Report of the Expert Group on Resource Allocation and Financing in the Health Sector

  Report of the Expert Group on Resource Allocation and Financing in the Health Sector Download this document (PDF 4.77mb) Alternatively, there is a lower resolution version available (PDF 2.31mb) Related Documents Resource Allocation, Financing and Sustainability in Health Care Evidence for the Expert Group on Resource Allocation and Financing in the Health Sector (Volume I) – PDF, 4.25mbAlternatively, a Lower Resolution version is available – PDF, 2.23mb Resource Allocation, Financing and Sustainability in Health Care Evidence for the Expert Group on Resource Allocation and Financing in the Health Sector (Volume II) – PDF 4.87mbAlternatively, a Lower Resolution version is available – PDF, 2.65mb Presentation by Professor, Frances Ruane Director , ESRI and Chair of the Expert Group. PDF 235KB Presentation by Professor Charles Normand, a member of the Expert Group. PDF 32KB

Bonding and Bridging Social Capital in Step- and First-Time Families and the Issue of Family Boundaries

Divorce and remarriage usually imply a redefinition of family boundaries, with consequences for the production and availability of social capital. This research shows that bonding and bridging social capitals are differentially made available by families. It first hypothesizes that bridging social capital is more likely to be developed in stepfamilies, and bonding social capital in first-time families. Second, the boundaries of family configurations are expected to vary within stepfamilies and within first-time families creating a diversity of family configurations within both structures. Third, in both cases, social capital is expected to depend on the ways in which their family boundaries are set up by individuals by including or excluding ex-partners, new partner's children, siblings, and other family ties. The study is based on a sample of 300 female respondents who have at least one child of their own between 5 and 13 years, 150 from a stepfamily structure and 150 from a first-time family structure. Social capital is empirically operationalized as perceived emotional support in family networks. The results show that individuals in first-time families more often develop bonding social capital and individuals in stepfamilies bridging social capital. In both cases, however, individuals in family configurations based on close blood and conjugal ties more frequently develop bonding social capital, whereas individuals in family configurations based on in-law, stepfamily or friendship ties are more likely to develop bridging social capital.

Losing Track of Time: Dementia and the ageing prison population

Dementia and the ageing prison population: treatment challenges and examples of good practice.The aims of this report are to scope existing research on treating and managing male offenders with cognitive impairment to identify and share examples of good practice employed by a handful of prisons around the globe.Read full report here (pdf).��

Effects of exaggerated amino acid and protein supply in man.

A general update review of the dynamic aspect of protein metabolism is presented. The effect of excess protein level on protein metabolism has been the object of a limited number of studies in man. From the information available, it appears that the primary regulatory pathway for body protein homeostasis is the process of amino acid (protein) oxidation.

Space-time relatedness and Hamilton's rule for long-lasting behaviors in viscous populations.

Genes affect not only the behavior and fitness of their carriers but also that of other individuals. According to Hamilton's rule, whether a mutant gene will spread in the gene pool depends on the effects of its carrier on the fitness of all individuals in the population, each weighted by its relatedness to the carrier. However, social behaviors may affect not only recipients living in the generation of the actor but also individuals living in subsequent generations. In this note, I evaluate space-time relatedness coefficients for localized dispersal. These relatedness coefficients weight the selection pressures on long-lasting behaviors, which stem from a multigenerational gap between phenotypic expression by actors and the resulting environmental feedback on the fitness of recipients. Explicit values of space-time relatedness coefficients reveal that they can be surprisingly large for typical dispersal rates, even for hundreds of generations in the future.

Do plants adjust their sex allocation and secondary sexual morphology in response to their neighbours?

BACKGROUND AND AIMS: Changes in the sex allocation (i.e. in pollen versus seed production) of hermaphroditic plants often occur in response to the environment. In some homosporous ferns, gametophytes choose their gender in response to chemical cues sent by neighbours, such that spores develop as male gametophytes if they perceive a female or hermaphrodite nearby. Here it is considered whether a similar process might occur in the androdioecious angiosperm species Mercurialis annua, in which males co-occur with hermaphrodites; previous work on a Spanish population of M. annua found that individuals were more likely to develop as males at high density. METHODS: Using a novel approach to treat plants with leachate from pots containing males or hermaphrodites of M. annua, the hypothesis that individuals assess their mating opportunities, and adjust their sex expression accordingly, was tested through an exchange of chemical cues through the soil. KEY RESULTS: For the population under study, from Morocco, no evidence was found for soil-signal-dependent sex expression: neither sex ratios nor sex allocation differed among experimental treatments. CONCLUSIONS: The results imply either that the Moroccan population under study behaves differently from that previously studied in Spain (pointing to potential geographical variation in plasticity for sex expression), or that our method failed to capture the signals used by M. annua for adjustment of sex expression.

