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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) The Amazon biome is under severe threat due to increasing deforestation rates and loss of biodiversity and ecosystem services while sustaining a high burden of neglected tropical diseases. Approximately two thirds of this biome are located within Brazilian territory. There, socio-economic and environmental landscape transformations are linked to the regional agrarian economy dynamics, which has developed into six techno-productive trajectories (TTs). These TTs are the product of the historical interaction between Peasant and Farmer and Rancher practices, technologies and rationalities. This article investigates the distribution of the dominant Brazilian Amazon TTs and their association with environmental degradation and vulnerability to neglected tropical diseases. The goal is to provide a framework for the joint debate of the local economic, environmental and health dimensions. We calculated the dominant TT for each municipality in 2017. Peasant trajectories (TT1, TT2, and TT3) are dominant in ca. fifty percent of the Amazon territory, mostly concentrated in areas covered by continuous forest where malaria is an important morbidity and mortality cause. Cattle raising trajectories are associated with higher deforestation rates. Meanwhile, Farmer and Rancher economies are becoming dominant trajectories, comprising large scale cattle and grain production. These trajectories are associated with rapid biodiversity loss and a high prevalence of neglected tropical diseases, such as leishmaniasis, Aedes-borne diseases and Chagas disease. Overall, these results defy simplistic views that the dominant development trajectory for the Amazon will optimize economic, health and environmental indicators. This approach lays the groundwork for a more integrated narrative consistent with the economic history of the Brazilian Amazon 442357/2019-2

Additional file 2. The estimated malaria case probability based on typical person-hour-origin-destination matrix and the estimated effect of each locality to the probability of observing a malaria case. Points represent the median and vertical lines the 95% CI over 1000 samples of the posterior distribution.

Population dynamic models requires the evaluation of the best scale of analysis. This work analyses three spatial scales in the context of the mosquito Aedes aegypti, main vector of dengue fever. One scale is the neighborhood, the others scales are the census tract and the lot. A geographical database was developed including point maps with trap locations, number of eggs collected per trap per week, polygons of census tracts, census data, among others. For simulation purposes, a layer of regular cells (10 x 10 meters) was created to store the model’s inputs and outputs. A population dynamic model with temperature as input variable was parameterized and ?tted to the neighborhood and census tract data. For the lot level, an allocation procedure was developed as the spatial resolution was higher than the data resolution. This procedure couples the population dynamic model with a kernel density map. Results indicate that at the neighborhood level, the population model captured well the overall pattern with lower mosquito densityduring the cold season and larger during the warm season. However, in the ?first warm season, two peaks did not ?ot well, suggesting the importance of investigating the role of other variables in the dynamics of Aedes aegypti. At the census tract level, we found no evidence of spatial clustering. At the lot level, the allocation model represented well the overall summer to winter variation in hotspot intensity. The cost of vector surveillance is high and the procedures proposed here can be used to design optimized control strategies and activities.