Enhanced Model Selection for motion segmentation

In this paper a novel rank estimation technique for trajectories motion segmentation within the Local Subspace Affinity (LSA) framework is presented. This technique, called Enhanced Model Selection (EMS), is based on the relationship between the estimated rank of the trajectory matrix and the affinity matrix built by LSA. The results on synthetic and real data show that without any a priori knowledge, EMS automatically provides an accurate and robust rank estimation, improving the accuracy of the final motion segmentation

Subjective health assessments and active labor market participation of older men: evidence from a semiparametric binary choice model with nonadditive correlated individual-specific effects

We use panel data from the U. S. Health and Retirement Study, 1992-2002, to estimate the effect of self-assessed health limitations on the active labor market participation of older men. Self-assessments of health are likely to be endogenous to labor supply due to justification bias and individual-specific heterogeneity in subjective evaluations. We address both concerns. We propose a semiparametric binary choice procedure that incorporates nonadditive correlated individual-specific effects. Our estimation strategy identifies and estimates the average partial effects of health and functioning on labor market participation. The results indicate that poor health plays a major role in labor market exit decisions.

Dense Deformation Field Estimation for Atlas Registration using the Active Contour Framework

In this paper, we propose a new paradigm to carry outthe registration task with a dense deformation fieldderived from the optical flow model and the activecontour method. The proposed framework merges differenttasks such as segmentation, regularization, incorporationof prior knowledge and registration into a singleframework. The active contour model is at the core of ourframework even if it is used in a different way than thestandard approaches. Indeed, active contours are awell-known technique for image segmentation. Thistechnique consists in finding the curve which minimizesan energy functional designed to be minimal when thecurve has reached the object contours. That way, we getaccurate and smooth segmentation results. So far, theactive contour model has been used to segment objectslying in images from boundary-based, region-based orshape-based information. Our registration technique willprofit of all these families of active contours todetermine a dense deformation field defined on the wholeimage. A well-suited application of our model is theatlas registration in medical imaging which consists inautomatically delineating anatomical structures. Wepresent results on 2D synthetic images to show theperformances of our non rigid deformation field based ona natural registration term. We also present registrationresults on real 3D medical data with a large spaceoccupying tumor substantially deforming surroundingstructures, which constitutes a high challenging problem.

Adaptively weighted maximum likelihood estimation of discrete distributions

SummaryDiscrete data arise in various research fields, typically when the observations are count data.I propose a robust and efficient parametric procedure for estimation of discrete distributions. The estimation is done in two phases. First, a very robust, but possibly inefficient, estimate of the model parameters is computed and used to indentify outliers. Then the outliers are either removed from the sample or given low weights, and a weighted maximum likelihood estimate (WML) is computed.The weights are determined via an adaptive process such that if the data follow the model, then asymptotically no observation is downweighted.I prove that the final estimator inherits the breakdown point of the initial one, and that its influence function at the model is the same as the influence function of the maximum likelihood estimator, which strongly suggests that it is asymptotically fully efficient.The initial estimator is a minimum disparity estimator (MDE). MDEs can be shown to have full asymptotic efficiency, and some MDEs have very high breakdown points and very low bias under contamination. Several initial estimators are considered, and the performances of the WMLs based on each of them are studied.It results that in a great variety of situations the WML substantially improves the initial estimator, both in terms of finite sample mean square error and in terms of bias under contamination. Besides, the performances of the WML are rather stable under a change of the MDE even if the MDEs have very different behaviors.Two examples of application of the WML to real data are considered. In both of them, the necessity for a robust estimator is clear: the maximum likelihood estimator is badly corrupted by the presence of a few outliers.This procedure is particularly natural in the discrete distribution setting, but could be extended to the continuous case, for which a possible procedure is sketched.RésuméLes données discrètes sont présentes dans différents domaines de recherche, en particulier lorsque les observations sont des comptages.Je propose une méthode paramétrique robuste et efficace pour l'estimation de distributions discrètes. L'estimation est faite en deux phases. Tout d'abord, un estimateur très robuste des paramètres du modèle est calculé, et utilisé pour la détection des données aberrantes (outliers). Cet estimateur n'est pas nécessairement efficace. Ensuite, soit les outliers sont retirés de l'échantillon, soit des faibles poids leur sont attribués, et un estimateur du maximum de vraisemblance pondéré (WML) est calculé.Les poids sont déterminés via un processus adaptif, tel qu'asymptotiquement, si les données suivent le modèle, aucune observation n'est dépondérée.Je prouve que le point de rupture de l'estimateur final est au moins aussi élevé que celui de l'estimateur initial, et que sa fonction d'influence au modèle est la même que celle du maximum de vraisemblance, ce qui suggère que cet estimateur est pleinement efficace asymptotiquement.L'estimateur initial est un estimateur de disparité minimale (MDE). Les MDE sont asymptotiquement pleinement efficaces, et certains d'entre eux ont un point de rupture très élevé et un très faible biais sous contamination. J'étudie les performances du WML basé sur différents MDEs.Le résultat est que dans une grande variété de situations le WML améliore largement les performances de l'estimateur initial, autant en terme du carré moyen de l'erreur que du biais sous contamination. De plus, les performances du WML restent assez stables lorsqu'on change l'estimateur initial, même si les différents MDEs ont des comportements très différents.Je considère deux exemples d'application du WML à des données réelles, où la nécessité d'un estimateur robuste est manifeste : l'estimateur du maximum de vraisemblance est fortement corrompu par la présence de quelques outliers.La méthode proposée est particulièrement naturelle dans le cadre des distributions discrètes, mais pourrait être étendue au cas continu.

