The importance of good data, analysis and interpretation for showing the economics of reducing healthcare-associated infection

To the Editor—In a recent review article in Infection Control and Hospital Epidemiology, Umscheid et al1 summarized published data on incidence rates of catheter-associated bloodstream infection (CABSI), catheter-associated urinary tract infection (CAUTI), surgical site infection (SSI), and ventilator- associated pneumonia (VAP); estimated how many cases are preventable; and calculated the savings in hospital costs and lives that would result from preventing all preventable cases. Providing these estimates to policy makers, political leaders, and health officials helps to galvanize their support for infection prevention programs. Our concern is that important limitations of the published studies on which Umscheid and colleagues built their findings are incompletely addressed in this review. More attention needs to be drawn to the techniques applied to generate these estimates...

Systematic Review Protocol : "Are community-based interventions effective in identifying and responding to emerging zoonotic infectious diseases?"

Review question/objective The objective of this review is to identify the effectiveness of surveillance systems and community-based interventions in identifying and responding to emerging and re-emerging zoonotic infections in Southeast Asia (SE Asia). More specifically the research questions are: 1. What is the effectiveness of community-based surveillance interventions designed to identify emerging zoonotic infectious diseases? 2. What is the effectiveness of non-pharmaceutical community-based interventions designed to prevent transmission of emerging zoonotic infectious diseases? 3. How do factors related to the emergence and management of emerging zoonotic infectious diseases impact the effectiveness of interventions designed to identify and respond to them?

In for the long haul : family business succession at HaulageCo

This is a case about family business succession. Because many successions fail, the 'problem of succession' is a key issue in the family business field (see Aronoff 1998; Bird eta/. 2002; Dyer & Sanchez 1998; Sharma 2004; Zalu·a & Sharma 2004). Indeed, from the non-family business literature, we know one third of relay successions - like this case where there is an identified successor - will fail, with the prospective CEO leaving before succeeding the incumbent CEO (Cmmella & Shen 2001). Research on next generation family business members is limited. Successor ath·ibutes (Chrisman, Chua & Sharma 1998; Sharma & Rao 2000), as well as various characteristics such as socialisation (Garcia-Aivmez, L6pez-Sintas & Gonzalvo 2002) a11d gender (Haberman & Danes 2007; Vera & Dean 2005) have all been considered to play a role. So too have successor intentions (Stavrou & Swiercz 1998), motivation (Le Breton-Miller, Miller & Steier 2004), commitment (Sharma & Irving 2005) and transformation from follower to leadership (Cater & Justis 2009). In this case, by outlining the socialisation of the successors, explanations of their motivations for joining a11d their current employment we can begin to see some of the underlying mechanisms at work motivating the next generation to join and stay in the family business.

Robotic explosive charging in mining and construction applications

Describes the development and testing of a robotic system for charging blast holes in underground mining. The automation system supports four main tactical functions: detection of blast holes; teleoperated arm pose control; automatic arm pose control; and human-in-the-loop visual servoing. We present the system architecture, and analyse the major components, Hole detection is crucial for automating the process, and we discuss theoretical and practical aspects in detail. The sensors used are laser range finders and cameras installed in the end effector. For automatic insertion, we consider image processing techniques to support visual servoing the tool to the hole. We also discuss issues surrounding the control of heavy-duty mining manipulators, in particular, friction, stiction, and actuator saturation.

Interpreting and comparing risks in the presence of competing events

Competing events are common in medical research. Ignoring them in the statistical analysis can easily lead to flawed results and conclusions. This article uses a real dataset and a simple simulation to show how standard analysis fails and how such data should be analysed

Heat-related morbidity in Brisbane, Australia : spatial variation and area-level predictors

