ABSTRACT
Objetivo: caracterizar a epidemiologia da malária em área de Assentamento na Amazônia mato-grossense. Método: estudo ecológico, realizado no Assentamento Vale do Amanhecer, no Município de Juruena, Mato Grosso. Foram analisadas 336 fichas. Utilizou-se o software EpiInfo 3.3.2 para a construção dos bancos de dados e software Terraview 3.1.4 e ArcGIS 9.2 para análise espacial, construção do mapa de distribuição de casos e os mapas temáticos de uso e ocupação do solo. Resultados: em 2005, o Assentamento era composto por 718 habitantes, 394 (54,87%) sexo masculino e 324 (45,13.%) sexo feminino. Dos 336 casos de malária, 133 era residente na Estrada 08, 37,60% das notificações. Nas Estradas 13 e 5, foram notificados 124 (35,10%) e 58 (16,40%) casos de malária, respectivamente. A região sul do assentamento apresentou 276 casos e maior número de notificações acima de 10 casos/domicílio. Desses, 102 (30,36%) casos foram causados pelo P. falciparum e 174 (51,79%) por P. vivax. A região norte apresentou 60 casos e notificações abaixo de 10 casos/domicílio. A área de formações florestais apresentou 70 (20,83%) casos. Conclusão: a ocorrência e distribuição de malária no assentamento são influenciadas pelos fatores ambientais e suas alterações.
Objective: to characterize the epidemiology of malaria in settlement area in Mato Grosso Amazon. Method: ecological study conducted in settlement Vale do Amanhecer, in the municipality of Juruena, Mato Grosso. 336 records were analyzed. the software was used EpiInfo 3.3.2 for the construction of databases and Terraview 3.1.4 and ArcGIS 9.2 software for spatial analysis, case distribution map construction and thematic maps of land use and occupation. Results: in 2005, the settlement was composed of 718 inhabitants, 394 (54.87%) male and 324 (45.13%.) Female. Of the 336 cases of malaria, 133 were resident on Highway 08, 37.60% of notifications. Roads in 13:05, were reported 124 (35.10%) and 58 (16.40%) cases of malaria, respectively. South of the settlement region had 276 cases and more up to 10 cases / home notifications. Of these, 102 (30.36%) cases were caused by P. falciparum and 174 (51.79%) by P. vivax. The northern region had 60 cases and 10 cases notifications under / home. The area of forest formations had 70 (20.83%) cases. Conclusion: the occurrence and distribution of malaria in the settlement are influenced by environmental factors, as amended.
Objetivo: caracterizar la epidemiología de la malaria en el área de asentamiento en Mato Grosso del Amazonas. Método: estudio ecológico con datos de asentamiento Vale do Amanhecer, en el municipio de Juruena, Mato Grosso. Se analizaron 336 registros. el software se utilizó EpiInfo 3.3.2 para la construcción de bases de datos y Terraview 3.1.4 y el software ArcGIS 9.2 para el análisis espacial, la construcción caja de mapa de distribución y mapas temáticos de uso y ocupación del suelo. Resultados: en 2005, el asentamiento se compone de 718 habitantes, 394 (54,87%) y 324 hombres (45.13%). Mujer. De los 336 casos de malaria, 133 eran residentes en la autopista 08, 37.60% de las notificaciones. Las carreteras de 13:05, se reportaron casos de malaria 124 (35.10%) y 58 (16,40%), respectivamente. Al sur de la región de asentamiento tenía 276 casos y más casos hasta 10 / notificaciones de origen. De éstos, 102 (30,36%) casos fueron causados por P. falciparum y 174 (51,79%) por P. vivax. La región del norte tenía 60 casos y 10 notificaciones de casos bajo / home. El área de las formaciones forestales contaba con 70 (20,83%) casos. Conclusión: la presencia y la distribución de la malaria en el asentamiento son influenciados por factores ambientales, en su versión modificada.
