972 resultados para Logistic Epidemic


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Discrete Conditional Phase-type (DC-Ph) models are a family of models which represent skewed survival data conditioned on specific inter-related discrete variables. The survival data is modeled using a Coxian phase-type distribution which is associated with the inter-related variables using a range of possible data mining approaches such as Bayesian networks (BNs), the Naïve Bayes Classification method and classification regression trees. This paper utilizes the Discrete Conditional Phase-type model (DC-Ph) to explore the modeling of patient waiting times in an Accident and Emergency Department of a UK hospital. The resulting DC-Ph model takes on the form of the Coxian phase-type distribution conditioned on the outcome of a logistic regression model.

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Modeling dynamical systems represents an important application class covering a wide range of disciplines including but not limited to biology, chemistry, finance, national security, and health care. Such applications typically involve large-scale, irregular graph processing, which makes them difficult to scale due to the evolutionary nature of their workload, irregular communication and load imbalance. EpiSimdemics is such an application simulating epidemic diffusion in extremely large and realistic social contact networks. It implements a graph-based system that captures dynamics among co-evolving entities. This paper presents an implementation of EpiSimdemics in Charm++ that enables future research by social, biological and computational scientists at unprecedented data and system scales. We present new methods for application-specific processing of graph data and demonstrate the effectiveness of these methods on a Cray XE6, specifically NCSA's Blue Waters system.

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A Rift Valley fever (RVF) epidemic affecting animals on domestic livestock farms was reported in South Africa during January-August 2010. The first cases occurred after heavy rainfall, and the virus subsequently spread countrywide. To determine the possible effect of environmental conditions and vaccination on RVF virus transmissibility, we estimated the effective reproduction number (R) for the virus over the course of the epidemic by extending the Wallinga and Teunis algorithm with spatial information. Re reached its highest value in mid-February and fell below unity around mid-March, when vaccination coverage was 7.5%-45.7% and vector-suitable environmental conditions were maintained. The epidemic fade-out likely resulted first from the immunization of animals following natural infection or vaccination. The decline in vector-suitable environmental conditions from April onwards and further vaccination helped maintain R below unity. Increased availability of vaccine use data would enable evaluation of the effect of RVF vaccination campaigns.

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13.Vidovic M., Miljus M., Vlajic J., (2002), "Risk minimization in logistic processes with oil products", Proceedings of the 6th International Conference on Traffic Science, ICTS 2002, Portorož, Slovenia, pp. 568-577;

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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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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 A large epidemic of asthma occurred following a thunderstorm in southern and central England on 24/25 June 1994. A collaborative study group was formed. Objectives To describe the epidemic and the meteorological, aerobiological and other environmental characteristics associated with it. Methods Collation of data from the Meteorological Office, the Pollen Research Unit, the Department of the Environment's Automatic Urban Network, from health surveillance by the Department of Health and the National Poisons Unit, from clinical experience in general practice and hospitals, and from an immunological study of some of the affected cases from north east London. Results The thunderstorm was a Mesoscale Convective System, an unusual and large form of storm with several centres and severe wind gusts. It occurred shortly after the peak grass pollen concentration in the London area. A sudden and extensive epidemic occurred within about an hour affecting possibly several thousand patients. Emergency services were stretched but the epidemic did not last long. Cases had high serum levels of IgE antibody to mixed grass pollen. Conclusion This study supports the view that patients with specific IgE to grass pollen are at risk of thunderstorm-related asthma. The details of the causal pathway from storm to asthma attack are not clear. Case-control and time series studies are being carried out.