Background: Extreme heat is a leading weather-related cause of illness and death in many locations across the globe, including subtropical Australia. The possibility of increasingly frequent and severe heat waves warrants continued efforts to reduce this health burden, which could be accomplished by targeting intervention measures toward the most vulnerable communities. Objectives: We sought to quantify spatial variability in heat-related morbidity in Brisbane, Australia, to highlight regions of the city with the greatest risk. We also aimed to find area-level social and environmental determinants of high risk within Brisbane. Methods: We used a series of hierarchical Bayesian models to examine city-wide and intracity associations between temperature and morbidity using a 2007–2011 time series of geographically referenced hospital admissions data. The models accounted for long-term time trends, seasonality, and day of week and holiday effects. Results: On average, a 10°C increase in daily maximum temperature during the summer was associated with a 7.2% increase in hospital admissions (95% CI: 4.7, 9.8%) on the following day. Positive statistically significant relationships between admissions and temperature were found for 16 of the city’s 158 areas; negative relationships were found for 5 areas. High-risk areas were associated with a lack of high income earners and higher population density. Conclusions: Geographically targeted public health strategies for extreme heat may be effective in Brisbane, because morbidity risk was found to be spatially variable. Emergency responders, health officials, and city planners could focus on short- and long-term intervention measures that reach communities in the city with lower incomes and higher population densities, including reduction of urban heat island effects.

Co-occurring anger in young people with Asperger's syndrome

Objectives: The co-occurrence of anger in young people with Asperger's syndrome (AS) has received little attention despite aggression, agitation, and tantrums frequently being identified as issues of concern in this population. The present study investigated the occurrence of anger in young people with AS and explores its relationship with anxiety and depression. Method: Sixty-two young people (12-23 years old) diagnosed with AS were assessed using the Beck Anger Inventory for Youth, Spence Children's Anxiety Scale, and Reynolds Adolescent Depression Scale. Results: Among young people with AS who participated in this study, 41% of participants reported clinically significant levels of anger (17%), anxiety (25.8%) and/or depression (11.5%). Anger, anxiety, and depression were positively correlated with each other. Depression, however, was the only significant predictor of anger. Conclusion: Anger is commonly experienced by young people with AS and is correlated with anxiety and depression. These findings suggest that the emotional and behavioral presentation of anger could serve as a cue for further assessment, and facilitate earlier identification and intervention for anger, as well as other mental health problems.

The influence of families on early adolescent school connectedness : evidence that this association varies with adolescent involvement in peer drinking networks

School connectedness is central to the long term well-being of adolescents, and high quality parent-child relationships facilitate school connectedness. This study examined the extent to which family relationship quality is associated with the school connectedness of pre- and early teenagers, and how this association varies with adolescent involvement in peer drinking networks. The sample consisted of 7,372 10-14 year olds recruited from 231 schools in 30 Australian communities. Participants completed the Communities that Care youth survey. A multi-level model of school connectedness was used, with a random term for school-level variation. Key independent variables included family relationship quality, peer drinking networks, and school grade. Control variables included child gender, sensation seeking, depression, child alcohol use, parent education, and language spoken at home. For grade 6 students, the association of family relationship quality and school connectedness was lower when peer drinking networks were present, and this effect was nonsignificant for older (grade 8) students. Post hoc analyses indicated that the effect for family relationship quality on school connectedness was nonsignificant when adolescents in grade 6 reported that the majority of friends consumed alcohol. The results point to the importance of familyschool partnerships in early intervention and prevention.

The topography of multiple drug use among adolescent Australians : findings from the National Drug Strategy Household Survey

Introduction and aims: Despite evidence that many Australian adolescents have considerable experience with various drug types, little is known about the extent to which adolescents use multiple substances. The aim of this study was to examine the degree of clustering of drug types within individuals, and the extent to which demographic and psychosocial predictors are related to cluster membership. Design and method: A sample of 1402 adolescents aged 12-17. years were extracted from the Australian 2007 National Drug Strategy Household Survey. Extracted data included lifetime use of 10 substances, gender, psychological distress, physical health, perceived peer substance use, socioeconomic disadvantage, and regionality. Latent class analysis was used to determine clusters, and multinomial logistic regression employed to examine predictors of cluster membership. Result: There were 3 latent classes. The great majority (79.6%) of adolescents used alcohol only, 18.3% were limited range multidrug users (encompassing alcohol, tobacco, and marijuana), and 2% were extended range multidrug users. Perceived peer drug use and psychological distress predicted limited and extended multiple drug use. Psychological distress was a more significant predictor of extended multidrug use compared to limited multidrug use. Discussion and conclusion: In the Australian school-based prevention setting, a very strong focus on alcohol use and the linkages between alcohol, tobacco and marijuana are warranted. Psychological distress may be an important target for screening and early intervention for adolescents who use multiple drugs.

