Lymphedema after breast or gynecological cancer : use and effectiveness of mainstream and complementary therapies

Objectives: The purpose of this study was to describe the use, as well as perceived effectiveness, of mainstream and complementary and alternative medicine (CAM) therapies in the treatment of lymphedema following breast or gynecological cancer. Further, the study assessed the relationship between the characteristics of lymphedema (including type, severity, stability, and duration), and the use of CAM and/or mainstream treatment. Methods: This was a cross-sectional study using a convenience sample of women with lymphedema following breast and gynecological cancers. A self-administered questionnaire was sent to 247 potentially eligible women. Of those returned (50%), 23 were ineligible and 6 were excluded due to level of missing data. Results: In the previous 12 months, the majority of women (90%) had used mainstream treatments to treat their lymphedema, with massage being the most commonly used (86%). One (1) in 2 women had used CAM to treat their lymphedema, and 98% of those using CAM were also using mainstream treatments. Over 27 types of CAM were reported, with use of a chi machine, vitamin E supplements, yoga, and meditation being the most commonly reported forms. The perceived effectiveness ratings (1–7 with 7 = completely effective) of mainstream(mean – standard deviation (SD): 5.3 – 1.5) and CAM therapies (mean – SD: 5.2 + 1.6) were considered high. Conclusions: These results demonstrate that mainstream and CAM treatment use is common, varied, and considered to be effective among women with lymphedema following breast or gynecological cancer. Furthermore, it highlights the immediate need for larger prospective studies assessing the inter-relationship between the use of mainstream and CAM therapies for treatment success.

Arterial travel time estimation : revisiting the classical procedure

Travel time is an important network performance measure and it quantifies congestion in a manner easily understood by all transport users. In urban networks, travel time estimation is challenging due to number of reasons such as, fluctuations in traffic flow due to traffic signals, significant flow to/from mid link sinks/sources, etc. The classical analytical procedure utilizes cumulative plots at upstream and downstream locations for estimating travel time between the two locations. In this paper, we discuss about the issues and challenges with classical analytical procedure such as its vulnerability to non conservation of flow between the two locations. The complexity with respect to exit movement specific travel time is discussed. Recently, we have developed a methodology utilising classical procedure to estimate average travel time and its statistic on urban links (Bhaskar, Chung et al. 2010). Where, detector, signal and probe vehicle data is fused. In this paper we extend the methodology for route travel time estimation and test its performance using simulation. The originality is defining cumulative plots for each exit turning movement utilising historical database which is self updated after each estimation. The performance is also compared with a method solely based on probe (Probe-only). The performance of the proposed methodology has been found insensitive to different route flow, with average accuracy of more than 94% given a probe per estimation interval which is more than 5% increment in accuracy with respect to Probe-only method.

Screening, isolation, and decolonisation strategies in the control of meticillin resistant Staphylococcus aureus in intensive care units : cost effectiveness evaluation

Objective: To assess the cost-effectiveness of screening, isolation and decolonisation strategies in the control of methicillin-resistant Staphylococcus aureus (MRSA) in intensive care units (ICUs). Design: Economic evaluation. Setting: England and Wales. Population: ICU patients. Main outcome measures: Infections, deaths, costs, quality adjusted life years (QALYs), incremental cost-effectiveness ratios for alternative strategies, net monetary benefits (NMBs). Results: All strategies using isolation but not decolonisation improved health outcomes but increased costs. When MRSA prevalence on admission to the ICU was 5% and the willingness to pay per QALY gained was between £20,000 and £30,000, the best such strategy was to isolate only those patients at high risk of carrying MRSA (either pre-emptively or following identification by admission and weekly MRSA screening using chromogenic agar). Universal admission and weekly screening using polymerase chain reaction (PCR)-based MRSA detection coupled with isolation was unlikely to be cost-effective unless prevalence was high (10% colonised with MRSA on admission to the ICU). All decolonisation strategies improved health outcomes and reduced costs. While universal decolonisation (regardless of MRSA status) was the most cost-effective in the short-term, strategies using screening to target MRSA carriers may be preferred due to reduced risk of selecting for resistance. Amongst such targeted strategies, universal admission and weekly PCR screening coupled with decolonisation with nasal mupirocin was the most cost-effective. This finding was robust to ICU size, MRSA admission prevalence, the proportion of patients classified as high-risk, and the precise value of willingness to pay for health benefits. Conclusions: MRSA control strategies that use decolonisation are likely to be cost-saving in an ICU setting provided resistance is lacking, and combining universal PCR-based screening with decolonisation is likely to represent good value for money if untargeted decolonisation is considered unacceptable. In ICUs where decolonisation is not implemented there is insufficient evidence to support universal MRSA screening outside high prevalence settings.

