959 resultados para spatial distribution


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This paper describes population structure, spatial distribution and habitat selection of wild and peridomestic populations of Triatoma rubrovaria (Blanchard, 1843). Field studies were carried out at Las Piedras and La Bolsa in the Northern Department of Artigas, Uruguay. A semicircular sampling area, divided in seven or eight triangular sectors was sequentially examined from October 1990 to November 1991. At Las Piedras (typical wild habitat) 1063 T. rubrovaria bugs were collected from 84 of the rocky outcroops ("pedregales"). Abundance varied by season peaking in October-November (spring). Throughout the year, most of the population was made up of third, fourth and fifth instar nymphs; adults were found from October to March. In the peridomestic environment of La Bolsa, however T. rubrovaria was less common and showed a more irregular instar distribution. Colonized ecotopes, were those close to houses. In both sites T. rubrovaria was mainly associated with the geckonid Homonota uruguayensis and the cockroach Blaptica dubia.

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Assembling behaviour associated with mating was investigated in Triatoma infestans. The spatial distribution of both sexes was observed by video films, in the presence or absence of a copulating pair. Males aggregated around copulating pairs. Females did not exhibit this behaviour and their mean spatial density remained unaffected. Spontaneous aggregation tendency was observed in males in the absence of a copulating pair, but the temporal course significantly differed from that observed in the presence of a mating pair. Results support the existence of an aggregation signal that is released during mating, affecting the behaviour of males.

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This paper examines the results of spatial (microgeographical) water contact/schistosomiasis studies in two African (Egyptian and Kenyan) and one Brazilian communities. All three studies used traditional cartographic and statistical methods but one of them emploeyd also GIS (geographical information systems) tools. The advantage of GIS and their potential role in schistosomiasis control are briefly described. The three cases revealed considerable variation in the spatial distribution of water contact, transmission parameters and infection levels at the household and individual levels. All studies showed considerable variation in the prevalence and intensity of infection between households. They also show a variable influence of distance on water contact behavior associated with type of activity, age, sex, socioeconomic level, perception of water quality, season and availability of water in the home. Water contact behavior and schistosomiasis were evaluated in the Brazilian village of Nova União within the context of water sharing between household and age/sex groups. Recommendations are made for further spatial studies on the transmission and control of schistosomiasis.

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We tested experimentally the effects of the presence of non-susceptible hosts on the infection with Trypanosoma cruzi of the vector Triatoma infestans. The experiment consisted in two treatments: with chickens, including two chickens (non-susceptible hosts) and two infected guinea pigs (susceptible hosts), and without chickens, including only two infected guinea pigs. The hosts were held unrestrained in individual metal cages inside a closed tulle chamber. A total of 200 uninfected T. infestans third instar nymphs were liberated in each replica, collected on day 14, and examined for infection and blood meal sources on day 32-36. The additional presence of chickens relative to infected guinea pigs: (a) significantly modified the spatial distribution of bugs; (b) increased significantly the likelihoods of having a detectable blood meal on any host and molting to the next instar; (c) did not affect the bugs' probability of death by predation; and (d) decreased significantly the overall percentage of T. infestans infected with T. cruzi. The bugs collected from inside or close to the guinea pigs' cages showed a higher infection rate (71-88%) than those collected from the chickens' cages (22-32%). Mixed blood meals on chickens and guinea pigs were detected in 12-21% of bugs. Although the presence of chickens would decrease the overall percentage of infected bugs in short term experiments, the high rate of host change of T. infestans would make this difference fade out if longer exposure times had been provided.

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Models predicting species spatial distribution are increasingly applied to wildlife management issues, emphasising the need for reliable methods to evaluate the accuracy of their predictions. As many available datasets (e.g. museums, herbariums, atlas) do not provide reliable information about species absences, several presence-only based analyses have been developed. However, methods to evaluate the accuracy of their predictions are few and have never been validated. The aim of this paper is to compare existing and new presenceonly evaluators to usual presence/absence measures. We use a reliable, diverse, presence/absence dataset of 114 plant species to test how common presence/absence indices (Kappa, MaxKappa, AUC, adjusted D-2) compare to presenceonly measures (AVI, CVI, Boyce index) for evaluating generalised linear models (GLM). Moreover we propose a new, threshold-independent evaluator, which we call "continuous Boyce index". All indices were implemented in the B10MAPPER software. We show that the presence-only evaluators are fairly correlated (p > 0.7) to the presence/absence ones. The Boyce indices are closer to AUC than to MaxKappa and are fairly insensitive to species prevalence. In addition, the Boyce indices provide predicted-toexpected ratio curves that offer further insights into the model quality: robustness, habitat suitability resolution and deviation from randomness. This information helps reclassifying predicted maps into meaningful habitat suitability classes. The continuous Boyce index is thus both a complement to usual evaluation of presence/absence models and a reliable measure of presence-only based predictions.