A model for physical activity, bahaviour and energy expenditure assessment in real-life condition

RésuméL'origine de l'obésité, qui atteint des proportions épidémiques, est complexe. Elle est liée au mode de vie et au comportement des individus par rapport à l'activité physique, expression des choix individuels et de l'interaction avec l'environnement. Les mesures du comportement au niveau de l'activité physique des individus face à leur environnement, la répartition des types d'activité physique, la durée, la fréquence, l'intensité, et la dépense énergétique sont d'une grande importance. Aujourd'hui, il y a un manque de méthodes permettant une évaluation précise et objective de l'activité physique et du comportement des individus. Afin de compléter les recherches relatives à l'activité physique, à l'obésité et à certaines maladies, le premier objectif du travail de thèse était de développer un modèle pour l'identification objective des types d'activité physique dans des conditions de vie réelles et l'estimation de la dépense énergétique basée sur une combinaison de 2 accéléromètres et 1 GPS. Le modèle prend en compte qu'une activité donnée peut être accomplie de différentes façons dans la vie réelle. Les activités quotidiennes ont pu être classées en 8 catégories, de sédentaires à actives, avec une précision de 1 min. La dépense énergétique a pu peut être prédite avec précision par le modèle. Après validation du modèle, le comportement des individus de l'activité physique a été évalué dans une seconde étude. Nous avons émis l'hypothèse que, dans un environnement caractérisé par les pentes, les personnes obèses sont tentées d'éviter les pentes raides et de diminuer la vitesse de marche au cours d'une activité physique spontanée, ainsi que pendant les exercices prescrits et structurés. Nous avons donc caractérisé, par moyen du modèle développé, le comportement des individus obèses dans un environnement vallonné urbain. La façon dont on aborde un environnement valloné dans les déplacements quotidiens devrait également être considérée lors de la prescription de marche supplémentaire afin d'augmenter l'activité physique.SummaryOrigin of obesity, that reached epidemic proportion, is complex and may be linked to different lifestyle and physical activity behaviour. Measurement of physical activity behaviour of individuals towards their environment, the distribution of physical activity in terms of physical activity type, volume, duration, frequency, intensity, and energy expenditure is of great importance. Nowadays, there is a lack of methods for accurate and objective assessment of physical activity and of individuals' physical activity behaviour. In order to complement the research relating physical activity to obesity and related diseases, the first aim of the thesis work was to develop a model for objective identification of physical activity types in real-life condition and energy expenditure based on a combination of 2 accelerometers and 1 GPS device. The model takes into account that a given activity can be achieved in many different ways in real life condition. Daily activities could be classified in 8 categories, as sedentary to active physical activity, within 1 min accuracy, and physical activity patterns determined. The energy expenditure could be predicted accurately with an accuracy below 10%. Furthermore, individuals' physical activity behaviour is expression of individual choices and their interaction with the neighbourhood environment. In a second study, we hypothesized that, in an environment characterized by inclines, obese individuals are tempted to avoid steep positive slopes and to decrease walking speed during spontaneous outdoor physical activity, as well as during prescribed structured bouts of exercise. Finally, we characterized, by mean of the developed model, the physical activity behaviour of obese individuals in a hilly urban environment. Quantifying how one tackles hilly environment or avoids slope in their everyday displacements should be also considered while prescribing extra walking in free-living conditions in order to increase physical activity.