Intensive Case Management: A Critical Re-Appraisal of the Scientific Evidence for Effectiveness

Intensive Case Management (ICM) is widely claimed to be an evidence-based and cost effective program for people with high levels of disability as a result of mental illness. However, the findings of recent randomized controlled trials comparing ICM with ‘usual services’ suggest that both clinical and cost effectiveness of ICM may be weakening. Possible reasons for this, including fidelity of implementation, researcher allegiance effects and changes in the wider service environment within which ICM is provided, are considered. The implications for service delivery and research are discussed.

A multi-resolution image alignment technique based on direct methods for pose estimation of aerial vehicles

In this paper, we seek to expand the use of direct methods in real-time applications by proposing a vision-based strategy for pose estimation of aerial vehicles. The vast majority of approaches make use of features to estimate motion. Conversely, the strategy we propose is based on a MR (Multi- Resolution) implementation of an image registration technique (Inverse Compositional Image Alignment ICIA) using direct methods. An on-board camera in a downwards-looking configuration, and the assumption of planar scenes, are the bases of the algorithm. The motion between frames (rotation and translation) is recovered by decomposing the frame-to-frame homography obtained by the ICIA algorithm applied to a patch that covers around the 80% of the image. When the visual estimation is required (e.g. GPS drop-out), this motion is integrated with the previous known estimation of the vehicles’ state, obtained from the on-board sensors (GPS/IMU), and the subsequent estimations are based only on the vision-based motion estimations. The proposed strategy is tested with real flight data in representative stages of a flight: cruise, landing, and take-off, being two of those stages considered critical: take-off and landing. The performance of the pose estimation strategy is analyzed by comparing it with the GPS/IMU estimations. Results show correlation between the visual estimation obtained with the MR-ICIA and the GPS/IMU data, that demonstrate that the visual estimation can be used to provide a good approximation of the vehicle’s state when it is required (e.g. GPS drop-outs). In terms of performance, the proposed strategy is able to maintain an estimation of the vehicle’s state for more than one minute, at real-time frame rates based, only on visual information.

But does it work? Effectiveness of scientific visualisations in high school chemistry and physics instruction.

Scientific visualisations such as computer-based animations and simulations are increasingly a feature of high school science instruction. Visualisations are adopted enthusiastically by teachers and embraced by students, and there is good evidence that they are popular and well received. There is limited evidence, however, of how effective they are in enabling students to learn key scientific concepts. This paper reports the results of a quantitative study conducted in Australian physics and chemistry classrooms. In general there was no statistically significant difference between teaching with and without visualisations, however there were intriguing differences around student sex and academic ability.

Measuring the effectiveness of computer-based scientific visualisations for conceptual development in Australian chemistry classrooms

Visual modes of representation have always been very important in science and science education. Interactive computer-based animations and simulations offer new visual resources for chemistry education. Many studies have shown that students enjoy learning with visualisations but few have explored how learning outcomes compare when teaching with or without visualisations. This study employs a quasi-experimental crossover research design and quantitative methods to measure the educational effectiveness - defined as level of conceptual development on the part of students - of using computer-based scientific visualisations versus teaching without visualisations in teaching chemistry. In addition to finding that teaching with visualisations offered outcomes that were not significantly different from teaching without visualisations, the study also explored differences in outcomes for male and female students, students with different learning styles (visual, aural, kinesthetic) and students of differing levels of academic ability.

One approach to finding evidence for the effectiveness of scientific visualisations in high school physics and chemistry education

Enormous amounts of money and energy are being devoted to the development, use and organisation of computer-based scientific visualisations (e.g. animations and simulations) in science education. It seems plausible that visualisations that enable students to gain visual access to scientific phenomena that are too large, too small or occur too quickly or too slowly to be seen by the naked eye, or to scientific concepts and models, would yield enhanced conceptual learning. When the literature is searched, however, it quickly becomes apparent that there is a dearth of quantitative evidence for the effectiveness of scientific visualisations in enhancing students’ learning of science concepts. This paper outlines an Australian project that is using innovative research methodology to gather evidence on this question in physics and chemistry classrooms.

