The feasibility of forecasting influenza epidemics in Cuba

A large influenza epidemic took place in Havana during the winter of 1988. The epidemiologic surveillance unit of the Pedro Kouri Institute of Tropical Medicine detected the begining of the epidemic wave. The Rvachev-Baroyan mathematical model of the geographic spread of an epidemic was used to forecast this epidemic under routine conditions of the public health system. The expected number of individuals who would attend outpatient services, because of influenza-like illness, was calculated and communicated to the health authorities within enough time to permit the introduction of available control measures. The approximate date of the epidemic peak, the daily expected number of individuals attending medical services, and the approximate time of the end of the epidemic wave were estimated. The prediction error was 12%. The model was sufficienty accurate to warrant its use as a pratical forecasting tool in the Cuban public health system.

Species distribution models for conservation-oriented studies in Switzerland : filling data and tools gaps

SUMMARYSpecies distribution models (SDMs) represent nowadays an essential tool in the research fields of ecology and conservation biology. By combining observations of species occurrence or abundance with information on the environmental characteristic of the observation sites, they can provide information on the ecology of species, predict their distributions across the landscape or extrapolate them to other spatial or time frames. The advent of SDMs, supported by geographic information systems (GIS), new developments in statistical models and constantly increasing computational capacities, has revolutionized the way ecologists can comprehend species distributions in their environment. SDMs have brought the tool that allows describing species realized niches across a multivariate environmental space and predict their spatial distribution. Predictions, in the form of probabilistic maps showing the potential distribution of the species, are an irreplaceable mean to inform every single unit of a territory about its biodiversity potential. SDMs and the corresponding spatial predictions can be used to plan conservation actions for particular species, to design field surveys, to assess the risks related to the spread of invasive species, to select reserve locations and design reserve networks, and ultimately, to forecast distributional changes according to scenarios of climate and/or land use change.By assessing the effect of several factors on model performance and on the accuracy of spatial predictions, this thesis aims at improving techniques and data available for distribution modelling and at providing the best possible information to conservation managers to support their decisions and action plans for the conservation of biodiversity in Switzerland and beyond. Several monitoring programs have been put in place from the national to the global scale, and different sources of data now exist and start to be available to researchers who want to model species distribution. However, because of the lack of means, data are often not gathered at an appropriate resolution, are sampled only over limited areas, are not spatially explicit or do not provide a sound biological information. A typical example of this is data on 'habitat' (sensu biota). Even though this is essential information for an effective conservation planning, it often has to be approximated from land use, the closest available information. Moreover, data are often not sampled according to an established sampling design, which can lead to biased samples and consequently to spurious modelling results. Understanding the sources of variability linked to the different phases of the modelling process and their importance is crucial in order to evaluate the final distribution maps that are to be used for conservation purposes.The research presented in this thesis was essentially conducted within the framework of the Landspot Project, a project supported by the Swiss National Science Foundation. The main goal of the project was to assess the possible contribution of pre-modelled 'habitat' units to model the distribution of animal species, in particular butterfly species, across Switzerland. While pursuing this goal, different aspects of data quality, sampling design and modelling process were addressed and improved, and implications for conservation discussed. The main 'habitat' units considered in this thesis are grassland and forest communities of natural and anthropogenic origin as defined in the typology of habitats for Switzerland. These communities are mainly defined at the phytosociological level of the alliance. For the time being, no comprehensive map of such communities is available at the national scale and at fine resolution. As a first step, it was therefore necessary to create distribution models and maps for these communities across Switzerland and thus to gather and collect the necessary data. In order to reach this first objective, several new developments were necessary such as the definition of expert models, the classification of the Swiss territory in environmental domains, the design of an environmentally stratified sampling of the target vegetation units across Switzerland, the development of a database integrating a decision-support system assisting in the classification of the relevés, and the downscaling of the land use/cover data from 100 m to 25 m resolution.The main contributions of this thesis to the discipline of species distribution modelling (SDM) are assembled in four main scientific papers. In the first, published in Journal of Riogeography different issues related to the modelling process itself are investigated. First is assessed the effect of five different stepwise selection methods on model performance, stability and parsimony, using data