Abstract. We performed bimonthly mosquito larval collections during 1 year, in an agricultural settlement in the Brazilian Amazon, as well as an analysis of malaria incidence in neighboring houses. Water collections located at forest fringes were more commonly positive for Anopheles darlingi larvae and Kulldorff spatial analysis pinpointed significant larval clusters at sites directly beneath forest fringes, which were called larval "hotspots." Remote sensing identified 43 "potential" hotspots. Sampling of these areas revealed an 85.7% positivity rate for A. darlingi larvae. Malaria was correlated with shorter distances to potential hotpots and settlers living within 400 m of potential hotspots had a 2.60 higher risk of malaria. Recently arrived settlers, usually located closer to the tip of the triangularly shaped deforestation imprints of side roads, may be more exposed to malaria due to their proximity to the forest fringe. As deforestation progresses, transmission decreases. However, forest remnants inside deforested areas conferred an increased risk of malaria. We propose a model for explaining frontier malaria in the Amazon: because of adaptation of A. darlingi to the forest fringe ecotone, humans are exposed to an increased transmission risk when in proximity to these areas, especially when small dams are created on naturally running water collections.
Dengue fever has become the most important vector-borne viral disease in Brazil. Human facilitated transport of desiccation-resistant eggs has led to its two most important vectors, Aedes aegypti and Ae. albopictus, becoming widespread. In this paper, we report seasonal and spatial variation in larval abundances of Ae. aegypti and Ae. albopictus across a small-scale transition zone between an urban area and an urban wooded/forested area within Rio de Janeiro, Brazil. We installed 400 ovitraps across 10 sites with different human population densities and vegetation coverage. Eggs and larvae were collected for three weeks during the wet and dry seasons of 2002 and 2003. Ae. albopictus was predominantly found in the forested areas of the study site whereas in the urbanized area Ae. aegypti was more abundant. Both species peaked during the wet season. This distribution pattern, which may reflect adult flight range, may favor the co-occurrence of larvae of these species in a small-scale urban/urban forest transition zone.
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.
Fish farming in the Amazon has been stimulated as a solution to increase economic development. However, poorly managed fish ponds have been sometimes associated with the presence of Anopheles spp. and consequently, with malaria transmission. In this study, we analyzed the spatial and temporal dynamics of malaria in the state of Acre (and more closely within a single county) to investigate the potential links between aquaculture and malaria transmission in this region. At the state level, we classified the 22 counties into three malaria endemicity patterns, based on the correlation between notification time series. Furthermore, the study period (2003–2013) was divided into two phases (epidemic and post-epidemic). Higher fish pond construction coincided both spatially and temporally with increased rate of malaria notification. Within one malaria endemic county, we investigated the relationship between the geolocation of malaria cases (2011–2012) and their distance to fish ponds. Entomological surveys carried out in these ponds provided measurements of anopheline abundance that were significantly associated with the abundance of malaria cases within 100 m of the ponds (P < 0.005; r = 0.39). These results taken together suggest that fish farming contributes to the maintenance of high transmission levels of malaria in this region.
Malaria control has been directed towards regional actions where more detailed knowledge of local determinants of transmission is of primary importance. This is a short report on range distribution and biting indices forThe most important local vector species have been determined to be An. darlingi Root and An. albitarsis sensu lato. As we have not taxonomically determined the species in the albitarsis complex ourselves, hereinafter the species will be simply referred as An. albitarsis. Nonetheless, previous studies determined the An. albitarsis population in Jardim das Copaíbas, our study area, as An. albitarsis species E (Póvoa et al. 2006). Studies using entomological inoculation rates and biting indices have implicated An. darlingi and An. albitarsis as the most important vectors in the area (Silva-Vasconcelos et al. 2002, Póvoa et al. 2006.In this communication we describe seasonal variations in the biting rate of two main local malaria vectors in Jardim das Copaíbas a riverside settlement in the Northern Amazon Basin during one year. An equation describing the distribution range of An. darlingi during the rainy season was also determined.The study area Jardim das Copaíbas is a rural settlement (02°45'28''N, 60°42' 18''W) by the Branco River 5 km south of Boa Vista, the capital of the state of Roraima (Fig. 1B). Jardim das Copaíbas can be characterized as a savanna/alluvial forest landscape area. This is because the settlement is located in a savanna in close contact (~ 100 m) to a dense alluvial rainforest that delineates the Branco River. The area has a long rainy season (April-November), a short dry season (DecemberMarch), in which the Branco River water levels increase (Póvoa et al. 2006, Fig. 2). During the rainy season, the alluvial forest becomes partly flooded. Average yearly rainfall is 1100-1400 mm/year and temperatures are permanently high (daily average 27.8ºC) with little yearlong variation. Relative humidity is also high (daily average 73.8%) and varies little over the year (Furley 1994).In . Rainfall data and river water levels were registered (Fig. 2).The 1n + 1 transformed numbers of mosquitoes captured during peak biting activity (the first 4 h after sunset) were used during the rainy season for deriving an exponential regression function for An. darlingi distribution range. Estimations of the percentages of the adult An. darlingi population that could reach over specified distances were given by the expression: y = 4.435 exp(x*-0.003) (p < 0.001, r = 0.98) where x is the distance from the larval habitat and y the percentage of the adult mosquitoes. Since An. albitarsis also has larval habitat dispersed in the open savanna fields, a distribution range function could not be derived from the data collected. It was not possible to determine all larval habitats for each species. The transect represents the closest distance a certain mosquito would have to fly to reach the capture stations.
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