O processo de mudanças climáticas e ambientais globais, que vem se agravando nas últimas décadas mas que foi divulgado mais amplamente pela mídia nos últimos dois anos, porta para a sociedade e setores de governo um desafio sobre as causas e o papel das alterações ambientais sobre as condições de saúde. Esse trabalho tem como objetivo avaliar cenários de mudanças climáticas e ambientais e suas incertezas para o Brasil. Além disso identifica recursos que podem ser utilizados para desenvolver uma rede de diagnóstico, modelagem, análise e intervenção sobre as repercussões dessas mudanças sobre as condições de saúde. Os principais grupos de doenças que podem ser afetados por essas mudanças são as doenças de veiculação hídrica, as transmitidas por vetores e as respiratórias. No entanto, os riscos associados às mudanças climáticas globais não podem ser avaliados em separado do contexto globalização, mudanças ambientais e precarização de sistemas de governo. Cabe ao setor saúde, não só prevenir esses riscos, mas atuar na redução de suas vulnerabilidades sociais.Palavras-chave: mudanças globais; vigilância ambiental em saúde; vigilância epidemiológica; modelos preditivos.

Deforestation has been linked to a rise in malaria prevalence. In this paper, we studied longitudinally 20 spots, including forested and deforested portions of a temporary river in a malarigenous frontier zone. Larval habitat parameters influencing distribution of Anopheles darlingi (Diptera: Culicidae) larvae were studied. We observed that larvae were clustered in forested-deforested transitions. For the first time in the literature, it was verified that parameters determining larval distribution varied from deforested to forested areas. The proximity to human dwellings was also a significant factor determining distribution, but larvae was most importantly associated with a previously undescribed parameter, the presence of small obstructions to river flow, such as tree trunks within the river channel, which caused pooling of water during the dry season ('microdams'). In deforested areas, the most important factor determining distribution of larvae was shade (reduced luminance). Larvae were absent in the entire studied area during the wet season and present in most sites during the dry season. During the wet-dry transition, larvae were found sooner in areas with microdams, than in other areas, suggesting that flow obstruction prolongs the breeding season of An. darlingi. Adult mosquito densities and malaria incidence were higher during the dry season. Our data correlate well with the published literature, including the distribution of malaria cases near the forest fringes, and has permitted the creation of a model of An. darlingi breeding, where preference for sites with reduced luminance, human presence and microdams would interact to determine larval distribution.

The nine countries sharing the Amazon forest accounted for 89% of all malaria cases reported in the Americas in 2008. Remote sensing can help identify the environmental determinants of malaria transmission and their temporo-spatial evolution. Seventeen studies characterizing land cover or land use features, and relating them to malaria in the Amazon subregion, were identified. These were reviewed in order to improve the understanding of the land cover/use class roles in malaria transmission. The indicators affecting the transmission risk were summarized in terms of temporal components, landscape fragmentation and anthropic pressure. This review helps to define a framework for future studies aiming to characterize and monitor malaria.

This study deals with the connections between vegetation cover and the annual and interannual climatic variability in Brazil. The analyses were based on the normalized difference vegetation index (NDVI) derived from the Advanced Very High Resolution Radiometer (AVHRR) sensor for the Global Inventory Modeling and Monitoring Study (GIMMS) continental dataset and monthly mean outgoing longwave radiation (OLR) data. The statistical technique of principal component analysis (PCA) was used for analysing the data for the January 1982-December 1993 period. The first component reveals that NDVI data have potential for characterizing the main patterns of vegetation types in Brazil. It was also possible to characterize the annual and interannual climate-related variability of the vegetation types. Specifically, the second and third leading PCA are associated with the summer/winter and spring/ autumn portions of the annual cycle while their interannual variations are modulated by El Niñ o Southern Oscillation (ENSO) phenomena. The fourth component showed that 'non-climatic' factors, such as slash burning events, do affect NDVI values mainly in central Brazil. The high correlation coefficients between NDVI and OLR eigenvectors, corresponding to the summer/winter (r~0.91) and spring/autumn (r~0.70) modes, suggest that the annual variability of the vegetation coverage in Brazilian territory is largely modulated by the prevailing climatic conditions.

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