Diogo Francisco Rossoni

Scaling of pores in 3D images of Latosols (Oxisols) with contrasting mineralogy under a conservation management system

The aim of this study was to evaluate the spatial and morphological configuration of the pore space in 3D images of Latosols with different mineralogy under a conservation tillage system in a coffee crop area. The visualisation and quantification of pore size distribution by data mining and spatial variability by semi-variogams were investigated in 3D images with 60-µm spatial resolution generated by X-ray CT scan (EVS/GE MS8x-130) in soil core samples collected at different depths of a kaolinitic Red-Yellow Latosol (RYL) and a gibbsitic Red Latosol (RL) from Brazil. Greater spatial variability occurred in the horizontal direction of the 3D image, a novel finding in this area of research. The pores detected were different between the Latosols studied, mainly at 0.20–0.34 m depth. The largest number (>4000) and volume (±30 mm3) of pores was found in the RL. The soil classes differed in 3D pore characteristics, and this aspect may be important in the characterisation of causes of pore variability. Sphericity was similar for both soils, with greater emphasis on pore classes with a diameter 15%).

Distribuição espacial das raízes de cafeeiro e dos poros de dois Latossolos sob manejo conservacionista

The aim of this study was to evaluate the effect of management system employing soil conservation practices in the coffee root system distribution and in the structure of two Latosols after six years in the crop establishment in Alto Sao Francisco Valley, MG. Three random trenches were made lengthwise along the row planting (0.70 x 1.50 m) in a gibbsitic Latosol and a kaolinitc Latosol both under soil management system employing soil conservationist practices. The root system evaluation was done by crop profile methods and 2D image analyze, with subsequent surface mapping of the root variables analyzed by kriging. Intact soil cores were sampled for pore diameter distribution analysed by X-ray CT scan. The roots and pores were classified by diameter:1, > 1 and ≤ 3 and > 3 mm. The coffee root system in both soils under study on the same management system showed good branching in horizontal and vertical direction. The highest root concentration occurred at 0.20-0.34 m depth in kaolinitic Latosol. In gibbsitic Latosol the root distribution was uniform, especially in the vertical soil profile reaching greater depths. The highest occurrence of fine roots in the gibbsitic Latosol occurred at 0.80-0.94 m depth.

Epidemiological and clinical profile of patients with Chagas disease in the Central-North area of Paraná, Southern Brazil

INTRODUCTION Profiles of patients with Chagas disease in Paraná were studied. METHODS A descriptive, questionnaire-based study was performed. RESULTS Of 270 participants, 64% were female, 60% were aged ≥65 years, 91% were infected via vector transmission, and 44% were infected in Paraná. Indeterminate (30%), cardiac (36%), cardiodigestive (20%) and digestive (14%) forms were found. CONCLUSIONS Patients who were older than 65 years of age, retired, female, living in the urban area of Maringá, and infected by vector transmission in childhood in Paraná presented cardiac and digestive signs and did not receive etiological treatment when first diagnosed.

Effect of vegetation on cutaneous leishmaniasis in Paraná, Brazil

BACKGROUND Cutaneous leishmaniasis (CL) is endemic in the state of Paraná, Brazil. OBJECTIVE This study aimed at analysing the influence of the remaining native vegetation on the prevalence of CL in Paraná. METHODS Global testing was used for spatial autocorrelation along with simultaneous autoregressive model (SAR). The regression was based on the CL coefficient (cases/100,000 inhabitants) as a function of the percentage of natural vegetation cover, altitude, total number of cases, and spatial density (SD) per km2; the location data of the Paraná state municipalities and the detection coefficient (DC) (cases/100,000 inhabitants) of autochthonous cases of CL were obtained from the SINAN in 2012 and 2016. Data on the remaining forests were collected from the Fundação SOS Mata Atlântica and Instituto Nacional de Pesquisas Espaciais. FINDINGS The spatial regression of DC revealed statistical significance for SD (Z = 24.1359, p < 0.05, 2012-2013; Z = 24.0817, p < 0.05, 2013-2014; Z = 33.4824, p < 0.05, 2014-2015; and Z = 27.1515, p < 0.05, 2015-2016. CONCLUSIONS CL cases are reported in areas with native vegetation, such as in riparian forests. However, vegetation is not the only variable that influences the incidence of CL.