Development of a new chlamydiales-specific real-time PCR and its application to respiratory clinical samples.

Originally composed of the single family Chlamydiaceae, the Chlamydiales order has extended considerably over the last several decades. Chlamydia-related bacteria were added and classified into six different families and family-level lineages: the Criblamydiaceae, Parachlamydiaceae, Piscichlamydiaceae, Rhabdochlamydiaceae, Simkaniaceae, and Waddliaceae. While several members of the Chlamydiaceae family are known pathogens, recent studies showed diverse associations of Chlamydia-related bacteria with human and animal infections. Some of these latter bacteria might be of medical importance since, given their ability to replicate in free-living amoebae, they may also replicate efficiently in other phagocytic cells, including cells of the innate immune system. Thus, a new Chlamydiales-specific real-time PCR targeting the conserved 16S rRNA gene was developed. This new molecular tool can detect at least five DNA copies and show very high specificity without cross-amplification from other bacterial clade DNA. The new PCR was validated with 128 clinical samples positive or negative for Chlamydia trachomatis or C. pneumoniae. Of 65 positive samples, 61 (93.8%) were found to be positive with the new PCR. The four discordant samples, retested with the original test, were determined to be negative or below detection limits. Then, the new PCR was applied to 422 nasopharyngeal swabs taken from children with or without pneumonia; a total of 48 (11.4%) samples were determined to be positive, and 45 of these were successfully sequenced. The majority of the sequences corresponded to Chlamydia-related bacteria and especially to members of the Parachlamydiaceae family.

Predictability of music descriptor time series and its application to cover song detection

Intuitively, music has both predictable and unpredictable components. In this work we assess this qualitative statement in a quantitative way using common time series models fitted to state-of-the-art music descriptors. These descriptors cover different musical facets and are extracted from a large collection of real audio recordings comprising a variety of musical genres. Our findings show that music descriptor time series exhibit a certain predictability not only for short time intervals, but also for mid-term and relatively long intervals. This fact is observed independently of the descriptor, musical facet and time series model we consider. Moreover, we show that our findings are not only of theoretical relevance but can also have practical impact. To this end we demonstrate that music predictability at relatively long time intervals can be exploited in a real-world application, namely the automatic identification of cover songs (i.e. different renditions or versions of the same musical piece). Importantly, this prediction strategy yields a parameter-free approach for cover song identification that is substantially faster, allows for reduced computational storage and still maintains highly competitive accuracies when compared to state-of-the-art systems.

Macroprudential policy, countercyclical bank capital buffers and credit supply: Evidence from the Spanish dynamic provisioning experiments

We analyze the impact of countercyclical capital buffers held by banks on the supplyof credit to firms and their subsequent performance. Spain introduced dynamicprovisioning unrelated to specific bank loan losses in 2000 and modified its formulaparameters in 2005 and 2008. In each case, individual banks were impacteddifferently. The resultant bank-specific shocks to capital buffers, coupled withcomprehensive bank-, firm-, loan-, and loan application-level data, allow us toidentify its impact on the supply of credit and on real activity. Our estimates showthat countercyclical dynamic provisioning smooths cycles in the supply of credit andin bad times upholds firm financing and performance.

Sex allocation and sex-dependent selection for body size in Trypoxylon rogenhoferi Kohl (Hymenoptera, Sphecidae)