A model of organizational innovation implementation effectiveness in small to medium firms

The present study aims to validate the current best-practice model of implementation effectiveness in small and mid-size businesses. Data from 135 organizations largely confirm the original model across various types of innovation. In addition, we extended this work by highlighting the importance of human resources in implementation effectiveness and the consequences of innovation effectiveness on future adoption attitudes. We found that the availability of skilled employees was positively related to implementation effectiveness. Furthermore, organizations that perceived a high level of benefits from implemented innovations were likely to have a positive attitude towards future innovation adoption. The implications of our improvements to the original model of implementation effectiveness are discussed.

LMP estimation considering the uncertainty of wind power

One of the impediments to large-scale use of wind generation within power system is its variable and uncertain real-time availability. Due to the low marginal cost of wind power, its output will change the merit order of power markets and influence the Locational Marginal Price (LMP). For the large scale of wind power, LMP calculation can't ignore the essential variable and uncertain nature of wind power. This paper proposes an algorithm to estimate LMP. The estimation result of conventional Monte Carlo simulation is taken as benchmark to examine accuracy. Case study is conducted on a simplified SE Australian power system, and the simulation results show the feasibility of proposed method.

The effectiveness of a short-term group music therapy intervention for young parents and their children

The quality of early life experiences are known to influence a child’s capacities for emotional, social, cognitive and physical competence throughout their life (Peterson, 1996; Zubrick et al., 2008). These early life experiences are directly affected by parenting and family environments. A lack of positive parenting has significant implications both for children, and the broader communities in which they live (Davies & Cummings, 1994; Dryfoos, 1990; Sanders, 1995). Young parents are known to be at risk of experiencing adverse circumstances that affect their ability to provide positive parenting to their children (Milan et al., 2004; Trad, 1995). There is a need to provide parenting support programs to young parents that offer opportunities for them to come together, support each other and learn ways to provide for their children’s developmental needs in a friendly, engaging and non-judgemental environment. This research project examines the effectiveness of a 10 week group music therapy program Sing & Grow as an early parenting intervention for 535 young parents. Sing & Grow is a national early parenting intervention program funded by the Australian Government and delivered by Playgroup Queensland. It is designed and delivered by Registered Music Therapists for families at risk of marginalisation with children aged from birth to three years. The aim of the program is to improve parenting skills and parent-child interactions, and increase social support networks through participation in a group that is strengths-based and structured in a way that lends itself to modelling, peer learning and facilitated learning. During the 10 weeks parents have opportunities to learn practical, hands-on ways to interact and play with their children that are conducive to positive parent-child relationships and ongoing child development. A range of interactive, nurturing, stimulating and developmental music activities provide the framework for parents to interact and play with their children. This research uses data collected through the Sing & Grow National Evaluation Study to examine outcomes for all participants aged 25 years and younger, who attended programs during the Sing & Grow pilot study and main study from mid-2005 to the end of 2007. The research examines the change from pre to post in self-reported parent behaviours, parent mental health and parent social support, and therapist observed parent-child interactions. A range of statistical analyses are used to address each Research Objective for the young parent population, and for subgroups within this population. Research Objective 1 explored the patterns of attendance in the Sing & Grow program for young parents, and for subgroups within this population. Results showed that levels of attendance were lower than expected and influenced by Indigenous status and source of family income. Patterns of attendance showed a decline over time and incomplete data rates were high which may indicate high dropout rates. Research Objective 2 explored perceived satisfaction, benefits and social support links made. Satisfaction levels with the program and staff were very high. Indigenous status was associated with lower levels of reported satisfaction with both the program and staff. Perceived benefits from participation in the program were very high. Employment status was associated with perceived benefits: parents who were not employed were more likely than employed parents to report that their understanding of child development had increased as a result of participation in the program. Social support connections were reported for participants with other professionals, services and parents. In particular, families were more likely to link up with playgroup staff and services. Those parents who attended six or more sessions were significantly more likely to attend a playgroup than those who attended five sessions or less. Social support connections were related to source of family income, level of education, Indigenous status and language background. Research Objective 3 investigated pre to post change on self-report parenting skills and parent mental health. Results indicated that participation in the Sing & Grow program was associated with improvements in parent mental health. No improvements were found for self-reported parenting skills. Research Objective 4 investigated pre to post change in therapist observation measures of parent-child interactions. Results indicated that participation in the Sing & Grow program was associated with large and significant improvements in parent sensitivity to, engagement with and acceptance of the child. There were significant interactions across time (pre to post) for the parent characteristics of Indigenous status, family income and level of education. Research Objective 5 explored the relationship between the number of sessions attended and extent of change on self-report outcomes and therapist observed outcomes, respectively. For each, an overall change score was devised to ascertain those parents who had made any positive changes over time. Results showed that there was no significant relationship between high attendance and positive change in either the self-report or therapist observed behavioural measures. A risk index was also constructed to test for a relationship between the risk status of the parent. Parents with the highest risk status were significantly more likely to attend six or more sessions than other parents, but risk status was not associated with any differences in parent reported outcomes or therapist observations. The results of this research study indicate that Sing & Grow is effective in improving outcomes for young parents’ mental health, parent-child interactions and social support connections. High attendance by families in the highest category for risk factors may indicate that the program is effective at engaging and retaining parents who are most at-risk and therefore traditionally hard to reach. Very high levels of satisfaction and perceived benefits support this. Further research is required to help confirm the promising evidence from the current study that a short term group music therapy program can support young parents and improve their parenting outcomes. In particular, this needs to address the more disappointing outcomes of the current research study to improve attendance and engagement of all young parents in the program and especially the needs of young Indigenous parents.

