Trends and predictors of transmitted drug resistance (TDR) and clusters with TDR in a local Belgian HIV-1 epidemic

We aimed to study epidemic trends and predictors for transmitted drug resistance (TDR) in our region, its clinical impact and its association with transmission clusters. We included 778 patients from the AIDS Reference Center in Leuven (Belgium) diagnosed from 1998 to 2012. Resistance testing was performed using population-based sequencing and TDR was estimated using the WHO-2009 surveillance list. Phylogenetic analysis was performed using maximum likelihood and Bayesian techniques. The cohort was predominantly Belgian (58.4%), men who have sex with men (MSM) (42.8%), and chronically infected (86.5%). The overall TDR prevalence was 9.6% (95% confidence interval (CI): 7.7-11.9), 6.5% (CI: 5.0-8.5) for nucleoside reverse transcriptase inhibitors (NRTI), 2.2% (CI: 1.4-3.5) for non-NRTI (NNRTI), and 2.2% (CI: 1.4-3.5) for protease inhibitors. A significant parabolic trend of NNRTI-TDR was found (p = 0.019). Factors significantly associated with TDR in univariate analysis were male gender, Belgian origin, MSM, recent infection, transmission clusters and subtype B, while multivariate and Bayesian network analysis singled out subtype B as the most predictive factor of TDR. Subtype B was related with transmission clusters with TDR that included 42.6% of the TDR patients. Thanks to resistance testing, 83% of the patients with TDR who started therapy had undetectable viral load whereas half of the patients would likely have received a suboptimal therapy without this test. In conclusion, TDR remained stable and a NNRTI up-and-down trend was observed. While the presence of clusters with TDR is worrying, we could not identify an independent, non-sequence based predictor for TDR or transmission clusters with TDR that could help with guidelines or public health measures

HIV-1 Infection in Cyprus, the Eastern Mediterranean European Frontier: A Densely Sampled Transmission Dynamics Analysis from 1986 to 2012

Since HIV-1 treatment is increasingly considered an effective preventionstrategy, it is important to study local HIV-1 epidemics to formulate tailored preventionpolicies. The prevalence of HIV-1 in Cyprus was historically low until 2005. To investigatethe shift in epidemiological trends, we studied the transmission dynamics of HIV-1 in Cyprususing a densely sampled Cypriot HIV-1 transmission cohort that included 85 percent ofHIV-1-infected individuals linked to clinical care between 1986 and 2012 based on detailedclinical, epidemiological, behavioral and HIV-1 genetic information. Subtyping andtransmission cluster reconstruction were performed using maximum likelihood and Bayesianmethods, and the transmission chain network was linked to the clinical, epidemiological andbehavioral data. The results reveal that for the main HIV-1 subtype A1 and B sub-epidemics,young and drug-naïve HIV-1-infected individuals in Cyprus are driving the dynamics of thelocal HIV-1 epidemic. The results of this study provide a better understanding of thedynamics of the HIV-1 infection in Cyprus, which may impact the development of preventionstrategies. Furthermore, this methodology for analyzing densely sampled transmissiondynamics is applicable to other geographic regions to implement effective HIV-1 preventionstrategies in local settings

Increase in transmitted resistance to non-nucleoside reverse transcriptase inhibitors among newly diagnosed HIV-1 infections in Europe

Background: One out of ten newly diagnosed patients in Europe was infected with a virus carrying a drug resistant mutation. We analysed the patterns over time for transmitted drug resistance mutations (TDRM) using data from the European Spread program.Methods: Clinical, epidemiological and virological data from 4317 patients newly diagnosed with HIV-1 infection between 2002 and 2007 were analysed. Patients were enrolled using a pre-defined sampling strategy.Results: The overall prevalence of TDRM in this period was 8.9% (95% CI: 8.1-9.8). Interestingly, significant changes over time in TDRM caused by the different drug classes were found. Whereas nucleoside resistance mutations remained constant at 5%, a significant decline in protease inhibitors resistance mutations was observed, from 3.9% in 2002 to 1.6% in 2007 (p = 0.001). In contrast, resistance to non-nucleoside reverse transcriptase inhibitors (NNRTIs) doubled from 2.0% in 2002 to 4.1% in 2007 (p = 0.004) with 58% of viral strains carrying a K103N mutation. Phylogenetic analysis showed that these temporal changes could not be explained by large clusters of TDRM.Conclusion: During the years 2002 to 2007 transmitted resistance to NNRTI has doubled to 4% in Europe. The frequent use of NNRTI in first-line regimens and the clinical impact of NNRTI mutations warrants continued monitoring

The global spread of HIV-1 subtype B epidemic

Human immunodeficiency virus type 1 (HIV-1) was discovered in the early 1980s when the virus had already established a pandemic. For at least three decades the epidemic in the Western World has been dominated by subtype B infections, as part of a sub-epidemic that traveled from Africa through Haiti to United States. However, the pattern of the subsequent spread still remains poorly understood. Here we analyze a large dataset of globally representative HIV-1 subtype B strains to map their spread around the world over the last 50. years and describe significant spread patterns. We show that subtype B travelled from North America to Western Europe in different occasions, while Central/Eastern Europe remained isolated for the most part of the early epidemic. Looking with more detail in European countries we see that the United Kingdom, France and Switzerland exchanged viral isolates with non-European countries than with European ones. The observed pattern is likely to mirror geopolitical landmarks in the post-World War II era, namely the rise and the fall of the Iron Curtain and the European colonialism. In conclusion, HIV-1 spread through specific migration routes which are consistent with geopolitical factors that affected human activities during the last 50. years, such as migration, tourism and trade. Our findings support the argument that epidemic control policies should be global and incorporate political and socioeconomic factors. . .