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

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

Eliminació autotròfica de nitrogen en una pila biològica (microbial fuel cells )

L’aigua i l’energia formen un binomi indissociable. En relació al cicle de l’aigua, des de fa varies dècades s’han desenvolupat diferents formes per recuperar part de l’energia relacionada amb l’aigua, per exemple a partir de centrals hidroelèctriques. No obstant, l’ús d’aquesta aigua també porta associat un gran consum energètic, relacionat sobretot amb el transport, la distribució, la depuració, etc... La depuració d’aigües residuals porta associada una elevada demanda energètica (Obis et al.,2009). En termes energètics, tot i que la despesa elèctrica d’una EDAR varia en funció de diferents paràmetres com la configuració i la capacitat de la planta, la càrrega a tractar, etc... es podria considerar que el rati mig seria d’ aproximadament 0.5 KWh•m-3.Els principals costos d’explotació estan relacionats tant amb la gestió de fangs (28%) com amb el consum elèctric (25%) (50% tractament biològic). Tot i que moltes investigacions relacionades amb el tractament d’aigua residual estan encaminades en disminuir els costos d’operació, des de fa poques dècades s’està investigant la viabilitat de que l’aigua residual fins i tot sigui una font d’energia, canviant la perspectiva, i començant a veure l’aigua residual no com a una problemàtica sinó com a un recurs. Concretament s’estima que l’aigua domèstica conté 9.3 vegades més energia que la necessària per el seu tractament mitjançant processos aerobis (Shizas et al., 2004). Un dels processos més desenvolupats relacionats amb el tractament d’aigües residuals i la producció energètica és la digestió anaeròbia. No obstant, aquesta tecnologia permet el tractament d’altes càrregues de matèria orgànica generant un efluent ric en nitrogen que s’haurà de tractar amb altres tecnologies. Per altre banda, recentment s’està investigant una nova tecnologia relacionada amb el tractament d’aigües residuals i la producció energètica: les piles biològiques (microbial fuel cells, MFC). Aquesta tecnologia permet obtenir directament energia elèctrica a partir de la degradació de substrats biodegradables (Rabaey et al., 2005). Les piles biològiques, més conegudes com a Microbial Fuel Cells (acrònim en anglès, MFC), són una emergent tecnologia que està centrant moltes mirades en el camp de l’ investigació, i que es basa en la producció d’energia elèctrica a partir de substrats biodegradables presents en l’aigua residual (Logan., 2008). Els fonaments de les piles biològiques és molt semblant al funcionament d’una pila Daniell, en la qual es separa en dos compartiments la reacció d’oxidació (compartiment anòdic) i la de reducció (compartiment catòdic) amb l’objectiu de generar un determinat corrent elèctric. En aquest estudi, bàsicament es mostra la posada en marxa d'una pila biològica per a l'eliminació de matèria orgànica i nitrogen de les aigües residuals.

Random amplified polymorphic DNA analysis of Anopheles nuneztovari (Diptera: Culicidae) from Western and Northeastern Colombia

Random amplified polymorphic DNA (RAPD) markers were used to analyze 119 DNA samples of three Colombian Anopheles nuneztovari populations to study genetic variation and structure. Genetic diversity, estimated from heterozygosity, averaged 0.34. Genetic flow was greater between the two populations located in Western Colombia (F ST: 0.035; Nm: 6.8) but lower between these two and the northeastern population (F ST: 0.08; Nm: 2.8). According to molecular variance analysis, the genetic distance between populations was significant (phiST 0.1131, P < 0.001). The variation among individuals within populations (phiST 0.8869, P < 0.001)was also significant, suggesting a greater degree of population subdivision, not considered in this study. Both the parameters evaluated and the genetic flow suggest that Colombian An. nuneztovari populations are co-specific.

