Here, we make use of mathematical models to consider the case of partner notification Galunisertib concentration for sexually transmitted infection, however these models are sufficiently simple to allow more general conclusions to be drawn. We show that, when contact network structure is considered in addition to contact tracing, standard “”mass action” models are generally

inadequate. To consider the impact of mutual contacts (specifically clustering) we develop an improvement to existing pairwise network models, which we use to demonstrate that ceteris paribus, clustering improves the efficacy of contact

tracing for a large region of parameter space. This result is sometimes reversed, however, for the case of highly effective contact tracing. We also develop stochastic simulations for comparison, using simple re-wiring methods that allow the generation of appropriate comparator networks. In this way we contribute to the general theory of network-based interventions against infectious disease.”
“BACKGROUND: Considerable criticism has lately been raised by the media selleck chemicals regarding the quality of Swiss medical expertises. The present investigation was therefore undertaken to assess the professional quality of Swiss medical expertises. The study was part of a market analysis of medical expertises (MGS study).

METHODS: A sample of 97 anonymised expertises randomly chosen from a total of 3165, collected in the MGS study over a period of 3 months, were evaluated by an international board of medical experts and Selleckchem Luminespib reviewers, using a stepwise developed questionnaire.

Each expertise was independently evaluated by two experts. Data were then tested for plausibility (obvious errors and misunderstandings). The main outcome was the overall quality rating of the expertise that was graded from 1 (very poor) to 6 (excellent) in analogy to the Swiss school grading system. For analysis and interpretation the grades were divided into sufficient (grades >= 4) and insufficient (grades <4).

RESULTS: Overall 19.6% (95% confidence interval: 13.1%; 28.3%) of the expertises were rated to be of insufficient quality. The quality was inversely related to the number of involved medical disciplines, the time relapsed since injury and positively related to the difficulty of the expertise.