Risk Assessment of the Introduction of H5N1 Highly Pathogenic Avian Influenza as a Tool to be Applied in Prevention Strategy Plan

Risks of the introduction of highly pathogenic avian influenza (HPAI) H5N1 through migratory birds to the main wintering site for wild birds in southern Brazil and its consequences were assessed. Likelihoods were estimated by a qualitative scale ranging from negligible to high. Northern migrants that breed in Alaska and regularly migrate to South America (primary Charadriiformes) can have contact with birds from affected areas in Asia. The likelihood of the introduction of HPAI H5N1 through migratory birds was found to be very low as it is a probability conditioned to successful transmission in breeding areas and the probabilities of an infected bird migrating and shedding the virus as far as southern Brazil. The probability of wild species becoming exposed to H5N1-infected birds is high as they nest with northern migrants from Alaska, whereas for backyard poultry it is moderate to high depending on proximity to wetlands and the presence of species that could increase the likelihood of contact with wild birds such as domestic duck. The magnitude of the biological and economic consequences of successful transmission to poultry or wild birds would be low to severe depending on the probability of the occurrence of outbreak scenarios described. As a result, the risk estimate is greater than negligible, and HPAI H5N1 prevention strategy in the region should always be carefully considered by the veterinary services in Brazil.

Use of Leptospira spp. strains isolated in Brazil in the microscopic agglutination test applied to diagnosis of leptospirosis in cattle herds in eight brazilian states

Sarmento A.M.C., Azevedo S.S., Morais Z.M., Souza G.O., Oliveira F.C.S., Goncales A.P., Miraglia F. & Vasconcellos S.A. 2012. [Use of Leptospira spp. strains isolated in Brazil in the microscopic agglutination test applied to diagnosis of leptospirosis in cattle herds in eight brazilian states.] Emprego de estirpes Leptospira spp. isoladas no Brasil na microtecnica de soroaglutinacao microscopica aplicada ao diagnostico da leptospirose em rebanhos bovinos de oito estados brasileiros. Pesquisa Veterinaria Brasileira 32(7);601-606. Universidade de Sao Paulo, Faculdade de Medicina Veterinaria e Zootecnia, Departamento de Medicina Veterinaria Preventiva e Saude Animal, Av. Prof. Dr. Orlando Marques de Paiva 87, Sao Paulo, SP 05508-270, Brazil. E-mail: savasco@usp.br The aim of this study was to investigate the adequacy of the use of autochthonous strains of leptospires isolated in Brazil, added to antigen collection of the microscopic agglutination test (MAT) applied to the diagnosis of bovine leptospirosis. By means of non-probability sampling, 109 farms and 9,820 cattle, females at reproductive age were chosen from 85 municipalities in the states of Goias, Mato Grosso, Mato Grosso do Sul, Minas Gerais, Parana, Rio Grande do Sul, Santa Catarina and Sao Paulo. Among the 9,820 examined animals, 5,806 (59.12%) were reactants at MAT for at least one serovar using the 23 reference serovars. Employing the collection of reference serovars and the ten autochthonous strains, 6,400 (65.24%) reactants and significant difference (p=0.001) was found. The most probable serovars identified by the collection of reference antigens were Hardjo (43.03%), Shermani (20%), Wolfi (9.96%), Grippothyphosa (5.42%) and Pomona (4.28%). With the collection amplified with the ten strains isolated in Brazil, the most probable serovars were Hardjo (31%), Guaricura-M4/84 (22.50%), Shermani (15.43%), Wolffi (4.76%), Grippothyphosa (3.71%) and Autumnalis (3.24%). The serovar Guaricura, strain M4/84, isolated from bovines and buffaloes in the State of Sao Paulo, was ranked as one of the three most probable serovars in the states of Goias, Mato Grosso, Mato Grosso do Sul, Minas Gerais and Sao Paulo. The addition of autochthonous strains to the MAT antigen collection provided the confirmation of the diagnosis of leptospirosis in 594 cattle (6%) which have been classified as non-reactants by the reference collection (p=0.001).