Subject(s)
Epidemiology , Amazonian Ecosystem , Malaria , Rural PopulationABSTRACT
BACKGROUND: In Brazil, 99% of the cases of malaria are concentrated in the Amazon region, with high level of transmission. The objectives of the study were to use geographic information systems (GIS) analysis and logistic regression as a tool to identify and analyse the relative likelihood and its socio-environmental determinants of malaria infection in the Vale do Amanhecer rural settlement, Brazil. METHODS: A GIS database of georeferenced malaria cases, recorded in 2005, and multiple explanatory data layers was built, based on a multispectral Landsat 5 TM image, digital map of the settlement blocks and a SRTM digital elevation model. Satellite imagery was used to map the spatial patterns of land use and cover (LUC) and to derive spectral indices of vegetation density (NDVI) and soil/vegetation humidity (VSHI). An Euclidian distance operator was applied to measure proximity of domiciles to potential mosquito breeding habitats and gold mining areas. The malaria risk model was generated by multiple logistic regression, in which environmental factors were considered as independent variables and the number of cases, binarized by a threshold value was the dependent variable. RESULTS: Out of a total of 336 cases of malaria, 133 positive slides were from inhabitants at Road 08, which corresponds to 37.60% of the notifications. The southern region of the settlement presented 276 cases and a greater number of domiciles in which more than ten cases/home were notified. From these, 102 (30.36%) cases were caused by Plasmodium falciparum and 174 (51.79%) cases by Plasmodium vivax. Malaria risk is the highest in the south of the settlement, associated with proximity to gold mining sites, intense land use, high levels of soil/vegetation humidity and low vegetation density. CONCLUSIONS: Mid-resolution, remote sensing data and GIS-derived distance measures can be successfully combined with digital maps of the housing location of (non-) infected inhabitants to predict relative likelihood of disease infection through the analysis by logistic regression. Obtained findings on the relation between malaria cases and environmental factors should be applied in the future for land use planning in rural settlements in the Southern Amazon to minimize risks of disease transmission.
Subject(s)
Malaria, Falciparum/epidemiology , Malaria, Vivax/epidemiology , Topography, Medical , Brazil/epidemiology , Geographic Information Systems , Humans , Logistic Models , Risk Assessment , Rural Population , Spatial AnalysisABSTRACT
INTRODUCTION: The present study compares human landing catches of primary malaria vectors with two alternative methods of capture: the Shannon trap and the Mosquito magnet. METHODS: This study used regression models to adjust capture data to a negative binominal distribution. RESULTS: Capture numbers and relative percentages obtained from the three methods vary strongly between species. The highest overall captures were obtained for Anopheles triannulatus with captures for the Shannon trap and the Mosquito magnet measuring more than 330 percent higher than captures obtained by human landings. For Anopheles darlingi, captures by the Shannon trap and the Mosquito magnet were about 14 percent and 26 percent of human landing catches, respectively. Another species with malaria transmission potential that was not sampled by human landing captures weascaptured by the Shannon trap and the Mosquito magnet (Anopheles oswaldoi). Both alternative sampling techniques can predict the human landing of Anopheles triannulatus, but without proportionality. Models for Anopheles darlingi counts, after totaling daily captures, are significant and proportional, but prediction models are more reliable when using the Shannon trap compared with the Mosquito magnet captures. CONCLUSIONS: These alternative capture methods can be partially recommended for the substitution of human landing captures or, at least, as complementary forms of monitoring for malarial mosquitoes.
