Use of Poisson spatiotemporal regression models for the Brazilian Amazon Forest: malaria count data

INTRODUCTION: Malaria is a serious problem in the Brazilian Amazon region, and the detection of possible risk factors could be of great interest for public health authorities. The objective of this article was to investigate the association between environmental variables and the yearly registers of malaria in the Amazon region using Bayesian spatiotemporal methods. METHODS: We used Poisson spatiotemporal regression models to analyze the Brazilian Amazon forest malaria count for the period from 1999 to 2008. In this study, we included some covariates that could be important in the yearly prediction of malaria, such as deforestation rate. We obtained the inferences using a Bayesian approach and Markov Chain Monte Carlo (MCMC) methods to simulate samples for the joint posterior distribution of interest. The discrimination of different models was also discussed. RESULTS: The model proposed here suggests that deforestation rate, the number of inhabitants per km², and the human development index (HDI) are important in the prediction of malaria cases. CONCLUSIONS: It is possible to conclude that human development, population growth, deforestation, and their associated ecological alterations are conducive to increasing malaria risk. We conclude that the use of Poisson regression models that capture the spatial and temporal effects under the Bayesian paradigm is a good strategy for modeling malaria counts.

Geographic weighted regression: applicability to epidemiological studies of leprosy

Abstract: INTRODUCTION: Geographic information systems (GIS) enable public health data to be analyzed in terms of geographical variability and the relationship between risk factors and diseases. This study discusses the application of the geographic weighted regression (GWR) model to health data to improve the understanding of spatially varying social and clinical factors that potentially impact leprosy prevalence. METHODS: This ecological study used data from leprosy case records from 1998-2006, aggregated by neighborhood in the Duque de Caxias municipality in the State of Rio de Janeiro, Brazil. In the GWR model, the associations between the log of the leprosy detection rate and social and clinical factors were analyzed. RESULTS: Maps of the estimated coefficients by neighborhood confirmed the heterogeneous spatial relationships between the leprosy detection rates and the predictors. The proportion of households with piped water was associated with higher detection rates, mainly in the northeast of the municipality. Indeterminate forms were strongly associated with higher detections rates in the south, where access to health services was more established. CONCLUSIONS: GWR proved a useful tool for epidemiological analysis of leprosy in a local area, such as Duque de Caxias. Epidemiological analysis using the maps of the GWR model offered the advantage of visualizing the problem in sub-regions and identifying any spatial dependence in the local study area.

Association between LDL-C, Non HDL-C, and Apolipoprotein B Levels with Coronary Plaque Regression

Background:Previous reports have inferred a linear relationship between LDL-C and changes in coronary plaque volume (CPV) measured by intravascular ultrasound. However, these publications included a small number of studies and did not explore other lipid markers.Objective:To assess the association between changes in lipid markers and regression of CPV using published data.Methods:We collected data from the control, placebo and intervention arms in studies that compared the effect of lipidlowering treatments on CPV, and from the placebo and control arms in studies that tested drugs that did not affect lipids. Baseline and final measurements of plaque volume, expressed in mm3, were extracted and the percentage changes after the interventions were calculated. Performing three linear regression analyses, we assessed the relationship between percentage and absolute changes in lipid markers and percentage variations in CPV.Results:Twenty-seven studies were selected. Correlations between percentage changes in LDL-C, non-HDL-C, and apolipoprotein B (ApoB) and percentage changes in CPV were moderate (r = 0.48, r = 0.47, and r = 0.44, respectively). Correlations between absolute differences in LDL-C, non‑HDL-C, and ApoB with percentage differences in CPV were stronger (r = 0.57, r = 0.52, and r = 0.79). The linear regression model showed a statistically significant association between a reduction in lipid markers and regression of plaque volume.Conclusion:A significant association between changes in different atherogenic particles and regression of CPV was observed. The absolute reduction in ApoB showed the strongest correlation with coronary plaque regression.

Morphological aspects of the myocarditis and myositis in Calomys callosus experimentally infected with Trypanosoma cruzi: fibrogenesis and spontaneous regression of fibrosis

Calomys callosus a wild rodent, is a natural host of Trypanosoma cruzi. Twelve C. callosus were infected with 10(5) trypomastigotes of the F strain (a myotropic strain) of T. cruzi. Parasitemia decreased on the 21 st day becoming negative around the 40th day of infection. All animals survived but had positive parasitological tests, until the end of the experiment. The infected animals developed severe inflammation in the myocardium and skeletal muscle. This process was pronounced from the 26 th to the 30th day and gradually subsided from the 50 th day becoming absent or residual on the 64 th day after infection. Collagen was identified by the picro Sirius red method. Fibrogenesis developed early, but regression of fibrosis occurred between the 50th and 64th day. Ultrastructural study disclosed a predominance of macrophages and fibroblasts in the inflammatory infiltrates, with small numbers of lymphocytes. Macrophages had active phagocytosis and showed points of contact with altered muscle cells. Different degrees of matrix expansion were present, with granular and fibrilar deposits and collagen bundles. These alterations subsided by the 64th days. Macrophages seem to be the main immune effector cell in the C. callosus model of infection with T. cruzi. The mechanisms involved in the rapid fibrogenesis and its regression deserve further investigation.