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Sustained atrial fibrillation (AF) is maintained by sites displaying high dominant frequency (DF). In patients (pts) with long-standing persistent AF (LS-pAF), their spatial distribution and the presence of a left-to-right atrial DF gradient remain poorly known. We hypothesized that the pre-ablation bi-atrial frequency characteristics of LS-pAF pts terminated within the left atrium (LT) are different from that of non terminated (NT) ones. Methods: 23 consecutive pts (59±7y, LS-pAF duration 19±12m) underwent stepwise catheter ablation (step-CA) consisting in pulmonary veins isolation, left atrial (LA) defragmentation, and right atrial (RA) ablations for non terminated AF. A quadripolar catheter (CAT) was placed into the RA appendage (RAA), a decapolar CAT into the coronary sinus (CS) and a duodecapolar CAT into the LA divided into 8 segments. For each segment, 20-sec of bipolar recording was acquired. The DF was defined as the largest peak in the power spectrum (3-15 Hz). The inter-atrial DF gradient was defined as the DF difference between LA and RA appendages. Results: LS-pAF was terminated in 83% (19/23) of the pts: 17 LT, 2 during RA ablation and 4 NT. The figure shows that before ablation bi-atrial DF values of LT pts are significantly lower than that of NT pts for each LA segment as well as for the RAA (p < 0.05). No significant LA-to-RA DF gradient was observed both for LT (0.3±0.5 Hz, p=ns) and NT (0.5±0.03 Hz, p=ns) pts. No significant difference in DF values was observed between LA segments. Conclusions: The lower DF of LT pts is suggestive of a higher organization within both atria compared to NT pts. Our findings suggest that low bi-atrial DF values, but not inter-atrial DF gradient, might be of interest for selecting LS-pAF candidates for sinus rhythm restoration by step-CA.

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Our objective is to evaluate the habitat preference of freshwater snails in relation to environmental factors and the presence of the competitor snail Melanoides tuberculatus. In the first phase, snails was collected at 12 sites. This sampling sites presented a degree of organic input. In the second phase 33 sampling sites were chosen, covering a variety of lotic and lentic environments. The snail species found at Guapimirim, state of Rio de Janeiro, displayed a marked habitat preference, specially in relation to the physical characteristics of each environment. Other limiting factors for snail distribution at the studied lotic environments were the water current velocity and the amount of organic matter, mainly to Physa marmorata, M. tuberculatus, and Biomphalaria tenagophila. The absence of interactions between M. tuberculatus and another snails could be associated to the distinct spatial distribution of those species and the instability of habitats. This later factor may favor the coexistence of M. tuberculatus with B. glabrata by reduction of population density. In areas of schistosomiasis transmission some habitat modification may add to the instability of the environment, which would make room for the coexistence of M. tuberculatus and Biomphalaria spp. In this way, some of the usual measures for the control of snail hosts would prevent the extinction of populations of Biomphalaria spp. by M. tuberculatus in particular habitats.

