RESUMO
Blood infection by the simian parasite, Plasmodium simium, was identified in captive (n = 45, 4.4%) and in wild Alouatta clamitans monkeys (n = 20, 35%) from the Atlantic Forest of southern Brazil. A single malaria infection was symptomatic and the monkey presented clinical and haematological alterations. A high frequency of Plasmodium vivax-specific antibodies was detected among these monkeys, with 87% of the monkeys testing positive against P. vivax antigens. These findings highlight the possibility of malaria as a zoonosis in the remaining Atlantic Forest and its impact on the epidemiology of the disease.
Assuntos
Alouatta/parasitologia , Malária/veterinária , Doenças dos Macacos/epidemiologia , Plasmodium/classificação , Animais , Anticorpos Antiprotozoários/sangue , Brasil/epidemiologia , Florestas , Malária/epidemiologia , Malária/parasitologia , Doenças dos Macacos/parasitologia , Reação em Cadeia da PolimeraseRESUMO
Understanding the different background landscapes in which malaria transmission occurs is fundamental to understanding malaria epidemiology and to designing effective local malaria control programs. Geology, geomorphology, vegetation, climate, land use, and anopheline distribution were used as a basis for an ecological classification of the state of Roraima, Brazil, in the northern Amazon Basin, focused on the natural history of malaria and transmission. We used unsupervised maximum likelihood classification, principal components analysis, and weighted overlay with equal contribution analyses to fine-scale thematic maps that resulted in clustered regions. We used ecological niche modeling techniques to develop a fine-scale picture of malaria vector distributions in the state. Eight ecoregions were identified and malaria-related aspects are discussed based on this classification, including 5 types of dense tropical rain forest and 3 types of savannah. Ecoregions formed by dense tropical rain forest were named as montane (ecoregion I), submontane (II), plateau (III), lowland (IV), and alluvial (V). Ecoregions formed by savannah were divided into steppe (VI, campos de Roraima), savannah (VII, cerrado), and wetland (VIII, campinarana). Such ecoregional mappings are important tools in integrated malaria control programs that aim to identify specific characteristics of malaria transmission, classify transmission risk, and define priority areas and appropriate interventions. For some areas, extension of these approaches to still-finer resolutions will provide an improved picture of malaria transmission patterns.
Assuntos
Culicidae , Ecossistema , Insetos Vetores , Malária/transmissão , Algoritmos , Animais , Brasil/epidemiologia , Análise por Conglomerados , Humanos , Malária/epidemiologia , Malária/prevenção & controle , Densidade Demográfica , Análise de Componente Principal , Estações do Ano , Topografia Médica , Clima TropicalRESUMO
Knowledge of vector distribution is important for the design of effective local malaria control programs. Here we apply ecological niche modeling to analyze and predict the distributions of malaria vectors based on entomological collection points in the State of Roraima in the northern Brazilian Amazon Basin. Anopheline collections were conducted from 1999 to 2003 at 76 localities, all with active malaria transmission. A total of 13 anopheline species was identified from 17,074 adult females collected: Anopheles darlingi, An. albitarsis s.l., An. nuneztovari, An. triannulatus s.l., An. braziliensis, An. peryassui, An. oswaldoi s.l., An. mattogrossensis, An. strodei, An. evansae, An. squamifemur, An. mediopunctatus s.l, An. intermedius. Anopheles darlingi, and An. albitarsis were the most frequently found species. An. squamifemur was found for the first time in Roraima. A distributional prediction model (genetic algorithm for rule-set prediction-GARP) and environmental variables were used to predicted potential distribution range for six anopheline species that occurred at > or = 19 collection points. The method allows for the application of moderate sample sizes to produce distribution maps of vector species that could be used to maximize efficiency of surveys and optimize use of economic resources in epidemiology and control.