Performance control of distributed generation using digital estimation of signal parameters

The Queensland University of Technology (QUT) allows the presentation of a thesis for the Degree of Doctor of Philosophy in the format of published or submitted papers, where such papers have been published, accepted or submitted during the period of candidature. This thesis is composed of seven published/submitted papers, of which one has been published, three accepted for publication and the other three are under review. This project is financially supported by an Australian Research Council (ARC) Discovery Grant with the aim of proposing strategies for the performance control of Distributed Generation (DG) system with digital estimation of power system signal parameters. Distributed Generation (DG) has been recently introduced as a new concept for the generation of power and the enhancement of conventionally produced electricity. Global warming issue calls for renewable energy resources in electricity production. Distributed generation based on solar energy (photovoltaic and solar thermal), wind, biomass, mini-hydro along with use of fuel cell and micro turbine will gain substantial momentum in the near future. Technically, DG can be a viable solution for the issue of the integration of renewable or non-conventional energy resources. Basically, DG sources can be connected to local power system through power electronic devices, i.e. inverters or ac-ac converters. The interconnection of DG systems to power system as a compensator or a power source with high quality performance is the main aim of this study. Source and load unbalance, load non-linearity, interharmonic distortion, supply voltage distortion, distortion at the point of common coupling in weak source cases, source current power factor, and synchronism of generated currents or voltages are the issues of concern. The interconnection of DG sources shall be carried out by using power electronics switching devices that inject high frequency components rather than the desired current. Also, noise and harmonic distortions can impact the performance of the control strategies. To be able to mitigate the negative effect of high frequency and harmonic as well as noise distortion to achieve satisfactory performance of DG systems, new methods of signal parameter estimation have been proposed in this thesis. These methods are based on processing the digital samples of power system signals. Thus, proposing advanced techniques for the digital estimation of signal parameters and methods for the generation of DG reference currents using the estimates provided is the targeted scope of this thesis. An introduction to this research – including a description of the research problem, the literature review and an account of the research progress linking the research papers – is presented in Chapter 1. One of the main parameters of a power system signal is its frequency. Phasor Measurement (PM) technique is one of the renowned and advanced techniques used for the estimation of power system frequency. Chapter 2 focuses on an in-depth analysis conducted on the PM technique to reveal its strengths and drawbacks. The analysis will be followed by a new technique proposed to enhance the speed of the PM technique while the input signal is free of even-order harmonics. The other techniques proposed in this thesis as the novel ones will be compared with the PM technique comprehensively studied in Chapter 2. An algorithm based on the concept of Kalman filtering is proposed in Chapter 3. The algorithm is intended to estimate signal parameters like amplitude, frequency and phase angle in the online mode. The Kalman filter is modified to operate on the output signal of a Finite Impulse Response (FIR) filter designed by a plain summation. The frequency estimation unit is independent from the Kalman filter and uses the samples refined by the FIR filter. The frequency estimated is given to the Kalman filter to be used in building the transition matrices. The initial settings for the modified Kalman filter are obtained through a trial and error exercise. Another algorithm again based on the concept of Kalman filtering is proposed in Chapter 4 for the estimation of signal parameters. The Kalman filter is also modified to operate on the output signal of the same FIR filter explained above. Nevertheless, the frequency estimation unit, unlike the one proposed in Chapter 3, is not segregated and it interacts with the Kalman filter. The frequency estimated is given to the Kalman filter and other parameters such as the amplitudes and phase angles estimated by the Kalman filter is taken to the frequency estimation unit. Chapter 5 proposes another algorithm based on the concept of Kalman filtering. This time, the state parameters are obtained through matrix arrangements where the noise level is reduced on the sample vector. The purified state vector is used to obtain a new measurement vector for a basic Kalman filter applied. The Kalman filter used has similar structure to a basic Kalman filter except the initial settings are computed through an extensive math-work with regards to the matrix arrangement utilized. Chapter 6 proposes another algorithm based on the concept of Kalman filtering similar to that of Chapter 3. However, this time the initial settings required for the better performance of the modified Kalman filter are calculated instead of being guessed by trial and error exercises. The simulations results for the parameters of signal estimated are enhanced due to the correct settings applied. Moreover, an enhanced Least Error Square (LES) technique is proposed to take on the estimation when a critical transient is detected in the input signal. In fact, some large, sudden changes in the parameters of the signal at these critical transients are not very well tracked by Kalman filtering. However, the proposed LES technique is found to be much faster in tracking these changes. Therefore, an appropriate combination of the LES and modified Kalman filtering is proposed in Chapter 6. Also, this time the ability of the proposed algorithm is verified on the real data obtained from a prototype test object. Chapter 7 proposes the other algorithm based on the concept of Kalman filtering similar to those of Chapter 3 and 6. However, this time an optimal digital filter is designed instead of the simple summation FIR filter. New initial settings for the modified Kalman filter are calculated based on the coefficients of the digital filter applied. Also, the ability of the proposed algorithm is verified on the real data obtained from a prototype test object. Chapter 8 uses the estimation algorithm proposed in Chapter 7 for the interconnection scheme of a DG to power network. Robust estimates of the signal amplitudes and phase angles obtained by the estimation approach are used in the reference generation of the compensation scheme. Several simulation tests provided in this chapter show that the proposed scheme can very well handle the source and load unbalance, load non-linearity, interharmonic distortion, supply voltage distortion, and synchronism of generated currents or voltages. The purposed compensation scheme also prevents distortion in voltage at the point of common coupling in weak source cases, balances the source currents, and makes the supply side power factor a desired value.

