Schistosomiasis risk mapping in the state of Minas Gerais, Brazil, using a decision tree approach, remote sensing data and sociological indicators

Schistosomiasis mansoni is not just a physical disease, but is related to social and behavioural factors as well. Snails of the Biomphalaria genus are an intermediate host for Schistosoma mansoni and infect humans through water. The objective of this study is to classify the risk of schistosomiasis in the state of Minas Gerais (MG). We focus on socioeconomic and demographic features, basic sanitation features, the presence of accumulated water bodies, dense vegetation in the summer and winter seasons and related terrain characteristics. We draw on the decision tree approach to infection risk modelling and mapping. The model robustness was properly verified. The main variables that were selected by the procedure included the terrain's water accumulation capacity, temperature extremes and the Human Development Index. In addition, the model was used to generate two maps, one that included risk classification for the entire of MG and another that included classification errors. The resulting map was 62.9% accurate.

Cost of schizophrenia: direct costs and use of resources in the State of São Paulo

OBJECTIVE: To estimate the direct costs of schizophrenia for the public sector. METHODS: A study was carried out in the state of São Paulo, Brazil, during 1998. Data from the medical literature and governmental research bodies were gathered for estimating the total number of schizophrenia patients covered by the Brazilian Unified Health System. A decision tree was built based on an estimated distribution of patients under different types of psychiatric care. Medical charts from public hospitals and outpatient services were used to estimate the resources used over a one-year period. Direct costs were calculated by attributing monetary values for each resource used. RESULTS: Of all patients, 81.5% were covered by the public sector and distributed as follows: 6.0% in psychiatric hospital admissions, 23.0% in outpatient care, and 71.0% without regular treatment. The total direct cost of schizophrenia was US$191,781,327 (2.2% of the total health care expenditure in the state). Of this total, 11.0% was spent on outpatient care and 79.2% went for inpatient care. CONCLUSIONS: Most schizophrenia patients in the state of São Paulo receive no regular treatment. The study findings point out to the importance of investing in research aimed at improving the resource allocation for the treatment of mental disorders in Brazil.

Economic analysis of surgical treatment of hip fracture in older adults

OBJECTIVE To analyze the incremental cost-utility ratio for the surgical treatment of hip fracture in older patients.METHODS This was a retrospective cohort study of a systematic sample of patients who underwent surgery for hip fracture at a central hospital of a macro-region in the state of Minas Gerais, Southeastern Brazil between January 1, 2009 and December 31, 2011. A decision tree creation was analyzed considering the direct medical costs. The study followed the healthcare provider’s perspective and had a one-year time horizon. Effectiveness was measured by the time elapsed between trauma and surgery after dividing the patients into early and late surgery groups. The utility was obtained in a cross-sectional and indirect manner using the EuroQOL 5 Dimensions generic questionnaire transformed into cardinal numbers using the national regulations established by the Center for the Development and Regional Planning of the State of Minas Gerais. The sample included 110 patients, 27 of whom were allocated in the early surgery group and 83 in the late surgery group. The groups were stratified by age, gender, type of fracture, type of surgery, and anesthetic risk.RESULTS The direct medical cost presented a statistically significant increase among patients in the late surgery group (p < 0.005), mainly because of ward costs (p < 0.001). In-hospital mortality was higher in the late surgery group (7.4% versus 16.9%). The decision tree demonstrated the dominance of the early surgery strategy over the late surgery strategy: R$9,854.34 (USD4,387.17) versus R$26,754.56 (USD11,911.03) per quality-adjusted life year. The sensitivity test with extreme values proved the robustness of the results.CONCLUSIONS After controlling for confounding variables, the strategy of early surgery for hip fracture in the older adults was proven to be dominant, because it presented a lower cost and better results than late surgery.