of the forest inventory of State of Vaud. In the same paper are also assessed: the effect of weighting absences to ensure a prevalence of 0.5 prior to model calibration; the effect of limiting absences beyond the environmental envelope defined by presences; four different methods for incorporating spatial autocorrelation; and finally, the effect of integrating predictor interactions. Results allowed to specifically enhance the GRASP tool (Generalized Regression Analysis and Spatial Predictions) that now incorporates new selection methods and the possibility of dealing with interactions among predictors as well as spatial autocorrelation. The contribution of different sources of remotely sensed information to species distribution models was also assessed. The second paper (to be submitted) explores the combined effects of sample size and data post-stratification on the accuracy of models using data on grassland distribution across Switzerland collected within the framework of the Landspot project and supplemented with other important vegetation databases. For the stratification of the data, different spatial frameworks were compared. In particular, environmental stratification by Swiss Environmental Domains was compared to geographical stratification either by biogeographic regions or political states (cantons). The third paper (to be submitted) assesses the contribution of pre- modelled vegetation communities to the modelling of fauna. It is a two-steps approach that combines the disciplines of community ecology and spatial ecology and integrates their corresponding concepts of habitat. First are modelled vegetation communities per se and then these 'habitat' units are used in order to model animal species habitat. A case study is presented with grassland communities and butterfly species. Different ways of integrating vegetation information in the models of butterfly distribution were also evaluated. Finally, a glimpse to climate change is given in the fourth paper, recently published in Ecological Modelling. This paper proposes a conceptual framework for analysing range shifts, namely a catalogue of the possible patterns of change in the distribution of a species along elevational or other environmental gradients and an improved quantitative methodology to identify and objectively describe these patterns. The methodology was developed using data from the Swiss national common breeding bird survey and the article presents results concerning the observed shifts in the elevational distribution of breeding birds in Switzerland.The overall objective of this thesis is to improve species distribution models as potential inputs for different conservation tools (e.g. red lists, ecological networks, risk assessment of the spread of invasive species, vulnerability assessment in the context of climate change). While no conservation issues or tools are directly tested in this thesis, the importance of the proposed improvements made in species distribution modelling is discussed in the context of the selection of reserve networks.RESUMELes modèles de distribution d'espèces (SDMs) représentent aujourd'hui un outil essentiel dans les domaines de recherche de l'écologie et de la biologie de la conservation. En combinant les observations de la présence des espèces ou de leur abondance avec des informations sur les caractéristiques environnementales des sites d'observation, ces modèles peuvent fournir des informations sur l'écologie des espèces, prédire leur distribution à travers le paysage ou l'extrapoler dans l'espace et le temps. Le déploiement des SDMs, soutenu par les systèmes d'information géographique (SIG), les nouveaux développements dans les modèles statistiques, ainsi que la constante augmentation des capacités de calcul, a révolutionné la façon dont les écologistes peuvent comprendre la distribution des espèces dans leur environnement. Les SDMs ont apporté l'outil qui permet de décrire la niche réalisée des espèces dans un espace environnemental multivarié et prédire leur distribution spatiale. Les prédictions, sous forme de carte probabilistes montrant la distribution potentielle de l'espèce, sont un moyen irremplaçable d'informer chaque unité du territoire de sa biodiversité potentielle. Les SDMs et les prédictions spatiales correspondantes peuvent être utilisés pour planifier des mesures de conservation pour des espèces particulières, pour concevoir des plans d'échantillonnage, pour évaluer les risques liés à la propagation d'espèces envahissantes, pour choisir l'emplacement de réserves et les mettre en réseau, et finalement, pour prévoir les changements de répartition en fonction de scénarios de changement climatique et/ou d'utilisation du sol. En évaluant l'effet de plusieurs facteurs sur la performance des modèles et sur la précision des prédictions spatiales, cette thèse vise à améliorer les techniques et les données disponibles pour la modélisation de la distribution des espèces et à fournir la meilleure information possible aux gestionnaires pour appuyer leurs décisions et leurs plans d'action pour la conservation de la biodiversité en Suisse et au-delà. Plusieurs programmes de surveillance ont été mis en place de l'échelle nationale à l'échelle globale, et différentes sources de données sont désormais disponibles pour les chercheurs qui veulent modéliser la distribution des espèces. Toutefois, en raison du manque de moyens, les données sont souvent collectées à une résolution inappropriée, sont échantillonnées sur des zones limitées, ne sont pas spatialement explicites ou ne fournissent pas une information écologique suffisante. Un exemple typique est fourni par les données sur 'l'habitat' (sensu biota). Même s'il s'agit d'une information essentielle pour des mesures de conservation efficaces, elle est souvent approximée par l'utilisation du sol, l'information qui s'en approche le plus. En outre, les données ne sont