Analysis and estimative of schistosomiasis prevalence for the state of Minas Gerais, Brazil, using multiple regression with social and environmental spatial data

The aim of this work is to establish a relationship between schistosomiasis prevalence and social-environmental variables, in the state of Minas Gerais, Brazil, through multiple linear regression. The final regression model was established, after a variables selection phase, with a set of spatial variables which contains the summer minimum temperature, human development index, and vegetation type variables. Based on this model, a schistosomiasis risk map was built for Minas Gerais.

Consumo e custo da alimentação para recuperação da atividade ovariana luteal cíclica de vacas mestiças leiteiras com anestro

O objetivo do trabalho foi verificar o consumo e o custo de alimentos para recuperação da atividade ovariana luteal cíclica (AOLC) em vacas mestiças Holandês x Zebu com anestro. Foram usadas 18 vacas, não-gestantes, não-lactantes, magras, apresentando ovários sem função luteal, de tamanho normal e sem folículos palpáveis na superfície. Doze animais permaneceram em confinamento e receberam alimentação para ganho de peso até o reinício da AOLC. Os seis animais restantes, constituindo o grupo controle, receberam alimentação de mantença para o baixo peso apresentado e permaneceram em anestro durante o período experimental. A AOLC foi avaliada pela concentração de progesterona no soro sangüíneo (coleta de sangue a cada sete dias), pelo exame dos ovários por palpação retal a cada 12 dias, e observação visual dos sinais do estro três vezes ao dia. A recuperação da AOLC nas vacas com anestro exigiu um consumo médio de 722,4 kg de matéria seca, 50,4 kg de proteína bruta e 402,4 kg de NDT, relativos à ingestão média de 2.374,2 kg de volumoso e 194,1 kg de concentrado. O custo desses alimentos somado à perda estimada da produção de leite numa vaca de 3.000 litros de leite/lactação, provocada pelo prolongamento do intervalo de partos, foi equivalente a 1.364,2 litros de leite (preço recebido pelo produtor = R$ 0,20/litro). Esse custo elevado da recuperação do anestro onera o custo final da produção de leite, tendo em vista a alta incidência de anestro nos rebanhos brasileiros.

Peso para recuperação da atividade ovariana luteal cíclica em vacas leiteiras mestiças em anestro

Procurou-se conhecer o ganho de peso necessário e o peso mínimo para restabelecimento da atividade ovariana luteal cíclica (AOLC) em vacas adultas, mestiças Holandês x Zebu, não-lactantes, magras e com ovários inativos, anestro adquirido após longo período de restrição alimentar. Seis animais, com peso médio de 322,0 ± 27,0 kg, receberam dieta de mantença para o baixo peso apresentado (grupo I) e 12 animais, com peso médio de 315,0 ± 29,4 kg, foram alimentados para ganho de peso até a recuperação da AOLC (grupo II). O sangue foi coletado (dosagem de progesterona-RIA), e os animais, pesados semanalmente. A AOLC foi avaliada pela concentração de progesterona no sangue, exame dos ovários por palpação retal a cada 12 dias e observação visual do estro três vezes ao dia. O reinício da AOLC ocorreu nos animais do grupo II quando pesaram em média 392,7 ± 29,4 kg. A média do ganho de peso total nesse grupo foi de 77,7 ± 11,2 kg, correspondendo a 24,7 ± 4,5% do peso desses animais em anestro, ou 37,7% dos 206,2 kg perdidos na fase de restrição alimentar para adquirir anestro. Os seis animais do grupo I permaneceram em anestro. Os resultados mostram a influência do nível alimentar sobre a função luteal ovariana e a necessidade de ganho de peso para o restabelecimento do ciclo estral em vacas mestiças leiteiras, magras e em anestro.