INTRODUÇÃO: O presente estudo compara a captura através da isca humana dos principais vetores da malária, com dois métodos alternativos de captura, a armadilha luminosa de Shannon e a armadilha Mosquito magnet. MÉTODOS: O presente estudo utiliza modelos de regressão para ajustar os dados obtidos para uma distribuição binomial negativa. RESULTADOS: Os números e as proporções relativas obtidas nos três métodos variaram fortemente entre as espécies. A maior densidade capturada foi de Anopheles triannulatus, através das armadilhas de Shannon e do Mosquito magnet sendo mais de 330 por cento superior que a obtida pela captura por isca humana. Para Anopheles darlingi, capturas com a armadilha de Shannon e com o Mosquito magnet representaram cerca de 14 por cento e 26 por cento, respectivamente, em comparação com a captura através da isca humana. Outras espécies com potencial de transmissão da malária não foram capturadas com a utilização da isca humana, mas foram coletadas na armadilha de Shannon e no Mosquito magnet (Anopheles oswaldoi). Ambas as técnicas alternativas de captura, podem predizer significativamente a captura através da isca humana de Anopheles triannulatus, porém sem proporcionalidade. Os números previstos para o Anopheles darlingi, após a contagem total da captura diária, são significativos e proporcionais, mas a previsão é mais confiável para a armadilha de Shannon que para o Mosquito magnet. CONCLUSÕES: A comparação de métodos alternativos de captura pode ser parcialmente recomendada para a substituição da captura através da isca humana ou, pelo menos, como uma forma complementar de coleta de mosquitos.
Subject(s)
Animals , Anopheles/classification , Insect Vectors/classification , Brazil , Linear Models , Malaria/transmission , Mosquito Control/methods , Population DensityABSTRACT
INTRODUCTION: The present study compares human landing catches of primary malaria vectors with two alternative methods of capture: the Shannon trap and the Mosquito magnet. METHODS: This study used regression models to adjust capture data to a negative binominal distribution. RESULTS: Capture numbers and relative percentages obtained from the three methods vary strongly between species. The highest overall captures were obtained for Anopheles triannulatus with captures for the Shannon trap and the Mosquito magnet measuring more than 330% higher than captures obtained by human landings. For Anopheles darlingi, captures by the Shannon trap and the Mosquito magnet were about 14% and 26% of human landing catches, respectively. Another species with malaria transmission potential that was not sampled by human landing captures weascaptured by the Shannon trap and the Mosquito magnet (Anopheles oswaldoi). Both alternative sampling techniques can predict the human landing of Anopheles triannulatus, but without proportionality. Models for Anopheles darlingi counts, after totaling daily captures, are significant and proportional, but prediction models are more reliable when using the Shannon trap compared with the Mosquito magnet captures. CONCLUSIONS: These alternative capture methods can be partially recommended for the substitution of human landing captures or, at least, as complementary forms of monitoring for malarial mosquitoes.
Subject(s)
Anopheles/classification , Insect Vectors/classification , Animals , Brazil , Linear Models , Malaria/transmission , Mosquito Control/methods , Population DensityABSTRACT
BACKGROUND: In Brazil, 99% of malaria cases are concentrated in the Amazon, and malaria's spatial distribution is commonly associated with socio-environmental conditions on a fine landscape scale. In this study, the spatial patterns of malaria and its determinants in a rural settlement of the Brazilian agricultural reform programme called "Vale do Amanhecer" in the northern Mato Grosso state were analysed. METHODS: In a fine-scaled, exploratory ecological study, geocoded notification forms corresponding to malaria cases from 2005 were compared with spectral indices, such as the Normalized Difference Vegetation Index (NDVI) and the third component of the Tasseled Cap Transformation (TC_3) and thematic layers, derived from the visual interpretation of multispectral TM-Landsat 5 imagery and the application of GIS distance operators. RESULTS: Of a total of 336 malaria cases, 102 (30.36%) were caused by Plasmodium falciparum and 174 (51.79%) by Plasmodium vivax. Of all the cases, 37.6% (133 cases) were from residents of a unique road. In total, 276 cases were reported for the southern part of the settlement, where the population density is higher, with notification rates higher than 10 cases per household. The local landscape mostly consists of open areas (38.79 km²). Training forest occupied 27.34 km² and midsize vegetation 7.01 km². Most domiciles with more than five notified malaria cases were located near areas with high NDVI values. Most domiciles (41.78%) and malaria cases (44.94%) were concentrated in areas with intermediate values of the TC_3, a spectral index representing surface and vegetation humidity. CONCLUSIONS: Environmental factors and their alteration are associated with the occurrence and spatial distribution of malaria cases in rural settlements.