souvent pas échantillonnées selon un plan d'échantillonnage établi, ce qui biaise les échantillons et par conséquent les résultats de la modélisation. Comprendre les sources de variabilité liées aux différentes phases du processus de modélisation s'avère crucial afin d'évaluer l'utilisation des cartes de distribution prédites à des fins de conservation.La recherche présentée dans cette thèse a été essentiellement menée dans le cadre du projet Landspot, un projet soutenu par le Fond National Suisse pour la Recherche. L'objectif principal de ce projet était d'évaluer la contribution d'unités 'd'habitat' pré-modélisées pour modéliser la répartition des espèces animales, notamment de papillons, à travers la Suisse. Tout en poursuivant cet objectif, différents aspects touchant à la qualité des données, au plan d'échantillonnage et au processus de modélisation sont abordés et améliorés, et leurs implications pour la conservation des espèces discutées. Les principaux 'habitats' considérés dans cette thèse sont des communautés de prairie et de forêt d'origine naturelle et anthropique telles que définies dans la typologie des habitats de Suisse. Ces communautés sont principalement définies au niveau phytosociologique de l'alliance. Pour l'instant aucune carte de la distribution de ces communautés n'est disponible à l'échelle nationale et à résolution fine. Dans un premier temps, il a donc été nécessaire de créer des modèles de distribution de ces communautés à travers la Suisse et par conséquent de recueillir les données nécessaires. Afin d'atteindre ce premier objectif, plusieurs nouveaux développements ont été nécessaires, tels que la définition de modèles experts, la classification du territoire suisse en domaines environnementaux, la conception d'un échantillonnage environnementalement stratifié des unités de végétation cibles dans toute la Suisse, la création d'une base de données intégrant un système d'aide à la décision pour la classification des relevés, et le « downscaling » des données de couverture du sol de 100 m à 25 m de résolution. Les principales contributions de cette thèse à la discipline de la modélisation de la distribution d'espèces (SDM) sont rassemblées dans quatre articles scientifiques. Dans le premier article, publié dans le Journal of Biogeography, différentes questions liées au processus de modélisation sont étudiées en utilisant les données de l'inventaire forestier de l'Etat de Vaud. Tout d'abord sont évalués les effets de cinq méthodes de sélection pas-à-pas sur la performance, la stabilité et la parcimonie des modèles. Dans le même article sont également évalués: l'effet de la pondération des absences afin d'assurer une prévalence de 0.5 lors de la calibration du modèle; l'effet de limiter les absences au-delà de l'enveloppe définie par les présences; quatre méthodes différentes pour l'intégration de l'autocorrélation spatiale; et enfin, l'effet de l'intégration d'interactions entre facteurs. Les résultats présentés dans cet article ont permis d'améliorer l'outil GRASP qui intègre désonnais de nouvelles méthodes de sélection et la possibilité de traiter les interactions entre variables explicatives, ainsi que l'autocorrélation spatiale. La contribution de différentes sources de données issues de la télédétection a également été évaluée. Le deuxième article (en voie de soumission) explore les effets combinés de la taille de l'échantillon et de la post-stratification sur le la précision des modèles. Les données utilisées ici sont celles concernant la répartition des prairies de Suisse recueillies dans le cadre du projet Landspot et complétées par d'autres sources. Pour la stratification des données, différents cadres spatiaux ont été comparés. En particulier, la stratification environnementale par les domaines environnementaux de Suisse a été comparée à la stratification géographique par les régions biogéographiques ou par les cantons. Le troisième article (en voie de soumission) évalue la contribution de communautés végétales pré-modélisées à la modélisation de la faune. C'est une approche en deux étapes qui combine les disciplines de l'écologie des communautés et de l'écologie spatiale en intégrant leurs concepts de 'habitat' respectifs. Les communautés végétales sont modélisées d'abord, puis ces unités de 'habitat' sont utilisées pour modéliser les espèces animales. Une étude de cas est présentée avec des communautés prairiales et des espèces de papillons. Différentes façons d'intégrer l'information sur la végétation dans les modèles de répartition des papillons sont évaluées. Enfin, un clin d'oeil aux changements climatiques dans le dernier article, publié dans Ecological Modelling. Cet article propose un cadre conceptuel pour l'analyse des changements dans la distribution des espèces qui comprend notamment un catalogue des différentes formes possibles de changement le long d'un gradient d'élévation ou autre gradient environnemental, et une méthode quantitative améliorée pour identifier et décrire ces déplacements. Cette méthodologie a été développée en utilisant des données issues du monitoring des oiseaux nicheurs répandus et l'article présente les résultats concernant les déplacements observés dans la distribution altitudinale des oiseaux nicheurs en Suisse.L'objectif général de cette thèse est d'améliorer les modèles de distribution des espèces en tant que source d'information possible pour les différents outils de conservation (par exemple, listes rouges, réseaux écologiques, évaluation des risques de propagation d'espèces envahissantes, évaluation de la vulnérabilité des espèces dans le contexte de changement climatique). Bien que ces questions de conservation ne soient pas directement testées dans cette thèse, l'importance des améliorations proposées pour la modélisation de la distribution des espèces est discutée à la fin de ce travail dans le contexte de la sélection de réseaux de réserves.

