Infant mortality in Brazil, 1980-2000: A spatial panel data analysis

Background: Infant mortality is an important measure of human development, related to the level of welfare of a society. In order to inform public policy, various studies have tried to identify the factors that influence, at an aggregated level, infant mortality. The objective of this paper is to analyze the regional pattern of infant mortality in Brazil, evaluating the effect of infrastructure, socio-economic, and demographic variables to understand its distribution across the country. Methods: Regressions including socio-economic and living conditions variables are conducted in a structure of panel data. More specifically, a spatial panel data model with fixed effects and a spatial error autocorrelation structure is used to help to solve spatial dependence problems. The use of a spatial modeling approach takes into account the potential presence of spillovers between neighboring spatial units. The spatial units considered are Minimum Comparable Areas, defined to provide a consistent definition across Census years. Data are drawn from the 1980, 1991 and 2000 Census of Brazil, and from data collected by the Ministry of Health (DATASUS). In order to identify the influence of health care infrastructure, variables related to the number of public and private hospitals are included. Results: The results indicate that the panel model with spatial effects provides the best fit to the data. The analysis confirms that the provision of health care infrastructure and social policy measures (e. g. improving education attainment) are linked to reduced rates of infant mortality. An original finding concerns the role of spatial effects in the analysis of IMR. Spillover effects associated with health infrastructure and water and sanitation facilities imply that there are regional benefits beyond the unit of analysis. Conclusions: A spatial modeling approach is important to produce reliable estimates in the analysis of panel IMR data. Substantively, this paper contributes to our understanding of the physical and social factors that influence IMR in the case of a developing country.

MATHEMATICAL ANALYSIS OF MAXIMUM POWER GENERATED BY PHOTOVOLTAIC SYSTEMS AND FITTING CURVES FOR STANDARD TEST CONDITIONS

The rural electrification is characterized by geographical dispersion of the population, low consumption, high investment by consumers and high cost. Moreover, solar radiation constitutes an inexhaustible source of energy and in its conversion into electricity photovoltaic panels are used. In this study, equations were adjusted to field conditions presented by the manufacturer for current and power of small photovoltaic systems. The mathematical analysis was performed on the photovoltaic rural system I- 100 from ISOFOTON, with power 300 Wp, located at the Experimental Farm Lageado of FCA/UNESP. For the development of such equations, the circuitry of photovoltaic cells has been studied to apply iterative numerical methods for the determination of electrical parameters and possible errors in the appropriate equations in the literature to reality. Therefore, a simulation of a photovoltaic panel was proposed through mathematical equations that were adjusted according to the data of local radiation. The results have presented equations that provide real answers to the user and may assist in the design of these systems, once calculated that the maximum power limit ensures a supply of energy generated. This real sizing helps establishing the possible applications of solar energy to the rural producer and informing the real possibilities of generating electricity from the sun.

Pilot Studies for Development of an HIV Subtype Panel for Surveillance of Global Diversity

The continued global spread and evolution of HIV diversity pose significant challenges to diagnostics and vaccine strategies. NIAID partnered with the FDA, WRAIR, academia, and industry to form a Viral Panel Working Group to design and prepare a panel of well-characterized current and diverse HIV isolates. Plasma samples that had screened positive for HIV infection and had evidence of recently acquired infection were donated by blood centers in North and South America, Europe, and Africa. A total of 80 plasma samples were tested by quantitative nucleic acid tests, p24 antigen, EIA, and Western blot to assign a Fiebig stage indicative of approximate time from initial infection. Evaluation of viral load using FDA-cleared assays showed excellent concordance when subtype B virus was tested, but lower correlations for subtype C. Plasma samples were cocultivated with phytohemagglutinin (PHA)-stimulated peripheral blood mononuclear cells (PBMCs) from normal donors to generate 30 viral isolates (50-80% success rate for samples with viral load >10,000 copies/ml), which were then expanded to 10(7)-10(9) virus copies per ml. Analysis of env sequences showed that sequences derived from cultured PBMCs were not distinguishable from those obtained from the original plasma. The pilot collection includes 30 isolates representing subtypes B, C, B/F, CRF04_cpx, and CRF02_AG. These studies will serve as a basis for the development of a comprehensive panel of highly characterized viral isolates that reflects the current dynamic and complex HIV epidemic, and will be made available through the External Quality Assurance Program Oversight Laboratory (EQAPOL).