996 resultados para GENERAL EPIDEMIC


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The increasing adoption of cloud computing, social networking, mobile and big data technologies provide challenges and opportunities for both research and practice. Researchers face a deluge of data generated by social network platforms which is further exacerbated by the co-mingling of social network platforms and the emerging Internet of Everything. While the topicality of big data and social media increases, there is a lack of conceptual tools in the literature to help researchers approach, structure and codify knowledge from social media big data in diverse subject matter domains, many of whom are from nontechnical disciplines. Researchers do not have a general-purpose scaffold to make sense of the data and the complex web of relationships between entities, social networks, social platforms and other third party databases, systems and objects. This is further complicated when spatio-temporal data is introduced. Based on practical experience of working with social media datasets and existing literature, we propose a general research framework for social media research using big data. Such a framework assists researchers in placing their contributions in an overall context, focusing their research efforts and building the body of knowledge in a given discipline area using social media data in a consistent and coherent manner.

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New, automated forms of data-analysis are required in order to understand the high-dimensional trajectories that are obtained from molecular dynamics simulations on proteins. Dimensionality reduction algorithms are particularly appealing in this regard as they allow one to construct unbiased, low-dimensional representations of the trajectory using only the information encoded in the trajectory. The downside of this approach is that different sets of coordinates are required for each different chemical systems under study precisely because the coordinates are constructed using information from the trajectory. In this paper we show how one can resolve this problem by using the sketch-map algorithm that we recently proposed to construct a low-dimensional representation of the structures contained in the protein data bank (PDB). We show that the resulting coordinates are as useful for analysing trajectory data as coordinates constructed using landmark configurations taken from the trajectory and that these coordinates can thus be used for understanding protein folding across a range of systems.

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The problem of detecting spatially-coherent groups of data that exhibit anomalous behavior has started to attract attention due to applications across areas such as epidemic analysis and weather forecasting. Earlier efforts from the data mining community have largely focused on finding outliers, individual data objects that display deviant behavior. Such point-based methods are not easy to extend to find groups of data that exhibit anomalous behavior. Scan Statistics are methods from the statistics community that have considered the problem of identifying regions where data objects exhibit a behavior that is atypical of the general dataset. The spatial scan statistic and methods that build upon it mostly adopt the framework of defining a character for regions (e.g., circular or elliptical) of objects and repeatedly sampling regions of such character followed by applying a statistical test for anomaly detection. In the past decade, there have been efforts from the statistics community to enhance efficiency of scan statstics as well as to enable discovery of arbitrarily shaped anomalous regions. On the other hand, the data mining community has started to look at determining anomalous regions that have behavior divergent from their neighborhood.In this chapter,we survey the space of techniques for detecting anomalous regions on spatial data from across the data mining and statistics communities while outlining connections to well-studied problems in clustering and image segmentation. We analyze the techniques systematically by categorizing them appropriately to provide a structured birds eye view of the work on anomalous region detection;we hope that this would encourage better cross-pollination of ideas across communities to help advance the frontier in anomaly detection.

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Objective: To determine the long-term effectiveness of a complex intervention in primary care aimed at improving outcomes for patients with coronary heart disease.

Design: A 6-year follow-up of a cluster randomised controlled trial, which found after 18 months that both total and cardiovascular hospital admissions were significantly reduced in intervention practices (8% absolute reduction).

Setting: 48 general practices in the Republic of Ireland and Northern Ireland.

Participants: 903 patients with established coronary heart disease at baseline in the original trial.

Intervention: The original intervention consisted of tailored practice and patient plans; training sessions for practitioners in medication prescribing and behavioural change; and regular patient recall system. Control practices provided usual care. Following the intervention period, all supports from the research team to intervention practices ceased.

Outcome measures: Primary outcome: hospital admissions, all cause and cardiovascular; secondary outcomes: mortality; blood pressure and cholesterol control.

Results: At 6-year follow-up, data were collected from practice records of 696 patients (77%). For those who had died, we censored their data at the point of death and cause of death was established. There were no significant differences between the intervention and control practices in either total (OR 0.83 (95% CI 0.54 to 1.28)) or cardiovascular hospital admissions (OR 0.91 (95% CI 0.49 to 1.65)). We confirmed mortality status of 886 of the original 903 patients (98%). There were no significant differences in mortality (15% in intervention and 16% in control) or in the proportions of patients above target control for systolic blood pressure or total cholesterol.

Conclusions: Initial significant differences in the numbers of total and cardiovascular hospital admissions were not maintained at 6 years and no differences were found in mortality or blood pressure and cholesterol control. Policymakers need to continue to assess the effectiveness of previously efficacious programmes.

Trial registration number: Current Controlled Trials ISRCTN24081411.

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Diabetic retinopathy (DR), a major microvascular complication of diabetes, has a significant impact on the world′s health systems. Globally, the number of people with DR will grow from 126.6 million in 2010 to 191.0 million by 2030, and we estimate that the number with vision-threatening diabetic retinopathy (VTDR) will increase from 37.3 million to 56.3 million, if prompt action is not taken. Despite growing evidence documenting the effectiveness of routine DR screening and early treatment, DR frequently leads to poor visual functioning and represents the leading cause of blindness in working-age populations. DR has been neglected in health-care research and planning in many low-income countries, where access to trained eye-care professionals and tertiary eye-care services may be inadequate. Demand for, as well as, supply of services may be a problem. Rates of compliance with diabetes medications and annual eye examinations may be low, the reasons for which are multifactorial. Innovative and comprehensive approaches are needed to reduce the risk of vision loss by prompt diagnosis and early treatment of VTDR.

