The rapid growth of biotechnology has promoted industries to harness the market in the field of human energy systems. A growing literature of research has linked human energy systems to weight loss, major diseases or illnesses. In our modern society, the general public is exposed to everyday stress, which often results in the development of chronic stress. Therefore, stress becomes an important area of medicine. It has been postulated that suppressing these physiological responses may help in disease prevention. Consequently, there is an urge for defining a model integrating stress with the human energy model. Over the past decades, a large amount of research has been put forward in defining the physiological responses or changes when an individual experiences psychological or environmental changes such as interpersonal dysfunction, traumatic experiences and diseases. Interestingly, it reveals that blood glucose fluctuation tends to be the end product of most psychological or physiological stressors. The blood glucose system is one of the major subsystems of the complete metabolic fuel system in humans. In this study, an empirical model and procedure for the derivation of the model due to various psychological influences on the human energy system are presented. This study can be divided into two main sections. An overview of a previously developed unit (ets: equivalent teaspoon sugar) for blood glucose quantification is given in the first section. Stress quantification methods are derived in the second section and a link between these methods and ets is drawn. A verification study of the derived model is also presented in the second section. Stress can be divided into physiological stress and psychological stress. Between the two types of stress, a generalised model based on studies of physiological stress has been drawn and accepted by the public. However, the generalised model does not account for psychological stress. Evidence shows that depending on the specific nature of a stressful circumstance, it can cause different activations of central circuits leading to the release of different neurotransmitters. However, these neurotransmitters have a common effect of increasing blood glucose concentrations. A substantial amount of literature shows that, when stress involves mental effort, epinephrine (EPI) is the main endocrine response. However, stress that does not require mental effort mainly induces cortisol release. The response models for different types of stress were derived using these relations. Furthermore, it is known that prolonged stress may lead to the development of disease. Several studies have used this observation and associated chronic stress with the relative risk factor of cardiovascular disease (CVD). Previously, different quartiles of risk factors for CVD have been related to blood glucose energy and ets expenditure. This link was further utilised to quantify chronic stress in this study. Increases in either of the two endocrine concentrations have been shown to raise the blood glucose level. In order to demonstrate the benefits of applying the ets concept, the cortisol and epinephrine responses were further quantified using the new glucose quantification method, the equivalent teaspoon sugar (ets) concept. The models derived in this study were verified against measured data. The models reveal a strong agreement with the measured data and therefore support the feasibility of these quantification methods. In conclusion, a link does exist between blood glucose energy and stress, and the highly accurate models derived for this association may serve as an adjunct tool for glycaemic control and stress management. / Thesis (Ph.D. (Electronical Engineering))--North-West University, Potchefstroom Campus, 2008.

The rapid growth of biotechnology has promoted industries to harness the market in the field of human energy systems. A growing literature of research has linked human energy systems to weight loss, major diseases or illnesses. In our modern society, the general public is exposed to everyday stress, which often results in the development of chronic stress. Therefore, stress becomes an important area of medicine. It has been postulated that suppressing these physiological responses may help in disease prevention. Consequently, there is an urge for defining a model integrating stress with the human energy model. Over the past decades, a large amount of research has been put forward in defining the physiological responses or changes when an individual experiences psychological or environmental changes such as interpersonal dysfunction, traumatic experiences and diseases. Interestingly, it reveals that blood glucose fluctuation tends to be the end product of most psychological or physiological stressors. The blood glucose system is one of the major subsystems of the complete metabolic fuel system in humans. In this study, an empirical model and procedure for the derivation of the model due to various psychological influences on the human energy system are presented. This study can be divided into two main sections. An overview of a previously developed unit (ets: equivalent teaspoon sugar) for blood glucose quantification is given in the first section. Stress quantification methods are derived in the second section and a link between these methods and ets is drawn. A verification study of the derived model is also presented in the second section. Stress can be divided into physiological stress and psychological stress. Between the two types of stress, a generalised model based on studies of physiological stress has been drawn and accepted by the public. However, the generalised model does not account for psychological stress. Evidence shows that depending on the specific nature of a stressful circumstance, it can cause different activations of central circuits leading to the release of different neurotransmitters. However, these neurotransmitters have a common effect of increasing blood glucose concentrations. A substantial amount of literature shows that, when stress involves mental effort, epinephrine (EPI) is the main endocrine response. However, stress that does not require mental effort mainly induces cortisol release. The response models for different types of stress were derived using these relations. Furthermore, it is known that prolonged stress may lead to the development of disease. Several studies have used this observation and associated chronic stress with the relative risk factor of cardiovascular disease (CVD). Previously, different quartiles of risk factors for CVD have been related to blood glucose energy and ets expenditure. This link was further utilised to quantify chronic stress in this study. Increases in either of the two endocrine concentrations have been shown to raise the blood glucose level. In order to demonstrate the benefits of applying the ets concept, the cortisol and epinephrine responses were further quantified using the new glucose quantification method, the equivalent teaspoon sugar (ets) concept. The models derived in this study were verified against measured data. The models reveal a strong agreement with the measured data and therefore support the feasibility of these quantification methods. In conclusion, a link does exist between blood glucose energy and stress, and the highly accurate models derived for this association may serve as an adjunct tool for glycaemic control and stress management. / Thesis (Ph.D. (Electronical Engineering))--North-West University, Potchefstroom Campus, 2008.