Quantification of in vivo short echo-time proton magnetic resonance spectra at 14.1 T using two different approaches of modelling the macromolecule spectrum

Reliable quantification of the macromolecule signals in short echo-time H-1 MRS spectra is particularly important at high magnetic fields for an accurate quantification of metabolite concentrations (the neurochemical profile) due to effectively increased spectral resolution of the macromolecule components. The purpose of the present study was to assess two approaches of quantification, which take the contribution of macromolecules into account in the quantification step. H-1 spectra were acquired on a 14.1 T/26 cm horizontal scanner on five rats using the ultra-short echo-time SPECIAL (spin echo full intensity acquired localization) spectroscopy sequence. Metabolite concentrations were estimated using LCModel, combined with a simulated basis set of metabolites using published spectral parameters and either the spectrum of macromolecules measured in vivo, using an inversion recovery technique, or baseline simulated by the built-in spline function. The fitted spline function resulted in a smooth approximation of the in vivo macromolecules, but in accordance with previous studies using Subtract-QUEST could not reproduce completely all features of the in vivo spectrum of macromolecules at 14.1 T. As a consequence, the measured macromolecular 'baseline' led to a more accurate and reliable quantification at higher field strengths.

Uncertainties regarding dengue modeling in Rio de Janeiro, Brazil

Dengue fever is currently the most important arthropod-borne viral disease in Brazil. Mathematical modeling of disease dynamics is a very useful tool for the evaluation of control measures. To be used in decision-making, however, a mathematical model must be carefully parameterized and validated with epidemiological and entomological data. In this work, we developed a simple dengue model to answer three questions: (i) which parameters are worth pursuing in the field in order to develop a dengue transmission model for Brazilian cities; (ii) how vector density spatial heterogeneity influences control efforts; (iii) with a degree of uncertainty, what is the invasion potential of dengue virus type 4 (DEN-4) in Rio de Janeiro city. Our model consists of an expression for the basic reproductive number (R0) that incorporates vector density spatial heterogeneity. To deal with the uncertainty regarding parameter values, we parameterized the model using a priori probability density functions covering a range of plausible values for each parameter. Using the Latin Hypercube Sampling procedure, values for the parameters were generated. We conclude that, even in the presence of vector spatial heterogeneity, the two most important entomological parameters to be estimated in the field are the mortality rate and the extrinsic incubation period. The spatial heterogeneity of the vector population increases the risk of epidemics and makes the control strategies more complex. At last, we conclude that Rio de Janeiro is at risk of a DEN-4 invasion. Finally, we stress the point that epidemiologists, mathematicians, and entomologists need to interact more to find better approaches to the measuring and interpretation of the transmission dynamics of arthropod-borne diseases.

Parameters affecting cellular invasion and escape from the parasitophorous vacuole by different infective forms of Trypanosoma cruzi

In this study we have examined certain aspects of the process of cell invasion and parasitophorous vacuole escape by metacyclic trypomastigotes and extracellular amastigote forms of Trypanosoma cruzi (G strain). Using Vero (and HeLa) cells as targets, we detected differences in the kinetics of vacuole escape by the two forms. Alcalinization of intercellular pH influenced both invasion as well as the escape from the parasitophorous vacuole by metacyclic trypomastigotes, but not the escape kinetics of extracellular amastigotes. We used sialic acid mutants as target cells and observed that the deficiency of this molecule facilitated the escape of both infective forms. Hemolysin activity was only detected in extracellular amastigotes and neither form presented detectable transialidase activity. Invasion of extracellular amastigotes and trypomastigotes in Vero cells was affected in different ways by drugs that interfere with host cell Ca2+ mobilization. These results are in line with previous results that indicate that metacyclic trypomastigotes and extracellular amastigote forms utilize mechanisms with particular features to invade host cells and to escape from their parasitophorous vacuoles.

Effect of Platinum-Based Chemoradiotherapy on Cellular Proliferation in Bone Marrow and Spleen, Estimated by 18F-FLT PET/CT in Patients with Locally Advanced Non-Small Cell Lung Cancer.

