Geographic information systems and logistic regression for high-resolution malaria risk mapping in a rural settlement of the southern Brazilian Amazon

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

Habitat suitability mapping of Anopheles darlingi in the surroundings of the Manso hydropower plant reservoir, Mato Grosso, Central Brazil

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

Spatial analysis in the risk areas determination for malaria in Mato Grosso: an innovation for the programs of control

Made available in DSpace on 2012-09-05T18:23:41Z (GMT). No. of bitstreams: 2 license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) 270.pdf: 2465684 bytes, checksum: 95da944419372d0cd0af02c42b05481a (MD5) Previous issue date: 2006Fundação Oswaldo Cruz. Escola Nacional de Saúde Pública Sergio Arouca. Rio de Janeiro, RJ, Brasil.O presente estudo tem por objetivo analisar a distribuição temporal e espacial da malária no Mato Grosso, entre o período de 1980 a 2003, utilizando a análise espacial como ferramenta para identificação de áreas prioritárias pra controle da malária e contribuir para o aprimoramento dos métodos de estratificação epidemiológica do risco de adoecer por malária. O trabalho está apresentado em três artigos. No primeiro artigo, analisou-se a evolução dos casos de malária no Estado de Mato Grosso, entre 1980 e 2003, segundo microrregião homogênea de residência. No segundo artigo, analisou-se a estratificação de áreas prioritárias e os fatores envolvidos na ocorrência de malária em Mato Grosso, de 1986 a 2003, utilizando-se análise espacial através das medidas de autocorrelação de Moran, global e local. No terceiro artigo buscou-se verificar a aplicabilidade do método de estratificação de área prioritária para controle da malária adotando a técnica de análise espacial utilizada no segundo artigo. Este artigo comparou a estratificação de risco adotada pelo Plano de Intensificação das Ações de Controle da Malária na Amazônia Legal, desenvolvido pela FUNASA e a estratificação de área prioritária determinada pela análise espacial, antes e depois de um ano de implantação do Plano, utilizando-se dados de 1999 e de 2001. Concluiu-se que houve variação na distribuição da mortalidade e morbidade por microrregiões e esta variação esteve influenciada por contextos específicos de cada localidade. A metodologia de análise espacial utilizada permitiu a determinação de áreas prioritárias que contemplam a dinâmica da epidemia/endemia para além dos limites estritos de municípios. O uso da análise espacial mostrou-se um recurso importante para estratificação de áreas prioritárias e úteis para instrumentalização dos níveis, central e regional, no planejamento das ações de controle, monitoramento e avaliação. (...

Fatores socioambientais associados à distribuição espacial de malária no assentamento Vale do Amanhecer, Município de Juruena, Estado de Mato Grosso, 2005

Malaria é uma doença de distribuição focal. No Brasil, áreas de assentamento e garimpos de ouro na Amazônia Legal apresentam grande concentração de casos. Este artigo analisa a distribuição espacial de casos de malária, considerando fatores ambientais e sociais, no assentamento Vale do Amanhecer, Município de Juruena, Mato Grosso, Brasil. Em 2005, notificou-se 359 casos autóctones no assentamento e pelo método de Kernel identificaram-se áreas de maior e menor intensidade de número de casos. As áreas de maior intensidade apresentaram 290 casos e na de menor intensidade 64 casos. A intensidade da distribuição variou no assentamento, indicando áreas de grande intensidade de casos favoráveis para transmissão como área de garimpos. Assim, apesar de assentamentos serem considerados como foco de malária, existem no seu interior, especificidades que, uma vez identificadas, podem contribuir para o controle da doença

Spatial patterns of malaria in a land reform colonization project, Juruena municipality, Mato Grosso, Brazil

<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Methods</p> <p>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.</p> <p>Results</p> <p>Of a total of 336 malaria cases, 102 (30.36%) were caused by <it>Plasmodium falciparum </it>and 174 (51.79%) by <it>Plasmodium vivax</it>. 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.</p> <p>Conclusions</p> <p>Environmental factors and their alteration are associated with the occurrence and spatial distribution of malaria cases in rural settlements.</p