Diversity of Prophage DNA Regions of Streptococcus agalactiae Clonal Lineages from Adults and Neonates with Invasive Infectious Disease

The phylogenetic position and prophage DNA content of the genomes of 142 S. agalactiae (group-B streptococcus, GBS) isolates responsible for bacteremia and meningitis in adults and neonates were studied and compared. The distribution of the invasive isolates between the various serotypes, sequence types (STs) and clonal complexes (CCs) differed significantly between adult and neonatal isolates. Use of the neighbor-net algorithm with the PHI test revealed evidence for recombination in the population studied (PHI, P = 2.01×10−6), and the recombination-mutation ratio (R/M) was 6∶7. Nevertheless, the estimated R/M ratio differed between CCs. Analysis of the prophage DNA regions of the genomes of the isolates assigned 90% of the isolates to five major prophage DNA groups: A to E. The mean number of prophage DNA fragments amplified per isolate varied from 2.6 for the isolates of prophage DNA group E to 4.0 for the isolates of prophage DNA group C. The isolates from adults and neonates with invasive diseases were distributed differently between the various prophage DNA groups (P<0.00001). Group C prophage DNA fragments were found in 52% of adult invasive isolates, whereas 74% of neonatal invasive isolates had prophage DNA fragments of groups A and B. Differences in prophage DNA content were also found between serotypes, STs and CCs (P<0.00001). All the ST-1 and CC1 isolates, mostly of serotype V, belonged to the prophage DNA group C, whereas 84% of the ST-17 and CC17 isolates, all of serotype III, belonged to prophage DNA groups A and B. These data indicate that the transduction mechanisms, i.e., gene transfer from one bacterium to another by a bacteriophage, underlying genetic recombination in S. agalactiae species, are specific to each intraspecies lineage and population of strains responsible for invasive diseases in adults and neonates

Reconstructing the 2003/2004 H3N2 influenza epidemic in Switzerland with a spatially explicit, individual-based model

ABSTRACT: BACKGROUND: Simulation models of influenza spread play an important role for pandemic preparedness. However, as the world has not faced a severe pandemic for decades, except the rather mild H1N1 one in 2009, pandemic influenza models are inherently hypothetical and validation is, thus, difficult. We aim at reconstructing a recent seasonal influenza epidemic that occurred in Switzerland and deem this to be a promising validation strategy for models of influenza spread. METHODS: We present a spatially explicit, individual-based simulation model of influenza spread. The simulation model bases upon (i) simulated human travel data, (ii) data on human contact patterns and (iii) empirical knowledge on the epidemiology of influenza. For model validation we compare the simulation outcomes with empirical knowledge regarding (i) the shape of the epidemic curve, overall infection rate and reproduction number, (ii) age-dependent infection rates and time of infection, (iii) spatial patterns. RESULTS: The simulation model is capable of reproducing the shape of the 2003/2004 H3N2 epidemic curve of Switzerland and generates an overall infection rate (14.9 percent) and reproduction numbers (between 1.2 and 1.3), which are realistic for seasonal influenza epidemics. Age and spatial patterns observed in empirical data are also reflected by the model: Highest infection rates are in children between 5 and 14 and the disease spreads along the main transport axes from west to east. CONCLUSIONS: We show that finding evidence for the validity of simulation models of influenza spread by challenging them with seasonal influenza outbreak data is possible and promising. Simulation models for pandemic spread gain more credibility if they are able to reproduce seasonal influenza outbreaks. For more robust modelling of seasonal influenza, serological data complementing sentinel information would be beneficia

Abstracts from the 8th International Conference on cGMP Generators, Effectors and Therapeutic Implications

This work was supported by a restricted research grant of Bayer AG

FoPraNet-BW: an infrastructure for clinical studies in practice-based research networks in the German health system

General practice-based research networks have become an integral tool to gain medical knowledge from primary care in many countries. For this purpose, a scalable IT-infrastructure is presented considering the limiting peculiarities in the German health system and enabling GPs to participate in clinical studies based on their patient population. The infrastructure consists of a central study management server and local clients for each practice. It adopts to the currently limited digital connectivity of GP practices, data protection regulations for clinical data and the needs of the medical staff to manage a clinical study. The infrastructure is in production at the four university hospitals in the state of Baden-Württemberg. Until now three clinical studies with over 70 GPs and 350 Participants are successfully conducted or have been finished. Further clinical studies are in the planning stages