Subject(s)
Malaria, Falciparum/epidemiology , Malaria, Vivax/epidemiology , Brazil/epidemiology , Female , Geography , Human Activities , Humans , Male , Plasmodium falciparum/isolation & purification , Plasmodium vivax/isolation & purificationABSTRACT
Este trabalho teve por objetivo caracterizar e quantificar as unidades fitofisionômicas em mesoescala e estabelecer suas relações com a intensidade e duração da inundação e com a topografia. O estudo foi realizado no Sítio de Amostragem de Longa Duração (SALD), implantado em uma área de 25 km² localizado na planície de inundação do rio Cuiabá, Pantanal de Mato Grosso. As unidades fitofisionômicas foram determinadas a partir da classificação supervisionada de imagens CBERS 2B sensor CCD. Os mapas de intensidade e duração da inundação e topografia foram gerados a partir da interpolação espacial de levantamentos planialtimétricos de campos. Foi evidenciada a existência de quatro unidades, sendo o Campo (pastagem inundável) a unidade com maior área de ocorrência, seguido pelas Cordilheiras (savana arbórea densa), Landizal (floresta inundável sempre verde) e Cambarazal (floresta inundável monodominante de Vochysia divergens Pohl.) respectivamente. O Campo apresentou sua maior distribuição em áreas de alta intensidade e duração de inundação e topografia baixa. O Cambarazal predomina em áreas de intensidade média e duração e topografia alta, o Landizal em áreas com intensidade e duração alta e topografia baixa, enquanto as cordilheiras são caracterizadas por intensidade e duração baixa e topografia alta. Testes estatísticos indicaram que a inundação foi o principal fator responsável pela distribuição das unidades fitofisionômicas em mesoescala no Pantanal norte.
The purpose of this work was to characterize and quantify phytophysiognomic units at mesoscale and evaluate their relationships with flood intensity, flood duration and topography. The study was conducted at a 25 km² Long-Term Sampling Site (LTSS), located within the floodplain of the Cuiabá River in the Pantanal of Mato Grosso. The phytophysiognomic units were determined from the supervised classification of CBERS 2B sensor CCD satellite images. The maps of flood intensity, flood duration and of topography were generated from the spatial interpolation of planialtimetric field surveys. Four phytophysiognomic units were identified; Campo inundável (flooded grassland) was the unit with the largest area of occurrence, followed by Cordilheiras (dense arboreal savanna), Landizal (seasonally flooded evergreen forest), and Cambarazal (monodominant Vochysia divergens Pohl. forest), respectively. Campo inundável is distributed mainly in areas of high flood intensity and duration and low topographic positions. Cambarazal predominates in areas of medium flood intensity and duration and intermediate elevation, Landizal in areas of high flood intensity and duration and low topographic position, whereas Cordilheiras are characterized by low flood intensity and duration and location in higher elevations. Statistical tests indicated that flood intensity is the main factor responsible for the mesoscale distribution of phytophysiognomic units in the northern Pantanal.
ABSTRACT
Lutzomyia (Nyssomyia) whitmani s.l.is the main vector of cutaneous leishmaniasis in state of Mato Grosso, but little is known about environmental determinants of its spatial distribution on a regional scale. Entomologic surveys of this sand fly species, conducted between 1996 and 2001 in 41 state municipalities, were used to investigate the relationships between environmental factors and the presence of the species, and to develop a spatial model of habitat suitability. The relationship between averaged CDC light trap indexes and 15 environmental and socio-economic factors were tested by logistic regression (LR) analysis. Spatial layers of deforestation tax and the Brazilian index of gross net production (IGNP) were identified as significant explanatory variables for vector presence in the LR model, and these were then overlaid with habitat maps. The highest habitat suitability in 2001 was obtained for the heavily deforested areas in the Central-North, South, East, and Southwest of Mato Grosso, particularly in municipalities with lower IGNP values.
