935 resultados para injury data surveillance


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Objective: Childhood injury remains the single most important cause of mortality in children aged between 1-14 years in many countries. It has been proposed that lower socio-economic status (SES) and poorer housing contribute to potential hazards in the home environment. This study sought to establish whether the prevalence of observed hazards in and around the home was differentially distributed by SES, in order to identify opportunities for injury prevention. Methods: This study was a cross-sectional, random sample survey of primary school children from 32 schools in Brisbane. Interviews and house audits were conducted between July 2000 and April 2003 to collect information on SES (income, employment and education) and previously identified household hazards. Results: There was evidence of a relationship between prevalence of household environmental hazards and household SES; however, the magnitude and direction of this relationship appeared to be hazard-specific. Household income was related to play equipment characteristics, with higher SES groups being more likely to be exposed to risk. All three SES indicators were associated with differences in the home safety characteristics, with the lower SES groups more likely to be exposed to risk. Conclusion:The differential distribution of environmental risk factors by SES of household may help explain the SES differential in the burden of injury and provides opportunities for focusing efforts to address the problem.

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Background and purpose Survey data quality is a combination of the representativeness of the sample, the accuracy and precision of measurements, data processing and management with several subcomponents in each. The purpose of this paper is to show how, in the final risk factor surveys of the WHO MONICA Project, information on data quality were obtained, quantified, and used in the analysis. Methods and results In the WHO MONICA (Multinational MONItoring of trends and determinants in CArdiovascular disease) Project, the information about the data quality components was documented in retrospective quality assessment reports. On the basis of the documented information and the survey data, the quality of each data component was assessed and summarized using quality scores. The quality scores were used in sensitivity testing of the results both by excluding populations with low quality scores and by weighting the data by its quality scores. Conclusions Detailed documentation of all survey procedures with standardized protocols, training, and quality control are steps towards optimizing data quality. Quantifying data quality is a further step. Methods used in the WHO MONICA Project could be adopted to improve quality in other health surveys.

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Background: Children engage in various physical activities that pose different injury risks. However, the lack of adequate data on exposure has meant that these risks have not been quantified or compared in young children aged 5-12 years. Objectives: To measure exposure to popular activities among Australian primary school children and to quantify the associated injury risks. Method: The Childhood Injury Prevention Study prospectively followed up a cohort of randomly selected Australian primary and preschool children aged 5-12 years. Time (min) engaged in various physical activities was measured using a parent-completed 7-day diary. All injuries over 12 months were reported to the study. All data on exposure and injuries were coded using the International classification of external causes of injury. Injury rates per 1000 h of exposure were calculated for the most popular activities. Results: Complete diaries and data on injuries were available for 744 children. Over 12 months, 314 injuries relating to physical activity outside of school were reported. The highest injury risks per exposure time occurred for tackle-style football (2.18/1000 h), wheeled activities (1.72/1000 h) and tennis (1.19/1000 h). Overall, boys were injured more often than girls; however, the differences were non-significant or reversed for some activities including soccer, trampolining and team ball sports. Conclusion: Although the overall injury rate was low in this prospective cohort, the safety of some popular childhood activities can be improved so that the benefits may be enjoyed with fewer negative consequences.

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This is the third article of a series entitled Astronauts as Audiences. In this article, we investigate the roles that situation awareness (SA), communications, and reality TV (including media communications) might have on the lives of astronauts in remote space communities. We examined primary data about astronauts’ living and working environments, applicable theories of SA, communications, and reality TV (including media communications). We then surmised that the collective application of these roles might be a means of enhancing the lives of astronauts in remote space communities.

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Analyzing geographical patterns by collocating events, objects or their attributes has a long history in surveillance and monitoring, and is particularly applied in environmental contexts, such as ecology or epidemiology. The identification of patterns or structures at some scales can be addressed using spatial statistics, particularly marked point processes methodologies. Classification and regression trees are also related to this goal of finding "patterns" by deducing the hierarchy of influence of variables on a dependent outcome. Such variable selection methods have been applied to spatial data, but, often without explicitly acknowledging the spatial dependence. Many methods routinely used in exploratory point pattern analysis are2nd-order statistics, used in a univariate context, though there is also a wide literature on modelling methods for multivariate point pattern processes. This paper proposes an exploratory approach for multivariate spatial data using higher-order statistics built from co-occurrences of events or marks given by the point processes. A spatial entropy measure, derived from these multinomial distributions of co-occurrences at a given order, constitutes the basis of the proposed exploratory methods. © 2010 Elsevier Ltd.