Computer-assisted cartography using topographic properties: precision and accuracy of local soil maps in central Mexico

Map units directly related to properties of soil-landscape are generated by local soil classes. Therefore to take into consideration the knowledge of farmers is essential to automate the procedure. The aim of this study was to map local soil classes by computer-assisted cartography (CAC), using several combinations of topographic properties produced by GIS (digital elevation model, aspect, slope, and profile curvature). A decision tree was used to find the number of topographic properties required for digital cartography of the local soil classes. The maps produced were evaluated based on the attributes of map quality defined as precision and accuracy of the CAC-based maps. The evaluation was carried out in Central Mexico using three maps of local soil classes with contrasting landscape and climatic conditions (desert, temperate, and tropical). In the three areas the precision (56 %) of the CAC maps based on elevation as topographical feature was higher than when based on slope, aspect and profile curvature. The accuracy of the maps (boundary locations) was however low (33 %), in other words, further research is required to improve this indicator.

Digital soil mapping: strategy for data pre-processing

The region of greatest variability on soil maps is along the edge of their polygons, causing disagreement among pedologists about the appropriate description of soil classes at these locations. The objective of this work was to propose a strategy for data pre-processing applied to digital soil mapping (DSM). Soil polygons on a training map were shrunk by 100 and 160 m. This strategy prevented the use of covariates located near the edge of the soil classes for the Decision Tree (DT) models. Three DT models derived from eight predictive covariates, related to relief and organism factors sampled on the original polygons of a soil map and on polygons shrunk by 100 and 160 m were used to predict soil classes. The DT model derived from observations 160 m away from the edge of the polygons on the original map is less complex and has a better predictive performance.

An appropriate data set size for digital soil mapping in Erechim, Rio Grande do Sul, Brazil

Digital information generates the possibility of a high degree of redundancy in the data available for fitting predictive models used for Digital Soil Mapping (DSM). Among these models, the Decision Tree (DT) technique has been increasingly applied due to its capacity of dealing with large datasets. The purpose of this study was to evaluate the impact of the data volume used to generate the DT models on the quality of soil maps. An area of 889.33 km² was chosen in the Northern region of the State of Rio Grande do Sul. The soil-landscape relationship was obtained from reambulation of the studied area and the alignment of the units in the 1:50,000 scale topographic mapping. Six predictive covariates linked to the factors soil formation, relief and organisms, together with data sets of 1, 3, 5, 10, 15, 20 and 25 % of the total data volume, were used to generate the predictive DT models in the data mining program Waikato Environment for Knowledge Analysis (WEKA). In this study, sample densities below 5 % resulted in models with lower power of capturing the complexity of the spatial distribution of the soil in the study area. The relation between the data volume to be handled and the predictive capacity of the models was best for samples between 5 and 15 %. For the models based on these sample densities, the collected field data indicated an accuracy of predictive mapping close to 70 %.

Prediction of soil orders with high spatial resolution: response of different classifiers to sampling density

The objective of this work was to evaluate sampling density on the prediction accuracy of soil orders, with high spatial resolution, in a viticultural zone of Serra Gaúcha, Southern Brazil. A digital elevation model (DEM), a cartographic base, a conventional soil map, and the Idrisi software were used. Seven predictor variables were calculated and read along with soil classes in randomly distributed points, with sampling densities of 0.5, 1, 1.5, 2, and 4 points per hectare. Data were used to train a decision tree (Gini) and three artificial neural networks: adaptive resonance theory, fuzzy ARTMap; self‑organizing map, SOM; and multi‑layer perceptron, MLP. Estimated maps were compared with the conventional soil map to calculate omission and commission errors, overall accuracy, and quantity and allocation disagreement. The decision tree was less sensitive to sampling density and had the highest accuracy and consistence. The SOM was the less sensitive and most consistent network. The MLP had a critical minimum and showed high inconsistency, whereas fuzzy ARTMap was more sensitive and less accurate. Results indicate that sampling densities used in conventional soil surveys can serve as a reference to predict soil orders in Serra Gaúcha.