Proactive safety assessment in roadwork zones : a synthesis of surrogate measures of safety

Work zone safety studies have traditionally relied on historical crash records—an approach which is reactive in nature as it requires crashes to accumulate first before taking any preventive actions. However, detailed and accurate data on work zone crashes are often not available, as is the case for Australian road work zones. The lack of reliable safety records and the reactive nature of the crash-based safety analysis approach motivated this research to seek alternative and proactive measures of safety. Various surrogate measures of safety have been developed in the traffic safety literature including time to collision, time to accident, gap time, post encroachment time, required deceleration rate, proportion of stopping distances, lateral distance to departure, and time to departure. These measures express how close road-user(s) are from a potential crash by analysing their movement trajectories. A review of this fast-growing literature is presented in this paper from the viewpoint of applying the measures to untangle work zone safety issues. The review revealed that the use of the surrogate measures is very limited for analysing work zone safety, although numerous studies have used these measures for analysing safety in other parts of the road network, such as intersections and motorway ramps. There exist great opportunities for adopting this proactive safety assessment approach to transform work zone safety for both roadworkers and motorists.

Reforming the procurement of construction and financing of Australian infrastructure : advancing capacity, competition and investment

Funded by an Australian Research Council (ARC) Linkage grant over four years (2009–13), the Major Infrastructure Procurement project sought to find more effective and efficient ways of procuring and delivering the nation’s social and economic infrastructure by investigating constraints relating to construction capacity, competition, and finance in new public sector major infrastructure.1 The research team comprised researchers in construction economics and finance from Queensland University of Technology (QUT), Griffith University (GU), The University of Hong Kong (UHK), and The University of Newcastle (UoN). Project partners included state government departments and agencies responsible for infrastructure procurement and delivery from all Australian mainland states, and private sector companies and peak bodies in the infrastructure sector (see “Introduction” for complete list). There are a number of major outcomes from this research project. The first of these is a scientifically developed decisionmaking model for procurement of infrastructure that deploys a novel and state-of-the-art integration of dominant microeconomic theory (including theories developed by two Nobel Prize winners). The model has been established through empirical testing and substantial experiential evidence as a valid and reliable guide to configuring procurement of new major and mega infrastructure projects in pursuance of superior Valuefor- Money (VfM). The model specifically addresses issues of project size, bundling of contracts, and exchange relationships. In so doing, the model determines the suitability of adopting a Public-Private Partnership (PPP) mode.

A national satellite-based land-use regression model for air pollution exposure assessment in Australia

Land-use regression (LUR) is a technique that can improve the accuracy of air pollution exposure assessment in epidemiological studies. Most LUR models are developed for single cities, which places limitations on their applicability to other locations. We sought to develop a model to predict nitrogen dioxide (NO2) concentrations with national coverage of Australia by using satellite observations of tropospheric NO2 columns combined with other predictor variables. We used a generalised estimating equation (GEE) model to predict annual and monthly average ambient NO2 concentrations measured by a national monitoring network from 2006 through 2011. The best annual model explained 81% of spatial variation in NO2 (absolute RMS error=1.4 ppb), while the best monthly model explained 76% (absolute RMS error=1.9 ppb). We applied our models to predict NO2 concentrations at the ~350,000 census mesh blocks across the country (a mesh block is the smallest spatial unit in the Australian census). National population-weighted average concentrations ranged from 7.3 ppb (2006) to 6.3 ppb (2011). We found that a simple approach using tropospheric NO2 column data yielded models with slightly better predictive ability than those produced using a more involved approach that required simulation of surface-to-column ratios. The models were capable of capturing within-urban variability in NO2, and offer the ability to estimate ambient NO2 concentrations at monthly and annual time scales across Australia from 2006–2011. We are making our model predictions freely available for research.