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Analyzing geographical patterns by collocating events, objects or their attributes has a long history in surveillance and monitoring, and is particularly applied in environmental contexts, such as ecology or epidemiology. The identification of patterns or structures at some scales can be addressed using spatial statistics, particularly marked point processes methodologies. Classification and regression trees are also related to this goal of finding "patterns" by deducing the hierarchy of influence of variables on a dependent outcome. Such variable selection methods have been applied to spatial data, but, often without explicitly acknowledging the spatial dependence. Many methods routinely used in exploratory point pattern analysis are2nd-order statistics, used in a univariate context, though there is also a wide literature on modelling methods for multivariate point pattern processes. This paper proposes an exploratory approach for multivariate spatial data using higher-order statistics built from co-occurrences of events or marks given by the point processes. A spatial entropy measure, derived from these multinomial distributions of co-occurrences at a given order, constitutes the basis of the proposed exploratory methods. © 2010 Elsevier Ltd.

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The broad objectives of the work were to develop standard methods for the routine biological surveillance of river water quality, using the non-planktonic algae. Studies on sampling methodology indicated that natural substrata should be sampled directly wherever possible, but for routine purposes, only a semi-quantitative approach was found to be feasible. Artificial substrata were considered to be useful for sample collection in deeper waters, and of three different types tested, Polythene strips were selected for further investigation essentially on grounds of practicality. These were tested in the deeper reaches of a wide range of river types and water qualities: 26 pool sites in 14 different rivers were studied over a period of 9 months. At each site, the assemblages developing on 3 strips following a 4, or less commonly, an 3 week immersion period were analysed quantitatively. Where possible, the natural substrata were also sampled semi-quantitatively at each site, and at a nearby riffle. The results of this survey were very fragmentary: many strips failed to yield useful data, and the results were often difficult to interpret, and of limited value for water quality surveillance purposes. In one river, the Churnet, the natural substrata at 14 riffle sites were sampled semi-quantitatively on 14 occasions at intervals of 4 weeks. In this survey, the results were more readily interpreted in relation to water quality, and no special data processing was found to be necessary or helpful. Further studies carried out on the filamentous green alga Cladophora showed that this alga may have some value as a bioaccumulation indicator for metals, and as a bioassay organism for the assessment of the algal growth promoting potential of natural river waters.

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Some of the factors affecting colonisation of a colonisation sampler, the Standard Aufwuchs Unit (S. Auf. U.) were investigated, namely immersion period, whether anchored on the bottom or suspended, and the influence of riffles. It was concluded that a four-week immersion period was best. S. Auf. U. anchored on the bottom collected both more taxa and individuals than suspended ones. Fewer taxa but more individuals colonised S. Auf. U. in the potamon zone compared to the rhithron zone with a consequent reduction in the values of pollution indexes and diversity. It was concluded that a completely different scoring system was necessary for lowland rivers. Macroinvertebrates colonising S. Auf. U. in simulated streams, lowland rivers and the R. Churnet reflected water quality. A variety of pollution and diversity indexes were applied to results from lowland river sites. Instead of these, it was recommended that an abbreviated species - relative abundance list be used to summarise biological data for use in lowland river surveillance. An intensive study of gastropod populations was made in simulated streams. Lynnaea peregra increased in abundance whereas Potamopyrgas jenkinsi decreased with increasing sewage effluent concentration. No clear-cut differences in reproduction were observed. The presence/absence of eight gastropod taxa was compared with concentrations of various pollutants in lowland rivers. On the basis of all field work it appeared that ammonia, nitrite, copper and zinc were the toxicants most likely to be detrimental to gastropods and that P. jenkinsi and Theodoxus fluviatilis were the least tolerant taxa. 96h acute toxicity tests of P. jenkinsi using ammonia and copper were carried out in a flow-through system after a variety of static range finding tests. P. jenkinsi was intolerant to both toxicants compared to reports on other taxa and the results suggested that these toxicants would affect distribution of this species in the field.

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In recent years, we have witnessed the mushrooming of pro- democracy and protest movements not only in the Arab world, but also within Europe and the Americas. Such movements have ranged from popular upheavals, like in Tunisia and Egypt, to the organization of large- scale demonstrations against unpopular policies, as in Spain, Greece and Poland. What connects these different events are not only their democratic aspirations, but also their innovative forms of communication and organization through online means, which are sometimes considered to be outside of the State’s control. At the same time, however, it has become more and more apparent that countries are attempting to increase their understanding of, and control over, their citizens’ actions in the digital sphere. This involves striving to develop surveillance instruments, control mechanisms and processes engineered to dominate the digital public sphere, which necessitates the assistance and support of private actors such as Internet intermediaries. Examples include the growing use of Internet surveillance technology with which online data traffic is analysed, and the extensive monitoring of social networks. Despite increased media attention, academic debate on the ambivalence of these technologies, mechanisms and techniques remains relatively limited, as is discussion of the involvement of corporate actors. The purpose of this edited volume is to reflect on how Internet-related technologies, mechanisms and techniques may be used as a means to enable expression, but also to restrict speech, manipulate public debate and govern global populaces.

