Mortalidade infantil e condições socioeconômicas nas microrregiões do Nordeste Brasileiro

The study aims to answer the following question: what are the different profiles of infant mortality, according to demographic, socioeconomic, infrastructure and health care, for the micro-regions at the Northeast of Brazil? Thus, the main objective is to analyze the profiles or typologies associated mortality levels sociodemographic conditions of the micro-regions, in the year 2010. To this end, the databases of birth and death certificates of SIM and SINASC (DATASUS/MS), were taken from the 2010 population Census microdata and from SIDRA/IBGE. As a methodology, a weighted multiple linear regression model was used in the analysis in order to find the most significant variables in the explanation child mortality for the year 2010. Also a cluster analysis was performed, seeking evidence, initially, of homogeneous groups of micro-regions, from of the significant variables. The logit of the infant mortality rate was used as dependent variable, while variables such as demographic, socioeconomic, infrastructure and health care in the micro-regions were taken as the independent variables of the model. The Bayesian estimation technique was applied to the database of births and deaths, due to the inconvenient fact of underreporting and random fluctuations of small quantities in small areas. The techniques of Spatial Statistics were used to determine the spatial behavior of the distribution of rates from thematic maps. In conclusion, we used the method GoM (Grade of Membership), to find typologies of mortality, associated with the selected variables by micro-regions, in order to respond the main question of the study. The results points out to the formation of three profiles: Profile 1, high infant mortality and unfavorable social conditions; Profile 2, low infant mortality, with a median social conditions of life; and Profile 3, median and high infant mortality social conditions. With this classification, it was found that, out of 188 micro-regions, 20 (10%) fits the extreme profile 1, 59 (31.4%) was characterized in the extreme profile 2, 34 (18.1%) was characterized in the extreme profile 3 and only 9 (4.8%) was classified as amorphous profile. The other micro-regions framed up in the profiles mixed. Such profiles suggest the need for different interventions in terms of public policies aimed to reducing child mortality in the region

Caracterização e modelagem dos sistemas de produção de caprinos leiteiros

The objectives of this research were characterizing the dairy goat production systems and model it using linear program. On the first step of this research, the model was developed using data from farms that was affiliated in the ACCOMIG/Caprileite, used a similar dairy goat production systems and have a partnership program with Universidade Federal de Minas Gerais . The data of research were from a structured questionnaire applied with farmers and monitoring of production systems during a guided visit on their farms. The results permitted identify that all farms were classified as a small and have a intensive production system. The average herd size had 63.75 dairy goats on lactation; it permits a production of 153, 38 kg of goat milk per day. It was observed that existing more than one channel of commercialization for the goat milk and their derivative products. The data obtained, on the first step of this research, was used to develop a linear program model. It was evaluated in two goat production systems, called P1 and P2. The results showed that the P1 system, with an annual birth and lactation during approximately 300 days was the best alternative for business. These results were compared with a mixed (beef and dairy) goat system in the semiarid region, which indicated merged with both systems. Therefore, to achieve profits and sustainability of the system, in all simulations it was necessary a minimum limit of funding of U.S. $ 10,000.00; this value permit earning of U.S. $ 792.00 per month and pay the investment within 5 years

Modelos de dispersão para extremos de precipitação. Estudo de caso: o nordeste do Brasil

In this thesis used four different methods in order to diagnose the precipitation extremes on Northeastern Brazil (NEB): Generalized Linear Model s via logistic regression and Poisson, extreme value theory analysis via generalized extre me value (GEV) and generalized Pareto (GPD) distributions and Vectorial Generalized Linea r Models via GEV (MVLG GEV). The logistic regression and Poisson models were used to identify the interactions between the precipitation extremes and other variables based on the odds ratios and relative risks. It was found that the outgoing longwave radiation was the indicator variable for the occurrence of extreme precipitation on eastern, northern and semi arid NEB, and the relative humidity was verified on southern NEB. The GEV and GPD distribut ions (based on the 95th percentile) showed that the location and scale parameters were presented the maximum on the eastern and northern coast NEB, the GEV verified a maximum core on western of Pernambuco influenced by weather systems and topography. The GEV and GPD shape parameter, for most regions the data fitted by Weibull negative an d Beta distributions (ξ < 0) , respectively. The levels and return periods of GEV (GPD) on north ern Maranhão (centerrn of Bahia) may occur at least an extreme precipitation event excee ding over of 160.9 mm /day (192.3 mm / day) on next 30 years. The MVLG GEV model found tha t the zonal and meridional wind components, evaporation and Atlantic and Pacific se a surface temperature boost the precipitation extremes. The GEV parameters show the following results: a) location ( ), the highest value was 88.26 ± 6.42 mm on northern Maran hão; b) scale ( σ ), most regions showed positive values, except on southern of Maranhão; an d c) shape ( ξ ), most of the selected regions were adjusted by the Weibull negative distr ibution ( ξ < 0 ). The southern Maranhão and southern Bahia have greater accuracy. The level period, it was estimated that the centern of Bahia may occur at least an extreme precipitatio n event equal to or exceeding over 571.2 mm/day on next 30 years.