Subject(s)
Ecosystem , Insect Vectors/classification , Psychodidae/classification , Animals , Brazil , Geography , Logistic Models , Models, Biological , Population Density , Population Dynamics , Seasons , TreesABSTRACT
Lutzomyia (Nyssomyia) whitmani s.l.is the main vector of cutaneous leishmaniasis in state of Mato Grosso, but little is known about environmental determinants of its spatial distribution on a regional scale. Entomologic surveys of this sand fly species, conducted between 1996 and 2001 in 41 state municipalities, were used to investigate the relationships between environmental factors and the presence of the species, and to develop a spatial model of habitat suitability. The relationship between averaged CDC light trap indexes and 15 environmental and socio-economic factors were tested by logistic regression (LR) analysis. Spatial layers of deforestation tax and the Brazilian index of gross net production (IGNP) were identified as significant explanatory variables for vector presence in the LR model, and these were then overlaid with habitat maps. The highest habitat suitability in 2001 was obtained for the heavily deforested areas in the Central-North, South, East, and Southwest of Mato Grosso, particularly in municipalities with lower IGNP values.
Subject(s)
Animals , Ecosystem , Insect Vectors/classification , Psychodidae/classification , Brazil , Geography , Logistic Models , Models, Biological , Population Density , Population Dynamics , Seasons , TreesABSTRACT
Intense environmental impacts, causing alterations of the natural habitats of fauna, including those of sandfly disease vectors are observed in Mato Grosso State, Central Brazil. Entomologic survey of phlebotomines was based on light trap and was carried out by entomological nucleus of the FUNASA and SES in the period between 1996 and 2001. Eighty eight species were identified, including the following sandflies with medical importance to leishmaniasis: Lutzomyia amazonensis, L. anduzei, L. antunesi, L. ayrozai, L. carrerai carrerai, L. complexa, L. cruzi, L. flaviscutellata, L. intermedia, L. longipalpis, L. migonei, L. paraensis, L. ubiquitalis, L. whitmani and L. yuilli yuilli. Most sandflies of medical importance occurred in the Amazon forest and savannah. L. longipalpis and L. cruzi had high densities in the savannah region. L. flaviscutellata is predominating in both the Amazon forest and the savannah region. L. whitmani and L. antunesi were sampled in the Amazon forest, savannah and marsh land.
Subject(s)
Insect Vectors/classification , Psychodidae/classification , Animals , Brazil , Population Density , Population Dynamics , TreesABSTRACT
Intense environmental impacts, causing alterations of the natural habitats of fauna, including those of sandfly disease vectors are observed in Mato Grosso State, Central Brazil. Entomologic survey of phlebotomines was based on light trap and was carried out by entomological nucleus of the FUNASA and SES in the period between 1996 and 2001. Eighty eight species were identified, including the following sandflies with medical importance to leishmaniasis: Lutzomyia amazonensis, L. anduzei, L. antunesi, L. ayrozai, L. carrerai carrerai, L. complexa, L. cruzi, L. flaviscutellata, L. intermedia, L. longipalpis, L. migonei, L. paraensis, L. ubiquitalis, L. whitmani and L. yuilli yuilli. Most sandflies of medical importance occurred in the Amazon forest and savannah. L. longipalpis and L. cruzi had high densities in the savannah region. L. flaviscutellata is predominating in both the Amazon forest and the savannah region. L. whitmani and L. antunesi were sampled in the Amazon forest, savannah and marsh land.