Made available in DSpace on 2015-05-14T12:47:21Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 1245861 bytes, checksum: 4856937dfa198976bc266a7cb0a525a9 (MD5) Previous issue date: 2011-02-17 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / From decade of 80 the external causes, especially traffic accidents, have become a big problem that afflicts the Brazil and the World. This work aims to study the traffic accidents in the city of João Pessoa from the spatial distribution and fuzzy logic to the decision making of priority areas and non-priority. The analysis was an initial observation a study of aggregated neighborhood and after separately. The data used in the analysis were of secondary type collected by the Department of Legal Medicine (DML). The analysis carried out were the follows: descriptive statistics, spatial distribution and fuzzy logic. From the results of descriptive statistics found that the males accounted for 562 victims and the female 102 victms of all the years studied in the city of Joao Pessoa. The main means of transport that caused the accidents were the cars followed by motorcycle. The nature of the traffic accidents most frequent were: pedestrian collisions that occurred during the years 2005, 2006, 2008 and 2009, followed by collisions. In the morning and afternoon occurred the highest numbers of accidents due to the large number of vehicles on roads in the city and in the shift dawn the number of fatal accidents decreased. The days of the week were more fatal accidents occurred on Saturday, Sunday and Monday. The main victims of accidents were young people and adults in the age groups of 20 to 24, 25 to 29, 30 to 39 and 40 to 49 years. Spatial analysis the main areas of the city with relatively high risk and significant spatial clusters are: northwest, north, northeast and west of the city of João Pessoa. In these areas included the neighborhood of Cabo Branco, Altiplano Cabo Branco,Centro, Mandacaru, Bessa, Cruz das Armas, Pedro Gondim, Tambauzinho and Tambiá. The decision model was used fuzzy logic which aimed to identify priority areas and non-priority traffic accidents in the city of João Pessoa. Were elaborated four linguistic variables and eleven linguistic terms. The results of logic fuzzy were satisfactory because it reached the objective proposed of identification of priority areas and non-priority in the city of João Pessoa. Enabling the decision making of public policies more effectives in order to decrease the number of deaths from traffic accidents.q / A partir da década de 80 as causas externas, em especial os acidentes de trânsito, passaram a ser um grande problema que aflinge o Brasil e o mundo. Este trabalho tem por objetivo estudar os acidentes de trânsito na cidade de João Pessoa, a partir da distribuição espacial e lógica fuzzy para a tomada de decisão das áreas prioritárias e nãoprioritárias. A análise foi numa primeira observação um estudo dos bairros agregados e depois separadamente. Os dados utilizados nas análises foram do tipo secundário, levantados no Departamento de Medicina Legal (DML). As análises foram: estatísticas descritivas, distribuição espacial e lógica fuzzy. A partir dos resultados das estatísticas descritivas, observou-se que o sexo masculino representou 562 vítimas fatais e o sexo feminino 102 vítimas do total dos anos estudados na cidade de João Pessoa. Os principais meios de transporte que causaram os acidentes foram os automóveis, seguido das motos. A natureza dos acidentes de trânsito mais frequentes foram os atropelamentos, ocorridos nos anos de 2005, 2006, 2008 e 2009, seguido das colisões. Nos períodos da manhã e tarde ocorreram os maiores números de acidentes, em virtude do grande número de veículos nas vias da cidade e, no turno da madrugada, os números de acidentes fatais diminuíram. Os dias da semana que mais ocorreram acidentes fatais foram no sábado, segunda-feira e domingo. As principais vítimas dos acidentes são os jovens e adultos nas faixas etárias dos 20 aos 49 anos. Na análise espacial as principais regiões da cidade com risco relativo alto e conglomerados espaciais significativos são: noroeste, norte, nordeste e oeste da cidade de João Pessoa. Nestas regiões estão incluídos os bairros do Cabo Branco, Altiplano Cabo Branco, Varadouro, Centro, Mandacaru, Bessa, Cruz das Armas, Pedro Gondim, Tambia e Tambauzinho. O modelo de decisão foi baseado em lógica fuzzy, que teve como finalidade identificar as áreas prioritárias e não-prioritárias dos acidentes de trânsito na cidade de João Pessoa. Foram elaborados seis variáveis fuzzy e quinze termos linguísticos. Os resultados de lógica fuzzy foram satisfatórios, pois atingiu o objetivo proposto da identificação total das áreas prioritárias e não-prioritárias na cidade de João Pessoa. Possibilitando a tomada de decisão de políticas públicas mais efetivas com o intuito de diminuir o número de óbitos por acidentes de trânsito.