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Lifelong surveillance is not cost-effective after endovascular aneurysm repair (EVAR), but is required to detect aortic complications which are fatal if untreated (type 1/3 endoleak, sac expansion, device migration). Aneurysm morphology determines the probability of aortic complications and therefore the need for surveillance, but existing analyses have proven incapable of identifying patients at sufficiently low risk to justify abandoning surveillance. This study aimed to improve the prediction of aortic complications, through the application of machine-learning techniques. Patients undergoing EVAR at 2 centres were studied from 2004–2010. Aneurysm morphology had previously been studied to derive the SGVI Score for predicting aortic complications. Bayesian Neural Networks were designed using the same data, to dichotomise patients into groups at low- or high-risk of aortic complications. Network training was performed only on patients treated at centre 1. External validation was performed by assessing network performance independently of network training, on patients treated at centre 2. Discrimination was assessed by Kaplan-Meier analysis to compare aortic complications in predicted low-risk versus predicted high-risk patients. 761 patients aged 75 +/− 7 years underwent EVAR in 2 centres. Mean follow-up was 36+/− 20 months. Neural networks were created incorporating neck angu- lation/length/diameter/volume; AAA diameter/area/volume/length/tortuosity; and common iliac tortuosity/diameter. A 19-feature network predicted aor- tic complications with excellent discrimination and external validation (5-year freedom from aortic complications in predicted low-risk vs predicted high-risk patients: 97.9% vs. 63%; p < 0.0001). A Bayesian Neural-Network algorithm can identify patients in whom it may be safe to abandon surveillance after EVAR. This proposal requires prospective study.

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The rate of fatal crashes in Florida has remained significantly higher than the national average for the last several years. The 2003 statistics from the National Highway Traffic Safety Administration (NHTSA), the latest available, show a fatality rate in Florida of 1.71 per 100 million vehicle-miles traveled compared to the national average of 1.48 per 100 million vehicle-miles traveled. The objective of this research is to better understand the driver, environmental, and roadway factors that affect the probability of injury severity in Florida. ^ In this research, the ordered logit model was used to develop six injury severity models; single-vehicle and two-vehicle crashes on urban freeways and urban principal arterials and two-vehicle crashes at urban signalized and unsignalized intersections. The data used in this research included all crashes that occurred on the state highway system for the period from 2001 to 2003 in the Southeast Florida region, which includes the Miami-Dade, Broward and Palm Beach Counties.^ The results of the analysis indicate that the age group and gender of the driver at fault were significant factors of injury severity risk across all models. The greatest risk of severe injury was observed for the age groups 55 to 65 and 66 and older. A positive association between injury severity and the race of the driver at fault was also found. Driver at fault of Hispanic origin was associated with a higher risk of severe injury for both freeway models and for the two-vehicle crash model on arterial roads. A higher risk of more severe injury crash involvement was also found when an African-American was the at fault driver on two-vehicle crashes on freeways. In addition, the arterial class was also found to be positively associated with a higher risk of severe crashes. Six-lane divided arterials exhibited the highest injury severity risk of all arterial classes. The lowest severe injury risk was found for one way roads. Alcohol involvement by the driver at fault was also found to be a significant risk of severe injury for the single-vehicle crash model on freeways. ^

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In the current study, we examined how supraspinal and spinal excitability were altered bilaterally after unilateral anterior cruciate ligament reconstruction (ACLr). 7 participants with ACLr and 7 healthy controls underwent transcranial magnetic stimulation (TMS) and electrical stimulation. To evaluate supraspinal excitability, resting motor thresholds (RMT) and motor evoked potential (MEP) stimulus response curves (SRC) were used. To measure spinal excitability, H-reflex SRC gain was assessed. Mixed factorial ANOVAs were used to compare measures between limbs and between groups. Cohen’s d was used to assess effect sizes between groups. Data indicated no significant differences between subject groups or between limbs. However, large effect sizes were found between limbs for H-reflex gain and RMTs suggesting that ACLr can have an effect on some of the variables examined. This study identified decreases in strength in the injured limbs and that subjects with an ACL injury exhibited decreases in spinal and supraspinal excitability of the quadriceps compared to Healthy controls.

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We would like to thank the study participants and the clinical and research staff at the Queen Elizabeth National Spinal Injury Unit, as without them this study would not have been possible. We are grateful for the funding received from Glasgow Research Partnership in Engineering for the employment of SC during data collection for this study. We would like to thank the Royal Society of Edinburgh's Scottish Crucible scheme for providing the opportunity for this collaboration to occur. We are also indebted to Maria Dumitrascuta for her time and effort in producing inter-repeatability results for the shape models.

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We would like to thank the study participants and the clinical and research staff at the Queen Elizabeth National Spinal Injury Unit, as without them this study would not have been possible. We are grateful for the funding received from Glasgow Research Partnership in Engineering for the employment of SC during data collection for this study. We would like to thank the Royal Society of Edinburgh's Scottish Crucible scheme for providing the opportunity for this collaboration to occur. We are also indebted to Maria Dumitrascuta for her time and effort in producing inter-repeatability results for the shape models.