Health and Employment, Sources of Information

The Institute of Public Health in Ireland (IPH) has produced a series of reviews which look at the health impacts of identified subject areas. Four reviews have been produced in the areas of employment, transport, the built environment and education. All reviews may be found at http://www.publichealth.ie/ireland/hiaresources. This resource supplements the ‘Health Impacts of Employment’ report. It highlights a number of organisations whose work considers issues relevant to the relationship between health and employment.

Health Impact Review - Sources of information reports

To support each of the IPH series of Health Impact Reviews, a sources of information report is now avalable for each of the four reports. These provide links to organisations who have conducted a wealth of information related to health and either employment, transport, education or the built environment.

Integration of Trypanosoma cruzi kDNA minicircle sequence in the host genome may be associated with autoimmune serum factors in Chagas disease patients

Integration of kDNA sequences within the genome of the host cell shown by PCR amplification with primers to the conserved Trypanosoma cruzi kDNA minicircle sequence was confirmed by Southern hybridization with specific probes. The cells containing the integrated kDNA sequences were then perpetuated as transfected macrophage subclonal lines. The kDNA transfected macrophages expressed membrane antigens that were recognized by antibodies in a panel of sera from ten patients with chronic Chagas disease. These antigens barely expressed in the membrane of uninfected, control macrophage clonal lines were recognized neither by factors in the control, non-chagasic subjects nor in the chagasic sera. This finding suggests the presence of an autoimmune antibody in the chagasic sera that recognizes auto-antigens in the membrane of T. cruzi kDNA transfected macrophage subclonal lines.

Quantitative integration of geophysical and hydraulic data : from the local towards the regional scale range

