24 resultados para Space representation
em Scielo Saúde Pública - SP
Resumo:
INTRODUCTION: The objective was to identify space and space-time risk clusters for the occurrence of deaths in a priority city for the control of tuberculosis (TB) in the Brazilian Northeast. METHODS: Ecological research was undertaken in the City of São Luis/Maranhão. Cases were considered that resulted in deaths in the population living in the urban region of the city with pulmonary TB as the basic cause, between 2008 and 2012. To detect space and space-time clusters of deaths due to pulmonary TB in the census sectors, the spatial analysis scan technique was used. RESULTS: In total, 221 deaths by TB occurred, 193 of which were due to pulmonary TB. Approximately 95% of the cases (n=183) were geocoded. Two significant spatial clusters were identified, the first of which showed a mortality rate of 5.8 deaths per 100,000 inhabitants per year and a high relative risk of 3.87. The second spatial cluster showed a mortality rate of 0.4 deaths per 100,000 inhabitants per year and a low relative risk of 0.10. A significant cluster was observed in the space-time analysis between 11/01/2008 and 04/30/2011, with a mortality rate of 8.10 deaths per 100,000 inhabitants per year and a high relative risk (3.0). CONCLUSIONS: The knowledge of priority sites for the occurrence of deaths can support public management to reduce inequities in the access to health services and permit an optimization of the resources and teams in the control of pulmonary TB, providing support for specific strategies focused on the most vulnerable populations.
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Abstract: INTRODUCTION This study presents two decades of epidemiological data on tuberculosis (TB), in order to understanding the disease profile and its spatiotemporal dynamics. METHODS This descriptive study was performed in the City of Olinda/Pernambuco, Brazil, from 1991-2010, and it analyzed new patients with TB living in the city. We used the χ²-test with a p-value <0.05 to identify differences in trends. Incidence and cluster distribution were identified using spatial scan statistics. RESULTS In total, 6202 new cases were recorded during the two decades. The highest incidence occurred in 1995 (110 cases/100,000 inhabitants), and the lowest occurred in 2009 (65 cases/100,000 inhabitants) (β=-1.44; R²=0.43; p=0.0018). The highest mortality occurred in 1998 (16 deaths/100,000 inhabitants), and the lowest occurred in 2008 (5 deaths/100,000 inhabitants) (β=-0.19; R²=0.17; p=0.07). There was a male predominance (65%), and ages ranged from 20-49 years (65%). There was a substantial increase in the number of patients that were cured after treatment (60% to 67%; p<0.001) as well as those tested for HIV (1.9% to 58.5%; p<0.001). During the first decade, clusters with p-values <0.05 included 29% of the total notified cases, and in the second decade, that percentage was 12%. CONCLUSIONS We observed a decreasing trend in incidence, which was significant, and mortality rates, which was not significant. The increased number of laboratory tests performed reflects advances in surveillance, and a reduction in the proportion of cases in primary clusters suggests, among other things, that the disease is spreading across the region.
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The authors report the magnetic resonance imaging diagnostic features in two cases with respectively lumbar epidural hematoma and cavernous hemangioma of the lumbar epidural space. Enhanced MRI T1-weighted scans show a hyperintense signal rim surrounding the vascular lesion. Non-enhanced T2-weighted scans showed hyperintense signal.
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This work describes the spatial-temporal variation of the relative abundance and size of Limnoperna fortunei (Dunker, 1857) collected in São Gonçalo Channel through bottom trawl with a 0.5 cm mesh, at depths between 3 and 6 m. The estimative of mean relative abundance (CPUE) ranged from 2,425.3 individuals per drag (ind./drag) in the spring to 21,715.0 ind./drag in the fall, with an average of 9,515.3 ind./drag throughout the year. The estimated mean density of L. fortunei for the deep region of São Gonçalo Channel ranged from 1.2 to 10.3 ind./m², and it was recorded a maximum density of 84.9 ind./m² in the fall of 2008. The method of sampling using bottom trawl enabled the capture of L. fortunei under the soft muddy bottom of the channel, in different sizes ranging from 0.4 to 3.2 cm. This shows that the structure of the L. fortunei adult population under the bottom of the São Gonçalo Channel is composed mostly of small individuals (<1.4 cm), which represent up to 74% of the population collected.
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We live in a "Demon-Haunted World". Human health care requires the ever increasing resistance of pathogens to be confronted by a correspondingly fast rate of discovery of novel antibiotics. One of the possible strategies towards this objective involves the rational localization of bioactive phytochemicals. The conceptual basis of the method consists in the surprisingly little known gearings of natural products with morphology, ecology and evolution of their plant source, i. e. an introspection into the general mechanisms of nature.
