947 resultados para PROBABILISTIC FORECASTS
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Chronic airflow obstruction (CAO) is a chronic lung condition that interferes with normal breathing. CAO includes chronic obstructive pulmonary disease (COPD), chronic bronchitis and emphysema. IPH has systematically estimated and forecast the prevalence of CAO on the island of Ireland. This document details the methods used to calculate these estimates and forecasts.
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Diabetes mellitus is a group of metabolic disorders characterised by too much glucose in the blood. The body breaks down digested food into a sugar called glucose from which it derives energy. The hormone insulin allows the body to use that sugar by helping glucose to enter the cells. When a person has diabetes, either the pancreas fails to produce enough insulin or the body cannot properly use the insulin it has. As a result there is a build-up of glucose in the blood causing the cells to be starved of energy. The Chronic Conditions Hub is a website that brings together information on chronic health conditions. It allows you to easily access, manage and share relevant information resources. The Chronic Conditions Hub includes the Institute of Public Health in Ireland’s (IPH) estimates and forecasts of the number of people living with chronic conditions. On the Chronic Conditions Hub you will find:- A Briefing for each condition - Detailed technical documentation - Detailed national and sub-national data that can be downloaded or explored using online data tools
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Coronary heart disease (CHD) is a collective term for diseases that occur when the walls of the coronary arteries become narrowed by a gradual build up of fatty material called atheroma. For the purpose of this briefing, CHD includes heart attack and angina (chest pain on exertion or stress). The Chronic Conditions Hub is a website that brings together information on chronic health conditions. It allows you to easily access, manage and share relevant information resources. The Chronic Conditions Hub includes the Institute of Public Health in Ireland’s (IPH) estimates and forecasts of the number of people living with chronic conditions. On the Chronic Conditions Hub you will find: - A Briefing for each condition - Detailed technical documentation - Detailed national and sub-national data that can be downloaded or explored using online data tools - A prevalence tool that allows you to calculate prevalence figures for your population data
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Blood pressure is the force exerted on artery walls as the heart pumps blood through the body. Hypertension, or high blood pressure, occurs when blood pressure is constantly higher than the pressure needed to carry blood through the body. The Chronic Conditions Hub is a website that brings together information on chronic health conditions. It allows you to easily access, manage and share relevant information resources. The Chronic Conditions Hub includes the Institute of Public Health in Ireland’s (IPH) estimates and forecasts of the number of people living with chronic conditions. On the Chronic Conditions Hub you will find:- A Briefing for each condition - Detailed technical documentation - Detailed national and sub-national data that can be downloaded or explored using online data tools - A prevalence tool that allows you to calculate prevalence figures for your population data
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Musculoskeletal conditions (MSCs) are a group of diseases that affect the body’s bones, joints, muscles and the tissues that connect them. Common MSCs include back pain, rheumatoid arthritis, osteoarthritis, osteoporosis, and spinal disorders. MSCs are the most common cause of severe long term pain and physical disability in developed countries. They significantly affect the psychosocial wellbeing of individuals as well as their families and carers. They are responsible for substantial costs to the health and social care system and the economy. They are a leading cause of absence from work and lost productivity at work. MSCs comprise a diverse group of conditions. Some have a specific medical diagnosis (eg rheumatoid arthritis) but others have no clear medical diagnosis (eg back pain). Risk factors for the development and progression of MSCs include age, sex, family history, obesity, physical inactivity, injury and biomechanical occupational health issues. This document details the methods used to calculate the estimates and forecasts.
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The Chronic Conditions Hub is a website that brings together information on chronic health conditions. It allows you to easily access, manage and share relevant information resources. The Chronic Conditions Hub includes the Institute of Public Health in Ireland’s (IPH) estimates and forecasts of the number of people living with chronic conditions. On the Chronic Conditions Hub you will find: - A Briefing for each condition - Detailed technical documentation - Detailed national and sub-national data that can be downloaded or explored using online data tools - A prevalence tool that allows you to calculate prevalence figures for your population data A stroke happens when blood flow to a part of the brain is interrupted by a blocked or burst blood vessel. A lack of blood supply can damage brain cells and affect body functions. IPH has systematically estimated and forecast the prevalence of stroke on the island of Ireland. Epidemiology Age, family history, diabetes, high blood pressure, high cholesterol, smoking, unhealthy diet, physical inactivity and alcohol are the main risk factors for stroke. The World Health Organization estimates that stroke and cerebrovascular disease is responsible for 10% of all world deaths and is the second most common cause of death worldwide. Cerebrovascular diseases (ICD 10 codes I60-I69) were responsible for 7.2% of all deaths in the Republic of Ireland in 2009 and for 8.6% of all deaths in Northern Ireland in 2010.