Robust statistical modeling using the Birnbaum-Saunders-t distribution applied to insurance

In this paper, we carry out robust modeling and influence diagnostics in Birnbaum-Saunders (BS) regression models. Specifically, we present some aspects related to BS and log-BS distributions and their generalizations from the Student-t distribution, and develop BS-t regression models, including maximum likelihood estimation based on the EM algorithm and diagnostic tools. In addition, we apply the obtained results to real data from insurance, which shows the uses of the proposed model. Copyright (c) 2011 John Wiley & Sons, Ltd.

Reliability algorithms applied to reinforced concrete structures durability assessment

This paper addresses the analysis of probabilistic corrosion time initiation in reinforced concrete structures exposed to ions chloride penetration. Structural durability is an important criterion which must be evaluated in every type of structure, especially when these structures are constructed in aggressive atmospheres. Considering reinforced concrete members, chloride diffusion process is widely used to evaluate the durability. Therefore, at modelling this phenomenon, corrosion of reinforcements can be better estimated and prevented. These processes begin when a threshold level of chlorides concentration is reached at the steel bars of reinforcements. Despite the robustness of several models proposed in the literature, deterministic approaches fail to predict accurately the corrosion time initiation due to the inherently randomness observed in this process. In this regard, the durability can be more realistically represented using probabilistic approaches. A probabilistic analysis of ions chloride penetration is presented in this paper. The ions chloride penetration is simulated using the Fick's second law of diffusion. This law represents the chloride diffusion process, considering time dependent effects. The probability of failure is calculated using Monte Carlo simulation and the First Order Reliability Method (FORM) with a direct coupling approach. Some examples are considered in order to study these phenomena and a simplified method is proposed to determine optimal values for concrete cover.

Confocal microscopy applied to the study of single entity fluorescence and light scattering

A sample scanning confocal optical microscope (SCOM) was designed and constructed in order to perform local measurements of fluorescence, light scattering and Raman scattering. This instrument allows to measure time resolved fluorescence, Raman scattering and light scattering from the same diffraction limited spot. Fluorescence from single molecules and light scattering from metallic nanoparticles can be studied. First, the electric field distribution in the focus of the SCOM was modelled. This enables the design of illumination modes for different purposes, such as the determination of the three-dimensional orientation of single chromophores. Second, a method for the calculation of the de-excitation rates of a chromophore was presented. This permits to compare different detection schemes and experimental geometries in order to optimize the collection of fluorescence photons. Both methods were combined to calculate the SCOM fluorescence signal of a chromophore in a general layered system. The fluorescence excitation and emission of single molecules through a thin gold film was investigated experimentally and modelled. It was demonstrated that, due to the mediation of surface plasmons, single molecule fluorescence near a thin gold film can be excited and detected with an epi-illumination scheme through the film. Single molecule fluorescence as close as 15nm to the gold film was studied in this manner. The fluorescence dynamics (fluorescence blinking and excited state lifetime) of single molecules was studied in the presence and in the absence of a nearby gold film in order to investigate the influence of the metal on the electronic transition rates. The trace-histogram and the autocorrelation methods for the analysis of single molecule fluorescence blinking were presented and compared via the analysis of Monte-Carlo simulated data. The nearby gold influences the total decay rate in agreement to theory. The gold presence produced no influence on the ISC rate from the excited state to the triplet but increased by a factor of 2 the transition rate from the triplet to the singlet ground state. The photoluminescence blinking of Zn0.42Cd0.58Se QDs on glass and ITO substrates was investigated experimentally as a function of the excitation power (P) and modelled via Monte-Carlo simulations. At low P, it was observed that the probability of a certain on- or off-time follows a negative power-law with exponent near to 1.6. As P increased, the on-time fraction reduced on both substrates whereas the off-times did not change. A weak residual memory effect between consecutive on-times and consecutive off-times was observed but not between an on-time and the adjacent off-time. All of this suggests the presence of two independent mechanisms governing the lifetimes of the on- and off-states. The simulated data showed Poisson-distributed off- and on-intensities, demonstrating that the observed non-Poissonian on-intensity distribution of the QDs is not a product of the underlying power-law probability and that the blinking of QDs occurs between a non-emitting off-state and a distribution of emitting on-states with different intensities. All the experimentally observed photo-induced effects could be accounted for by introducing a characteristic lifetime tPI of the on-state in the simulations. The QDs on glass presented a tPI proportional to P-1 suggesting the presence of a one-photon process. Light scattering images and spectra of colloidal and C-shaped gold nano-particles were acquired. The minimum size of a metallic scatterer detectable with the SCOM lies around 20 nm.