La dengue est actuellement un problème de santé publique majeur en Colombie avec un fardeau sanitaire et économique important. Les facteurs environnementaux sont connus pour influencer le risque de dengue ; cependant, la forme, l'ampleur et le moment de ces relations ne sont pas clairement établis. L'ampleur et le moment des épidémies de dengue varient selon le lieu. Cette thèse a examiné les composantes temporelles des séries chronologiques hebdomadaires de cas de dengue dans les municipalités de Villavicencio, Castilla la Nueva et Puerto Lopez en Colombie de 2014 à 2019. Il a procédé à l'estimation de la forme et de l'ampleur des associations entre les cas hebdomadaires de dengue et cinq facteurs météorologiques, mesurés chaque semaine, pour chacune des municipalités à l'aide du cadre des modèles non linéaires à décalage distribué avec une distribution binomiale négative. Il a finalement comparé les associations dans les trois municipalités (urbaines, périurbaines et rurales) pour observer si les associations trouvées étaient cohérentes entre les municipalités. Les résultats ont montré que Castilla la Nueva (périurbain) avait la fréquence d'épidémies la plus élevée, avec quatre pics distincts, tandis que Puerto Lopez (rural) en avait le moins. L'ampleur du nombre d'infections était la plus élevée à Villavicencio (urbain), probablement parce qu'elle était la plus peuplée des trois. Les trois municipalités avaient toutes deux une tendance qui dépendait des pics et des creux des flambées de dengue et toutes avaient une composante saisonnière distincte. L'association avec la température, les précipitations, l'humidité relative, la vitesse du vent et la pression de surface à travers les décalages n'était pas linéaire. La non-linéarité a été présentée par un comportement en forme de dôme simple à multiple, dépendant de la municipalité. L'ampleur du risque relatif associé à chaque facteur environnemental dépendait également de la municipalité. Cette thèse propose la création d'un tableau de bord de prévisions utilisant des modèles non linéaires à décalage distribué pour chaque commune comme outil d’aide aux politiques et programmes de lutte contre la dengue. / Dengue is presently a major public health issue in Colombia with significant health and economic burden. Environmental factors are known to influence dengue risk; however the shape, strength and timing of these relationships are not clearly established. The scale and timing of dengue outbreaks vary according to location. This thesis examined the temporal components of weekly dengue cases time series in Villavicencio, Castilla la Nueva and Puerto Lopez municipalities of Colombia from 2014 to 2019. It proceeded to estimate the shape and magnitude of the associations between weekly dengue cases and five meteorological factors, measured weekly, for each of the municipalities using the Distributed lag non-linear models framework with negative binomial distribution. It finally compared the associations across the three municipalities (urban, peri urban, and rural) to observe whether the associations found were consistent across municipalities. The results showed that Castilla la Nueva (peri-urban) had the highest frequency of epidemics, with four distinct peaks, while Puerto Lopez (rural) had the fewest. The magnitude of the number of infections was greatest in Villavicencio (urban), likely as a result of it being the most populated among the three. All three municipalities both had a trend which was dependent on the peaks and troughs of dengue outbreaks and all had a distinct seasonal component. The association with temperature, precipitation, relative humidity, wind speed and surface pressure across lags were non-linear. The non-linearity was exhibited by single to multiple dome-shaped behaviour dependent on the municipality. The magnitude of the relative risk associated with each environmental factor was also dependent on the municipality. This thesis suggest the creation of a dashboard of forecasts of distributed lag non-linear models for each municipality as a policy and program aid, in the fight against dengue.