Historically, it has been difficult to monitor the acute impact of anticancer therapies on hematopoietic organs on a whole-body scale. Deeper understanding of the effect of treatments on bone marrow would be of great potential value in the rational design of intensive treatment regimens. 3'-deoxy-3'-(18)F-fluorothymidine ((18)F-FLT) is a functional radiotracer used to study cellular proliferation. It is trapped in cells in proportion to thymidine-kinase 1 enzyme expression, which is upregulated during DNA synthesis. This study investigates the potential of (18)F-FLT to monitor acute effects of chemotherapy on cellular proliferation and its recovery in bone marrow, spleen, and liver during treatment with 2 different chemotherapy regimens.

Alzheimer's Disease Biomarkers, 2009

This report gives a comprehensive and up-to-date review of Alzheimer's disease biomarkers. Recent years have seen significant advances in this field. Whilst considerable effort has focused on A�_ and tau related markers, a substantial number of other molecules have been identified, that may offer new opportunities.This Report : Identifies 60 candidate Alzheimer's (AD) biomarkers and their associated studies. Of these, 49 are single species or single parameters, 7 are combinations or panels and 4 involve the measurement of two species or parameters or their ratios. These include proteins (n=34), genes (n=11), image-based parameters (n=7), small molecules (n=3), proteins + genes (n=2) and others (n=3). Of these, 30 (50%) relate to species identified in CSF and 19 (32%) were found in the blood. These candidate may be classified on the basis of their diagnostic utility, namely those which i) may allow AD to be detected when the disease has developed (48 of 75†= 64%), ii) may allow early detection of AD (18 of 75† = 24%) and iii) may allow AD to be predicted before the disease has begun to develop (9 of 75†= 12%). † Note: Of these, 11 were linked to two or more of these capabilities (e.g. allowed both early-stage detection as well as diagnosis after the disease has developed).Biomarkers: AD biomarkers identified in this report show significant diversity, however of the 60 described, 18 (30%) are associated with amyloid beta (A�_) and 9 (15%) relate to Tau. The remainder of the biomarkers (just over half) fall into a number of different groups. Of these, some are associated with other hypotheses on the pathogenesis of AD however the vast majority are individually unique and not obviously linked with other markers. Analysis and discussion presented in this report includes summaries of the studies and clinical trials that have lead to the identification of these markers. Where it has been calculated, diagnostic sensitivity, specificity and the capacity of these markers to differentiate patients with suspected AD from healthy controls and individuals believed to be suffering from other neurodegenerative conditions, have been indicated. These findings are discussed in relation to existing hypotheses on the pathogenesis of the AD and the current drug development pipeline. Many uncertainties remain in relation to the pathogenesis of AD, in diagnosing and treating the disease and many of the studies carried out to identify disease markers are at an early stage and will require confirmation through larger and longer investigations. Nevertheless, significant advances in the identification of AD biomarkers have now been made. Moreover, whilst much of the research on AD biomarkers has focused on amyloid and tau related species, it is evident that a substantial number of other species may provide important opportunities.Purpose of Report: To provide a comprehensive review of important and recently discovered candidate biomarkers of AD, in particular those with potential to reliably detect the disease or with utility in clinical development, drug repurposing, in studies of the pathogenesis and in monitoring drug response and the course of the disease. Other key goals were to identify markers that support current pipeline developments, indicate new potential drug targets or which advance understanding of the pathogenesis of this disease.Drug Repurposing: Studies of the pathogenesis of AD have identified aberrant changes in a number of other disease areas including inflammation, diabetes, oxidative stress, lipid metabolism and others. These findings have prompted studies to evaluate some existing approved drugs to treat AD. This report identifies studies of 9 established drug classes currently being investigated for potential repurposing.Alzheimer’s Disease: In 2005, the global prevalence of dementia was estimated at 25 million, with more than 4 million new cases occurring each year. It is also calculated that the number of people affected will double every 20 years, to 80 million by 2040, if a cure is not found. More than 50% of dementia cases are due to AD. Today, approximately 5 million individuals in the US suffer from AD, representing one in eight people over the age of 65. Direct and indirect costs of AD and other forms of dementia in the US are around $150 billion annually. Worldwide, costs for dementia care are estimated at $315 billion annually. Despite significant research into this debilitating and ultimately fatal disease, advances in the development of diagnostic tests for AD and moreover, effective treatments, remain elusive.Background: Alzheimer's disease is the most common cause of dementia, yet its clinical diagnosis remains uncertain until an eventual post-mortem histopathology examination is carried out. Currently, therapy for patients with Alzheimer disease only treats the symptoms; however, it is anticipated that new disease-modifying drugs will soon become available. The urgency for new and effective treatments for AD is matched by the need for new tests to detect and diagnose the condition. Uncertainties in the diagnosis of AD mean that the disease is often undiagnosed and under treated. Moreover, it is clear that clinical confirmation of AD, using cognitive tests, can only be made after substantial neuronal cell loss has occurred; a process that may have taken place over many years. Poor response to current therapies may therefore, in part, reflect the fact that such treatments are generally commenced only after neuronal damage has occurred. The absence of tests to detect or diagnose presymptomatic AD also means that there is no standard that can be applied to validate experimental findings (e.g. in drug discovery) without performing lengthy studies, and eventual confirmation by autopsy.These limitations are focusing considerable effort on the identification of biomarkers that advance understanding of the pathogenesis of AD and how the disease can be diagnosed in its early stages and treated. It is hoped that developments in these areas will help physicians to detect AD and guide therapy before the first signs of neuronal damage appears. The last 5-10 years have seen substantial research into the pathogenesis of AD and this has lead to the identification of a substantial number of AD biomarkers, which offer important insights into this disease. This report brings together the latest advances in the identification of AD biomarkers and analyses the opportunities they offer in drug R&D and diagnostics.��

