Project description:Human adenoviruses (HAdV) are one of the most frequent causes of respiratory infections around the world, causing mild to severe disease. In Argentina, many studies focused on the association of HAdV respiratory infection with severe disease and fatal outcomes leading to the discovery in 1984 of a genomic variant 7h associated with high fatality. Although several molecular studies reported the presence of at least 4 HAdV species (B, C, D and E) in Argentina, few sequences were available in the databases. In this study, sequences from the hexon gene region were obtained from 141 patients as a first approach to assess the genetic diversity of HAdVs circulating in Buenos Aires, Argentina. Phylogenetic analysis of these sequences and others recovered from public databases confirmed the circulation of the four above-mentioned species represented by 11 genotypes, with predominance in species B and C and shifts in their proportion in the studied period (2000 to 2018). The variants detected in Argentina, for most of the genotypes, were similar to those already described in other countries. However, uncommon lineages belonging to genotypes C2, C5 and E4 were detected, which might indicate the circulation of local variants and will deserve further studies of whole-genome sequences.
Project description:Analysis of language geography is increasingly being used for studying spatial patterns of social dynamics. This trend is fueled by social media platforms such as Twitter which provide access to large amounts of natural language data combined with geolocation and user metadata enabling reconstruction of detailed spatial patterns of language use. Most studies are performed on large spatial scales associated with countries and regions, where language dynamics are often dominated by the effects of geographic and administrative borders. Extending to smaller, urban scales, however, allows visualization of spatial patterns of language use determined by social dynamics within the city, providing valuable information for a range of social topics from demographic studies to urban planning. So far, few studies have been made in this domain, due, in part, to the challenges in developing algorithms that accurately classify linguistic features. Here we extend urban-scale geographical analysis of language use beyond lexical meaning to include other sociolinguistic markers that identify language style, dialect and social groups. Some features, which have not been explored with social-media data on the urban scale, can be used to target a range of social phenomena. Our study focuses on Twitter use in Buenos Aires and our approach classifies tweets based on contrasting sets of tokens manually selected to target precise linguistic features. We perform statistical analyses of eleven categories of language use to quantify the presence of spatial patterns and the extent to which they are socially driven. We then perform the first comparative analysis assessing how the patterns and strength of social drivers vary with category. Finally, we derive plausible explanations for the patterns by comparing them with independently generated maps of geosocial context. Identifying these connections is a key aspect of the social-dynamics analysis which has so far received insufficient attention.
Project description:The largest outbreak of dengue in Buenos Aires, Argentina, occurred during 2016. Phylogenetic, phylodynamic, and phylogeographic analyses of 82 samples from dengue patients revealed co-circulation of 2 genotype V dengue virus lineages, suggesting that this virus has become endemic to the Buenos Aires metropolitan area.