Anàlisi de la modelització hidrològica com a eina per la predicció d'inundacions i la gestió del territori

Les inundacions són actualment les catàstrofes naturals més recurrents i les que generen un major nombre de danys i víctimes arreu del món. L'ocupació de les zones inundables a les lleres del riu és la causa principal d’aquests desastres naturals. En aquest article es descriu la realització de models hidrològics com a mecanisme per la predicció d’inundacions i la gestió del territori. S’han estudiat les conques de la Riera de Santa Coloma (Catalunya) i del riu San Francisco (Guatemala) mitjançant els programes HEC-HMS i HEC-RAS, dels quals s’avalua la seva capacitat com eina per a la gestió del territori. S’ha analitzat l’efecte de la urbanització en el risc d’inundació en el cas de la Riera de Santa Coloma en base a la previsió del Plà d’Ordenament Urbanístic Municipal. S’han determinat les zones inundables resultants de episodis de precipitació extrems al Riu San Francisco per als episodis de les tempestes Stan(2005) i Agatha(2010).

Prevalence of chronic conditions – Stroke

IPH has estimated and forecast clinical diagnosis rates of stroke among adults for the years 2010, 2015 and 2020. In the Republic of Ireland, the data are based on the Survey of Lifestyle, Attitudes and Nutrition (SLÁN) 2007. The data describe the number of adults who report that they have experienced doctor-diagnosed stroke in the previous 12 months. Data are available by age and sex for each Local Health Office of the Health Service Executive (HSE) in the Republic of Ireland. In Northern Ireland, the data are based on the Health and Social Wellbeing Survey 2005/06. The data describe the number of adults who report that they have experienced doctor-diagnosed stroke at any time in the past. Data are available by age and sex for each Local Government District in Northern Ireland. Clinical diagnosis rates in the Republic of Ireland relate to the previous 12 months and are not directly comparable with clinical diagnosis rates in Northern Ireland which relate to anytime in the past. The IPH estimated prevalence per cents may be marginally different to estimated prevalence per cents taken directly from the reference study. There are two reasons for this: 1) The IPH prevalence estimates relate to 2010 while the reference studies relate to earlier years (Northern Ireland Health and Social Wellbeing Survey 2005/06, Survey of Lifestyle, Attitudes and Nutrition 2007, Understanding Society 2009). Although we assume that the risk of the condition in the risk groups do not change over time, the distribution of the number of people in the risk groups in the population changes over time (eg the population ages).  This new distribution of the risk groups in the population means that the risk of the condition is weighted differently to the reference study and this results in a different overall prevalence estimate. 2) The IPH prevalence estimates are based on a statistical model of the reference study. The model includes a number of explanatory variables to predict the risk of the condition. Therefore the model does not include records from the reference study that are missing data on these explanatory variables. A prevalence estimate for a condition taken directly from the reference study would include these records.