Forensic intelligence framework. Part II: study of the main generic building blocks and challenges through the examples of illicit drugs and false identity documents monitoring

The development of forensic intelligence relies on the expression of suitable models that better represent the contribution of forensic intelligence in relation to the criminal justice system, policing and security. Such models assist in comparing and evaluating methods and new technologies, provide transparency and foster the development of new applications. Interestingly, strong similarities between two separate projects focusing on specific forensic science areas were recently observed. These observations have led to the induction of a general model (Part I) that could guide the use of any forensic science case data in an intelligence perspective. The present article builds upon this general approach by focusing on decisional and organisational issues. The article investigates the comparison process and evaluation system that lay at the heart of the forensic intelligence framework, advocating scientific decision criteria and a structured but flexible and dynamic architecture. These building blocks are crucial and clearly lay within the expertise of forensic scientists. However, it is only part of the problem. Forensic intelligence includes other blocks with their respective interactions, decision points and tensions (e.g. regarding how to guide detection and how to integrate forensic information with other information). Formalising these blocks identifies many questions and potential answers. Addressing these questions is essential for the progress of the discipline. Such a process requires clarifying the role and place of the forensic scientist within the whole process and their relationship to other stakeholders.

Evidence-based Economic Policy - Three Essays in Applied Microeconometrics

Over thirty years ago, Leamer (1983) - among many others - expressed doubts about the quality and usefulness of empirical analyses for the economic profession by stating that "hardly anyone takes data analyses seriously. Or perhaps more accurately, hardly anyone takes anyone else's data analyses seriously" (p.37). Improvements in data quality, more robust estimation methods and the evolution of better research designs seem to make that assertion no longer justifiable (see Angrist and Pischke (2010) for a recent response to Leamer's essay). The economic profes- sion and policy makers alike often rely on empirical evidence as a means to investigate policy relevant questions. The approach of using scientifically rigorous and systematic evidence to identify policies and programs that are capable of improving policy-relevant outcomes is known under the increasingly popular notion of evidence-based policy. Evidence-based economic policy often relies on randomized or quasi-natural experiments in order to identify causal effects of policies. These can require relatively strong assumptions or raise concerns of external validity. In the context of this thesis, potential concerns are for example endogeneity of policy reforms with respect to the business cycle in the first chapter, the trade-off between precision and bias in the regression-discontinuity setting in chapter 2 or non-representativeness of the sample due to self-selection in chapter 3. While the identification strategies are very useful to gain insights into the causal effects of specific policy questions, transforming the evidence into concrete policy conclusions can be challenging. Policy develop- ment should therefore rely on the systematic evidence of a whole body of research on a specific policy question rather than on a single analysis. In this sense, this thesis cannot and should not be viewed as a comprehensive analysis of specific policy issues but rather as a first step towards a better understanding of certain aspects of a policy question. The thesis applies new and innovative identification strategies to policy-relevant and topical questions in the fields of labor economics and behavioral environmental economics. Each chapter relies on a different identification strategy. In the first chapter, we employ a difference- in-differences approach to exploit the quasi-experimental change in the entitlement of the max- imum unemployment benefit duration to identify the medium-run effects of reduced benefit durations on post-unemployment outcomes. Shortening benefit duration carries a double- dividend: It generates fiscal benefits without deteriorating the quality of job-matches. On the contrary, shortened benefit durations improve medium-run earnings and employment possibly through containing the negative effects of skill depreciation or stigmatization. While the first chapter provides only indirect evidence on the underlying behavioral channels, in the second chapter I develop a novel approach that allows to learn about the relative impor- tance of the two key margins of job search - reservation wage choice and search effort. In the framework of a standard non-stationary job search model, I show how the exit rate from un- employment can be decomposed in a way that is informative on reservation wage movements over the unemployment spell. The empirical analysis relies on a sharp discontinuity in unem- ployment benefit entitlement, which can be exploited in a regression-discontinuity approach to identify the effects of extended benefit durations on unemployment and survivor functions. I find evidence that calls for an important role of reservation wage choices for job search be- havior. This can have direct implications for the optimal design of unemployment insurance policies. The third chapter - while thematically detached from the other chapters - addresses one of the major policy challenges of the 21st century: climate change and resource consumption. Many governments have recently put energy efficiency on top of their agendas. While pricing instru- ments aimed at regulating the energy demand have often been found to be short-lived and difficult to enforce politically, the focus of energy conservation programs has shifted towards behavioral approaches - such as provision of information or social norm feedback. The third chapter describes a randomized controlled field experiment in which we discuss the effective- ness of different types of feedback on residential electricity consumption. We find that detailed and real-time feedback caused persistent electricity reductions on the order of 3 to 5 % of daily electricity consumption. Also social norm information can generate substantial electricity sav- ings when designed appropriately. The findings suggest that behavioral approaches constitute effective and relatively cheap way of improving residential energy-efficiency.