Laboratory estimation of the effects of increasing temperatures on the duration of gonotrophic cycle of Anopheles albimanus (Diptera: Culicidae)

The increase of malaria transmission in the Pacific Coast of Colombia during the occurrence of El Niño warm event has been found not to be linked to increases in the density of the vector Anopheles albimanus, but to other temperature-sensitive variables such as longevity, duration of the gonotrophic cycle or the sporogonic period of Plasmodium. The present study estimated the effects of temperature on duration of the gonotrophic cycle and on maturation of the ovaries of An. albimanus. Blood fed adult mosquitoes were exposed to temperatures of 24, 27, and 30°C, held individually in oviposition cages and assessed at 12 h intervals. At 24, 27, and 30°C the mean development time of the oocytes was 91.2 h (95% C.I.: 86.5-96), 66.2 h (61.5-70.8), and 73.1 h (64-82.3), respectively. The mean duration of the gonotrophic cycle for these three temperatures was 88.4 h (81.88-94.9), 75 h (71.4-78.7), and 69.1 h (64.6-73.6) respectively. These findings indicate that both parameters in An. albimanus are reduced when temperatures rose from 24 to 30°C, in a nonlinear manner. According to these results the increase in malaria transmission during El Niño in Colombia could be associated with a shortening of the gonotrophic cycle in malaria vectors, which could enhance the frequency of man-vector contact, affecting the incidence of the disease.

Higher genetic variation estimated by microsatellites compared to isoenzyme markers in Aedes aegypti from Rio de Janeiro

Aedes aegypti populations from five districts in Rio de Janeiro were analyzed using five microsatellites and six isoenzyme markers, to assess the amount of variation and patterns of gene flow at local levels. Microsatellite loci were polymorphic enough to detect genetic differentiation of populations collected at small geographic scales (e.g. within a city). Ae. aegypti populations were highly differentiated as well in the city center as in the outskirt. Thus, dengue virus propagation by mosquitoes could be as efficient in the urban area as in the outskirt of Rio de Janeiro, the main entry point of dengue in Brazil.