本研究探討長期投資人在面臨通貨膨脹風險時的最適投資決策。就長期投資者而言，諸如退休金規劃者等，通貨膨脹是無可避免卻又不易被數量化之風險，因為各國僅公布與之相關的消費者物價指數而沒有公布真實通貨膨脹數值，因此我們延伸Campbell和Viceira(2001)及Brennan和Xia(2002)的模型假設，以消費者物價指數的資訊來校正原先假定符合Vasicek模型之通貨膨脹動態過程。本研究之理論背景為：利用貝式過濾方法(Baysian Filtering Method)，將含有雜訊之消費者物價指數，透過後驗分配得出通貨膨脹動態過程。利用帄賭過程(Martingale Method)求解資產之公帄價格。再引進定值相對風險趨避(Constant Relative Risk Aversion，CRRA)的效用函數，求出最適投資組合下之期末累積財富、各期資產配置以及效用值。 / 本研究歸納數值結果如下： 一、投資期間越長，通貨膨脹學習效果越顯著。投資期間達25年以上時，有學習效果之累積財富為無學習效果時兩倍以上，25年為2.36倍；30年為2.18倍。此外，學習效果對投資人效用改善率於長期投資時也較顯著，投資10年效用改善率為35%，而投資30年則高達1289%，呈非線性成長。以上結果顯示：資產在市場上累積越久，受到通膨影響越明顯，更需要以學習方式動態調整資產配置進行通貨膨脹風險管理。 / 二、風險較趨避之投資人，CRRA參數值越大；於最適投資組合下之期末財富較少，因為風險較趨避投資人偏好低波動度資產組合。風險容忍度低之投資人較需要通貨膨脹之學習，否則效用減損過高，例如CRRA參數為1.5之投資人30年後效用減損65%，CRRA參數為4之投資人效用減損達96.5%。以上數據顯示：風險趨避投資人對風險關注程度較高，考慮學習效果時，較能根據目前通貨膨脹調整資產配置。 / This study examines the optimal portfolio selection incorporating inflation risk learning adjustments for a long-term investor. For long-term investors, it is inevitable to face the uncertainty of inflation. On the other hand, quantifying inflation risk needs more effort since the government announced the information on Consumer Price Index (CPI) rather than the real inflation rates. / In order to measure the inflation rate in planning the long-term investment strategies, we extend the works in Campbell and Viceira (2001) and Brennan and Xia (2002) to construct a stochastic process of the inflation rate. The prior distribution of inflation rate process, which is not directly observable, is assumed to follow the diffusion process. Based on the information of CPI, we then employ the optimal linear filtering equations to estimate the posterior distribution of the inflation rate process. Through these mechanisms, the inflation rate process is closer to reality by learning from CPI. We also construct the optimal portfolio strategy through a Martingale formulation based on the wealth constraints. The optimal portfolio strategies are given in closed-form solutions. / Furthermore, the importance of learning about inflation risk is summarized through the numerical results. (1) When the investment interval is longer, the learning effect becomes more significant. If the investment horizon is longer than 25 years, the wealth accumulation under learning will be twice more than that without learning effect, e.g., the wealth accumulation is approximately 2.36, 2.18 folds at the end of 25, 30 years. Utility increase under learning also become larger for long-term investor, e.g., the utility values will improve 35% after considering learning ability on inflation from 10-year interval, improve 1289% from 30 years. / (2)When the CRRA parameter increases, the investor have lower risk tolerance; and their wealth accumulation become less due to the lower volatility portfolio. A conservative investor requires more learning ability given the inflation, otherwise their utility value will be reduced, e.g., the utility values will be reduced 35% when CRRA=1.5 after 30 years’ investment, 96,5% when CRRA=4.

A hanseníase, doença crônica estigmatizante com potencial de causar danos neurológicos, resulta da infecção pelo Mycobacterium leprae. Análises epidemiológicas atuais têm utilizado ferramentas clínicas e de análise espacial para o mapeamento dos principais focos de ocorrência de doenças e de áreas de alto risco. Analisar os municípios maranhenses quanto à distribuição dos casos de hanseníase torna-se uma ferramenta a mais na prevenção e controle da Hanseníase no estado por inúmeros fatores: comporta-se como área hiperendêmica de hanseníase; apresenta fluxo migratório intenso com outras cidades de forma interestadual; e tem grandes contrastes sociais marcados por pouca, ou nenhuma, infraestrutura básica em algumas áreas dos vários municípios deste. Objetivos: Analisar a distribuição espaço-temporal da hanseníase para o estado do Maranhão, no período de 2001 a 2013. Identificar a ocorrência de agrupamentos espaços-temporais de provável alta transmissão (risco) e verificar se há associação dessa distribuição de taxas de detecção de risco relativo (RR) da doença com as variáveis do contexto geográfico como socioeconômicas e ambientais. Metodologia: A fonte de coleta dos dados clínicos e epidemiológicos foi o Sistema de Informação Nacional de Agravos Notificáveis do Ministério da Saúde e dos dados demográficos, ambientais e bases cartográficas digitais do Instituto Brasileiro de Geografia e Estatística. Foi adotada uma abordagem ecológica sobre tendências dos padrões espaçostemporais de transmissibilidade, com utilização dos métodos: varredura espacial (scan), para a identificação dos agregados (clusters) de risco, considerando o modelo de distribuição de probabilidade Discreto de Poisson; Estimador Bayesiano Empírico para a suavização local de taxas, a partir de informações de municípios vizinhos tendo como estratégia de construção o critério da contiguidade; regressão múltipla espacial considerando uma modelagem com distribuição de Poisson no contexto Bayesiano, levando em conta a dependência espacial, com o propósito de avaliar a relação entre a ocorrência da variável dependente com as variáveis demográficas, socioeconômicas e ambientais. Resultados: A taxa média de detecção foi de 6,73 casos por 10.000 hab., com 53.826 casos notificados no período. O estudo revelou que a distribuição dos casos de sexo