Spatial distribution of cutaneous leishmaniasis in the state of Paraná, Brazil

The geographic distribution of cutaneous leishmaniasis (CL) makes it a disease of major clinical importance in Brazil, where it is endemic in the state of Paraná. The objective of this study was to analyze the spatial distribution of CL in Paraná between 2001 and 2015, based on data from the Sistema de Informação de Agravos de Notificação (Information System for Notifiable Diseases) regarding autochthonous CL cases. Spatial autocorrelation was performed using Moran’s Global Index and the Local Indicator of Spatial Association (LISA). The construction of maps was based on categories of association (high-high, low-low, high-low, and low-high). A total of 4,557 autochthonous cases of CL were registered in the state of Paraná, with an annual average of 303.8 (± 135.2) and a detection coefficient of 2.91. No correlation was found between global indices and their respective significance in 2001 (I = -0.456, p = 0.676), but evidence of spatial autocorrelation was found in other years (p< 0.05). In the construction and analysis of the cluster maps, areas with a high-high positive association were found in the Ivaí-Pirapó, Tibagi, Cinzas-Laranjinha, and Ribeira areas. The state of Paraná should keep a constant surveillance over CL due to the prominent presence of socioeconomic and environmental factors such as the favorable circumstances for the vectors present in peri-urban and agriculture áreas.

Spatial distribution of intestinal parasitic infections in a Kaingáng indigenous village from Southern Brazil

Abstract The spatial distribution of enteroparasitosis in an indigenous village from Paraná was evaluated to identify areas of risk for these infections. A cross-sectional study (from November 2010 to June 2011) was performed using Three Faecal Test® and Kato & Katz method and a questionnaire on housing and hygiene conditions was administered. Local geostatistical analyses were performed to determine the spatial distribution of intestinal parasitic infections. The overall prevalence of enteroparasites was 67.2 % (457/680), and the most prevalent taxa were Ascaris lumbricoides (48.8 %) and Trichuris trichiura (44.7 %). The prevalence of heavy infection by soil-transmitted helminths was 3.6 % and the families lived in houses with an average of 5.1 residents and < 2 bedrooms per household. The average number of species per individual present spatial heterogeneity with the highest values (≥0.8) in areas with high clustering of residences. The visualization of the spatial distribution of intestinal parasites in this indigenous village is an important contribution to determining health risk areas and planning decisions and services.

ESTIMADORES DE SEMIVARIÂNCIA: UMA REVISÃO

A Geoestatistica e um ramo da estatistica responsavel pela incorporacao e entendimento das dependencias espaciais na modelagem de variaveis georreferenciadas. Na busca pelo melhor modelo ajustado, tem-se o desafio de desenvolver e dominar um ferramental que permita a analise, e quantificacao, da variabilidade espacial do fenomeno em estudo por meio de modelagens especificas, para isso, e comum fazer uso de medidas de correlacao espacial como covariância, correlacao e, especialmente, semivariância, uma medida resumo da variabilidade e dependencia espacial. E entao essencial um bom ajuste do semivariograma, e um estimador adequado para a semivariância e necessario para este ajuste. Uma vez que a maioria dos metodos de estimacao em Geoestatistica e algoritmos de simulacao requerem um modelo teorico ajustado a uma semivariância empirica, objetivou-se expor as construcoes, deducoes e a ideia geral que determina a adequabilidade dos principais estimadores de semivariância a fim de prover a melhor decisao a ser tomada. Portanto, este texto apresenta uma revisao de oito estimadores de semivariância: Classico de Matheron, Robusto de Cressie e Hawkins, das Medianas de Cressie, das Diferencas de Haslett, Altamente Robusto de Genton, Pairwise, New-1 (MW1) e New-2 (MW2).