O estado de Mato Grosso, Brasil vem sendo grandemente impactado, o que provoca uma alteração no habitat natural da fauna, incluindo-se os vetores das leishmanioses. Foram analisados dados de levantamentos entomológicos realizados pela FUNASA e SES no período de 1996 a 2001. Foram capturados indivíduos pertencentes a 88 espécies, sendo as de importância para a transmissão das leishmanioses: Lutzomyia amazonensis, L. anduzei, L. ayrozai, L. carrerai carrerai, L. complexa, L. cruzi, L. flaviscutellata, L. intermedia, L. longipalpis, L. migonei, L. paraensis, L. ubiquitalis, L. whitmani e L. yuilli yuilli, as quais foram plotadas no mapa do Estado. A maioria das espécies de importância médica compartilha a vegetação de floresta Amazônica e cerrado. L. longipalpis e L. cruzi possuem altas densidades na região de cerrado. L. flaviscutellata predomina na floresta Amazônica e no cerrado. L. whitmani e L. antunesi foram capturadas na floresta Amazônica, cerrado e pantanal.
Subject(s)
Animals , Insect Vectors/classification , Psychodidae/classification , Brazil , Population Density , Population Dynamics , TreesABSTRACT
A cross-sectional study utilizing spatial analysis techniques was conducted to study water quality problems and risk of waterborne enteric diseases in a lower-middle-class urban district of Cuiabá, the capital of Mato Grosso State, Brazil. Field surveys indicate high rates of supply water contamination in domiciles and, conspicuously, in public and private schools. Logistic regression models developed for the variables turbidity, Escherichia coli, total coliforms, and intestinal parasite infection did not identify singular explanatory factors for the supply water conditions and elevated incidences of enteric diseases among children. The contamination problems were found to be the result of precarious conditions involving both public infrastructure and in-building sanitary installations and their maintenance. GIS methods were successfully applied to create spatial datasets for logistic regression model building and to construct risk maps using regression coefficients.
Subject(s)
Enterobacteriaceae Infections/epidemiology , Geographic Information Systems , Intestinal Diseases, Parasitic , Topography, Medical , Water Microbiology , Water Supply/analysis , Brazil/epidemiology , Child , Enterobacteriaceae Infections/etiology , Epidemiologic Methods , Humans , Intestinal Diseases, Parasitic/epidemiology , Intestinal Diseases, Parasitic/etiology , Socioeconomic Factors , Urban Population , Water Supply/standardsABSTRACT
Foi realizado um estudo transversal incluindo técnicas da análise espacial para avaliar problemas de qualidade de água de consumo e riscos de doenças entéricas em um bairro da classe média baixa na cidade de Cuiabá, capital de Mato Grosso, Brasil. Os trabalhos de campo indicam altos índices de contaminação nos domicílios e, particularmente, nas escolas públicas e particulares. Modelos de regressão logística, desenvolvidos para as variáveis turbidez, Escherichia coli, coliformes totais e parasitas intestinais não puderam ser relacionados a fatores singulares que explicassem riscos de comprometimento da água de consumo e de infecção com parasitas em crianças. Os problemas detectados, entretanto, podem ser ligados às condições precárias da infra-estrutura pública de abastecimento e das instalações sanitárias e sua manutenção nos domicílios. Técnicas de geoprocessamento foram aplicadas com sucesso para a elaboração de planos de informação espaciais, utilizados na geração dos modelos de regressão logística e no mapeamento de risco com base nos coeficientes da regressão logística.
A cross-sectional study utilizing spatial analysis techniques was conducted to study water quality problems and risk of waterborne enteric diseases in a lower-middle-class urban district of Cuiabá, the capital of Mato Grosso State, Brazil. Field surveys indicate high rates of supply water contamination in domiciles and, conspicuously, in public and private schools. Logistic regression models developed for the variables turbidity, Escherichia coli, total coliforms, and intestinal parasite infection did not identify singular explanatory factors for the supply water conditions and elevated incidences of enteric diseases among children. The contamination problems were found to be the result of precarious conditions involving both public infrastructure and in-building sanitary installations and their maintenance. GIS methods were successfully applied to create spatial datasets for logistic regression model building and to construct risk maps using regression coefficients.