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A stroke happens when blood flow to a part of the brain is interrupted by a blocked or burst blood vessel. A lack of blood supply can damage brain cells and affect body functions. IPH has systematically estimated and forecast the prevalence of stroke on the island of Ireland. This document details the methods used to calculate these estimates and forecasts. Technical documentation
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The Institute of Public Health in Ireland publishes estimates and forecasts of the prevalence of chronic health conditions for national and subnational areas on the island of Ireland. The estimates and forecasts are based on statistical models of nationally representative health survey data that estimate the risk of having the condition. The risks of having the condition are then applied to population estimates and projections. The purpose of this document is to: 1. Compare IPH prevalence estimates with prevalence estimates from other health surveys on the island. 2. Highlight the methodological issues in comparing prevalence estimates from different surveys.
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Access audio, video and slides from the launch of the report The Institute of Public health in Ireland (IPH) produces population prevalence estimates and forecasts for a number of chronic conditions among adults. IPH has now applied the methodology to longstanding health conditions among young children across the island of Ireland. This report, based on a systematic analysis of data from the Growing Up in Ireland National Longitudinal Study of Children in the Republic of Ireland, is the first comprehensive look at longstanding health conditions among young children in Ireland. Estimated prevalence (per cent and number of cases) of longstanding health conditions among three-year-olds in the Republic of Ireland in 2011 by administrative counties/cities. The conditions are carer-reported: - "Longstanding illness, condition or disability” (where longstanding was defined as “anything that has troubled him/her over a period of time or that is likely to affect him/her over a period of time”) - Diagnosed asthma or asthma symptoms - Diagnosed eczema/any kind of skin allergy - Sight problem that required correction - Hearing problem that required correction - The estimates are based on data from the Growing Up in Ireland National Longitudinal Study of Children (www.growingup.ie) and population data. See the Chronic Conditions Hub for more details.
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Access audio, video and slides from the launch of the report The Institute of Public health in Ireland (IPH) produces population prevalence estimates and forecasts for a number of chronic conditions among adults. IPH has now applied the methodology to longstanding health conditions among young children across the island of Ireland. This report, based on a systematic analysis of data from the Growing Up in Ireland National Longitudinal Study of Children in the Republic of Ireland, is the first comprehensive look at longstanding health conditions among young children in Ireland. Estimated prevalence (per cent and number of cases) of longstanding health conditions among three-year-olds in the Republic of Ireland in 2011 by administrative counties/cities. The conditions are carer-reported: - "Longstanding illness, condition or disability” (where longstanding was defined as “anything that has troubled him/her over a period of time or that is likely to affect him/her over a period of time”) - Diagnosed asthma or asthma symptoms - Diagnosed eczema/any kind of skin allergy - Sight problem that required correction - Hearing problem that required correction - The estimates are based on data from the Growing Up in Ireland National Longitudinal Study of Children (www.growingup.ie) and population data. See the Chronic Conditions Hub for more details.
Resumo:
Access audio, video and slides from the launch of the report The Institute of Public health in Ireland (IPH) produces population prevalence estimates and forecasts for a number of chronic conditions among adults. IPH has now applied the methodology to longstanding health conditions among young children across the island of Ireland. This report, based on a systematic analysis of data from the Growing Up in Ireland National Longitudinal Study of Children in the Republic of Ireland, is the first comprehensive look at longstanding health conditions among young children in Ireland. Estimated prevalence (per cent and number of cases) of longstanding health conditions among three-year-olds in the Republic of Ireland in 2011 by administrative counties/cities. The conditions are carer-reported: - "Longstanding illness, condition or disability” (where longstanding was defined as “anything that has troubled him/her over a period of time or that is likely to affect him/her over a period of time”) - Diagnosed asthma or asthma symptoms - Diagnosed eczema/any kind of skin allergy - Sight problem that required correction - Hearing problem that required correction - The estimates are based on data from the Growing Up in Ireland National Longitudinal Study of Children (www.growingup.ie) and population data. See the Chronic Conditions Hub for more details.