Prevalence of chronic conditions – Diabetes

IPH has estimated and forecast clinical diagnosis rates of diabetes among adults for the years 2010, 2015 and 2020. In the Republic of Ireland, the data are based on the Survey of Lifestyle, Attitudes and Nutrition (SLÁN) 2007. The data describe the number of people who report that they have experienced doctor-diagnosed diabetes in the previous 12 months (annual clinical diagnosis).  Data are available by age and sex for each Local Health Office of the Health Service Executive (HSE) in the Republic of Ireland. Note that an adjustment was made for diabetes medication use recorded in the SLÁN physical examination sub-group of 45+ year olds. In Northern Ireland, the data is based on the Health and Social Wellbeing Survey 2005/06 . The data describe the number of people who report that they have experienced doctor-diagnosed diabetes at any time in the past (lifetime clinical diagnosis). Data are available by age and sex for each Local Government District in Northern Ireland.Clinical diagnosis rates in the Republic of Ireland relate to the previous 12 months and are not directly comparable with clinical diagnosis rates in Northern Ireland which relate to anytime in the past. Differences between IPH estimates and reference study estimates: The IPH estimated prevalence per cents may be marginally different to estimated prevalence per cents taken directly from the reference study. There are two reasons for this: 1) The IPH prevalence estimates relate to 2010 while the reference studies relate to earlier years (Northern Ireland Health and Social Wellbeing Survey 2005/06, Survey of Lifestyle, Attitudes and Nutrition 2007, Understanding Society 2009). Although we assume that the risk of the condition in the risk groups do not change over time, the distribution of the number of people in the risk groups in the population changes over time (eg the population ages).  This new distribution of the risk groups in the population means that the risk of the condition is weighted differently to the reference study and this results in a different overall prevalence estimate. 2) The IPH prevalence estimates are based on a statistical model of the reference study. The model includes a number of explanatory variables to predict the risk of the condition. Therefore the model does not include records from the reference study that are missing data on these explanatory variables. A prevalence estimate for a condition taken directly from the reference study would include these records.  

Chronic Airflow Obstruction Briefing: Technical Documentation

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.

Diabetes Briefing: Technical Documentation

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.  There are two types of diabetes: Type 1 diabetes is characterised by a lack of insulin production and occurs most frequently in children; Type 2 diabetes is the most common form in persons aged over 40 but cases are starting to emerge at younger ages, and is caused by the body’s ineffective use of insulin.   This document details hoe the IPH has systematically estimated and forecast the prevalence of diabetes on the island of Ireland

Coronary Heart Disease Briefing: Technical Documentation

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. This document details how the IPH has systematically estimated and forecast the prevalence of heart attack and/or angina (which we refer to as CHD) on the island of Ireland.

IPH response to Department of Health (UK) Standardised Packaging of Tobacco Products

Enhanced tobacco control policies and programmes are an important component of any strategic approach to improving population health and tackling health inequalities. The consultation on standardised packaging of tobacco products in the UK is particularly timely in view of the recent publication of the Ten Year Tobacco Strategy for Northern Ireland (DHSSPS, 2012). In this strategy the Department expressed its support for the introduction of further measures to reduce the influence of tobacco advertising and promotion upon children e.g. the introduction of plain packaging for cigarettes and hand rolling tobacco.  IPH key points •    The extent of tobacco-related harm across the island of Ireland and across the UK is unacceptable. Increasingly comprehensive and effective tobacco-control interventions are required. •    IPH recommends the adoption of option 2: require standardised packaging of tobacco products. •    IPH acknowledges that as plain packaging has not yet been introduced in any country, it is not possible at this time to accurately forecast the extent and nature of this intervention on population level health outcomes in the UK context. •    The proposed approach appears comprehensive in addressing the direct and indirect ways in which elements of tobacco packaging can promote brand appeal and can portray impressions in respect of tobacco-related harm. Consideration should be given to include specific provisions relating to roll-your-own (RYO) tobacco packaging. Any approach needs to be regularly reviewed to take into account attempts to bypass restrictions and evaluate responses in respect of consumer choices. •    IPH considers that the introduction of plain packaging has the potential to support the achievement of the goals set out in the Ten Year Tobacco Control Strategy for Northern Ireland ( DHSSPS, 2012). •    Among children in Northern Ireland who reported trying their first cigarette, around one quarter were aged 11 or under and three quarters were 14 or under when they did so (DHSSPS, 2012).  The very young age of these children is concerning on many levels including their susceptibility to sophisticated branding and marketing techniques linked to tobacco packaging.