Subject(s)
Humans , Male , Female , Waterborne Diseases , Environmental Monitoring , Geographic Information Systems , Water Microbiology , Water Quality , Water Supply , Brazil , Logistic Models , Quality ControlABSTRACT
BACKGROUND: Hydropower plants provide more than 78 % of Brazil's electricity generation, but the country's reservoirs are potential new habitats for main vectors of malaria. In a case study in the surroundings of the Manso hydropower plant in Mato Grosso state, Central Brazil, habitat suitability of Anopheles darlingi was studied. Habitat profile was characterized by collecting environmental data. Remote sensing and GIS techniques were applied to extract additional spatial layers of land use, distance maps, and relief characteristics for spatial model building. RESULTS: Logistic regression analysis and ROC curves indicate significant relationships between the environment and presence of An. darlingi. Probabilities of presence strongly vary as a function of land cover and distance from the lake shoreline. Vector presence was associated with spatial proximity to reservoir and semi-deciduous forests followed by Cerrado woodland. Vector absence was associated with open vegetation formations such as grasslands and agricultural areas. We suppose that non-significant differences of vector incidences between rainy and dry seasons are associated with the availability of anthropogenic breeding habitat of the reservoir throughout the year. CONCLUSION: Satellite image classification and multitemporal shoreline simulations through DEM-based GIS-analyses consist in a valuable tool for spatial modeling of A. darlingi habitats in the studied hydropower reservoir area. Vector presence is significantly increased in forested areas near reservoirs in bays protected from wind and wave action. Construction of new reservoirs under the tropical, sub-humid climatic conditions should therefore be accompanied by entomologic studies to predict the risk of malaria epidemics.
Subject(s)
Anopheles , Bites and Stings/epidemiology , Ecosystem , Environmental Monitoring/statistics & numerical data , Geographic Information Systems , Power Plants , Animals , Brazil/epidemiology , Climate , Environment , Epidemiological Monitoring , Humans , Insect Vectors , Logistic Models , Malaria/epidemiology , Malaria/transmission , ROC Curve , Risk Factors , SpacecraftABSTRACT
This study evaluates the spatial patterns of land occupation and their relationship to water quality in the Cuiabá River watershed, one of the main affluents of the Pantanal floodplain. The impact of farming and other land occupation forms were studied using a three year time series. Monitoring included 15 parameters at 21 stations with a total of 1266 different samples. Ten stations along the Cuiabá River were ordinated by Principal Component Analysis (PCA). For an exploratory analysis in the spatial domain, sub-basins of the Cuiabá watershed were classified according to mean concentrations of selected water quality parameters. Supervised classification of digital Landsat ETM imagery and standard GIS techniques were applied to parameterize land use and occupation according to a watershed scale. Redundancy Analysis (RDA) was then used to evaluate impacts of environmental and socio-economic factors on water quality. A Cuiabá headwater station only shows slightly elevated total coliform counts and concentrations of nutrients in the river after it passes regions of extensive cattle farming. After the confluence with the Manso River, nutrient and COD concentrations increase significantly, receiving loads from sub-basins under intensive agricultural land use, with mean annual concentrations up to 1.74 mg/L of total nitrogen (Kjedahl). Sub-watersheds with intensive fishing culture activities were shown to have significant impact on nitrogen concentrations, reaching mean concentrations of 2.66 mg/L of total nitrogen in the affluents. Most serious biological and chemical water pollution can be observed at stream outlets in the urban agglomeration of Cuiabá/Várzea Grande. Affluent pollution is reflected in the water quality of the Cuiabá River: subsequent monitoring stations in the urban area are ordinated on a gradient of increasing degradation of chemical and biological water quality. The auto-depuration capacity of the Cuiabá River is intact, but elevated concentrations of Phosphorous and Chemical Oxygen Demand can be observed as far away as the Pantanal floodplain, about 120 km downstream from the urban agglomeration.