Two populations of the wasp Trypoxylon rogenhoferi Kohl, 1884 from São Carlos and Luís Antônio, State of São Paulo, Brazil, were observed and sampled from May 1999 to February 2001 using trap-nests. This mass-provisioning wasp was used to test some aspects of optimal sex allocation theory. Both populations fit all the predictions of the models of Green and Brockmann and Grafen. Maternal provisions determined the size of each offspring, and females allocated well-stocked brood cells to daughters, the sex that benefits most being large. This strategy resulted in a difference in size between the sexes. In São Carlos, female weight at emergence was 1.18 times that of males, in Luís Antônio this value was 1.13. The brood cell volume was correlated with both wing length and weight at emergence in both sexes, and the chance that a given brood cell contained a male offspring decreased with increased brood cell volume. In T. rogenhoferi female body size was related to fitness. Larger females were able to collect more mass of spiders per day, the spiders they captured were heavier, and they provisioned more brood cells per day. They also produced larger daughters. For males, no relationship between body size and fitness was found, but the data were scarce. Since the patterns of provisioning were variable among different females in both study sites, it is possible that the females not follow a unique strategy for sex allocation. The sex ratio and/or investment ratio in the São Carlos population was female-biased and in Luís Antônio, male-biased. In spite of the influence of trap-nests diameters on male production in Luís Antônio, there is some evidence that in São Carlos population the local availability of prey and/or lower rate of parasitism may be major forces in determining the observed sex ratio, but further studies are necessary to verify such hypothesis.

Product market deregulation and labor market outcomes

We consider the dynamic relationship between product market entry regulationand equilibrium unemployment. The main theoretical contribution is combininga Mortensen-Pissarides model with monopolistic competition in the goods marketand individual wage bargaining. Product market competition affects unemploymentvia two channels: the output expansion effect and a countervailing effect dueto a hiring externality. Competition is then linked to barriers to entry. Acalibrated model compares a high-regulation European regime to a low-regulationAnglo-American one. Our quantitative analysis suggests that under individualbargaining, no more than half a percentage point of European unemployment ratescan be attributed to entry regulation.

Interest rate restrictions in a natural experiment: loan allocation and the change in the usury laws in 1714

This article studies the effects of interest rate restrictions on loan allocation. The British governmenttightened the usury laws in 1714, reducing the maximum permissible interest rate from 6% to5%. A sample of individual loan transactions reveals that average loan size and minimum loan sizeincreased strongly, while access to credit worsened for those with little social capital. Collateralisedcredits, which had accounted for a declining share of total lending, returned to their former role ofprominence. Our results suggest that the usury laws distorted credit markets significantly; we findno evidence that they offered a form of Pareto-improving social insurance.

Minimum price variations, time priority and quotes dynamics

We analyze the impact of a minimum price variation (tick) and timepriority on the dynamics of quotes and the trading costs when competitionfor the order flow is dynamic. We find that convergence to competitiveoutcomes can take time and that the speed of convergence is influencedby the tick size, the priority rule and the characteristics of the orderarrival process. We show also that a zero minimum price variation is neveroptimal when competition for the order flow is dynamic. We compare thetrading outcomes with and without time priority. Time priority is shownto guarantee that uncompetitive spreads cannot be sustained over time.However it can sometimes result in higher trading costs. Empiricalimplications are proposed. In particular, we relate the size of thetrading costs to the frequency of new offers and the dynamics of theinside spread to the state of the book.

Parental altruism under imperfect information: Theory and evidence

Can we reconcile the predictions of the altruism model of the family withthe evidence on parental monetary transfers in the US? This paper providesa new assessment of this question. I expand the altruism model by introducingeffort of the child and by relaxing the assumption of perfect informationof the parent about the labor market opportunities of the child. First,I solve and simulate a model of altruism and labor supply under imperfectinformation. Second, I use cross-sectional data to test the following prediction of the model: Are parental transfers especially responsive tothe income variations of children who are very attached to the labor market? The results of the analysis suggest that imperfect informationaccounts for many of the patterns of intergenerational transfers in theUS.

Time-lapse and probabilistic inversion strategies for plane-wave electromagnetic data.