masculino (57,75%) apresentou maior proporção em relação ao feminino (42,25%), havendo predominância da doença na faixa etária >15 anos (89,87%). A alta ocorrência na classificação operacional multibacilar (60,10%) é um forte indicativo decorrente do longo período de incubação da doença somado ao não diagnóstico precoce. A análise da distribuição dos agregados espaciais identificou 14 (7 de risco alto e 7 de risco baixo) e 6 (3 de risco alto e 3 de risco baixo) agrupamentos espaciais, considerando-se 10% e 50% da população em risco, respectivamente, em áreas com taxas de detecção alta e que possuem baixa qualidade de vida. O estimador Bayesiano empírico local possibilitou gerar índices corrigidos e com menores instabilidades. A análise de regressão múltipla espacial mostrou que as variáveis índice Gini, bioma predominante cerrado/caatinga e percentual de população urbana tiveram associação positiva e significativa para explicar o risco relativo (RR) no estado do Maranhão. Conclusões: O estudo mostrou que existem aglomerados com elevado risco para transmissão da hanseníase no estado do Maranhão. A associação entre o risco relativo da hanseníase e o percentual de população urbana indica que a hipótese que associa o M. leprae e a população que vive em condições de acentuada desigualdade socioeconômica ainda é forte. Essa hiperendemicidade pode demonstrar que o crescimento da população urbana é um preditor de incidência da hanseníase, face à urbanização descontrolada e ao fluxo de migrantes advindos de diferentes espaços rurais. Foi possível identificar áreas prioritárias para implementação de programas eficazes de controle de hanseníase no estado do Maranhão. / Leprosy, a chronic stigmatizing disease with the potential to cause neurological damage resulting from infection by Mycobacterium leprae. Current epidemiological studies have used clinical and spatial analysis for mapping of the main occurrence of disease outbreaks and high-risk areas. Analyze the municipalities of Maranhão state regarding the distribution of leprosy cases becomes another tool in the prevention and control of leprosy in the state by numerous factors like behaves as hyper-endemic area of leprosy; It presents intense migration to other interstate cities; and has great social contrasts marked by little or no basic infrastructure in some areas of several municipalities.. Objectives: To analyze the spatiotemporal distribution of leprosy in the Maranhão state, from 2001 to 2013. To identify the spatiotemporal clusters occurrence of probable high transmission (risk) and check for association of this distribution of relative risk (RR) detection rates of the disease with the variables of geographic context as socioeconomic and environmental. Methodology: Clinical and epidemiological data was obtained from the Ministry of Healths Disease Reporting System and demographic data, environmental and digital cartographic bases were obtained from the Brazilian Geography and Statistics Institute. An ecological approach to trends transmissibility of spatiotemporal patterns, using the methods: spatial scan to identification the clusters of risk, considering the Discrete Poisson probability distribution model; empirical Bayesian method was applied for local rate flattening, using data from municipalities having as building strategy the criterion of contiguity; ecological regression modeling with considering a Poisson distribution in the Bayesian context, taking into account the spatial dependence, in order to evaluate the relationship between the occurrence of the dependent variable with demographic, socioeconomic and environmental variables. Results: The mean detection rate was 6.73 cases per 10,000 inhabitants, with 53,826 reported cases. The study revealed that the distribution of male cases (57.75%) showed a predominance over female (42.25%), with predominance of the disease in the age group upper than 15 years (89.87%). The high occurrence in operational classification multibacillary (60.10%) is a strong indication due to the long incubation period of the disease added to no early diagnosis. The analysis of the distribution of spatial clusters identified 14 (7 high risk and 7 low risk) and 6 (3 high risk and 3 low risk) spatial clusters, considering 10% and 50% of the population at risk in areas with high detection rates and which have low quality of life. Local empirical Bayes estimator allowed to generate fixed and minor instabilities indexes. The best results of modeling to spatial multiple regression analysis for the relative risk (RR) presented for the variables Gini index, cerrado/caatinga biome and percentage of urban population. Conclusions: The study showed that there are clusters at high risk for transmission of leprosy in the Maranhao state. The association between the relative risk of leprosy and the percentage of urban population indicates that the hypothesis that associates M. leprae and the population living in severe socioeconomic inequality is still strong. This hyperendemicity can demonstrate that the growth of the urban population is a predictor incidence of leprosy due to uncontrolled urbanization and the influx of migrants coming from different rural areas.It was possible to identify priority areas for implementation of effective leprosy control programs in the Maranhão state.