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El riu Canaletes va resultar afectat per l’ incendi que es va produir a Horta de Sant Joan el juliol de l’any 2009. El foc va malmetre bona part de la flora i fauna de la zona, però un dels ecosistemes que en va sortir més perjudicat va ser el del bosc de ribera, ecosistema molt fràgil en front de pertorbacions d’aquest tipus, ja que la seva capacitat de regeneració no és tant senzilla ni ràpida com en altres ecosistemes mediterranis com podrien ser els boscos de pi blanc. No obstant, si que existeixen algunes espècies de ribera que presenten una ràpida resposta als incendis com és el cas dels salzes o alguns pollancres o àlbers, que en aquest cas, poc temps després del foc ja presentaven rebrots, segons observacions realitzades al camp. Per comprovar l’evolució de la recuperació del bosc de ribera en la zona afectada per l’incendi, es van realitzar diverses sortides de camp. D’aquestes observacions, es va poder deduir que actualment el bosc de ribera de la zona estudiada, evoluciona segons les previsions realitzades en estudis immediatament posteriors al foc, de manera que hi estan proliferant de manera ràpida bardisses amb esbarzer, gavarrera, roldor i sanguinyol, en aquells llocs que abans de l’incendi eren ocupats per arbres caducifolis.
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In the PhD thesis “Sound Texture Modeling” we deal with statistical modelling or textural sounds like water, wind, rain, etc. For synthesis and classification. Our initial model is based on a wavelet tree signal decomposition and the modeling of the resulting sequence by means of a parametric probabilistic model, that can be situated within the family of models trainable via expectation maximization (hidden Markov tree model ). Our model is able to capture key characteristics of the source textures (water, rain, fire, applause, crowd chatter ), and faithfully reproduces some of the sound classes. In terms of a more general taxonomy of natural events proposed by Graver, we worked on models for natural event classification and segmentation. While the event labels comprise physical interactions between materials that do not have textural propierties in their enterity, those segmentation models can help in identifying textural portions of an audio recording useful for analysis and resynthesis. Following our work on concatenative synthesis of musical instruments, we have developed a pattern-based synthesis system, that allows to sonically explore a database of units by means of their representation in a perceptual feature space. Concatenative syntyhesis with “molecules” built from sparse atomic representations also allows capture low-level correlations in perceptual audio features, while facilitating the manipulation of textural sounds based on their physical and perceptual properties. We have approached the problem of sound texture modelling for synthesis from different directions, namely a low-level signal-theoretic point of view through a wavelet transform, and a more high-level point of view driven by perceptual audio features in the concatenative synthesis setting. The developed framework provides unified approach to the high-quality resynthesis of natural texture sounds. Our research is embedded within the Metaverse 1 European project (2008-2011), where our models are contributting as low level building blocks within a semi-automated soundscape generation system.
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Hidden Markov models (HMMs) are probabilistic models that are well adapted to many tasks in bioinformatics, for example, for predicting the occurrence of specific motifs in biological sequences. MAMOT is a command-line program for Unix-like operating systems, including MacOS X, that we developed to allow scientists to apply HMMs more easily in their research. One can define the architecture and initial parameters of the model in a text file and then use MAMOT for parameter optimization on example data, decoding (like predicting motif occurrence in sequences) and the production of stochastic sequences generated according to the probabilistic model. Two examples for which models are provided are coiled-coil domains in protein sequences and protein binding sites in DNA. A wealth of useful features include the use of pseudocounts, state tying and fixing of selected parameters in learning, and the inclusion of prior probabilities in decoding. AVAILABILITY: MAMOT is implemented in C++, and is distributed under the GNU General Public Licence (GPL). The software, documentation, and example model files can be found at http://bcf.isb-sib.ch/mamot
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Despite efforts to eradicate American trypanosomiasis (AT) and Chagas disease from the Americas, there are still areas of active transmission that can eventually become a source of reinfection in previously controlled regions. Mexico could be one of those areas, where there are no formal preventive control programs despite the presence of communities infested by Triatominae bugs infected with Trypanosoma cruzi. This study explored the prevalence of T. cruzi infection in 405 habitants of 17 communities in the state of Colima, on the Pacific Mexican coast, through a seroepidemiological probabilistic survey. The results revealed a point seroprevalence of 2.4% positive for anti-T. cruzi. In addition, 2 clinical cases of chronic and 2 of acute Chagas disease were detected in the explored communities. These findings confirm the risk of active transmission of AT in Western Mexico, especially in rural and suburban communities infested with intra-domestic triatominae, where control programs should be implemented.