CO2 emissions embodied in international trade: A multiregional Inputoutput model for Spain

As a result of globalization and free trade agreements, international trade is enormously growing and inevitably putting more pressure on the environment over the last few decades. This has drawn the attention of both environmentalist and economist in response to the ever growing concerns of climate change and urgent need of international action for its mitigation. In this work we aim at analyzing the implication of international trade in terms of CO2 between Spain and its important partners using a multi-regional input-output (MRIO) model. A fully integrated 13 regions MRIO model is constructed to examine the pollution responsibility of Spain both from production and consumption perspectives. The empirical results show that Spain is a net importer of CO2 emissions which is equivalent to 29% of its emission due to production. Even though the leading partner with regard to import values are countries such as Germany, France, Italy and Great Britain, the CO2 embodied due to trade with China takes the largest share. This is mainly due to the importation of energy intensive products from China coupled with Chinese poor energy mix which is dominated by coal-power plant. The largest portion (67%) of the global imported CO2 emissions is due to intermediate demand requirements by production sectors. Products such as Motor vehicles, chemicals, a variety of machineries and equipments, textile and leather products, construction materials are the key imports that drive the emissions due to their production in the respective exporting countries. Being at its peak in 2005, the Construction sector is the most responsible activity behind both domestic and imported emissions.

Non-invasive and non-occlusive blood pressure estimation via a chest sensor.

The clinical demand for a device to monitor Blood Pressure (BP) in ambulatory scenarios with minimal use of inflation cuffs is increasing. Based on the so-called Pulse Wave Velocity (PWV) principle, this paper introduces and evaluates a novel concept of BP monitor that can be fully integrated within a chest sensor. After a preliminary calibration, the sensor provides non-occlusive beat-by-beat estimations of Mean Arterial Pressure (MAP) by measuring the Pulse Transit Time (PTT) of arterial pressure pulses travelling from the ascending aorta towards the subcutaneous vasculature of the chest. In a cohort of 15 healthy male subjects, a total of 462 simultaneous readings consisting of reference MAP and chest PTT were acquired. Each subject was recorded at three different days: D, D+3 and D+14. Overall, the implemented protocol induced MAP values to range from 80 ± 6 mmHg in baseline, to 107 ± 9 mmHg during isometric handgrip maneuvers. Agreement between reference and chest-sensor MAP values was tested by using intraclass correlation coefficient (ICC = 0.78) and Bland-Altman analysis (mean error = 0.7 mmHg, standard deviation = 5.1 mmHg). The cumulative percentage of MAP values provided by the chest sensor falling within a range of ±5 mmHg compared to reference MAP readings was of 70%, within ±10 mmHg was of 91%, and within ±15mmHg was of 98%. These results point at the fact that the chest sensor complies with the British Hypertension Society (BHS) requirements of Grade A BP monitors, when applied to MAP readings. Grade A performance was maintained even two weeks after having performed the initial subject-dependent calibration. In conclusion, this paper introduces a sensor and a calibration strategy to perform MAP measurements at the chest. The encouraging performance of the presented technique paves the way towards an ambulatory-compliant, continuous and non-occlusive BP monitoring system.