Dans les études épidémiologiques, les erreurs de mesure de l’exposition étudiée peuvent biaiser l’estimation des risques liés à cette exposition. Un grand nombre de méthodes de correction de l’effet de ces erreurs a été développé mais en pratique elles ont été rarement appliquées, probablement à cause du fait que leur capacité de correction et leur mise en œuvre sont peu maîtrisées. Une autre raison non moins importante est que, en l’absence de données répétées ou de données de validation, ces méthodes de correction exigent la connaissance détaillée des caractéristiques (taille, nature, structure et distribution) des erreurs de mesure. L’objectif principal de cette thèse est d’étudier l’impact de la prise en compte des erreurs de mesure dans les analyses du risque de décès par cancer du poumon associé à l’exposition au radon à partir de la cohorte française des mineurs d’uranium (qui ne dispose ni de données répétées, ni de données de validation). Les objectifs spécifiques étaient (1) de caractériser les erreurs de mesure associées aux expositions radiologiques (radon et ses descendants, poussières d’uranium et rayonnements gamma), (2) d’étudier l’impact des erreurs de mesure de l’exposition au radon et à ses descendants sur l’estimation de l’excès de risque relatif (ERR) de décès par cancer du poumon et (3) d’étudier et comparer la performance des méthodes de correction de l’effet de ces erreurs. La cohorte française des mineurs d’uranium comprend plus de 5000 individus exposés de manière chronique au radon et à ses descendants qui ont été suivis en moyenne pendant 30 ans. Les erreurs de mesure ont été caractérisées en prenant en compte l’évolution des méthodes d’extraction et de la surveillance radiologique des mineurs au fil du temps. Une étude de simulation basée sur la cohorte française des mineurs d’uranium a été mise en place pour étudier l’impact de ces erreurs sur l’ERR ainsi que pour comparer la performance des méthodes de correction. Les résultats montrent que les erreurs de mesure de l’exposition au radon et à ses descendants ont diminué au fil des années. Pour les premières années, avant 1970, elles dépassaient 45 % et après 1980 elles étaient de l’ordre de 10 %. La nature de ces erreurs a aussi changé au cours du temps ; les erreurs essentiellement de nature Berkson ont fait place à des erreurs de nature classique après la mise en place des dosimètres individuels à partir de 1983. Les résultats de l’étude de simulation ont montré que les erreurs de mesure conduisent à une atténuation de l’ERR vers la valeur nulle, avec un biais important de l’ordre de 60 %. Les trois méthodes de correction d’erreurs considérées ont permis une réduction notable mais partielle du biais d’atténuation. Un avantage semble exister pour la méthode de simulation extrapolation (SIMEX) dans notre contexte, cependant, les performances des trois méthodes de correction sont fortement tributaires de la détermination précise des caractéristiques des erreurs de mesure.Ce travail illustre l’importance de l’effet des erreurs de mesure sur les estimations de la relation entre l’exposition au radon et le risque de décès par cancer du poumon. L’obtention d’estimation de risque pour laquelle l’effet des erreurs de mesure est corrigé devrait s’avérer d’un intérêt majeur en support des politiques de protection contre le radon en radioprotection et en santé publique. / In epidemiological studies, measurement errors in exposure can substantially bias the estimation of the risk associated to exposure. A broad variety of methods for measurement error correction has been developed, but they have been rarely applied in practice, probably because their ability to correct measurement error effects and their implementation are poorly understood. Another important reason is that many of the proposed correction methods require to know measurement errors characteristics (size, nature, structure and distribution).The aim of this thesis is to take into account measurement error in the analysis of risk of lung cancer death associated to radon exposure based on the French cohort of uranium miners. The mains stages were (1) to assess the characteristics (size, nature, structure and distribution) of measurement error in the French uranium miners cohort, (2) to investigate the impact of measurement error in radon exposure on the estimated excess relative risk (ERR) of lung cancer death associated to radon exposure, and (3) to compare the performance of methods for correction of these measurement error effects.The French cohort of uranium miners includes more than 5000 miners chronically exposed to radon with a follow-up duration of 30 years. Measurement errors have been characterized taking into account the evolution of uranium extraction methods and of radiation protection measures over time. A simulation study based on the French cohort of uranium miners has been carried out to investigate the effects of these measurement errors on the estimated ERR and to assess the performance of different methods for correcting these effects.Measurement error associated to radon exposure decreased over time, from more than 45% in the early 70’s to about 10% in the late 80’s. Its nature also changed over time from mostly Berkson to classical type from 1983. Simulation results showed that measurement error leads to an attenuation of the ERR towards the null, with substantial bias on ERR estimates in the order of 60%. All three error-correction methods allowed a noticeable but partial reduction of the attenuation bias. An advantage was observed for the simulation-extrapolation method (SIMEX) in our context, but the performance of the three correction methods highly depended on the accurate determination of the characteristics of measurement error.This work illustrates the importance of measurement error correction in order to obtain reliable estimates of the exposure-risk relationship between radon and lung cancer. Corrected risk estimates should prove of great interest in the elaboration of protection policies against radon in radioprotection and in public health.

