A new epidemiological scenario involving the oral transmission of Chagas disease, mainly in the Amazon basin, requires innovative control measures. Geospatial analyses of the Trypanosoma cruzi transmission cycle in the wild mammals have been scarce. We applied interpolation and map algebra methods to evaluate mammalian fauna variables related to small wild mammals and the T. cruzi infection pattern in dogs to identify hotspot areas of transmission. We also evaluated the use of dogs as sentinels of epidemiological risk of Chagas disease. Dogs (n = 649) were examined by two parasitological and three distinct serological assays. kDNA amplification was performed in patent infections, although the infection was mainly sub-patent in dogs. The distribution of T. cruzi infection in dogs was not homogeneous, ranging from 11–89% in different localities. The interpolation method and map algebra were employed to test the associations between the lower richness in mammal species and the risk of exposure of dogs to T. cruzi infection. Geospatial analysis indicated that the reduction of the mammal fauna (richness and abundance) was associated with higher parasitemia in small wild mammals and higher exposure of dogs to infection. A Generalized Linear Model (GLM) demonstrated that species richness and positive hemocultures in wild mammals were associated with T. cruzi infection in dogs. Domestic canine infection rates differed significantly between areas with and without Chagas disease outbreaks (Chi-squared test). Geospatial analysis by interpolation and map algebra methods proved to be a powerful tool in the evaluation of areas of T. cruzi transmission. Dog infection was shown to not only be an efficient indicator of reduction of wild mammalian fauna richness but to also act as a signal for the presence of small wild mammals with high parasitemia. The lower richness of small mammal species is discussed as a risk factor for the re-emergence of Chagas disease.
The classical methodology of mapping works with discrete units and sharp boundaries does not consider gradient transition areas. Spatial analysis by the interpolation method, followed by map algebra, is able to model the spatial distribution of biological phenomena and their distribution and eventual association with other parameters or variables, with a focus on enhancing the decision power of responsible authorities. Acute Chagas Disease outbreaks are increasing in the Amazon Basin as result of oral transmission. This scenario requires a new approach to identify hotspot transmission areas and implement control measures. We applied a geospatial approach using interpolation and map algebra methods to evaluate mammalian fauna variables related to these outbreaks. We constructed maps with mammalian fauna variables including the infection rates by Trypanosoma cruzi, in dogs and small wild mammals. The results obtained by visual examination of the maps were validated by statistical analysis. We observed that high prevalence of T. cruzi infection in dogs and small wild mammals was associated with mammal lower richness. Monitoring of T. cruzi infection in dogs may be a valuable tool for detecting the fauna lower richness of small wild mammals and elucidating the transmission cycle of T. cruzi in the wild.