L'utilisation efficace des systèmes géothermaux, la séquestration du CO2 pour limiter le changement climatique et la prévention de l'intrusion d'eau salée dans les aquifères costaux ne sont que quelques exemples qui démontrent notre besoin en technologies nouvelles pour suivre l'évolution des processus souterrains à partir de la surface. Un défi majeur est d'assurer la caractérisation et l'optimisation des performances de ces technologies à différentes échelles spatiales et temporelles. Les méthodes électromagnétiques (EM) d'ondes planes sont sensibles à la conductivité électrique du sous-sol et, par conséquent, à la conductivité électrique des fluides saturant la roche, à la présence de fractures connectées, à la température et aux matériaux géologiques. Ces méthodes sont régies par des équations valides sur de larges gammes de fréquences, permettant détudier de manières analogues des processus allant de quelques mètres sous la surface jusqu'à plusieurs kilomètres de profondeur. Néanmoins, ces méthodes sont soumises à une perte de résolution avec la profondeur à cause des propriétés diffusives du champ électromagnétique. Pour cette raison, l'estimation des modèles du sous-sol par ces méthodes doit prendre en compte des informations a priori afin de contraindre les modèles autant que possible et de permettre la quantification des incertitudes de ces modèles de façon appropriée. Dans la présente thèse, je développe des approches permettant la caractérisation statique et dynamique du sous-sol à l'aide d'ondes EM planes. Dans une première partie, je présente une approche déterministe permettant de réaliser des inversions répétées dans le temps (time-lapse) de données d'ondes EM planes en deux dimensions. Cette stratégie est basée sur l'incorporation dans l'algorithme d'informations a priori en fonction des changements du modèle de conductivité électrique attendus. Ceci est réalisé en intégrant une régularisation stochastique et des contraintes flexibles par rapport à la gamme des changements attendus en utilisant les multiplicateurs de Lagrange. J'utilise des normes différentes de la norme l2 pour contraindre la structure du modèle et obtenir des transitions abruptes entre les régions du model qui subissent des changements dans le temps et celles qui n'en subissent pas. Aussi, j'incorpore une stratégie afin d'éliminer les erreurs systématiques de données time-lapse. Ce travail a mis en évidence l'amélioration de la caractérisation des changements temporels par rapport aux approches classiques qui réalisent des inversions indépendantes à chaque pas de temps et comparent les modèles. Dans la seconde partie de cette thèse, j'adopte un formalisme bayésien et je teste la possibilité de quantifier les incertitudes sur les paramètres du modèle dans l'inversion d'ondes EM planes. Pour ce faire, je présente une stratégie d'inversion probabiliste basée sur des pixels à deux dimensions pour des inversions de données d'ondes EM planes et de tomographies de résistivité électrique (ERT) séparées et jointes. Je compare les incertitudes des paramètres du modèle en considérant différents types d'information a priori sur la structure du modèle et différentes fonctions de vraisemblance pour décrire les erreurs sur les données. Les résultats indiquent que la régularisation du modèle est nécessaire lorsqu'on a à faire à un large nombre de paramètres car cela permet d'accélérer la convergence des chaînes et d'obtenir des modèles plus réalistes. Cependent, ces contraintes mènent à des incertitudes d'estimations plus faibles, ce qui implique des distributions a posteriori qui ne contiennent pas le vrai modèledans les régions ou` la méthode présente une sensibilité limitée. Cette situation peut être améliorée en combinant des méthodes d'ondes EM planes avec d'autres méthodes complémentaires telles que l'ERT. De plus, je montre que le poids de régularisation des paramètres et l'écart-type des erreurs sur les données peuvent être retrouvés par une inversion probabiliste. Finalement, j'évalue la possibilité de caractériser une distribution tridimensionnelle d'un panache de traceur salin injecté dans le sous-sol en réalisant une inversion probabiliste time-lapse tridimensionnelle d'ondes EM planes. Etant donné que les inversions probabilistes sont très coûteuses en temps de calcul lorsque l'espace des paramètres présente une grande dimension, je propose une stratégie de réduction du modèle ou` les coefficients de décomposition des moments de Legendre du panache de traceur injecté ainsi que sa position sont estimés. Pour ce faire, un modèle de résistivité de base est nécessaire. Il peut être obtenu avant l'expérience time-lapse. Un test synthétique montre que la méthodologie marche bien quand le modèle de résistivité de base est caractérisé correctement. Cette méthodologie est aussi appliquée à un test de trac¸age par injection d'une solution saline et d'acides réalisé dans un système géothermal en Australie, puis comparée à une inversion time-lapse tridimensionnelle réalisée selon une approche déterministe. L'inversion probabiliste permet de mieux contraindre le panache du traceur salin gr^ace à la grande quantité d'informations a priori incluse dans l'algorithme. Néanmoins, les changements de conductivités nécessaires pour expliquer les changements observés dans les données sont plus grands que ce qu'expliquent notre connaissance actuelle des phénomenès physiques. Ce problème peut être lié à la qualité limitée du modèle de résistivité de base utilisé, indiquant ainsi que des efforts plus grands devront être fournis dans le futur pour obtenir des modèles de base de bonne qualité avant de réaliser des expériences dynamiques. Les études décrites dans cette thèse montrent que les méthodes d'ondes EM planes sont très utiles pour