliqués selon la perception des agents eux-mêmes, de jeunes et de chefs de permanence rencontrés. Ainsi, à la fin de ce mémoire de maîtrise, un portrait plus détaillé de l’agent d’intervention qui travaille auprès des adolescents de la Cité-Des-Prairies et du Mont St-Antoine est dressé. L’évolution du rôle et les pratiques du milieu sont également relatées afin de répondre aux objectifs de recherche.

First responders emergency medical care training: CIM course revision. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

An inverse method for determining source characteristics for emergency response applications

Following a malicious or accidental atmospheric release in an outdoor environment it is essential for first responders to ensure safety by identifying areas where human life may be in danger. For this to happen quickly, reliable information is needed on the source strength and location, and the type of chemical agent released. We present here an inverse modelling technique that estimates the source strength and location of such a release, together with the uncertainty in those estimates, using a limited number of measurements of concentration from a network of chemical sensors considering a single, steady, ground-level source. The technique is evaluated using data from a set of dispersion experiments conducted in a meteorological wind tunnel, where simultaneous measurements of concentration time series were obtained in the plume from a ground-level point-source emission of a passive tracer. In particular, we analyze the response to the number of sensors deployed and their arrangement, and to sampling and model errors. We find that the inverse algorithm can generate acceptable estimates of the source characteristics with as few as four sensors, providing these are well-placed and that the sampling error is controlled. Configurations with at least three sensors in a profile across the plume were found to be superior to other arrangements examined. Analysis of the influence of sampling error due to the use of short averaging times showed that the uncertainty in the source estimates grew as the sampling time decreased. This demonstrated that averaging times greater than about 5min (full scale time) lead to acceptable accuracy.

Emergency response to railroad accidents involving hazardous materials

The chemical industry has to face safety problems linked to the hazards of chemicals and the risks posed by the plants where they are handled. However, their transport may cause significant risk values too: it’s not totally possible to avoid the occurrence of accidents. This work is focused on the emergency response to railway accidents involving hazardous materials, that is what has to be done once they happen to limit their consequences. A first effort has been devoted to understand the role given to this theme within legislations: it has been found out that often it’s not even taken into account. Exceptionally a few countries adopt guidelines suggesting how to plan the response, who is appointed to intervene and which actions should be taken first. An investigation has been made to define the tools available for the responders, with attention on the availability of chemical-specific safety distances. It has emerged that the ERG book adopted by some American countries has suggestions and the Belgian legislation too establishes criteria to evaluate these distances. An analysis has been conducted then on the most recent accidents occurred worldwide, to understand how the response was performed and which safety distances were adopted. These values were compared with the numbers reported by the ERG book and the results of two devoted software tools for consequence analysis of accidental spills scenarios. This comparison has shown that there are differences between them and that a more standardized approach is necessary. This is why further developments of the topic should focus on promoting uniform procedures for emergency response planning and on a worldwide adoption of a guidebook with suggestions about actions to reduce consequences and about safety distances, determined following finer researches. For this aim, the development of a detailed database of hazardous materials transportation accidents could be useful.

Factors determining the use of universal precautions by emergency department nurses

The Health Belief Model (HBM) provided the theoretical framework for examining Universal Precautions (UP) compliance factors by Emergency Department nurses. A random sample of Emergency Nurses Association (ENA) clinical nurses (n = 900) from five states (New York, New Jersey, California, Texas, and Florida), were surveyed to explore the factors related to their decision to comply with UP. Five-hundred-ninety-eight (598) useable questionnaires were analyzed. The responders were primarily female (84.9%), hospital based (94.6%), staff nurses (66.6%) who had a mean 8.5 years of emergency nursing experience. The nurses represented all levels of hospitals from rural (4.5%) to urban trauma centers (23.7%). The mean UP training hours was 3.0 (range 0-38 hours). Linear regression was used to analyze the four hypotheses. The first hypothesis evaluating perceived susceptibility and seriousness with reported UP use was not significant (p = $>$.05). Hypothesis 2 tested perceived benefits with internal and external barriers. Both perceived benefits and internal barriers as well as the overall regression were significant (F = 26.03, p = $<$0.001). Hypothesis 3 which tested modifying factors, cues to action, select demographic variables, and the main effects of the HBM with self reported UP compliance, was also significant (F = 12.39, p = $<$0.001). The additive effects were tested by use of a stepwise regression that assessed the contribution of each of the significant variables. The regression was significant (F = 12.39, p = $<$0.001) and explained 18% of the total variance. In descending order of contribution, the significant variables related to compliance were: internal barriers (t = $-$6.267; p = $<$0.001) such as the perception that because of the nature of the emergency care environment there is sometimes inadequate time to put on UP; cues to action (t = 3.195; p = 0.001) such as posted reminder signs or verbal reminders from peers; the number of Universal Precautions training hours (t = 3.667; p = $<$0.001) meaning that as the number of training hours increase so does compliance; perceived benefits (t = 3.466; p = 0.001) such as believing that UP will provide adequate barrier protection; and perceived susceptibility (t = 2.880; p = 0.004) such as feeling that they are at risk of exposure. ^