Essays in Applied and Labor Economics

This thesis consists of three self-contained papers. In the first paper I analyze the labor supply behavior of Bologna Pizza Delivery Vendors. Recent influential papers analyze labor supply behavior of taxi drivers (Camerer et al., 1997; and Crawford and Meng, 2011) and suggest that reference-dependence preferences have an important influence on drivers’ labor-supply decisions. Unlike previous papers, I am able to identify an exogenous and transitory change in labor demand. Using high frequency data on orders and rainfall as an exogenous demand shifter, I invariably find that reference-dependent preferences play no role in their labor’ supply decisions and the behavior of pizza vendors is perfectly consistent with the predictions of the standard model of labor’ supply. In the second paper, I investigate how the voting behavior of Members of Parliament is influenced by the Members seating nearby. By exploiting the random seating arrangements in the Icelandic Parliament, I show that being seated next to Members of a different party increases the probability of not being aligned with one’s own party. Using the exact spatial orientation of the peers, I provide evidence that supports the hypothesis that interaction is the main channel that explain these results. In the third paper, I provide an estimate of the trade flows that there would have been between the UK and Europe if the UK had joined the Euro. As an alternative approach to the standard log-linear gravity equation I employ the synthetic control method. I show that the aggregate trade flows between Britain and Europe would have been 13% higher if the UK had adopted the Euro.

A sequential Cox approach for estimating the causal effect of treatment in the presence of time-dependent confounding applied to data from the Swiss HIV Cohort Study

When estimating the effect of treatment on HIV using data from observational studies, standard methods may produce biased estimates due to the presence of time-dependent confounders. Such confounding can be present when a covariate, affected by past exposure, is both a predictor of the future exposure and the outcome. One example is the CD4 cell count, being a marker for disease progression for HIV patients, but also a marker for treatment initiation and influenced by treatment. Fitting a marginal structural model (MSM) using inverse probability weights is one way to give appropriate adjustment for this type of confounding. In this paper we study a simple and intuitive approach to estimate similar treatment effects, using observational data to mimic several randomized controlled trials. Each 'trial' is constructed based on individuals starting treatment in a certain time interval. An overall effect estimate for all such trials is found using composite likelihood inference. The method offers an alternative to the use of inverse probability of treatment weights, which is unstable in certain situations. The estimated parameter is not identical to the one of an MSM, it is conditioned on covariate values at the start of each mimicked trial. This allows the study of questions that are not that easily addressed fitting an MSM. The analysis can be performed as a stratified weighted Cox analysis on the joint data set of all the constructed trials, where each trial is one stratum. The model is applied to data from the Swiss HIV cohort study.

Concordance Probability and Discriminatory Power in Proportional Hazards Regression

The concordance probability is used to evaluate the discriminatory power and the predictive accuracy of nonlinear statistical models. We derive an analytic expression for the concordance probability in the Cox proportional hazards model. The proposed estimator is a function of the regression parameters and the covariate distribution only and does not use the observed event and censoring times. For this reason it is asymptotically unbiased, unlike Harrell's c-index based on informative pairs. The asymptotic distribution of the concordance probability estimate is derived using U-statistic theory and the methodology is applied to a predictive model in lung cancer.

Montecarlo method applied to comparison of tenders in construction projects.