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In visceral leishmaniasis, phlebotomine vectors are targets for control measures. Understanding the ecosystem of the vectors is a prerequisite for creating these control measures. This study endeavours to delineate the suitable locations of Phlebotomus argentipes with relation to environmental characteristics between endemic and non-endemic districts in India. A cross-sectional survey was conducted on 25 villages in each district. Environmental data were obtained through remote sensing images and vector density was measured using a CDC light trap. Simple linear regression analysis was used to measure the association between climatic parameters and vector density. Using factor analysis, the relationship between land cover classes and P. argentipes density among the villages in both districts was investigated. The results of the regression analysis indicated that indoor temperature and relative humidity are the best predictors for P. argentipes distribution. Factor analysis confirmed breeding preferences for P. argentipes by landscape element. Minimum Normalised Difference Vegetation Index, marshy land and orchard/settlement produced high loading in an endemic region, whereas water bodies and dense forest were preferred in non-endemic sites. Soil properties between the two districts were studied and indicated that soil pH and moisture content is higher in endemic sites compared to non-endemic sites. The present study should be utilised to make critical decisions for vector surveillance and controlling Kala-azar disease vectors.
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Geographical Information Systems (GIS) facilitate access to epidemiological data through visualization and may be consulted for the development of mathematical models and analysis by spatial statistics. Variables such as land-cover, land-use, elevations, surface temperatures, rainfall etc. emanating from earth-observing satellites, complement GIS as this information allows the analysis of disease distribution based on environmental characteristics. The strength of this approach issues from the specific environmental requirements of those causative infectious agents, which depend on intermediate hosts for their transmission. The distribution of these diseases is restricted, both by the environmental requirements of their intermediate hosts/vectors and by the ambient temperature inside these hosts, which effectively govern the speed of maturation of the parasite. This paper discusses the current capabilities with regard to satellite data collection in terms of resolution (spatial, temporal and spectral) of the sensor instruments on board drawing attention to the utility of computer-based models of the Earth for epidemiological research. Virtual globes, available from Google and other commercial firms, are superior to conventional maps as they do not only show geographical and man-made features, but also allow instant import of data-sets of specific interest, e.g. environmental parameters, demographic information etc., from the Internet.
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Objective To aprehend the social representations about the solvability in mental health care with users of the Family Health Strategy and professionals of family health teams and of the Center for Psychosocial Care. Method A qualitative study using semi-structured interviews for data collection, and the Alceste software for analysis. This software uses the Hierarchical Descending Classification based on the examination of lexical roots, considering the words as units and providing context in the corpus. Results The representations emerge in two opposing poles: the users require satisfaction with care and the professionals realize the need for improvement of health actions. Although the matricial support in mental health and the home visits are developed, the barriers related to investment in health, continuing education and organization of care persist. Conclusion The different representations enable improvements in customer service, solvability of care and aggregate knowledge and practices in the expanded perspective of health needs in the family, social and therapeutic context.
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OBJECTIVE To analyze the social representations of the Nursing Technicians and Community Health Agents about domestic violence against women. METHOD A qualitative study carried out in the city of Rio Grande, RS, in which evocations and interviews were collected between July and November 2013. For the treatment of data were used the EVOC 2005 software and the context analysis. RESULT It is a structured representation, in which the central nucleus contains conceptual, imaging and attitudinal elements, namely: abuse, aggression, physical aggression, cowardice and lack of respect. Such terms were present in the context of the interviews. The professionals acknowledged that violence is not limited to physical aspects and were judgemental about the acts of the aggressor. CONCLUSION This knowledge may enable the problematization of the studied phenomenon with the team, and facilitate the search for prevention and intervention strategies for victims, offenders and managers of health services.
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Abstract OBJECTIVE To understand the content of Social Representation (SR) of family caregivers of Alzheimer's disease patients. METHOD Interviews were conducted with 26 caregivers and analyzed by the ALCESTE software. RESULTS The SR content was structured in two thematic axes called Daily Life and Care and Medical and Emotional Concepts and Outcomes. The first axis creates images related to the routine of interaction with the sick person, and contains a description of care procedures, experiences, and practices applied every day. The second is composed of subjective and conceptual aspects that make up the social representation of Alzheimer's disease, with meanings related to the emotional, medical, and biological contexts. CONCLUSION Due to the importance of topics related to patients' dependence and the personal and emotional consequences of the disease, overload is the main content of the SR of Alzheimer's disease for caregivers, and the understanding of these SR by health professionals should support the planning of interventions addressing this group of individuals.
