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The Middle Paranapanema region in the state of São Paulo, Brazil, is an area with high diversity for Biomphalaria species, with municipalities historically marked by cases of schistosomiasis transmission. The objectives of the study were to evaluate the current distribuition and predict the future distribution of habitats of Biomphalaria species at a high spatial resolution along 114 freshwater sites in the Middle Paranapanema watershed. The modelling encompassed 55 municipalities of the Middle Paranapanema region, which were analyzed through the maximum entropy algorithm. All geographic coordinates of the Biomphalaria species collected from 2015-2018 and environmental data were obtained through WorldClim, HydroSHEDS, TOPODATA and Secretaria do Meio Ambiente for the 1970-2017 period. For the 2041-2060 period we used the HadGEM2-ES climate model. Due to climate change, MaxEnt showed that there was a high probability for the maintenance of B. glabrata habitats near Ourinhos and Assis, an expansion of scattered spots, and a 50% probability that the species will spread throughout new suitable areas. The results showed that the geographical range of B. straminea will most likely expand in the future along the Middle Paranapanema hydrographic basin, especially in the municipalities near Ourinhos. For B. glabrata and B. straminea, the geographic expansion was related to the predicted increase in the annual temperature range. The habitats suitable for B. tenagophila and B. peregrina seemed to slightly expand around the west border of the Middle Paranapanema region. Biomphalaria occidentalis may have a small reduction in its distribution due to climate change. The variables that contributed the most to the future modelling for these three species were precipitation and temperature. Identifying the sites with intermediate hosts for schistosomiasis may guide public health measures to avoid or reduce future transmissions in this region., (Copyright © 2020. Published by Elsevier B.V.)

We addressed the potential associations among the temporal and spatial distribution of larval habitats of Aedes (Stegomyia) aegypti, the presence of urban heat islands and socioeconomic factors. Data on larval habitats were collected in Santa Bárbara d'Oeste, São Paulo, Brazil, from 2004 to 2006, and spatial and temporal variations were analysed using a wavelet-based approach. We quantified urban heat islands by calculating surface temperatures using the results of wavelet analyses and grey level transformation from Thematic Mapper images (Landsat 5). Ae. aegypti larval habitats were geo-referenced corresponding to the wavelet analyses to test the potential association between geographical distribution of habitats and surface temperature. In an inhomogeneous spatial point process, we estimated the frequency of occurrence of larval habitats in relation to temperature. The São Paulo State Social Vulnerability Index in the municipality of Santa Barbára d'Oeste was used to test the potential association between presence of larval habitats and social vulnerability. We found abundant Ae. aegypti larval habitats in areas of higher surface temperature and social vulnerability and fewer larval habitats in areas with lower surface temperature and social vulnerability.

Because of the high adaptive capacity of mosquitoes, studies that focus on transitional environments become very important, such as those in rural areas, which are considered as bridges between wild diseases and human populations of urban areas. In this study, a survey of the existing species of mosquitoes was performed in an Atlantic Forest area of the city of Santa Bárbara d'Oeste, São Paulo state, Brazil, using traps for immatures and analyzing the frequency and distribution of these insects over the sampling months. Five mosquito species were found: Aedes albopictus (the most frequent species), Aedes aegypti, Aedes fluviatilis, Culex quinquefasciatus, and Toxorhynchites theobaldi. The 4,524 eggs collected in ovitraps showed the presence of the tribe Aedini. Aedes aegypti and Ae. albopictus were identified after larval hatching in the laboratory, with different spatial distributions: the first of which coincides with the area of greatest diversity calculated using the Simpson index, while the second does not. The association of ecological analysis of spatial diversity with simple methods of data collection enables the identification of possible epidemiological risk situations and is a strategy that may be implemented to monitor ecological processes resulting from the interaction among different species of mosquitoes., (© 2013 The Society for Vector Ecology.)