Using data mining to identify factors that influence the degree of leg injuries in broilers

Locomotor problems prevent the bird to move freely, jeopardizing the welfare and productivity, besides generating injuries on the legs of chickens. The objective of this study was to evaluate the influence of age, use of vitamin D, the asymmetry of limbs and gait score, the degree of leg injuries in broilers, using data mining. The analysis was performed on a data set obtained from a field experiment in which it was used two groups of birds with 30 birds each, a control group and one treated with vitamin D. It was evaluated the gait score, the asymmetry between the right and left toes, and the degree of leg injuries. The Weka ® software was used in data mining. In particular, C4.5 algorithm (also known as J48 in Weka environment) was used for the generation of a decision tree. The results showed that age is the factor that most influences the degree of leg injuries and that the data from assessments of gait score were not reliable to estimate leg weakness in broilers.

Vocalization data mining for estimating swine stress conditions

This study aimed to identify differences in swine vocalization pattern according to animal gender and different stress conditions. A total of 150 barrow males and 150 females (Dalland® genetic strain), aged 100 days, were used in the experiment. Pigs were exposed to different stressful situations: thirst (no access to water), hunger (no access to food), and thermal stress (THI exceeding 74). For the control treatment, animals were kept under a comfort situation (animals with full access to food and water, with environmental THI lower than 70). Acoustic signals were recorded every 30 minutes, totaling six samples for each stress situation. Afterwards, the audios were analyzed by Praat® 5.1.19 software, generating a sound spectrum. For determination of stress conditions, data were processed by WEKA® 3.5 software, using the decision tree algorithm C4.5, known as J48 in the software environment, considering cross-validation with samples of 10% (10-fold cross-validation). According to the Decision Tree, the acoustic most important attribute for the classification of stress conditions was sound Intensity (root node). It was not possible to identify, using the tested attributes, the animal gender by vocal register. A decision tree was generated for recognition of situations of swine hunger, thirst, and heat stress from records of sound intensity, Pitch frequency, and Formant 1.

Predicting the distribution of forest tree species using topographic variables and vegetation index in eastern Acre, Brazil

Species distribution modeling has relevant implications for the studies of biodiversity, decision making about conservation and knowledge about ecological requirements of the species. The aim of this study was to evaluate if the use of forest inventories can improve the estimation of occurrence probability, identify the limits of the potential distribution and habitat preference of a group of timber tree species. The environmental predictor variables were: elevation, slope, aspect, normalized difference vegetation index (NDVI) and height above the nearest drainage (HAND). To estimate the distribution of species we used the maximum entropy method (Maxent). In comparison with a random distribution, using topographic variables and vegetation index as features, the Maxent method predicted with an average accuracy of 86% the geographical distribution of studied species. The altitude and NDVI were the most important variables. There were limitations to the interpolation of the models for non-sampled locations and that are outside of the elevation gradient associated with the occurrence data in approximately 7% of the basin area. Ceiba pentandra (samaúma), Castilla ulei (caucho) and Hura crepitans (assacu) is more likely to occur in nearby water course areas. Clarisia racemosa (guariúba), Amburana acreana (cerejeira), Aspidosperma macrocarpon (pereiro), Apuleia leiocarpa (cumaru cetim), Aspidosperma parvifolium (amarelão) and Astronium lecointei (aroeira) can also occur in upland forest and well drained soils. This modeling approach has potential for application on other tropical species still less studied, especially those that are under pressure from logging.

A validated method using RP-HPLC for quantification of reserpine in the Brazilian tree Rauvolfia sellowii Müll. Arg. (Apocynaceae)

This study describes a simple, fast and reproducible method using RP-HPLC-UV, in a gradient system, for quantification of reserpine in Rauvolfia sellowii stem bark. The analysis were carried out on a C18 column; mobile phase was water and acetonitrile, and separations were carried out in 10 min, flow rate of 1.0 mL min-1, 25 ºC and 268 nm. The validation data showed that the method was specific, accurate, precise and robust. Results were linear over a range of 0.625-40.0 μg mL-1, and the mean recovery was 95.1%. The amount of reserpine found in the dried stem bark was 0.01% (m/m).