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The state-space approach is used to evaluate the relation between soil physical and chemical properties in an area cultivated with sugarcane. The experiment was carried out on a Rhodic Kandiudalf in Piracicaba, State of São Paulo, Brazil. Sugarcane was planted on an area of 0.21 ha i.e., in 15 rows 100 m long, spaced 1.4 m. Soil water content, soil organic matter, clay content and aggregate stability were sampled along a transect of 84 points, meter by meter. The state-space approach is used to evaluate how the soil water content is affected by itself and by soil organic matter, clay content, and aggregate stability of neighboring locations, in different combinations, aiming to contribute to a better understanding of the relation among these variables in the soil. Results show that soil water contents were successfully estimated by this approach. Best performances were found when the estimate of soil water content at locations i was related to soil water content, clay content and aggregate stability at locations i-1. Results also indicate that this state-space model using all series describes the soil water content better than any equivalent multiple regression equation.
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Statistical models allow the representation of data sets and the estimation and/or prediction of the behavior of a given variable through its interaction with the other variables involved in a phenomenon. Among other different statistical models, are the autoregressive state-space models (ARSS) and the linear regression models (LR), which allow the quantification of the relationships among soil-plant-atmosphere system variables. To compare the quality of the ARSS and LR models for the modeling of the relationships between soybean yield and soil physical properties, Akaike's Information Criterion, which provides a coefficient for the selection of the best model, was used in this study. The data sets were sampled in a Rhodic Acrudox soil, along a spatial transect with 84 points spaced 3 m apart. At each sampling point, soybean samples were collected for yield quantification. At the same site, soil penetration resistance was also measured and soil samples were collected to measure soil bulk density in the 0-0.10 m and 0.10-0.20 m layers. Results showed autocorrelation and a cross correlation structure of soybean yield and soil penetration resistance data. Soil bulk density data, however, were only autocorrelated in the 0-0.10 m layer and not cross correlated with soybean yield. The results showed the higher efficiency of the autoregressive space-state models in relation to the equivalent simple and multiple linear regression models using Akaike's Information Criterion. The resulting values were comparatively lower than the values obtained by the regression models, for all combinations of explanatory variables.
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The graphical representation of spatial soil properties in a digital environment is complex because it requires a conversion of data collected in a discrete form onto a continuous surface. The objective of this study was to apply three-dimension techniques of interpolation and visualization on soil texture and fertility properties and establish relationships with pedogenetic factors and processes in a slope area. The GRASS Geographic Information System was used to generate three-dimensional models and ParaView software to visualize soil volumes. Samples of the A, AB, BA, and B horizons were collected in a regular 122-point grid in an area of 13 ha, in Pinhais, PR, in southern Brazil. Geoprocessing and graphic computing techniques were effective in identifying and delimiting soil volumes of distinct ranges of fertility properties confined within the soil matrix. Both three-dimensional interpolation and the visualization tool facilitated interpretation in a continuous space (volumes) of the cause-effect relationships between soil texture and fertility properties and pedological factors and processes, such as higher clay contents following the drainage lines of the area. The flattest part with more weathered soils (Oxisols) had the highest pH values and lower Al3+ concentrations. These techniques of data interpolation and visualization have great potential for use in diverse areas of soil science, such as identification of soil volumes occurring side-by-side but that exhibit different physical, chemical, and mineralogical conditions for plant root growth, and monitoring of plumes of organic and inorganic pollutants in soils and sediments, among other applications. The methodological details for interpolation and a three-dimensional view of soil data are presented here.
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Tissue analysis is a useful tool for the nutrient management of fruit orchards. The mineral composition of diagnostic tissues expressed as nutrient concentration on a dry weight basis has long been used to assess the status of 'pure' nutrients. When nutrients are mixed and interact in plant tissues, their proportions or concentrations change relatively to each other as a result of synergism, antagonism, or neutrality, hence producing resonance within the closed space of tissue composition. Ternary diagrams and nutrient ratios are early representations of interacting nutrients in the compositional space. Dual and multiple interactions were integrated by the Diagnosis and Recommendation Integrated System (DRIS) into nutrient indexes and by Compositional Nutrient Diagnosis into centered log ratios (CND-clr). DRIS has some computational flaws such as using a dry matter index that is not a part as well as nutrient products (e.g. NxCa) instead of ratios. DRIS and CND-clr integrate all possible nutrient interactions without defining an ad hoc interactive model. They diagnose D components while D-1 could be diagnosed in the D-compositional Hilbert space. The isometric log ratio (ilr) coordinates overcome these problems using orthonormal binary nutrient partitions instead of dual ratios. In this study, it is presented a nutrient interactive model as well as computation methods for DRIS and CND-clr and CND-ilr coordinates (CND-ilr) using leaf analytical data from an experimental apple orchard in Southwestern Quebec, Canada. It was computed the Aitchison and Mahalanobis distances across ilr coordinates as measures of nutrient imbalance. The effect of changing nutrient concentrations on ilr coordinates are simulated to identify the ones contributing the most to nutrient imbalance.