Prevalence of chronic conditions – Hypertension

IPH has estimated and forecast clinical diagnosis rates of hypertension among adults for the years 2010, 2015 and 2020. In the Republic of Ireland, the data are based on the Survey of Lifestyle, Attitudes and Nutrition (SLÁN) 2007. The data describe the number of people who report that they have experienced doctor-diagnosed hypertension in the previous 12 months (annual clinical diagnosis). Data are available by age and sex for each Local Health Office of the Health Service Executive (HSE) in the Republic of Ireland. In Northern Ireland, the data is based on the Health and Social Wellbeing Survey 2005/06. The data describe the number of people who report that they have experienced doctor/nurse-diagnosed hypertension at any time in the past (lifetime clinical diagnosis). Data are available by age and sex for each Local Government District in Northern Ireland. Clinical diagnosis rates in the Republic of Ireland relate to the previous 12 months and are not directly comparable with clinical diagnosis rates in Northern Ireland which relate to anytime in the past.   The IPH estimated prevalence per cents may be marginally different to estimated prevalence per cents taken directly from the reference study. There are two reasons for this: 1) The IPH prevalence estimates relate to 2010 while the reference studies relate to earlier years (Northern Ireland Health and Social Wellbeing Survey 2005/06, Survey of Lifestyle, Attitudes and Nutrition 2007, Understanding Society 2009). Although we assume that the risk of the condition in the risk groups do not change over time, the distribution of the number of people in the risk groups in the population changes over time (eg the population ages).  This new distribution of the risk groups in the population means that the risk of the condition is weighted differently to the reference study and this results in a different overall prevalence estimate. 2) The IPH prevalence estimates are based on a statistical model of the reference study. The model includes a number of explanatory variables to predict the risk of the condition. Therefore the model does not include records from the reference study that are missing data on these explanatory variables. A prevalence estimate for a condition taken directly from the reference study would include these records.

Prevalence of chronic conditions – Coronary Heart Disease

IPH has estimated and forecast clinical diagnosis rates of CHD (heart attack and/or angina) among adults for the years 2010, 2015 and 2020. In the Republic of Ireland, the data are based on the Survey of Lifestyle, Attitudes and Nutrition (SLÁN) 2007 . The data describe the number of people who report that they have experienced doctor-diagnosed heart attack and/or angina in the previous 12 months (annual clinical diagnosis). Data is available by age and sex for each Local Health Office of the Health Service Executive (HSE) in the Republic of Ireland. In Northern Ireland, the data are based on the Health and Social Wellbeing Survey 2005/06 . The data describe the number of people who report that they have experienced doctor-diagnosed heart attack and/or angina at any time in the past (lifetime clinical diagnosis). Data are available by age and sex for each Local Government District in Northern Ireland. Clinical diagnosis rates in the Republic of Ireland relate to the previous 12 months and are not directly comparable with clinical diagnosis rates in Northern Ireland which relate to anytime in the past. The IPH estimated prevalence per cents may be marginally different to estimated prevalence per cents taken directly from the reference study. There are two reasons for this: 1) The IPH prevalence estimates relate to 2010 while the reference studies relate to earlier years (Northern Ireland Health and Social Wellbeing Survey 2005/06, Survey of Lifestyle, Attitudes and Nutrition 2007, Understanding Society 2009). Although we assume that the risk of the condition in the risk groups do not change over time, the distribution of the number of people in the risk groups in the population changes over time (eg the population ages).  This new distribution of the risk groups in the population means that the risk of the condition is weighted differently to the reference study and this results in a different overall prevalence estimate. 2) The IPH prevalence estimates are based on a statistical model of the reference study. The model includes a number of explanatory variables to predict the risk of the condition. Therefore the model does not include records from the reference study that are missing data on these explanatory variables. A prevalence estimate for a condition taken directly from the reference study would include these records.