caractériser et suivre les variations temporelles du sous-sol sur de larges échelles. Les présentes approches améliorent l'évaluation des modèles obtenus, autant en termes d'incorporation d'informations a priori, qu'en termes de quantification d'incertitudes a posteriori. De plus, les stratégies développées peuvent être appliquées à d'autres méthodes géophysiques, et offrent une grande flexibilité pour l'incorporation d'informations additionnelles lorsqu'elles sont disponibles. -- The efficient use of geothermal systems, the sequestration of CO2 to mitigate climate change, and the prevention of seawater intrusion in coastal aquifers are only some examples that demonstrate the need for novel technologies to monitor subsurface processes from the surface. A main challenge is to assure optimal performance of such technologies at different temporal and spatial scales. Plane-wave electromagnetic (EM) methods are sensitive to subsurface electrical conductivity and consequently to fluid conductivity, fracture connectivity, temperature, and rock mineralogy. These methods have governing equations that are the same over a large range of frequencies, thus allowing to study in an analogous manner processes on scales ranging from few meters close to the surface down to several hundreds of kilometers depth. Unfortunately, they suffer from a significant resolution loss with depth due to the diffusive nature of the electromagnetic fields. Therefore, estimations of subsurface models that use these methods should incorporate a priori information to better constrain the models, and provide appropriate measures of model uncertainty. During my thesis, I have developed approaches to improve the static and dynamic characterization of the subsurface with plane-wave EM methods. In the first part of this thesis, I present a two-dimensional deterministic approach to perform time-lapse inversion of plane-wave EM data. The strategy is based on the incorporation of prior information into the inversion algorithm regarding the expected temporal changes in electrical conductivity. This is done by incorporating a flexible stochastic regularization and constraints regarding the expected ranges of the changes by using Lagrange multipliers. I use non-l2 norms to penalize the model update in order to obtain sharp transitions between regions that experience temporal changes and regions that do not. I also incorporate a time-lapse differencing strategy to remove systematic errors in the time-lapse inversion. This work presents improvements in the characterization of temporal changes with respect to the classical approach of performing separate inversions and computing differences between the models. In the second part of this thesis, I adopt a Bayesian framework and use Markov chain Monte Carlo (MCMC) simulations to quantify model parameter uncertainty in plane-wave EM inversion. For this purpose, I present a two-dimensional pixel-based probabilistic inversion strategy for separate and joint inversions of plane-wave EM and electrical resistivity tomography (ERT) data. I compare the uncertainties of the model parameters when considering different types of prior information on the model structure and different likelihood functions to describe the data errors. The results indicate that model regularization is necessary when dealing with a large number of model parameters because it helps to accelerate the convergence of the chains and leads to more realistic models. These constraints also lead to smaller uncertainty estimates, which imply posterior distributions that do not include the true underlying model in regions where the method has limited sensitivity. This situation can be improved by combining planewave EM methods with complimentary geophysical methods such as ERT. In addition, I show that an appropriate regularization weight and the standard deviation of the data errors can be retrieved by the MCMC inversion. Finally, I evaluate the possibility of characterizing the three-dimensional distribution of an injected water plume by performing three-dimensional time-lapse MCMC inversion of planewave EM data. Since MCMC inversion involves a significant computational burden in high parameter dimensions, I propose a model reduction strategy where the coefficients of a Legendre moment decomposition of the injected water plume and its location are estimated. For this purpose, a base resistivity model is needed which is obtained prior to the time-lapse experiment. A synthetic test shows that the methodology works well when the base resistivity model is correctly characterized. The methodology is also applied to an injection experiment performed in a geothermal system in Australia, and compared to a three-dimensional time-lapse inversion performed within a deterministic framework. The MCMC inversion better constrains the water plumes due to the larger amount of prior information that is included in the algorithm. The conductivity changes needed to explain the time-lapse data are much larger than what is physically possible based on present day understandings. This issue may be related to the base resistivity model used, therefore indicating that more efforts should be given to obtain high-quality base models prior to dynamic experiments. The studies described herein give clear evidence that plane-wave EM methods are useful to characterize and monitor the subsurface at a wide range of scales. The presented approaches contribute to an improved appraisal of the obtained models, both in terms of the incorporation of prior information in the algorithms and the posterior uncertainty quantification. In addition, the developed strategies can be applied to other geophysical methods, and offer great flexibility to incorporate additional information when available.