First-Order Macroscopic Traffic Models

Macroscopic traffic models describe the traffic behaviour at a high level of aggregation, i.e. the traffic dynamics is expressed through aggregate variables, such as traffic density, mean speed and flow. Macroscopic models rely on the analogy between the flow of vehicles and the flow of fluids or gases and are based on a limited number of equations that are relatively easy to handle. This chapter is devoted to describe a very relevant class of macroscopic models, i.e. first-order traffic flow models, which capture the dynamics of only one aggregate variable, namely, the traffic density. A very important first-order macroscopic model is the Lighthill\u2013Whitham\u2013Richards model, developed in the 50s, but still of interest nowadays both for theoretical analysis and practical applications. It is a continuous model, which describes the dynamics of the macroscopic variables through partial differential equations. The most famous discretised version of the Lighthill\u2013Whitham\u2013Richards model is the so-called Cell Transmission Model, developed in the 90s and very widespread in the communities of mathematicians and traffic engineers

HCV NS3 sequencing as a reliable and clinically useful tool for the assessment of genotype and resistance mutations for clinical samples with different HCV-RNA levels

Objectives: This study aims to evaluate the reliability and clinical utility of NS3 sequencing in hepatitis C virus (HCV) 1-infected patients who were candidates to start a PI-containing regimen. Methods: NS3 protease sequencing was performed by in-house-developed HCV-1 subtype-specific protocols. Phylogenetic analysis was used to test sequencing reliability and concordance with previous genotype/subtype assignment by commercial genotyping assays. Results: Five hundred and sixty-seven HCV plasma samples with quantifiable HCV-RNA from 326 HCV-infected patients were collected between 2011 and 2014. Overall, the success rate of NS3 sequencing was 88.9%. The success rate between the two subtype protocols (HCV-1a/HCV-1b) was similarly high for samples with HCV-RNA > 3 log IU/mL (>92% success rate), while it was slightly lower for HCV-1a samples with HCV-RNA 64 3 log IU/mL compared with HCV-1b samples. Phylogenetic analysis confirmed the genotype/subtype given by commercial genotyping assays in 92.9% (303/326) of cases analysed. In the remaining 23 cases (7.1%), 1 was HCV-1g (previously defined as subtype 1a), 1 was HCV-4d (previously defined as genotype 1b) and 1 was HCV-1b (previously defined as genotype 2a/2c). In the other cases, NS3 sequencing precisely resolved the either previous undetermined/discordant subtype 1 or double genotype/subtype assignment by commercial genotyping assays. Resistance-associated variants (RAVs) to PI were detected in 31.0% of samples. This prevalence changed according to PI experience (17.1% in PI-naive patients versus 79.2% in boceprevir/telaprevir/simeprevir-failing patients). Among 96 patients with available virological outcome following boceprevir/telaprevir treatment, a trend of association between baseline NS3 RAVs and virological failure was observed (particularly for HCV-1a-infected patients: 3/21 failing patients versus 0/22 achieving sustained virological response; P = 0.11). Conclusions: HCV-NS3 sequencing provides reliable results and at the same time gives two clinically relevant pieces of information: A correct subtype/genotype assignment and the detection of variants that may interfere with the efficacy of PI