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PURPOSE: In Switzerland, nationwide large-scale radon surveys have been conducted since the early 1980s to establish the distribution of indoor radon concentrations (IRC). The aim of this work was to study the factors influencing IRC in Switzerland using univariate analyses that take into account biases caused by spatial irregularities of sampling. METHODS: About 212,000 IRC measurements carried out in more than 136,000 dwellings were available for this study. A probability map to assess risk of exceeding an IRC of 300 Bq/m(3) was produced using basic geostatistical techniques. Univariate analyses of IRC for different variables, namely the type of radon detector, various building characteristics such as foundation type, year of construction and building type, as well as the altitude, the average outdoor temperature during measurement and the lithology, were performed comparing 95% confidence intervals among classes of each variable. Furthermore, a map showing the spatial aggregation of the number of measurements was generated for each class of variable in order to assess biases due to spatially irregular sampling. RESULTS: IRC measurements carried out with electret detectors were 35% higher than measurements performed with track detectors. Regarding building characteristics, the IRC of apartments are significantly lower than individual houses. Furthermore, buildings with concrete foundations have the lowest IRC. A significant decrease in IRC was found in buildings constructed after 1900 and again after 1970. Moreover, IRC decreases at higher outdoor temperatures. There is also a tendency to have higher IRC with altitude. Regarding lithology, carbonate rock in the Jura Mountains produces significantly higher IRC, almost by a factor of 2, than carbonate rock in the Alps. Sedimentary rock and sediment produce the lowest IRC while carbonate rock from the Jura Mountains and igneous rock produce the highest IRC. Potential biases due to spatially unbalanced sampling of measurements were identified for several influencing factors. CONCLUSIONS: Significant associations were found between IRC and all variables under study. However, we showed that the spatial distribution of samples strongly affected the relevance of those associations. Therefore, future methods to estimate local radon hazards should take the multidimensionality of the process of IRC into account.

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Background: Most mortality atlases show static maps from count data aggregated over time. This procedure has several methodological problems and serious limitations for decision making in Public Health. The evaluation of health outcomes, including mortality, should be approached from a dynamic time perspective that is specific for each gender and age group. At the moment, researches in Spain do not provide a dynamic image of the population’s mortality status from a spatio-temporal point of view. The aim of this paper is to describe the spatial distribution of mortality from all causes in small areas of Andalusia (Southern Spain) and evolution over time from 1981 to 2006. Methods: A small-area ecological study was devised using the municipality as the unit for analysis. Two spatiotemporal hierarchical Bayesian models were estimated for each age group and gender. One of these was used to estimate the specific mortality rate, together with its time trends, and the other to estimate the specific rate ratio for each municipality compared with Spain as a whole. Results: More than 97% of the municipalities showed a diminishing or flat mortality trend in all gender and age groups. In 2006, over 95% of municipalities showed male and female mortality specific rates similar or significantly lower than Spanish rates for all age groups below 65. Systematically, municipalities in Western Andalusia showed significant male and female mortality excess from 1981 to 2006 only in age groups over 65. Conclusions: The study shows a dynamic geographical distribution of mortality, with a different pattern for each year, gender and age group. This information will contribute towards a reflection on the past, present and future of mortality in Andalusia.

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Roraima is the northernmost state of Brazil, bordering both Venezuela and Guyana. Appropriate climate and vector conditions for dengue transmission together with its proximity to countries where all four dengue serotypes circulate make this state, particularly the capital Boa Vista, strategically important for dengue surveillance in Brazil. Nonetheless, few studies have addressed the population dynamics of Aedes aegypti in Boa Vista. In this study, we report temporal and spatial variations in Ae. aegypti population density using ovitraps in two highly populated neighbourhoods; Centro and Tancredo Neves. In three out of six surveys, Ae. aegypti was present in more than 80% of the sites visited. High presence levels of this mosquito suggest ubiquitous human exposure to the vector, at least during part of the year. The highest infestation rates occurred during the peak of the rainy seasons, but a large presence was also observed during the early dry season (although with more variation among years). Spatial distribution of positive houses changed from a sparse and local pattern to a very dense pattern during the dry-wet season transition. These results suggest that the risk of dengue transmission and the potential for the new serotype invasions are high for most of the year.

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Animal dispersal in a fragmented landscape depends on the complex interaction between landscape structure and animal behavior. To better understand how individuals disperse, it is important to explicitly represent the properties of organisms and the landscape in which they move. A common approach to modelling dispersal includes representing the landscape as a grid of equal sized cells and then simulating individual movement as a correlated random walk. This approach uses a priori scale of resolution, which limits the representation of all landscape features and how different dispersal abilities are modelled. We develop a vector-based landscape model coupled with an object-oriented model for animal dispersal. In this spatially explicit dispersal model, landscape features are defined based on their geographic and thematic properties and dispersal is modelled through consideration of an organism's behavior, movement rules and searching strategies (such as visual cues). We present the model's underlying concepts, its ability to adequately represent landscape features and provide simulation of dispersal according to different dispersal abilities. We demonstrate the potential of the model by simulating two virtual species in a real Swiss landscape. This illustrates the model's ability to simulate complex dispersal processes and provides information about dispersal such as colonization probability and spatial distribution of the organism's path.