Determining the best population-level alcohol consumption model and its impact on estimates of alcohol-attributable harms.

BACKGROUND: The goals of our study are to determine the most appropriate model for alcohol consumption as an exposure for burden of disease, to analyze the effect of the chosen alcohol consumption distribution on the estimation of the alcohol Population- Attributable Fractions (PAFs), and to characterize the chosen alcohol consumption distribution by exploring if there is a global relationship within the distribution. METHODS: To identify the best model, the Log-Normal, Gamma, and Weibull prevalence distributions were examined using data from 41 surveys from Gender, Alcohol and Culture: An International Study (GENACIS) and from the European Comparative Alcohol Study. To assess the effect of these distributions on the estimated alcohol PAFs, we calculated the alcohol PAF for diabetes, breast cancer, and pancreatitis using the three above-named distributions and using the more traditional approach based on categories. The relationship between the mean and the standard deviation from the Gamma distribution was estimated using data from 851 datasets for 66 countries from GENACIS and from the STEPwise approach to Surveillance from the World Health Organization. RESULTS: The Log-Normal distribution provided a poor fit for the survey data, with Gamma and Weibull distributions providing better fits. Additionally, our analyses showed that there were no marked differences for the alcohol PAF estimates based on the Gamma or Weibull distributions compared to PAFs based on categorical alcohol consumption estimates. The standard deviation of the alcohol distribution was highly dependent on the mean, with a unit increase in alcohol consumption associated with a unit increase in the mean of 1.258 (95% CI: 1.223 to 1.293) (R2 = 0.9207) for women and 1.171 (95% CI: 1.144 to 1.197) (R2 = 0. 9474) for men. CONCLUSIONS: Although the Gamma distribution and the Weibull distribution provided similar results, the Gamma distribution is recommended to model alcohol consumption from population surveys due to its fit, flexibility, and the ease with which it can be modified. The results showed that a large degree of variance of the standard deviation of the alcohol consumption Gamma distribution was explained by the mean alcohol consumption, allowing for alcohol consumption to be modeled through a Gamma distribution using only average consumption.

Sequential estimation of multipath MIMO-OFDM channels

Wireless “MIMO” systems, employing multiple transmit and receive antennas, promise a significant increase of channel capacity, while orthogonal frequency-division multiplexing (OFDM) is attracting a good deal of attention due to its robustness to multipath fading. Thus, the combination of both techniques is an attractive proposition for radio transmission. The goal of this paper is the description and analysis of a new and novel pilot-aided estimator of multipath block-fading channels. Typical models leading to estimation algorithms assume the number of multipath components and delays to be constant (and often known), while their amplitudes are allowed to vary with time. Our estimator is focused instead on the more realistic assumption that the number of channel taps is also unknown and varies with time following a known probabilistic model. The estimation problem arising from these assumptions is solved using Random-Set Theory (RST), whereby one regards the multipath-channel response as a single set-valued random entity.Within this framework, Bayesian recursive equations determine the evolution with time of the channel estimator. Due to the lack of a closed form for the solution of Bayesian equations, a (Rao–Blackwellized) particle filter (RBPF) implementation ofthe channel estimator is advocated. Since the resulting estimator exhibits a complexity which grows exponentially with the number of multipath components, a simplified version is also introduced. Simulation results describing the performance of our channel estimator demonstrate its effectiveness.

Lithuania’s Food Demand During Economic Transition, January 2000

The linear approximate version of the AIDS model is estimated using data from the Lithuanian household budget survey covering the period from July 1992 to December 1994. Price and real expenditure elasticities for twelve food groups were estimated based on the estimated coefficients of the model. Very little or nothing is known about the demand parameters of Lithuania and other former socialist countries, so the results are of intrinsic interest. Estimated expenditure elasticities were positive and statistically significant for all food groups while all own-price elasticities were negative and statistically significant, except for that of eggs which was insignificant. Results suggest that Lithuanian household consumption did respond to price and real income changes during their transition to a market-oriented economy.

