1,045,152 research outputs found

    Role of Epidemiological Studies in Disease Prevention

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    Today's society is full of disease that are of different natures including genetic, infectious and metabolic etc. Every disease has its own mechanisms of affecting humans and different prevention mechanisms as per disease nature. These factors are included in epidemiology of disease. Other factors include prevalence and incidence of diseases in different populations. Exactly knowing about disease epidemiology helps governing authorities to prevent the disease. Unfortunately, under-developed and developing nations are not focusing on diseases epidemiology. On the other hand, all developing nations developed best public health practices based on diseases epidemiology data. These studies may vary from basic epidemiological surveys to identification of microorganism strains etc

    Social epidemiology

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    Social epidemiology is the branch of epidemiology concerned with understanding how social and economic characteristics influence states of health in populations. There has been a resurgence recently in interest among epidemiologists about the roles that social and economic factors play in determining health, leading to valuable synergies with the social sciences. The determinants of health commonly studied in social epidemiology include absolute poverty, income inequality, as well as race and discrimination. Recently, social epidemiologists have been at the forefront of conceptual developments within the discipline that view the determinants of health at different levels of social organization. © 2008 Copyright © 2008 Elsevier Inc. All rights reserved

    Methodological Frontiers in Environmental Epidemiology

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    Environmental epidemiology comprises the epidemiologic study of those environmental factors that are outside the immediate control of the individual. Exposures of interest to environmental epidemiologists include air pollution, water pollution, occupational exposure to physical and chemical agents, as well as psychosocial elements of environmental concern. The main methodologic problem in environmental epidemiology is exposure assessment, a problem that extends through all of epidemiologic research but looms as a towering obstacle in environmental epidemiology. One of the most promising developments in improving exposure assessment in environmental epidemiology is to find exposure biomarkers, which could serve as built-in dosimeters that reflect the biologic footprint left behind by environmental exposures. Beyond exposure assessment, epidemiologists studying environmental exposures face the difficulty of studying small effects that may be distorted by confounding that eludes easy control. This challenge may prompt reliance on new study designs, such as two-stage designs in which exposure and disease information are collected in the first stage, and covariate information is collected on a subset of subjects in state two. While the analytic methods already available for environmental epidemiology are powerful, analytic methods for ecologic studies need further development. This workshop outlines the range of methodologic issues that environmental epidemiologists must address so that their work meets the goals set by scientists and society at large

    An ontology to standardize research output of nutritional epidemiology : from paper-based standards to linked content

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    Background: The use of linked data in the Semantic Web is a promising approach to add value to nutrition research. An ontology, which defines the logical relationships between well-defined taxonomic terms, enables linking and harmonizing research output. To enable the description of domain-specific output in nutritional epidemiology, we propose the Ontology for Nutritional Epidemiology (ONE) according to authoritative guidance for nutritional epidemiology. Methods: Firstly, a scoping review was conducted to identify existing ontology terms for reuse in ONE. Secondly, existing data standards and reporting guidelines for nutritional epidemiology were converted into an ontology. The terms used in the standards were summarized and listed separately in a taxonomic hierarchy. Thirdly, the ontologies of the nutritional epidemiologic standards, reporting guidelines, and the core concepts were gathered in ONE. Three case studies were included to illustrate potential applications: (i) annotation of existing manuscripts and data, (ii) ontology-based inference, and (iii) estimation of reporting completeness in a sample of nine manuscripts. Results: Ontologies for food and nutrition (n = 37), disease and specific population (n = 100), data description (n = 21), research description (n = 35), and supplementary (meta) data description (n = 44) were reviewed and listed. ONE consists of 339 classes: 79 new classes to describe data and 24 new classes to describe the content of manuscripts. Conclusion: ONE is a resource to automate data integration, searching, and browsing, and can be used to assess reporting completeness in nutritional epidemiology

    Networks and the epidemiology of infectious disease

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    The science of networks has revolutionised research into the dynamics of interacting elements. It could be argued that epidemiology in particular has embraced the potential of network theory more than any other discipline. Here we review the growing body of research concerning the spread of infectious diseases on networks, focusing on the interplay between network theory and epidemiology. The review is split into four main sections, which examine: the types of network relevant to epidemiology; the multitude of ways these networks can be characterised; the statistical methods that can be applied to infer the epidemiological parameters on a realised network; and finally simulation and analytical methods to determine epidemic dynamics on a given network. Given the breadth of areas covered and the ever-expanding number of publications, a comprehensive review of all work is impossible. Instead, we provide a personalised overview into the areas of network epidemiology that have seen the greatest progress in recent years or have the greatest potential to provide novel insights. As such, considerable importance is placed on analytical approaches and statistical methods which are both rapidly expanding fields. Throughout this review we restrict our attention to epidemiological issues

    On Understanding Catastrophe — The Case of Highly Severe Influenza-Like Illness

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    Computational epidemiology is a form of spatiotemporal reasoning in which social link structures are employed, and spatially explicit models are specified and executed. We point to issues thus far addressed neither by engineers, nor scientists, in the light of a use case focusing on catastrophic scenarios that assume the emergence of a highly unlikely but lethal and contagious strain of influenza. Our conclusion is that important perspectives are missing when dealing with policy issues resulting from scenario execution and analyses in computational epidemiology
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