Marked increase in community-associated methicillin-resistant Staphylococcus aureus infections, Western Australia, 2004–2018

This study presents enhanced surveillance data from 2004 – 2018 for all community-associated methicillin-resistant Staphylococcus aureus (CA-MRSA) specimens collected in Western Australia (WA), and describes the changing epidemiology over this period. A total of 57,557 cases were reviewed. Annual incidence rates increased from 86.2 cases per 100,000 population to 245.6 per 100,000 population (IRR = 2.9, CI95 2.7 – 3.0). The proportion of isolates carrying Panton-Valentine leukocidin (PVL)-associated genes increased from 3.4% to 59.8% (χ2 test for trend 7021.9, p\u3c0.001). The emergence of PVL-positive, “Queensland CA-MRSA” (ST93- IV) and “WA 121” (ST5-IV) accounted for the majority of increases in CA-MRSA across the study period. It is unclear why some clones are more prolific in certain regions. In WA, CA-MRSA rates increase as indices of temperature and humidity increase after controlling for socioeconomic disadvantage. We suggest climatic conditions may contribute to transmission, along with other socio-behavioural factors. A better understanding of the ability for certain clones to form ecological niches and cause outbreaks is required

Maturity and Fertilization Effects on Leaf Blade Tissue Percentages of Contrasting Fescue Cultivars

Palenque Plus and Ceres Torpedo are tall fescue (Festuca arundinacea Schreb.) cultivars available to the animal production systems in the humid Pampean Region of Argentina. They differ in growth cycle and morphological characteristics. At vegetative stage, Torpedo leaves are fine and tender, which suggests that their percentages of slowly digestible and indigestible tissues (SDIT) should be low. In this study we 1) explored the effects of phenological stage and nitrogen fertilization on leaf blade tissue percentages of both cultivars, using an ordination multivariate technique, and 2) evaluated the effects of these factors on the percentage of SDIT. Our results indicate that the analyzed cultivars have different histological responses to fertilization, and maturity. In vegetative stage, Torpedo responds to the fertilization increasing the percentages of live and suberizated tissues, and in reproductive stage increasing the percentage of a dead tissue which cells could be lignified. Palenque responds to both factors, maturity and fertilization increasing the percentage of sclerenchyma, but these responses interact. These different behaviours suggest that the percentage of SDIT would not be a good predictor of the quality in these cultivars in different development stages and fertilization levels

Recurrence of Clostridium difficile infection in the Western Australian population

Clostridium difficile, the most common cause of hospital-associated diarrhoea in developed countries, presents major public health challenges. The high clinical and economic burden from C. difficile infection (CDI) relates to the high frequency of recurrent infections caused by either the same or different strains of C. difficile. An interval of 8 weeks after index infection is commonly used to classify recurrent CDI episodes. We assessed strains of C. difficile in a sample of patients with recurrent CDI in Western Australia from October 2011 to July 2017. The performance of different intervals between initial and subsequent episodes of CDI was investigated. Of 4612 patients with CDI, 1471 (32%) were identified with recurrence. PCR ribotyping data were available for initial and recurrent episodes for 551 patients. Relapse (recurrence with same ribotype (RT) as index episode) was found in 350 (64%) patients and reinfection (recurrence with new RT) in 201 (36%) patients. Our analysis indicates that 8- and 20-week intervals failed to adequately distinguish reinfection from relapse. In addition, living in a non-metropolitan area modified the effect of age on the risk of relapse. Where molecular epidemiological data are not available, we suggest that applying an 8-week interval to define recurrent CDI requires more consideration

Respiratory illness in a piggery associated with the first identified outbreak of swine influenza in Australia: Assessing the risk to human health and zoonotic potential

Australia was previously believed to be free of enzootic swine influenza viruses due strict quarantine practices and use of biosecure breeding facilities. The first proven Australian outbreak of swine influenza occurred in Western Australian in 2012, revealing an unrecognized zoonotic risk, and a potential future pandemic threat. A public health investigation was undertaken to determine whether zoonotic infections had occurred and to reduce the risk of further transmission between humans and swine. A program of monitoring, testing, treatment, and vaccination was commenced, and a serosurvey of workers was also undertaken. No acute infections with the swine influenza viruses were detected. Serosurvey results were difficult to interpret due to previous influenza infections and past and current vaccinations. However, several workers had elevated haemagglutination inhibition (HI) antibody levels to the swine influenza viruses that could not be attributed to vaccination or infection with contemporaneous seasonal influenza A viruses. However, we lacked a suitable control population, so this was inconclusive. The experience was valuable in developing better protocols for managing outbreaks at the human–animal interface. Strict adherence to biosecurity practices, and ongoing monitoring of swine and their human contacts is important to mitigate pandemic risk. Strain specific serological assays would greatly assist in identifying zoonotic transmission

An Improved Hazard Rate Twisting Approach for the Statistic of the Sum of Subexponential Variates

In this letter, we present an improved hazard rate twisting technique for the estimation of the probability that a sum of independent but not necessarily identically distributed subexponential Random Variables (RVs) exceeds a given threshold. Instead of twisting all the components in the summation, we propose to twist only the RVs which have the biggest impact on the right-tail of the sum distribution and keep the other RVs unchanged. A minmax approach is performed to determine the optimal twisting parameter which leads to an asymptotic optimality criterion. Moreover, we show through some selected simulation results that our proposed approach results in a variance reduction compared to the technique where all the components are twisted

