Understanding the determinants of virus transmission is a fundamental step for effective design of screening and intervention strategies to control viral epidemics. Phylogenetic analysis can be a valid approach for the identification of transmission chains, and very-large data sets can be analysed through parallel computation. Here we propose and validate a new methodology for the partition of large-scale phylogenies and the inference of transmission clusters. This approach, on the basis of a depth-first search algorithm, conjugates the evaluation of node reliability, tree topology and patristic distance analysis. The method has been applied to identify transmission clusters of a phylogeny of 11,541 human immunodeficiency virus-1 subtype B pol gene sequences from a large Italian cohort. Molecular transmission chains were characterized by means of different clinical/demographic factors, such as the interaction between male homosexuals and male heterosexuals. Our method takes an advantage of a flexible notion of transmission cluster and can become a general framework to analyse other epidemics.
Recent developments include a better knowledge of the epidemiological, clinical, and laboratory aspects of sandfly infection, while the search for effective drugs and vaccines is still in progress.
Prevalence of TDR to nucleoside reverse transcriptase inhibitors seems to have declined in Italy over time. Increased prevalence of non-B subtypes partially justifies this phenomenon.
The role of Toscana (TOS) virus in producing encephalitis without meningitis is uncertain. We studied 2 cases of TOS virus encephalitis without meningitis by means of nested polymerase chain reaction assay and DNA sequencing. Findings confirm that TOS virus may directly cause encephalitis and suggest the usefulness of DNA sequencing in investigating relationships between TOS virus molecular patterns and the spectrum of neurological involvement.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.