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INTRODUCTION:

It has been widely suggested that the prevalence of myopia is growing worldwide, and that the increases observed in East Asia, in particular, are sufficiently severe as to warrant the term "epidemic". Data in favour of a cohort effect in myopia prevalence are reviewed, with attention to significant shortcomings in the quality of available evidence. Additional factors contributing to myopia prevalence, including near work, genetics and socioeconomic status, are detailed.

MATERIALS AND METHODS:

Medline search of articles regarding myopia prevalence, trends and mechanisms.

RESULTS:

Age-related changes in myopia prevalence (increase during childhood, and regression in the fifth and sixth decades) are discussed as an alternative explanation for cross-sectional patterns in myopia prevalence. There have only been a handful of studies that have examined the relative contribution of longitudinal changes in refraction over life and birth cohort differences on age-specific myopia prevalence as measured in cross-sectional studies. Available data suggest that both longitudinal changes and cohort effects may be present, and that their relative contribution may differ in different racial groups.

CONCLUSIONS:

In view of the relatively weak evidence in favour of a large cohort effect for myopia in East Asia, and the even greater lack of evidence for increased prevalence of secondary ocular pathology, there appears to be inadequate support for large-scale interventions to prevent or delay myopia at the present time.

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Rational catalyst design is one of the most fundamental goals in heterogeneous catalysis. Herein, we briefly review our previous design work, and then introduce a general optimization framework, which converts catalyst design into an optimization problem. Furthermore, an example is given using the gradient ascent method to show how this framework can be used for rational catalyst design. This framework may be applied to other design schemes.

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BACKGROUND: The health of doctors who work in primary care is threatened by workforce and workload issues. There is a need to find and appraise ways in which to protect their mental health, including how to achieve the broader, positive outcome of well-being. Our primary outcome was to evaluate systematically the research evidence regarding the effectiveness of interventions designed to improve General Practitioner (GP) well-being across two continua; psychopathology (mental ill-health focus) and 'languishing to flourishing' (positive mental health focus). In addition we explored the extent to which developments in well-being research may be integrated within existing approaches to design an intervention that will promote mental health and prevent mental illness among these doctors.

METHODS: Medline, Embase, Cinahl, PsychINFO, Cochrane Register of Trials and Web of Science were searched from inception to January 2015 for studies where General Practitioners and synonyms were the primary participants. Eligible interventions included mental ill-health prevention strategies (e.g. promotion of early help-seeking) and mental health promotion programmes (e.g. targeting the development of protective factors at individual and organizational levels). A control group was the minimum design requirement for study inclusion and primary outcomes had to be assessed by validated measures of well-being or mental ill-health. Titles and abstracts were assessed independently by two reviewers with 99 % agreement and full papers were appraised critically using validated tools.

RESULTS: Only four studies (with a total of 997 GPs) from 5392 titles met inclusion criteria. The studies reported statistically significant improvement in self-reported mental ill-health. Two interventions used cognitive-behavioural techniques, one was mindfulness-based and one fed-back GHQ scores and self-help information.

CONCLUSION: There is an urgent need for high quality, controlled studies in GP well-being. Research on improving GP well-being is limited by focusing mainly on stressors and not giving systematic attention to the development of positive mental health.

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The TELL ME agent based model simulates the connections between health agency communication, personal decisions to adopt protective behaviour during an influenza epidemic, and the effect of those decisions on epidemic progress. The behaviour decisions are modelled with a combination of personal attitude, behaviour adoption by neighbours, and the local recent incidence of influenza. This paper sets out and justifies the model design, including how these decision factors have been operationalised. By exploring the effects of different communication strategies, the model is intended to assist health authorities with their influenza epidemic communication plans. It can both assist users to understand the complex interactions between communication, personal behaviour and epidemic progress, and guide future data collection to improve communication planning.

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Background: Contact with primary care and psychiatric services prior to suicide may be considerable, presenting
opportunities for intervention. However, there is scant knowledge on the frequency, nature and determinants of
contact.
Method: Retrospective cohort study-an analysis of deaths recorded as suicide by the Northern Ireland Coroner’s
Office linked with data from General Practice patient records over a 2 year period
Results: Eighty-seven per cent of suicides were in contact with General Practice services in the 12 months before
suicide. The frequency of contact with services was considerable, particularly among patients with a common
mental disorder or substance misuse problems. A diagnosis of psychiatric problems was absent in 40 % of suicides.
Excluding suicide attempts, the main predictors of a noted general practitioner concern for patient suicidality are
male gender, frequency of consultations, diagnosis of mental illness and substance misuse.
Conclusions: Despite widespread and frequent contact, a substantial proportion of suicidal people were
undiagnosed and untreated for mental health problems. General Practitioner alertness to suicidality may be too
narrowly focused.

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Do ponto de vista da política económica, existe a possibilidade de utilizar a receita dos impostos ambientais para baixar os impostos sobre o trabalho, promovendo assim o emprego. Esta oportunidade surge na literatura como forma dos países industrializados responderem a um duplo desafio: um crescente nível de poluição e um decrescente nível de emprego. Alguns países tomaram já decisões no sentido de alcançar o “duplo dividendo”: melhorias ambientais e diminuição do desemprego. Os resultados teóricos, na sua maioria cépticos em relação à verificação do segundo dividendo, são substancialmente contrariados por uma série de estudos que utilizam modelos de equilíbrio geral. Pretendese com este trabalho fazer uma simulação para a economia portuguesa de uma reforma fiscal ambiental com as características referidas e a verificação da existência do “duplo dividendo”, através de um modelo computacional de equilíbrio geral. Para além disso, é feita uma análise dos impactos do Mercado Europeu de Licenças de Emissão, ao nível sectorial e regional, em Portugal, utilizando dados microeconómicos, com o objectivo de estudar as consequências ao nível das trasacções entre sectores e efeitos distributivos entre regiões.