Antibacterial and antifungal activity of extracts and exudates of the Amazonian medicinal tree Himatanthus articulatus (Vahl) Woodson (common name: sucuba)

Himatanthus articulatus (Vahl) Woodson is a tree found in the northern Amazon savannahs (common name: sucuba) that is used in local Amerindian medicine. Leaf, bark and branch wood methanol extracts, sequentially obtained hexane, ethyl acetate and methanol extracts and latex were evaluated for antifungal and antibacterial activities against American Type Culture Collection (ATCC) and local clinical strains using the disc diffusion method. Methanol extracts and latex inhibited Candida albicans, leaf methanol extracts inhibited Staphylococcus aureus and Bacillus subtilis and bark methanol extracts inhibited B. subtilis. Active extracts inhibited the ATCC and clinical strains. Polar antifungal and antibacterial principles in latex and extracts are thought to be responsible for the inhibition.

The decision of an obese woman to have bariatric surgery: the social phenomenology

Objective To understand the process by which an obese woman decides to have bariatric surgery. Method A qualitative survey with a social phenomenology approach, carried out in 2012, with 12 women, using the phenomenological interview. Results A woman bases the decision to have the surgery on: the inappropriateness of her eating habits; a physical appearance that is incompatible with an appearance that is standardized by society; the social prejudice that she has to live with; the limitations imposed by obesity; and her lack of success with previous attempts to lose weight. Outcomes that she hopes for from the decision to have the surgery include: restoring her health; achieving social inclusion; and entering the labor market. Conclusion This study allows one to reflect that prescriptive actions do not give a satisfactory response to a complexity of the subjective questions involved in the decision to have surgery for obesity. For this, what is called for is a program of work based on an interdisciplinary approach, and training that gives value to the bio-psycho-social aspects involved in a decision in favor of surgical treatment.

Informatics competencies essential to decision making in nursing management

Abstract OBJECTIVE To identify informatics abilities essential to decision making in nursing management. METHOD Survey study with specialist nurses in health informatics and management. An electronic questionnaire was built based on the competencies Information Literacy (five categories; 40 abilities) and Information Management (nine categories; 69 abilities) of the TIGER - Technology Informatics Guiding Education Reform - initiative, with the guiding question: Which informatics abilities are essential to decision making in management? Answers were sorted in a Likert scale, ranging from 1 to 5. Rasch analysis was conducted with the software WINSTEPS ®. Results were presented in logits, with cutoff value zero. RESULTS Thirty-two specialists participated, coming from all regions of Brazil. In the information literacy competency, 18 abilities were considered essential and in Information Management, 38; these were sorted according to their degree of essentiality. CONCLUSION It is believed that the incorporation of these abilities in teaching can support the education of nurse managers and contribute to evidence-based practice, incorporation of information and communication technologies in health and information management.

Variations on the nutritional status of eucalypt as influenced by the genetic material and age of tree

The Diagnosis and Recommendation System (DRIS) was applied to eucalypt trees (hybrids of Eucalyptus grandis x E. urophylla) with different ages and growing under different environmental conditions for three different clones. The basic data were obtained from 1,986 trees of commercial stands cultivated in the states of Espírito Santo and south Bahia, Brazil. The DRIS indices were calculated using the Beaufils' Range formula and grouped according to the Nutrient Application Potential Response method. The objective of this paper was to evaluate the N, P and Ca status in eucalypt trees, regarding the tree ages and genetic materials. The DRIS indices discriminated differences in the nutritional status of the trees, both in relation to age and the genetic materials (clones). The results indicated that the deficiency of N and Ca tended to decrease with tree age, whereas the P deficiency tended to increase. Furthermore, of the three evaluated clones, those numbered 00014 and 00034 showed opposite trends regarding to N, P, and Ca nutrition, and the clone numbered 00021, in general, presented the highest degree of unbalanced nutrition of N, P and Ca.