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Geographical information systems (GIS) are tools that have been recently tested for improving our understanding of the spatial distribution of disease. The objective of this paper was to further develop the GIS technology to model and control schistosomiasis using environmental, social, biological and remote-sensing variables. A final regression model (R² = 0.39) was established, after a variable selection phase, with a set of spatial variables including the presence or absence of Biomphalaria glabrata, winter enhanced vegetation index, summer minimum temperature and percentage of houses with water coming from a spring or well. A regional model was also developed by splitting the state of Minas Gerais (MG) into four regions and establishing a linear regression model for each of the four regions: 1 (R² = 0.97), 2 (R² = 0.60), 3 (R² = 0.63) and 4 (R² = 0.76). Based on these models, a schistosomiasis risk map was built for MG. In this paper, geostatistics was also used to make inferences about the presence of Biomphalaria spp. The result was a map of species and risk areas. The obtained risk map permits the association of uncertainties, which can be used to qualify the inferences and it can be thought of as an auxiliary tool for public health strategies.

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Geographical Information System (GIS) is a tool that has recently been applied to better understand spatial disease distributions. Using meteorological, social, sanitation, mollusc distribution data and remote sensing variables, this study aimed to further develop the GIS technology by creating a model for the spatial distribution of schistosomiasis and to apply this model to an area with rural tourism in the Brazilian state of Minas Gerais (MG). The Estrada Real, covering about 1,400 km, is the largest and most important Brazilian tourism project, involving 163 cities in MG with different schistosomiasis prevalence rates. The model with three variables showed a R² = 0.34, with a standard deviation of risk estimated adequate for public health needs. The main variables selected for modelling were summer vegetation, summer minimal temperature and winter minimal temperature. The results confirmed the importance of Remote Sensing data and the valuable contribution of GIS in identifying priority areas for intervention in tourism regions which are endemic to schistosomiasis.

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Every year, autochthonous cases of Plasmodium vivax malaria occur in low-endemicity areas of Vale do Ribeira in the south-eastern part of the Atlantic Forest, state of São Paulo, where Anopheles cruzii and Anopheles bellator are considered the primary vectors. However, other species in the subgenus Nyssorhynchus of Anopheles (e.g., Anopheles marajoara) are abundant and may participate in the dynamics of malarial transmission in that region. The objectives of the present study were to assess the spatial distribution of An. cruzii, An. bellator and An. marajoara and to associate the presence of these species with malaria cases in the municipalities of the Vale do Ribeira. Potential habitat suitability modelling was applied to determine both the spatial distribution of An. cruzii, An. bellator and An. marajoara and to establish the density of each species. Poisson regression was utilized to associate malaria cases with estimated vector densities. As a result, An. cruzii was correlated with the forested slopes of the Serra do Mar, An. bellator with the coastal plain and An. marajoara with the deforested areas. Moreover, both An. marajoara and An. cruzii were positively associated with malaria cases. Considering that An. marajoara was demonstrated to be a primary vector of human Plasmodium in the rural areas of the state of Amapá, more attention should be given to the species in the deforested areas of the Atlantic Forest, where it might be a secondary vector.

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The relationships between environmental exposure to risk agents and health conditions have been studied with the aid of remote sensing imagery, a tool particularly useful in the study of vegetation cover. This study aims to evaluate the influence of environmental variables on the spatial distribution of the abundance of Lutzomyia longipalpis and the reported canine and human visceral leishmaniasis (VL) cases at an urban area of Campo Grande, state of Mato Grosso do Sul. The sandfly captures were performed in 13 residences that were selected by raffle considering four residences or collection station for buffer. These buffers were generated from the central house with about 50, 100 and 200 m from it in an endemic area of VL. The abundance of sandflies and human and canine cases were georreferenced using the GIS software PCI Geomatica. The normalized difference vegetation index (NDVI) and percentage of land covered by vegetation were the environmental variables extracted from a remote sensing IKONOS-2 image. The average NDVI was considered as the complexity of habitat and the standard deviation as the heterogeneity of habitat. One thousand three hundred sixty-seven specimens were collected during the catch. We found a significant positive linear correlation between the abundance of sandflies and the percentage of vegetation cover and average NDVI. However, there was no significant association between habitat heterogeneity and the abundance of these flies.