Prevalence of chronic conditions – Chronic Airflow Obstruction

IPH has estimated and forecast clinical diagnosis rates of CAO among adults for the years 2010, 2015 and 2020. In the Republic of Ireland, the data are based on the Survey of Lifestyle, Attitudes and Nutrition (SLÁN) 2007. The data describe the number of people who report that they have experienced doctor-diagnosed chronic bronchitis, chronic obstructive lung (pulmonary) disease, or emphysema in the previous 12 months (annual clinical diagnosis). Data is available by age and sex for each Local Health Office of the Health Service Executive (HSE) in the Republic of Ireland. In Northern Ireland, the data are based on the Health and Social Wellbeing Survey 2005/06. The data describe the number of people who report that they have experienced doctor-diagnosed COPD or chronic obstructive pulmonary disease eg chronic bronchitis / emphysema or both disorders at any time in the past (lifetime clinical diagnosis). Data are available by age and sex for each Local Government District in Northern Ireland. Clinical diagnosis rates in the Republic of Ireland relate to the previous 12 months and are not directly comparable with clinical diagnosis rates in Northern Ireland which relate to anytime in the past.   The IPH estimated prevalence per cents may be marginally different to estimated prevalence per cents taken directly from the reference study. There are two reasons for this: 1) The IPH prevalence estimates relate to 2010 while the reference studies relate to earlier years (Northern Ireland Health and Social Wellbeing Survey 2005/06, Survey of Lifestyle, Attitudes and Nutrition 2007, Understanding Society 2009). Although we assume that the risk of the condition in the risk groups do not change over time, the distribution of the number of people in the risk groups in the population changes over time (eg the population ages).  This new distribution of the risk groups in the population means that the risk of the condition is weighted differently to the reference study and this results in a different overall prevalence estimate. 2) The IPH prevalence estimates are based on a statistical model of the reference study. The model includes a number of explanatory variables to predict the risk of the condition. Therefore the model does not include records from the reference study that are missing data on these explanatory variables. A prevalence estimate for a condition taken directly from the reference study would include these records.

Prevalence of chronic conditions – Musculoskeletal Conditions

IPH has estimated and forecast the number of adults with MSCs for the years 2010, 2015 and 2020. In the Republic of Ireland, the data are based on the Survey of Lifestyle, Attitudes and Nutrition (SLÁN) 2007 . The data describe the number of people who report that they have experienced doctor-diagnosed MSC in the previous 12 months:     Lower back pain or any other chronic back condition     Rheumatoid arthritis (inflammation of the joints)     Osteoarthritis (arthrosis, joint degradation) Data are  available by age and sex for each Local Health Office of the Health Service Executive (HSE) in the Republic of Ireland. In Northern Ireland, the data are based on the Health and Social Wellbeing Survey 2005/06 and Understanding Society 2009. The data describe the number of adults who:     Have ever consulted a doctor about back pain     Are currently receiving treatment for musculoskeletal problems (such as arthritis, rheumatism)     Have ever been told by a doctor or other health professional that they had have arthritis? Data are available by age and sex for each Local Government District in Northern Ireland. There are significant differences between the definitions used in RoI and NI and North-South comparisons are not valid. The RoI measures relate to specific MSCs in the previous 12 months that had been diagnosed by a doctor. The NI measures relate to doctor-consultations at any time in the past, doctor-diagnosis at any time in the past and current treatment. The IPH estimated prevalence per cents may be marginally different to estimated prevalence per cents taken directly from the reference study. There are two reasons for this: 1) The IPH prevalence estimates relate to 2010 while the reference studies relate to earlier years (Northern Ireland Health and Social Wellbeing Survey 2005/06, Survey of Lifestyle, Attitudes and Nutrition 2007, Understanding Society 2009). Although we assume that the risk of the condition in the risk groups do not change over time, the distribution of the number of people in the risk groups in the population changes over time (eg the population ages).  This new distribution of the risk groups in the population means that the risk of the condition is weighted differently to the reference study and this results in a different overall prevalence estimate. 2) The IPH prevalence estimates are based on a statistical model of the reference study. The model includes a number of explanatory variables to predict the risk of the condition. Therefore the model does not include records from the reference study that are missing data on these explanatory variables. A prevalence estimate for a condition taken directly from the reference study would include these records.

Stroke Briefing

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.

Stroke Briefing: Technical Documentation

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