Managing Quality under Heterogeneous Consumer Demand and Product Quality, October 2005

Based on accepted advances in the marketing, economics, consumer behavior, and satisfaction literatures, we develop a micro-foundations model of a firm that needs to manage the quality of a product that is inherently heterogeneous in the presence of varying customer tastes or expectations for quality. Our model blends elements of the returns to quality, customer lifetime value, and service profit chain approaches to marketing. The model is then used to explain several empirical results pertaining to the marketing literature by explicitly articulating the trade-offs between customer satisfaction and costs (including opportunity costs) of quality. In this environment firms will find it optimal to allow some customers to go unsatisfied. We show that the relationship between the expected number of repeated purchases by an individual customer is endogenous to the choice of quality by the firm, indicating that the number of purchases cannot be chosen freely to estimate a customer’s lifetime value.

Les coûts des dommages éléments naturels aux bâtiments et l'influence des facteurs du risque dans un contexte d'assurance immobilière : analyse de cas des innondations et de la grêle en Suisse

In Switzerland, the annual cost of damage by natural elements has been increasing for several years despite the introduction of protective measures. Mainly induced by material destruction building insurance companies have to pay the majority of this cost. In many European countries, governments and insurance companies consider prevention strategies to reduce vulnerability. In Switzerland, since 2004, the cost of damage due to natural hazards has surpassed the cost of damage due to fire; a traditional activity of the Cantonal Insurance company (EGA). Therefore, the strategy for efficient fire prevention incorporates a reduction of the vulnerability of buildings. The thesis seeks to illustrate the relevance of such an approach when applied to the damage caused by natural hazards. It examines the role of insurance place and its involvement in targeted prevention of natural disasters. Integrated risk management involves a faultless comprehension of all risk parameters The first part of the thesis is devoted to the theoretical development of the key concepts that influence risk management, such as: hazard, vulnerability, exposure or damage. The literature on this subject, very prolific in recent years, was taken into account and put in perspective in the context of this study. Among the risk parameters, it is shown in the thesis that vulnerability is a factor that we can influence efficiently in order to limit the cost of damage to buildings. This is confirmed through the development of an analysis method. This method has led to the development of a tool to assess damage to buildings by flooding. The tool, designed for the property insurer or owner, proposes several steps, namely: - Vulnerability and damage potential assessment; - Proposals for remedial measures and risk reduction from an analysis of the costs of a potential flood; - Adaptation of a global strategy in high-risk areas based on the elements at risk. The final part of the thesis is devoted to the study of a hail event in order to provide a better understanding of damage to buildings. For this, two samples from the available claims data were selected and analysed in the study. The results allow the identification of new trends A second objective of the study was to develop a hail model based on the available data The model simulates a random distribution of intensities and coupled with a risk model, proposes a simulation of damage costs for the determined study area. Le coût annuel des dommages provoqués par les éléments naturels en Suisse est conséquent et sa tendance est en augmentation depuis plusieurs années, malgré la mise en place d'ouvrages de protection et la mise en oeuvre de moyens importants. Majoritairement induit par des dégâts matériels, le coût est supporté en partie par les assurances immobilières en ce qui concerne les dommages aux bâtiments. Dans de nombreux pays européens, les gouvernements et les compagnies d'assurance se sont mis à concevoir leur stratégie de prévention en termes de réduction de la vulnérabilité. Depuis 2004, en Suisse, ce coût a dépassé celui des dommages dus à l'incendie, activité traditionnelle des établissements cantonaux d'assurance (ECA). Ce fait, aux implications stratégiques nombreuses dans le domaine public de la gestion des risques, résulte en particulier d'une politique de prévention des incendies menée efficacement depuis plusieurs années, notamment par le biais de la diminution de la vulnérabilité des bâtiments. La thèse, par la mise en valeur de données actuarielles ainsi que par le développement d'outils d'analyse, cherche à illustrer la pertinence d'une telle approche appliquée aux dommages induits par les phénomènes naturels. Elle s'interroge sur la place de l'assurance et son implication dans une prévention ciblée des catastrophes naturelles. La gestion intégrale des risques passe par une juste maîtrise de ses paramètres et de leur compréhension. La première partie de la thèse est ainsi consacrée au développement théorique des concepts clés ayant une influence sur la gestion des risques, comme l'aléa, la vulnérabilité, l'exposition ou le dommage. La littérature à ce sujet, très prolifique ces dernières années, a été repnse et mise en perspective dans le contexte de l'étude, à savoir l'assurance immobilière. Parmi les paramètres du risque, il est démontré dans la thèse que la vulnérabilité est un facteur sur lequel il est possible d'influer de manière efficace dans le but de limiter les coûts des dommages aux bâtiments. Ce raisonnement est confirmé dans un premier temps dans le cadre de l'élaboration d'une méthode d'analyse ayant débouché sur le développement d'un outil d'estimation des dommages aux bâtiments dus aux inondations. L'outil, destiné aux assurances immobilières, et le cas échéant aux propriétaires, offre plusieurs étapes, à savoir : - l'analyse de la vulnérabilité et le potentiel de dommages ; - des propositions de mesures de remédiation et de réduction du risque issues d'une analyse des coûts engendrés par une inondation potentielle; - l'adaptation d'une stratégie globale dans les zones à risque en fonction des éléments à risque. La dernière partie de la thèse est consacrée à l'étude d'un événement de grêle dans le but de fournir une meilleure compréhension des dommages aux bâtiments et de leur structure. Pour cela, deux échantillons ont été sélectionnés et analysés parmi les données de sinistres à disposition de l'étude. Les résultats obtenus, tant au niveau du portefeuille assuré que de l'analyse individuelle, permettent de dégager des tendances nouvelles. Un deuxième objectif de l'étude a consisté à élaborer une modélisation d'événements de grêle basée sur les données à disposition. Le modèle permet de simuler une distribution aléatoire des intensités et, couplé à un modèle d'estimation des risques, offre une simulation des coûts de dommages envisagés pour une zone d'étude déterminée. Les perspectives de ce travail permettent une meilleure focalisation du rôle de l'assurance et de ses besoins en matière de prévention.

