Investigation of a Staphylococcus aureus sequence type 72 food poisoning outbreak associated with food-handler contamination in Italy

On August 2019 a staphylococcal food poisoning outbreak occurred in an elderly home in Piedmont, Italy. The epidemiological investigation performed among the per- sons that consumed the meal identified chicken salad as the most likely source of the outbreak. Staphylococcus aureus was isolated from a total of seven samples, namely one vomit sample from a guest of the nursing home, two food samples (chicken salad with and without mayonnaise) and nasal swabs collected from a total of four persons working in the kitchen of the nursing home. The maximum likelihood tree obtained using single nucleotide polymorphisms analysis revealed that the isolates from the aforementioned samples clustered together. Multilocus sequence typing revealed that they belonged to Sequence Type 72. Fourier transform infrared spectroscopy (FTIR) was used in parallel to single nucleotide polymorphisms and whole genome sequencing for the determination of the degree of relatedness of the isolates. The results of the FTIR showed the same clustering obtained with single nucleotide poly- morphisms and whole genome sequencing and revealed the source of infection. This study underlines the importance of both laboratory evidence and epidemiological data for outbreak investigation and further confirms that FTIR is a suitable support for the short-term epidemiological investigation on source attribution in case of a S. aureus infection

Delays in IP routers, a Markov model

Delays in routers are an important component of end-to-end delay and therefore have a significant impact on quality of service. While the other component, the propagation time, is easy to predict as the distance divided by the speed of light inside the link, the queueing delays of packets inside routers depend on the current, usually dynamically changing congestion and on the stochastic features of the flows. We use a Markov model taking into account the distribution of the size of packets and self-similarity of incoming flows to investigate their impact on the queueing delays and their dynamics

Experimental comparison of some scheduling disciplines fed by self-similar traffic

Self-similar traffic models have permitted a more realistic description of the network devices behavior. However, the derivation of analytical results turns out to be a very demanding task, also in the single-server case. For the work-conserving switching architectures the characterization of the quality of service (QoS) parameters is even more complicated due to the correlation among the queues, induced by the scheduling policies. In this paper we present a detailed study, based on simulations of some paradigmatic scheduling disciplines, performed with an aim to furnish some useful tools for the design of high-speed network devices