Estimation and control for an open-source quadcopter

This paper describes modelling, estimation and control of the horizontal translational motion of an open-source and cost effective quadcopter — the MikroKopter. We determine the dynamics of its roll and pitch attitude controller, system latencies, and the units associated with the values exchanged with the vehicle over its serial port. Using this we create a horizontal-plane velocity estimator that uses data from the built-in inertial sensors and an onboard laser scanner, and implement translational control using a nested control loop architecture. We present experimental results for the model and estimator, as well as closed-loop positioning.

Using Bayesian methods for the estimation of uncertainty in complex statistical models

The research objectives of this thesis were to contribute to Bayesian statistical methodology by contributing to risk assessment statistical methodology, and to spatial and spatio-temporal methodology, by modelling error structures using complex hierarchical models. Specifically, I hoped to consider two applied areas, and use these applications as a springboard for developing new statistical methods as well as undertaking analyses which might give answers to particular applied questions. Thus, this thesis considers a series of models, firstly in the context of risk assessments for recycled water, and secondly in the context of water usage by crops. The research objective was to model error structures using hierarchical models in two problems, namely risk assessment analyses for wastewater, and secondly, in a four dimensional dataset, assessing differences between cropping systems over time and over three spatial dimensions. The aim was to use the simplicity and insight afforded by Bayesian networks to develop appropriate models for risk scenarios, and again to use Bayesian hierarchical models to explore the necessarily complex modelling of four dimensional agricultural data. The specific objectives of the research were to develop a method for the calculation of credible intervals for the point estimates of Bayesian networks; to develop a model structure to incorporate all the experimental uncertainty associated with various constants thereby allowing the calculation of more credible credible intervals for a risk assessment; to model a single day’s data from the agricultural dataset which satisfactorily captured the complexities of the data; to build a model for several days’ data, in order to consider how the full data might be modelled; and finally to build a model for the full four dimensional dataset and to consider the timevarying nature of the contrast of interest, having satisfactorily accounted for possible spatial and temporal autocorrelations. This work forms five papers, two of which have been published, with two submitted, and the final paper still in draft. The first two objectives were met by recasting the risk assessments as directed, acyclic graphs (DAGs). In the first case, we elicited uncertainty for the conditional probabilities needed by the Bayesian net, incorporated these into a corresponding DAG, and used Markov chain Monte Carlo (MCMC) to find credible intervals, for all the scenarios and outcomes of interest. In the second case, we incorporated the experimental data underlying the risk assessment constants into the DAG, and also treated some of that data as needing to be modelled as an ‘errors-invariables’ problem [Fuller, 1987]. This illustrated a simple method for the incorporation of experimental error into risk assessments. In considering one day of the three-dimensional agricultural data, it became clear that geostatistical models or conditional autoregressive (CAR) models over the three dimensions were not the best way to approach the data. Instead CAR models are used with neighbours only in the same depth layer. This gave flexibility to the model, allowing both the spatially structured and