Des progrès significatifs ont été réalisés dans le domaine de l'intégration quantitative des données géophysique et hydrologique l'échelle locale. Cependant, l'extension à de plus grandes échelles des approches correspondantes constitue encore un défi majeur. Il est néanmoins extrêmement important de relever ce défi pour développer des modèles fiables de flux des eaux souterraines et de transport de contaminant. Pour résoudre ce problème, j'ai développé une technique d'intégration des données hydrogéophysiques basée sur une procédure bayésienne de simulation séquentielle en deux étapes. Cette procédure vise des problèmes à plus grande échelle. L'objectif est de simuler la distribution d'un paramètre hydraulique cible à partir, d'une part, de mesures d'un paramètre géophysique pertinent qui couvrent l'espace de manière exhaustive, mais avec une faible résolution (spatiale) et, d'autre part, de mesures locales de très haute résolution des mêmes paramètres géophysique et hydraulique. Pour cela, mon algorithme lie dans un premier temps les données géophysiques de faible et de haute résolution à travers une procédure de réduction déchelle. Les données géophysiques régionales réduites sont ensuite reliées au champ du paramètre hydraulique à haute résolution. J'illustre d'abord l'application de cette nouvelle approche dintégration des données à une base de données synthétiques réaliste. Celle-ci est constituée de mesures de conductivité hydraulique et électrique de haute résolution réalisées dans les mêmes forages ainsi que destimations des conductivités électriques obtenues à partir de mesures de tomographic de résistivité électrique (ERT) sur l'ensemble de l'espace. Ces dernières mesures ont une faible résolution spatiale. La viabilité globale de cette méthode est testée en effectuant les simulations de flux et de transport au travers du modèle original du champ de conductivité hydraulique ainsi que du modèle simulé. Les simulations sont alors comparées. Les résultats obtenus indiquent que la procédure dintégration des données proposée permet d'obtenir des estimations de la conductivité en adéquation avec la structure à grande échelle ainsi que des predictions fiables des caractéristiques de transports sur des distances de moyenne à grande échelle. Les résultats correspondant au scénario de terrain indiquent que l'approche d'intégration des données nouvellement mise au point est capable d'appréhender correctement les hétérogénéitées à petite échelle aussi bien que les tendances à gande échelle du champ hydraulique prévalent. Les résultats montrent également une flexibilté remarquable et une robustesse de cette nouvelle approche dintégration des données. De ce fait, elle est susceptible d'être appliquée à un large éventail de données géophysiques et hydrologiques, à toutes les gammes déchelles. Dans la deuxième partie de ma thèse, j'évalue en détail la viabilité du réechantillonnage geostatique séquentiel comme mécanisme de proposition pour les méthodes Markov Chain Monte Carlo (MCMC) appliquées à des probmes inverses géophysiques et hydrologiques de grande dimension . L'objectif est de permettre une quantification plus précise et plus réaliste des incertitudes associées aux modèles obtenus. En considérant une série dexemples de tomographic radar puits à puits, j'étudie deux classes de stratégies de rééchantillonnage spatial en considérant leur habilité à générer efficacement et précisément des réalisations de la distribution postérieure bayésienne. Les résultats obtenus montrent que, malgré sa popularité, le réechantillonnage séquentiel est plutôt inefficace à générer des échantillons postérieurs indépendants pour des études de cas synthétiques réalistes, notamment pour le cas assez communs et importants où il existe de fortes corrélations spatiales entre le modèle et les paramètres. Pour résoudre ce problème, j'ai développé un nouvelle approche de perturbation basée sur une déformation progressive. Cette approche est flexible en ce qui concerne le nombre de paramètres du modèle et lintensité de la perturbation. Par rapport au rééchantillonage séquentiel, cette nouvelle approche s'avère être très efficace pour diminuer le nombre requis d'itérations pour générer des échantillons indépendants à partir de la distribution postérieure bayésienne. - Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending corresponding approaches beyond the local scale still represents a major challenge, yet is critically important for the development of reliable groundwater flow and contaminant transport models. To address this issue, I have developed a hydrogeophysical data integration technique based on a two-step Bayesian sequential simulation procedure that is specifically targeted towards larger-scale problems. The objective is to simulate the distribution of a target hydraulic parameter based on spatially exhaustive, but poorly resolved, measurements of a pertinent geophysical parameter and locally highly resolved, but spatially sparse, measurements of the considered geophysical and hydraulic parameters. To this end, my algorithm links the low- and high-resolution geophysical data via a downscaling procedure before relating the downscaled regional-scale geophysical data to the high-resolution hydraulic parameter field. I first illustrate the application of this novel data integration approach to a realistic synthetic database consisting of collocated high-resolution borehole measurements of the hydraulic and electrical conductivities and spatially exhaustive, low-resolution electrical conductivity estimates obtained from electrical resistivity tomography (ERT). The overall viability of this method is tested and verified by performing and comparing flow and transport simulations through the original and simulated hydraulic conductivity fields. The corresponding results indicate that the proposed data integration procedure does indeed allow for obtaining faithful estimates of the larger-scale hydraulic conductivity structure and reliable predictions of the transport characteristics over medium- to regional-scale distances. The approach is then applied to a corresponding field scenario consisting of collocated high- resolution measurements of the electrical conductivity, as measured using a cone penetrometer testing (CPT) system, and the hydraulic conductivity, as estimated from electromagnetic flowmeter and slug test measurements, in combination with spatially exhaustive low-resolution electrical conductivity estimates obtained from surface-based electrical resistivity tomography (ERT). The corresponding results indicate that the newly developed data integration approach is indeed capable of adequately capturing both the small-scale heterogeneity as well as the larger-scale trend of the prevailing hydraulic conductivity field. The results also indicate that this novel data integration approach is remarkably flexible and robust and hence can be expected to be applicable to a wide range of geophysical and hydrological data at all scale ranges. In the second part of my thesis, I evaluate in detail the viability of sequential geostatistical resampling as a proposal mechanism for Markov Chain Monte Carlo (MCMC) methods applied to high-dimensional geophysical and hydrological inverse problems in order to allow for a more accurate and realistic quantification of the uncertainty associated with the thus inferred models. Focusing on a series of pertinent crosshole georadar tomographic examples, I investigated two classes of geostatistical resampling strategies with regard to their ability to efficiently and accurately generate independent realizations from the Bayesian posterior distribution. The corresponding results indicate that, despite its popularity, sequential resampling is rather inefficient at drawing independent posterior samples for realistic synthetic case studies, notably for the practically common and important scenario of pronounced spatial correlation between model parameters. To address this issue, I have developed a new gradual-deformation-based perturbation approach, which is flexible with regard to the number of model parameters as well as the perturbation strength. Compared to sequential resampling, this newly proposed approach was proven to be highly effective in decreasing the number of iterations required for drawing independent samples from the Bayesian posterior distribution.