Unified Importance Sampling Schemes for Efficient Simulation of Outage Capacity Over Generalized Fading Channels

The outage capacity (OC) is among the most important performance metrics of communication systems operating over fading channels. Of interest in the present paper is the evaluation of the OC at the output of the Equal Gain Combining (EGC) and the Maximum Ratio Combining (MRC) receivers. In this case, it can be seen that this problem turns out to be that of computing the Cumulative Distribution Function (CDF) for the sum of independent random variables. Since finding a closed-form expression for the CDF of the sum distribution is out of reach for a wide class of commonly used distributions, methods based on Monte Carlo (MC) simulations take pride of price. In order to allow for the estimation of the operating range of small outage probabilities, it is of paramount importance to develop fast and efficient estimation methods as naive MC simulations would require high computational complexity. In this line, we propose in this work two unified, yet efficient, hazard rate twisting Importance Sampling (IS) based approaches that efficiently estimate the OC of MRC or EGC diversity techniques over generalized independent fading channels. The first estimator is shown to possess the asymptotic optimality criterion and applies for arbitrary fading models, whereas the second one achieves the well-desired bounded relative error property for the majority of the well-known fading variates. Moreover, the second estimator is shown to achieve the asymptotic optimality property under the particular Log-normal environment. Some selected simulation results are finally provided in order to illustrate the substantial computational gain achieved by the proposed IS schemes over naive MC simulations

On the Efficient Simulation of Outage Probability in a Log-Normal Fading Environment

The outage probability (OP) of the signal-to interference-plus-noise ratio (SINR) is an important metric that is used to evaluate the performance of wireless systems. One difficulty toward assessing the OP is that, in realistic scenarios, closed-form expressions cannot be derived. This is, for instance, the case of the Log-normal environment, in which evaluating the OP of the SINR amounts to computing the probability that a sum of correlated Log-normal variates exceeds a given threshold. Since such a probability does not admit a closed form expression, it has thus far been evaluated by several approximation techniques, the accuracies of which are not guaranteed in the region of small OPs. For these regions, simulation techniques based on variance reduction algorithms are a good alternative, being quick and highly accurate for estimating rare event probabilities. This constitutes the major motivation behind this paper. More specifically, we propose a generalized hybrid importance sampling scheme, based on a combination of a mean shifting and a covariance matrix scaling, to evaluate the OP of the SINR in a Log-normal environment. We further our analysis by providing a detailed study of two particular cases. Finally, the performance of these techniques is performed both theoretically and through various simulation results

An Accurate Sample Rejection Estimator of the Outage Probability With Equal Gain Combining

We evaluate the outage probability (OP) for L-branch equal gain combining (EGC) receivers operating over fading channels, i.e., equivalently the cumulative distribution function (CDF) of the sum of the L channel envelopes. In general, closed form expressions of OP values are out of reach. The use of Monte Carlo (MC) simulations is not a good alternative as it requires a large number of samples for small values of OP. In this paper, we use the concept of importance sampling (IS), being known to yield accurate estimates using fewer simulation runs. Our proposed IS scheme is based on sample rejection where the IS density is the truncation of the underlying density over the L dimensional sphere. It assumes the knowledge of the CDF of the sum of the L channel gains in closed-form. Such an assumption is not restrictive since it holds for various challenging fading models. We apply our approach to the case of independent Rayleigh, correlated Rayleigh, and independent and identically distributed Rice fading models. Next, we extend our approach to the interesting scenario of generalised selection combining receivers combined with EGC under the independent Rayleigh environment. For each case, we prove the desired bounded relative error property. Finally, we validate these theoretical results through some selected experiments

On the generalization of the hazard rate twisting-based simulation approach

Estimating the probability that a sum of random variables (RVs) exceeds a given threshold is a well-known challenging problem. A naive Monte Carlo simulation is the standard technique for the estimation of this type of probability. However, this approach is computationally expensive, especially when dealing with rare events. An alternative approach is represented by the use of variance reduction techniques, known for their efficiency in requiring less computations for achieving the same accuracy requirement. Most of these methods have thus far been proposed to deal with specific settings under which the RVs belong to particular classes of distributions. In this paper, we propose a generalization of the well-known hazard rate twisting Importance Sampling-based approach that presents the advantage of being logarithmic efficient for arbitrary sums of RVs. The wide scope of applicability of the proposed method is mainly due to our particular way of selecting the twisting parameter. It is worth observing that this interesting feature is rarely satisfied by variance reduction algorithms whose performances were only proven under some restrictive assumptions. It comes along with a good efficiency, illustrated by some selected simulation results comparing the performance of the proposed method with some existing techniques

Theory and methodology for estimation and control of errors due to modeling, approximation, and uncertainty

The reliability of computer predictions of physical events depends on several factors: the mathematical model of the event, the numerical approximation of the model, and the random nature of data characterizing the model. This paper addresses the mathematical theories, algorithms, and results aimed at estimating and controlling modeling error, numerical approximation error, and error due to randomness in material coefficients and loads. A posteriori error estimates are derived and applications to problems in solid mechanics are presented. (C) 2004 Elsevier B.V. All rights reserved