non-structured variances to differ at all depths. We call this model the CAR layered model. Given the experimental design, the fixed part of the model could have been modelled as a set of means by treatment and by depth, but doing so allows little insight into how the treatment effects vary with depth. Hence, a number of essentially non-parametric approaches were taken to see the effects of depth on treatment, with the model of choice incorporating an errors-in-variables approach for depth in addition to a non-parametric smooth. The statistical contribution here was the introduction of the CAR layered model, the applied contribution the analysis of moisture over depth and estimation of the contrast of interest together with its credible intervals. These models were fitted using WinBUGS [Lunn et al., 2000]. The work in the fifth paper deals with the fact that with large datasets, the use of WinBUGS becomes more problematic because of its highly correlated term by term updating. In this work, we introduce a Gibbs sampler with block updating for the CAR layered model. The Gibbs sampler was implemented by Chris Strickland using pyMCMC [Strickland, 2010]. This framework is then used to consider five days data, and we show that moisture in the soil for all the various treatments reaches levels particular to each treatment at a depth of 200 cm and thereafter stays constant, albeit with increasing variances with depth. In an analysis across three spatial dimensions and across time, there are many interactions of time and the spatial dimensions to be considered. Hence, we chose to use a daily model and to repeat the analysis at all time points, effectively creating an interaction model of time by the daily model. Such an approach allows great flexibility. However, this approach does not allow insight into the way in which the parameter of interest varies over time. Hence, a two-stage approach was also used, with estimates from the first-stage being analysed as a set of time series. We see this spatio-temporal interaction model as being a useful approach to data measured across three spatial dimensions and time, since it does not assume additivity of the random spatial or temporal effects.

Comparing the cost-effectiveness of MRSA control strategies between ICU and non-ICU settings

Introduction / objectives Many strategies are used to control MRSA in hospitals. Only a few have been assessed in clinical trials and it is not obvious how findings should be generalised between settings. Uncertainty remains about which strategies represent the most appropriate use of scarce resources. We assess the cost-effectiveness of alternative MRSA screening and infection control strategies in England and Wales and discuss international relevance. Methods Models of MRSA transmission in ICUs and general medical (GM) wards were developed and used to evaluate different screening methods combined with decolonisation or isolation. Strategies were compared in terms of costs and health benefits (quality adjusted life years, QALYs). Different prevalences, proportions of high risk patients and ward sizes were investigated, and probabilistic sensitivity analyses (PSA) conducted. Results Decolonisation strategies were cost-saving in ICUs at a 5% admission prevalence, with admission and weekly PCR screening the most cost-effective (£3,929/QALY). In ICUs, screening and isolation reduced infection rates by ~10%. With admission prevalence ≤5%, targeting screening and isolation to high risk patients was optimal. In GM wards decolonisation and isolation strategies, though able to reduce MRSA infection rates up to ~50%, were not cost-effective. Conclusion The largest reductions in MRSA infection were achieved by screening and decolonisation strategies, and were cost-effective in ICU settings. In comparison, there is limited potential for screening and control strategies to be cost-effective in GM wards due to lower infection and mortality rates.