Research Doctorate - Doctor of Philosophy (PhD) / Interval estimation of the Binomial parameter è, representing the true probability of a success, is a problem of long standing in statistical inference. The landmark work is by Bayes (1763) who applied the uniform prior to derive the Beta posterior that is the normalised Binomial likelihood function. It is not well known that Bayes favoured this ‘noninformative’ prior as a result of considering the observable random variable x as opposed to the unknown parameter è, which is an important difference. In this thesis we develop additional arguments in favour of the uniform prior for estimation of è. We start by describing the frequentist and Bayesian approaches to interval estimation. It is well known that for common continuous models, while different in interpretation, frequentist and Bayesian intervals are often identical, which is directly related to the existence of a pivotal quantity. The Binomial model, and its Poisson sister also, lack a pivotal quantity, despite having sufficient statistics. Lack of a pivotal quantity is the reason why there is no consensus on one particular estimation method, more so than its discreteness: frequentist (unconditional) coverage depends on è. Exact methods guarantee minimum coverage to be at least equal to nominal and approximate methods aim for mean coverage to be close to nominal. We agree with what seems like the majority of frequentists, that exact methods are too conservative in practice, and show additional undesirable properties. This includes more recent ‘short’ exact intervals. We argue that Bayesian intervals based on noninformative priors are preferable to the family of frequentist approximate intervals, some of which are wider than exact intervals for particular data values. A particular property of the interval based on the uniform prior is that its mean coverage is exactly equal to nominal. However, once committed to the Bayesian approach there is no denying that the current preferred choice, by ‘objective’ Bayesians, is the U-shaped Jeffreys prior which results from various methods aimed at finding noninformative priors. The most successful such method seems to be reference analysis which has led to sensible priors in previously unsolved problems, concerning multiparameter models that include ‘nuisance’ parameters. However, we argue that there is a class of models for which the Jeffreys/reference prior may be suboptimal and that in the case of the Binomial distribution the requirement of a uniform prior predictive distribution leads to a more reasonable ‘consensus’ prior.

A hanseníase, doença crônica estigmatizante com potencial de causar danos neurológicos, resulta da infecção pelo Mycobacterium leprae. Análises epidemiológicas atuais têm utilizado ferramentas clínicas e de análise espacial para o mapeamento dos principais focos de ocorrência de doenças e de áreas de alto risco. Analisar os municípios maranhenses quanto à distribuição dos casos de hanseníase torna-se uma ferramenta a mais na prevenção e controle da Hanseníase no estado por inúmeros fatores: comporta-se como área hiperendêmica de hanseníase; apresenta fluxo migratório intenso com outras cidades de forma interestadual; e tem grandes contrastes sociais marcados por pouca, ou nenhuma, infraestrutura básica em algumas áreas dos vários municípios deste. Objetivos: Analisar a distribuição espaço-temporal da hanseníase para o estado do Maranhão, no período de 2001 a 2013. Identificar a ocorrência de agrupamentos espaços-temporais de provável alta transmissão (risco) e verificar se há associação dessa distribuição de taxas de detecção de risco relativo (RR) da doença com as variáveis do contexto geográfico como socioeconômicas e ambientais. Metodologia: A fonte de coleta dos dados clínicos e epidemiológicos foi o Sistema de Informação Nacional de Agravos Notificáveis do Ministério da Saúde e dos dados demográficos, ambientais e bases cartográficas digitais do Instituto Brasileiro de Geografia e Estatística. Foi adotada uma abordagem ecológica sobre tendências dos padrões espaçostemporais de transmissibilidade, com utilização dos métodos: varredura espacial (scan), para a identificação dos agregados (clusters) de risco, considerando o modelo de distribuição de probabilidade Discreto de Poisson; Estimador Bayesiano Empírico para a suavização local de taxas, a partir de informações de municípios vizinhos tendo como estratégia de construção o critério da contiguidade; regressão múltipla espacial considerando uma modelagem com distribuição de Poisson no contexto Bayesiano, levando em conta a dependência espacial, com o propósito de avaliar a relação entre a ocorrência da variável dependente com as variáveis demográficas, socioeconômicas e ambientais. Resultados: A taxa média de detecção foi de 6,73 casos por 10.000 hab., com 53.826 casos notificados no período. O estudo revelou que a distribuição dos casos de sexo masculino (57,75%) apresentou maior proporção em relação ao feminino (42,25%), havendo predominância da doença na faixa etária >15 anos (89,87%). A alta ocorrência na classificação operacional multibacilar (60,10%) é um forte indicativo decorrente do longo período de incubação da doença somado ao não diagnóstico precoce. A análise da distribuição dos agregados espaciais identificou 14 (7 de risco alto e 7 de risco baixo) e 6 (3 de risco alto e 3 de risco baixo) agrupamentos espaciais, considerando-se 10% e 50% da população em risco, respectivamente, em áreas com taxas de detecção alta e que possuem baixa qualidade de vida. O estimador Bayesiano empírico local possibilitou gerar índices corrigidos e com menores instabilidades. A análise de regressão múltipla espacial mostrou que as variáveis índice Gini, bioma predominante cerrado/caatinga e percentual de população urbana tiveram associação positiva e significativa para explicar o risco relativo (RR) no estado do Maranhão. Conclusões: O estudo mostrou que existem aglomerados com elevado risco para transmissão da