The MIGCLIM R package - seamless integration of dispersal constraints into projections of species distribution models

The MIGCLIM R package is a function library for the open source R software that enables the implementation of species-specific dispersal constraints into projections of species distribution models under environmental change and/or landscape fragmentation scenarios. The model is based on a cellular automaton and the basic modeling unit is a cell that is inhabited or not. Model parameters include dispersal distance and kernel, long distance dispersal, barriers to dispersal, propagule production potential and habitat invasibility. The MIGCLIM R package has been designed to be highly flexible in the parameter values it accepts, and to offer good compatibility with existing species distribution modeling software. Possible applications include the projection of future species distributions under environmental change conditions and modeling the spread of invasive species.

Report of the Working Group to examine the development of appropriate systems to determine nursing and midwifery staffing levels

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Regional-scale integration of multi-scale hydrological and geophysical data using a two-step Bayesian sequential simulation approach

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale for the purpose of improving predictions of groundwater flow and solute transport. However, extending corresponding approaches to the regional scale still represents one of the major challenges in the domain of hydrogeophysics. To address this problem, we have developed a regional-scale data integration methodology based on a two-step Bayesian sequential simulation approach. Our objective is to generate high-resolution stochastic realizations of the regional-scale hydraulic conductivity field in the common case where there exist spatially exhaustive but poorly resolved measurements of a related geophysical parameter, as well as highly resolved but spatially sparse collocated measurements of this geophysical parameter and the hydraulic conductivity. To integrate this multi-scale, multi-parameter database, we first link the low- and high-resolution geophysical data via a stochastic downscaling procedure. This is followed by relating the downscaled geophysical data to the high-resolution hydraulic conductivity distribution. After outlining the general methodology of the approach, we demonstrate its application to a realistic synthetic example where we consider as data high-resolution measurements of the hydraulic and electrical conductivities at a small number of borehole locations, as well as spatially exhaustive, low-resolution estimates of the electrical conductivity obtained from surface-based electrical resistivity tomography. The different stochastic realizations of the hydraulic conductivity field obtained using our procedure are validated by comparing their solute transport behaviour with that of the underlying ?true? hydraulic conductivity field. We find that, even in the presence of strong subsurface heterogeneity, our proposed procedure allows for the generation of faithful representations of the regional-scale hydraulic conductivity structure and reliable predictions of solute transport over long, regional-scale distances.

The profiling of MDMA tablets: a study of the combination of physical characteristics and organic impurities as sources of information

The profiling of MDMA tablets can be carried out using different sets of characteristics. The first type of measurements performed on MDMA tablets are physical characteristics (i.e. post-tabletting characteristics). They yield preliminary profiling data that may be valuable in a first stage for investigation purposes. However organic impurities (i.e. pre-tabletting characteristics) are generally considered to bring more reliable information, particularly for presentation of evidence in court. This work aimed therefore at evaluating the added value of combining pre-tabletting characteristics and post-tabletting characteristics of seized MDMA tablets. In approximately half of the investigated cases, the post-tabletting links were confirmed with organic impurities analyses. In the remaining cases, post-tabletting batches (post-TBs) were divided in several pre-tabletting batches (pre-TBs), thus supporting the hypothesis that several production batches of MDMA powder (pre-TBs) were used to produce one single post-TB (i.e. tablets having the same shape, diameter, thickness, weight and score; but different organic impurities composition). In view of the obtained results, the hypotheses were discussed through illustrating examples. In conclusion, both sets of characteristics were found relevant alone and combined together. They actually provide distinct information about MDMA illicit production and trafficking.

Geographic patterns in the distribution of social systems in terrestrial arthropods.