Simple estimation of incident HIV infection rates in notification cohorts based on window periods of algorithms for evaluation of line-immunoassay result patterns.

BACKGROUND: Tests for recent infections (TRIs) are important for HIV surveillance. We have shown that a patient's antibody pattern in a confirmatory line immunoassay (Inno-Lia) also yields information on time since infection. We have published algorithms which, with a certain sensitivity and specificity, distinguish between incident (< = 12 months) and older infection. In order to use these algorithms like other TRIs, i.e., based on their windows, we now determined their window periods. METHODS: We classified Inno-Lia results of 527 treatment-naïve patients with HIV-1 infection < = 12 months according to incidence by 25 algorithms. The time after which all infections were ruled older, i.e. the algorithm's window, was determined by linear regression of the proportion ruled incident in dependence of time since infection. Window-based incident infection rates (IIR) were determined utilizing the relationship 'Prevalence = Incidence x Duration' in four annual cohorts of HIV-1 notifications. Results were compared to performance-based IIR also derived from Inno-Lia results, but utilizing the relationship 'incident = true incident + false incident' and also to the IIR derived from the BED incidence assay. RESULTS: Window periods varied between 45.8 and 130.1 days and correlated well with the algorithms' diagnostic sensitivity (R(2) = 0.962; P<0.0001). Among the 25 algorithms, the mean window-based IIR among the 748 notifications of 2005/06 was 0.457 compared to 0.453 obtained for performance-based IIR with a model not correcting for selection bias. Evaluation of BED results using a window of 153 days yielded an IIR of 0.669. Window-based IIR and performance-based IIR increased by 22.4% and respectively 30.6% in 2008, while 2009 and 2010 showed a return to baseline for both methods. CONCLUSIONS: IIR estimations by window- and performance-based evaluations of Inno-Lia algorithm results were similar and can be used together to assess IIR changes between annual HIV notification cohorts.