Experimental infection parameters in Galea spixii (Rodentia: Caviidae) with Leishmania infantum chagasi

In order to better understand the epidemiological transmission network of leishmaniasis, an endemic disease in Northeast Brazil, we investigated the susceptibility of Spix yellow-toothed cavies (Galea spixii) to the Leishmania infantum chagasi parasite. Nine cavies were experimentally infected, separated into three groups and monitored at 30, 90 and 180 days, respectively. Amastigotes were identified in the spleen slides of two cavies killed 180 days after infection. Antibodies against the L. i. chagasi were identified in one of the cavies. This demonstrates that G. spixii is in fact capable of maintaining a stable infection by L. i. chagasi without alterations in biochemical and hematological parameters of the host and without perceivable micro and macroscopic lesions.

Robust Factor Analysis for Compositional Data

Factor analysis as frequent technique for multivariate data inspection is widely used also for compositional data analysis. The usual way is to use a centered logratio (clr)transformation to obtain the random vector y of dimension D. The factor model istheny = Λf + e (1)with the factors f of dimension k & D, the error term e, and the loadings matrix Λ.Using the usual model assumptions (see, e.g., Basilevsky, 1994), the factor analysismodel (1) can be written asCov(y) = ΛΛT + ψ (2)where ψ = Cov(e) has a diagonal form. The diagonal elements of ψ as well as theloadings matrix Λ are estimated from an estimation of Cov(y).Given observed clr transformed data Y as realizations of the random vectory. Outliers or deviations from the idealized model assumptions of factor analysiscan severely effect the parameter estimation. As a way out, robust estimation ofthe covariance matrix of Y will lead to robust estimates of Λ and ψ in (2), seePison et al. (2003). Well known robust covariance estimators with good statisticalproperties, like the MCD or the S-estimators (see, e.g. Maronna et al., 2006), relyon a full-rank data matrix Y which is not the case for clr transformed data (see,e.g., Aitchison, 1986).The isometric logratio (ilr) transformation (Egozcue et al., 2003) solves thissingularity problem. The data matrix Y is transformed to a matrix Z by usingan orthonormal basis of lower dimension. Using the ilr transformed data, a robustcovariance matrix C(Z) can be estimated. The result can be back-transformed tothe clr space byC(Y ) = V C(Z)V Twhere the matrix V with orthonormal columns comes from the relation betweenthe clr and the ilr transformation. Now the parameters in the model (2) can beestimated (Basilevsky, 1994) and the results have a direct interpretation since thelinks to the original variables are still preserved.The above procedure will be applied to data from geochemistry. Our specialinterest is on comparing the results with those of Reimann et al. (2002) for the Kolaproject data

Container productivity, daily survival rates and dispersal of Aedes aegypti mosquitoes in a high income dengue epidemic neighbourhood of Rio de Janeiro: presumed influence of differential urban structure on mosquito biology

Different urban structures might affect the life history parameters of Aedes aegypti and, consequently, dengue transmission. Container productivity, probability of daily survival (PDS) and dispersal rates were estimated for mosquito populations in a high income neighbourhood of Rio de Janeiro. Results were contrasted with those previously found in a suburban district, as well as those recorded in a slum. After inspecting 1,041 premises, domestic drains and discarded plastic pots were identified as the most productive containers, collectively holding up to 80% of the total pupae. In addition, three cohorts of dust-marked Ae. aegypti females were released and recaptured daily using BGS-Traps, sticky ovitraps and backpack aspirators in 50 randomly selected houses; recapture rate ranged from 5-12.2% within cohorts. PDS was determined by two models and ranged from 0.607-0.704 (exponential model) and 0.659-0.721 (non-linear model), respectively. Mean distance travelled varied from 57-122 m, with a maximum dispersal of 263 m. Overall, lower infestation indexes and adult female survival were observed in the high income neighbourhood, suggesting a lower dengue transmission risk in comparison to the suburban area and the slum. Since results show that urban structure can influence mosquito biology, specific control strategies might be used in order to achieve cost-effective Ae. aegypti control.