hanseníase no estado do Maranhão. A associação entre o risco relativo da hanseníase e o percentual de população urbana indica que a hipótese que associa o M. leprae e a população que vive em condições de acentuada desigualdade socioeconômica ainda é forte. Essa hiperendemicidade pode demonstrar que o crescimento da população urbana é um preditor de incidência da hanseníase, face à urbanização descontrolada e ao fluxo de migrantes advindos de diferentes espaços rurais. Foi possível identificar áreas prioritárias para implementação de programas eficazes de controle de hanseníase no estado do Maranhão. / Leprosy, a chronic stigmatizing disease with the potential to cause neurological damage resulting from infection by Mycobacterium leprae. Current epidemiological studies have used clinical and spatial analysis for mapping of the main occurrence of disease outbreaks and high-risk areas. Analyze the municipalities of Maranhão state regarding the distribution of leprosy cases becomes another tool in the prevention and control of leprosy in the state by numerous factors like behaves as hyper-endemic area of leprosy; It presents intense migration to other interstate cities; and has great social contrasts marked by little or no basic infrastructure in some areas of several municipalities.. Objectives: To analyze the spatiotemporal distribution of leprosy in the Maranhão state, from 2001 to 2013. To identify the spatiotemporal clusters occurrence of probable high transmission (risk) and check for association of this distribution of relative risk (RR) detection rates of the disease with the variables of geographic context as socioeconomic and environmental. Methodology: Clinical and epidemiological data was obtained from the Ministry of Healths Disease Reporting System and demographic data, environmental and digital cartographic bases were obtained from the Brazilian Geography and Statistics Institute. An ecological approach to trends transmissibility of spatiotemporal patterns, using the methods: spatial scan to identification the clusters of risk, considering the Discrete Poisson probability distribution model; empirical Bayesian method was applied for local rate flattening, using data from municipalities having as building strategy the criterion of contiguity; ecological regression modeling with considering a Poisson distribution in the Bayesian context, taking into account the spatial dependence, in order to evaluate the relationship between the occurrence of the dependent variable with demographic, socioeconomic and environmental variables. Results: The mean detection rate was 6.73 cases per 10,000 inhabitants, with 53,826 reported cases. The study revealed that the distribution of male cases (57.75%) showed a predominance over female (42.25%), with predominance of the disease in the age group upper than 15 years (89.87%). The high occurrence in operational classification multibacillary (60.10%) is a strong indication due to the long incubation period of the disease added to no early diagnosis. The analysis of the distribution of spatial clusters identified 14 (7 high risk and 7 low risk) and 6 (3 high risk and 3 low risk) spatial clusters, considering 10% and 50% of the population at risk in areas with high detection rates and which have low quality of life. Local empirical Bayes estimator allowed to generate fixed and minor instabilities indexes. The best results of modeling to spatial multiple regression analysis for the relative risk (RR) presented for the variables Gini index, cerrado/caatinga biome and percentage of urban population. Conclusions: The study showed that there are clusters at high risk for transmission of leprosy in the Maranhao state. The association between the relative risk of leprosy and the percentage of urban population indicates that the hypothesis that associates M. leprae and the population living in severe socioeconomic inequality is still strong. This hyperendemicity can demonstrate that the growth of the urban population is a predictor incidence of leprosy due to uncontrolled urbanization and the influx of migrants coming from different rural areas.It was possible to identify priority areas for implementation of effective leprosy control programs in the Maranhão state.

Background: Numerous epidemiological studies have demonstrated a possible correlation between high temperature and mortality in different settings. Most of these studies have focused on urban settings in industrialized countries, concluding that urban populations are more vulnerable to heat effects than rural populations. This has mainly been attributed to the urban heat island (UHI) effect, a phenomenon which explains the elevated temperatures in urban areas. Others have contradicted this finding and concluded that rural residents are more vulnerable. For this study, we test the hypothesis that rural populations and sub-populations are also vulnerable to heat mortality. Method: A comprehensive literature search was conducted using PubMed, Web of Science and Google Scholar to identify peer-reviewed studies investigating heat mortality in rural settings. Using keywords and a set of rigorous inclusion and exclusion criteria, ten studies were selected. Meta-analysis was then performed using the Comprehensive MetaAnalysis V3.exe software. Results and discussion: The pooled relative risk (RR) was 1.191 (95% confidence interval: 1.130-1.251). Although rural populations may not be exposed to as high temperatures as urban populations, they remain vulnerable to heat effects. Conclusion: There is evidence of heat vulnerability in rural populations and subpopulations. Heat vulnerability is not only determined by heat exposure, but also by sensitivity and adaptive capacity. Rural populations and sub-populations may be vulnerable to heat mortality due to low adaptive capacity. Further studies are needed to assess risk factors that predispose rural populations and sub-populations to heat mortality in order to develop effective public health interventions.