The role of ecology in the evolution and maintenance of arthropod sociality has received increasing research attention in recent years. In some organisms, such as halictine bees, polistine wasps, and social spiders, researchers are investigating the environmental factors that may contribute to high levels of variation in the degree of sociality exhibited both among and within species. Within lineages that include only eusocial members, such as ants and termites, studies focus more on identifying extrinsic factors that may contribute to the dramatic variation in colony size, number of queens, and division of labour that is evident across these species. In this review, I propose a comparative approach that seeks to identify environmental factors that may have a common influence across such divergent social arthropod groups. I suggest that seeking common biogeographic patterns in the distribution of social systems or key social traits may help us to identify ecological factors that play a common role in shaping the evolution of sociality across different organisms. I first review previous studies of social gradients that form along latitudinal and altitudinal axes. Within families and within species, many organisms show an increasing degree of sociality at lower latitudes and altitudes. In a smaller number of cases, organisms form larger groups or found nests cooperatively at higher latitudes and altitudes. I then describe several environmental factors that vary consistently along such gradients, including climate variables and abundance of predators, and outline their proposed role in the social systems of terrestrial arthropods. Finally, I map distributions of a social trait against several climatic factors in five case studies to demonstrate how future comparative studies could inform empirical research.

Is hospital discharge administrative data an appropriate source of information for cancer registries purposes? Some insights from four Spanish registries

Background. The use of hospital discharge administrative data (HDAD) has been recommended for automating, improving, even substituting, population-based cancer registries. The frequency of false positive and false negative cases recommends local validation. Methods. The aim of this study was to detect newly diagnosed, false positive and false negative cases of cancer from hospital discharge claims, using four Spanish population-based cancer registries as the gold standard. Prostate cancer was used as a case study. Results. A total of 2286 incident cases of prostate cancer registered in 2000 were used for validation. In the most sensitive algorithm (that using five diagnostic codes), estimates for Sensitivity ranged from 14.5% (CI95% 10.3-19.6) to 45.7% (CI95% 41.4-50.1). In the most predictive algorithm (that using five diagnostic and five surgical codes) Positive Predictive Value estimates ranged from 55.9% (CI95% 42.4-68.8) to 74.3% (CI95% 67.0-80.6). The most frequent reason for false positive cases was the number of prevalent cases inadequately considered as newly diagnosed cancers, ranging from 61.1% to 82.3% of false positive cases. The most frequent reason for false negative cases was related to the number of cases not attended in hospital settings. In this case, figures ranged from 34.4% to 69.7% of false negative cases, in the most predictive algorithm. Conclusions. HDAD might be a helpful tool for cancer registries to reach their goals. The findings suggest that, for automating cancer registries, algorithms combining diagnoses and procedures are the best option. However, for cancer surveillance purposes, in those cancers like prostate cancer in which care is not only hospital-based, combining inpatient and outpatient information will be required.

The Role of Information in Contemporary Migration. More Sources but Less Informed

La migració internacional contemporània és integrada en un procés d'interconnexió global definit per les revolucions del transport i de les tecnologies de la informació i la comunicació. Una de les conseqüències d'aquesta interconnexió global és que les persones migrants tenen més capacitat per a processar informació tant abans com després de marxar. Aquests canvis podrien tenir implicacions inesperades per a la migració contemporània pel que fa a la capacitat de les persones migrants per a prendre decisions més informades, la reducció de la incertesa en contextos migratoris, el desdibuixament del concepte de distància o la decisió d'emigrar cap a llocs més llunyans. Aquesta recerca és important, ja que la manca de coneixement sobre aquesta qüestió podria contribuir a fer augmentar la distància entre els objectius de les polítiques de migració i els seus resultats. El paper que tenen els agents de la informació en els contextos migratoris també podria canviar. En aquest escenari, perquè les polítiques de migració siguin més efectives, s'haurà de tenir en compte la major capacitat de la població migrant de processar la informació i les fonts d'informació en què es confia. Aquest article demostra que l'equació més informació equival a més ben informat no es compleix sempre. Fins i tot en l'era de la informació, les fonts no fiables, les expectatives falses, la sobreinformació i els rumors encara són presents en els contextos migratoris. Tanmateix, defensem l'argument que aquests efectes no volguts es podrien reduir complint quatre requisits de la informació fiable: que sigui exhaustiva, que sigui rellevant, que s'hi confiï i que sigui actualitzada.