Restrição alimentar e atividade ovariana luteal cíclica pós-parto em vacas girolanda

Objetivou-se neste trabalho verificar se a restrição alimentar no pós-partoem vacas Girolanda, multíparas, de bom escore de condição corporal (ECC = 3,5 a 4,5) ao parto será suficiente para impedir o reinício da atividade ovariana luteal cíclica (AOLC) pós-parto.Os animais foram distribuídos em três tratamentos: Grupo I (n = 15), mantença; Grupo II (n = 10) e Grupo III (n = 13), sendo que os grupos II e III receberam restrição alimentar até 90 e 180 dias pós-parto, respectivamente. As pesagens e avaliações do ECC foram efetuadas logo após o parto, e depois semanalmente. A AOLC foi avaliada por palpação retal, observação de cio e concentração de progesterona no leite. Os intervalos do parto ao primeiro cio foram de 53,1, 63,2 e 51,2 dias (P>0,05), respectivamente para os Grupos I, II e III, que apresentaram perdas de peso de 7,3 kg, 57,0 kg e 63,7 kg nesse período; e de 14,2 kg, 63,8 kg e 78,4 kg do parto até 90 dias pós-parto, repectivamente. Em vacas Girolanda de bom escore de condição corporal ao parto, a perda de 15,2% do peso nos três primeiros meses de lactação, e de 16,3% do peso até 180 dias pós-parto, não é suficiente para atrasar o reinício ou interromper a AOLC nos respectivos períodos.

Stability and adaptability of runner peanut genotypes based on nonlinear regression and AMMI analysis

The objective of this work was to estimate the stability and adaptability of pod and seed yield in runner peanut genotypes based on the nonlinear regression and AMMI analysis. Yield data from 11 trials, distributed in six environments and three harvests, carried out in the Northeast region of Brazil during the rainy season were used. Significant effects of genotypes (G), environments (E), and GE interactions were detected in the analysis, indicating different behaviors among genotypes in favorable and unfavorable environmental conditions. The genotypes BRS Pérola Branca and LViPE‑06 are more stable and adapted to the semiarid environment, whereas LGoPE‑06 is a promising material for pod production, despite being highly dependent on favorable environments.

Random regression models to estimate genetic parameters for milk production of Guzerat cows using orthogonal Legendre polynomials

The objective of this work was to compare random regression models for the estimation of genetic parameters for Guzerat milk production, using orthogonal Legendre polynomials. Records (20,524) of test-day milk yield (TDMY) from 2,816 first-lactation Guzerat cows were used. TDMY grouped into 10-monthly classes were analyzed for additive genetic effect and for environmental and residual permanent effects (random effects), whereas the contemporary group, calving age (linear and quadratic effects) and mean lactation curve were analized as fixed effects. Trajectories for the additive genetic and permanent environmental effects were modeled by means of a covariance function employing orthogonal Legendre polynomials ranging from the second to the fifth order. Residual variances were considered in one, four, six, or ten variance classes. The best model had six residual variance classes. The heritability estimates for the TDMY records varied from 0.19 to 0.32. The random regression model that used a second-order Legendre polynomial for the additive genetic effect, and a fifth-order polynomial for the permanent environmental effect is adequate for comparison by the main employed criteria. The model with a second-order Legendre polynomial for the additive genetic effect, and that with a fourth-order for the permanent environmental effect could also be employed in these analyses.

Optimization of wood flour acetylation by factorial design and partial least squares regression

Acetylation was performed to reduce the polarity of wood and increase its compatibility with polymer matrices for the production of composites. These reactions were performed first as a function of acetic acid and anhydride concentration in a mixture catalyzed by sulfuric acid. A concentration of 50%/50% (v/v) of acetic acid and anhydride was found to produced the highest conversion rate between the functional groups. After these reactions, the kinetics were investigated by varying times and temperatures using a 3² factorial design, and showed time was the most relevant parameter in determining the conversion of hydroxyl into carbonyl groups.

Least squares regression with errors in both variables: case studies

Analytical curves are normally obtained from discrete data by least squares regression. The least squares regression of data involving significant error in both x and y values should not be implemented by ordinary least squares (OLS). In this work, the use of orthogonal distance regression (ODR) is discussed as an alternative approach in order to take into account the error in the x variable. Four examples are presented to illustrate deviation between the results from both regression methods. The examples studied show that, in some situations, ODR coefficients must substitute for those of OLS, and, in other situations, the difference is not significant.

Logistic regression to estimate the welfare of broiler breeders in relation to environmental and behavioral variables

The increasing demand of consumer markets for the welfare of birds in poultry house has motivated many scientific researches to monitor and classify the welfare according to the production environment. Given the complexity between the birds and the environment of the aviary, the correct interpretation of the conduct becomes an important way to estimate the welfare of these birds. This study obtained multiple logistic regression models with capacity of estimating the welfare of broiler breeders in relation to the environment of the aviaries and behaviors expressed by the birds. In the experiment, were observed several behaviors expressed by breeders housed in a climatic chamber under controlled temperatures and three different ammonia concentrations from the air monitored daily. From the analysis of the data it was obtained two logistic regression models, of which the first model uses a value of ammonia concentration measured by unit and the second model uses a binary value to classify the ammonia concentration that is assigned by a person through his olfactory perception. The analysis showed that both models classified the broiler breeder's welfare successfully.