La comparación de las diferentes ofertas presentadas en la licitación de un proyecto,con el sistema de contratación tradicional de medición abierta y precio unitario cerrado, requiere herramientas de análisis que sean capaces de discriminar propuestas que teniendo un importe global parecido pueden presentar un impacto económico muy diferente durante la ejecución. Una de las situaciones que no se detecta fácilmente con los métodos tradicionales es el comportamiento del coste real frente a las variaciones de las cantidades realmente ejecutadas en obra respecto de las estimadas en el proyecto. Este texto propone abordar esta situación mediante un sistema de análisis cuantitativo del riesgo como el método de Montecarlo. Este procedimiento, como es sabido, consiste en permitir que los datos de entrada que definen el problema varíen unas funciones de probabilidad definidas, generar un gran número de casos de prueba y tratar los resultados estadísticamente para obtener los valores finales más probables,con los parámetros necesarios para medir la fiabilidad de la estimación. Se presenta un modelo para la comparación de ofertas, desarrollado de manera que puede aplicarse en casos reales aplicando a los datos conocidos unas condiciones de variación que sean fáciles de establecer por los profesionales que realizan estas tareas. ABSTRACT: The comparison of the different bids in the tender for a project, with the traditional contract system based on unit rates open to and re-measurement, requires analysis tools that are able to discriminate proposals having a similar overall economic impact, but that might show a very different behaviour during the execution of the works. One situation not easily detected by traditional methods is the reaction of the actual cost to the changes in the exact quantity of works finally executed respect of the work estimated in the project. This paper intends to address this situation through the Monte Carlo method, a system of quantitative risk analysis. This procedure, as is known, is allows the input data defining the problem to vary some within well defined probability functions, generating a large number of test cases, the results being statistically treated to obtain the most probable final values, with the rest of the parameters needed to measure the reliability of the estimate. We present a model for the comparison of bids, designed in a way that it can be applied in real cases, based on data and assumptions that are easy to understand and set up by professionals who wish to perform these tasks.

Theory of intermittency applied to classical pathological cases

The classical theory of intermittency developed for return maps assumes uniform density of points reinjected from the chaotic to laminar region. Though it works fine in some model systems, there exist a number of so-called pathological cases characterized by a significant deviation of main characteristics from the values predicted on the basis of the uniform distribution. Recently, we reported on how the reinjection probability density (RPD) can be generalized. Here, we extend this methodology and apply it to different dynamical systems exhibiting anomalous type-II and type-III intermittencies. Estimation of the universal RPD is based on fitting a linear function to experimental data and requires no a priori knowledge on the dynamical model behind. We provide special fitting procedure that enables robust estimation of the RPD from relatively short data sets (dozens of points). Thus, the method is applicable for a wide variety of data sets including numerical simulations and real-life experiments. Estimated RPD enables analytic evaluation of the length of the laminar phase of intermittent behaviors. We show that the method copes well with dynamical systems exhibiting significantly different statistics reported in the literature. We also derive and classify characteristic relations between the mean laminar length and main controlling parameter in perfect agreement with data provided by numerical simulations

Improving classification using a Confidence Matrix based on weak classifiers applied to OCR

This paper proposes a new feature representation method based on the construction of a Confidence Matrix (CM). This representation consists of posterior probability values provided by several weak classifiers, each one trained and used in different sets of features from the original sample. The CM allows the final classifier to abstract itself from discovering underlying groups of features. In this work the CM is applied to isolated character image recognition, for which several set of features can be extracted from each sample. Experimentation has shown that the use of CM permits a significant improvement in accuracy in most cases, while the others remain the same. The results were obtained after experimenting with four well-known corpora, using evolved meta-classifiers with the k-Nearest Neighbor rule as a weak classifier and by applying statistical significance tests.

Spatial modeling of data with excessive zeros applied to reindeer pellet-group counts

We analyze a real data set pertaining to reindeer fecal pellet-group counts obtained from a survey conducted in a forest area in northern Sweden. In the data set, over 70% of counts are zeros, and there is high spatial correlation. We use conditionally autoregressive random effects for modeling of spatial correlation in a Poisson generalized linear mixed model (GLMM), quasi-Poisson hierarchical generalized linear model (HGLM), zero-inflated Poisson (ZIP), and hurdle models. The quasi-Poisson HGLM allows for both under- and overdispersion with excessive zeros, while the ZIP and hurdle models allow only for overdispersion. In analyzing the real data set, we see that the quasi-Poisson HGLMs can perform better than the other commonly used models, for example, ordinary Poisson HGLMs, spatial ZIP, and spatial hurdle models, and that the underdispersed Poisson HGLMs with spatial correlation fit the reindeer data best. We develop R codes for fitting these models using a unified algorithm for the HGLMs. Spatial count response with an extremely high proportion of zeros, and underdispersion can be successfully modeled using the quasi-Poisson HGLM with spatial random effects.