Capacity building : just rhetoric, or a way forward in addressing health inequality?

Issue addressed: It is time to move beyond defining the problem of health inequality to taking action. The response required is complex and calls for system wide action. It is in this context that a discussion of increasing the capacity of the health system to respond to health inequality is both timely and essential. Methods: This paper looks at a capacity building framework that has been developed by the New South Wales Health Department and provides an example of a number of projects that have applied capacity building strategies. Conclusion: Addressing health inequality presents a significant challenge to health promotion practitioners. Emerging capacity building theory provides direction for strategies to build the capacity of a health system to address equity. It proposes a set of practical actions using the five focus areas of organisational development, workforce development, resource allocation, partnerships and leadership. So what?: A capacity building approach by itself will not provide the mandate and framework for the action that needs to be taken to address health inequality, but it helps to ensure that once potential solutions are identified the health system has the capacity to respond.

Over-winter lipid depletion and mortality of age-0 rainbow trout (Oncorhynchus mykiss)

In this study we identify the size-dependent risk of winter starvation mortality as a strong selective pressure on age-0 rainbow trout (Oncorhynchus mykiss) that could promote the risk-taking behaviour and allocation of energy to lipids previously observed in young trout cohorts. Age-0 trout subjected to simulated winter starvation conditions gradually depleted lipid reserves to a critical minimum lipid content below which death occurred. Small fish with lower lipid content exhausted lipid reserves earlier, and experienced high mortality rates sooner, than larger fish with greater lipid content. Consequently, winter starvation endurance was dependent upon size-dependent lipid reserves and winter duration. To validate the laboratory findings in the field, we stocked several size classes of hatchery-raised trout with known lipid content at the start of winter into two experimental lakes, and estimated survival and lipid depletion at winter's end. Larger age-0 trout had greater initial lipid reserves than smaller trout. Individuals depleted most of their lipid reserves over the winter, and experienced mortality that ranged from just under 60% for the largest individuals to just over 90% of the smallest individuals. Many survivors had lipid contents near, but none were below, the minimum lipid content determined in the laboratory.

Differences in primary health care delivery to Australia's Indigenous population : a template for use in economic evaluations

Background Health economics is increasingly used to inform resource allocation decision-making, however, there is comparatively little evidence relevant to minority groups. In part, this is due to lack of cost and effectiveness data specific to these groups upon which economic evaluations can be based. Consequently, resource allocation decisions often rely on mainstream evidence which may not be representative, resulting in inequitable funding decisions. This paper describes a method to overcome this deficiency for Australia’s Indigenous population. A template has been developed which can adapt mainstream health intervention data to the Indigenous setting.

Methods The ‘Indigenous Health Service Delivery Template’ has been constructed using mixed methods, which include literature review, stakeholder discussions and key informant interviews. The template quantifies the differences in intervention delivery between best practice primary health care for the Indigenous population via Aboriginal Community Controlled Health Services (ACCHSs), and mainstream general practitioner (GP) practices. Differences in costs and outcomes have been identified, measured and valued. This template can then be used to adapt mainstream health intervention data to allow its economic evaluation as if delivered from an ACCHS.

Results The template indicates that more resources are required in the delivery of health interventions via ACCHSs, due to their comprehensive nature. As a result, the costs of such interventions are greater, however this is accompanied by greater benefits due to improved health service access. In the example case of the polypill intervention, 58% more costs were involved in delivery via ACCHSs, with 50% more benefits. Cost-effectiveness ratios were also altered accordingly.

Conclusions The Indigenous Health Service Delivery Template reveals significant differences in the way health interventions are delivered from ACCHSs compared to mainstream GP practices. It is important that these differences are included in the conduct of economic evaluations to ensure results are relevant to Indigenous Australians. Similar techniques would be generalisable to other disadvantaged minority populations. This will allow resource allocation decision-makers access to economic evidence that more accurately represents the needs and context of disadvantaged groups, which is particularly important if addressing health inequities is a stated goal.

GLOA : a new job scheduling algorithm for grid computing

The purpose of grid computing is to produce a virtual supercomputer by using free resources available through widespread networks such as the Internet. This resource distribution, changes in resource availability, and an unreliable communication infrastructure pose a major challenge for efficient resource allocation. Because of the geographical spread of resources and their distributed management, grid scheduling is considered to be a NP-complete problem. It has been shown that evolutionary algorithms offer good performance for grid scheduling. This article uses a new evaluation (distributed) algorithm inspired by the effect of leaders in social groups, the group leaders' optimization algorithm (GLOA), to solve the problem of scheduling independent tasks in a grid computing system. Simulation results comparing GLOA with several other evaluation algorithms show that GLOA produces shorter makespans.

An efficient scheduling method for grid systems based on a hierarchical stochastic petri net

This paper addresses the problem of resource scheduling in a grid computing environment. One of the main goals of grid computing is to share system resources among geographically dispersed users, and schedule resource requests in an efficient manner. Grid computing resources are distributed, heterogeneous, dynamic, and autonomous, which makes resource scheduling a complex problem. This paper proposes a new approach to resource scheduling in grid computing environments, the hierarchical stochastic Petri net (HSPN). The HSPN optimizes grid resource sharing, by categorizing resource requests in three layers, where each layer has special functions for receiving subtasks from, and delivering data to, the layer above or below. We compare the HSPN performance with the Min-min and Max-min resource scheduling algorithms. Our results show that the HSPN performs better than Max-min, but slightly underperforms Min-min.

Sustainable planning and design of large-scale metropolitan development projects

Actors in the built environment are increasingly considering environmental issues alongside functional and economic aspects of development projects. However, to date in Australia and internationally, there have been few practical examples of integrated applications of sustainability principles in the built environment across all lifecycle phases. In response to this gap, this paper proposes a conceptual framework based on the principal that early intervention is the most cost-effective and efficient means of implementing effective strategies for sustainability. A strategic environmental assessment (SEA) approach is forwarded as an umbrella analytical framework, assembled from analytical methods which are strategically 'tiered' to inform stages of the project decision-making process. Practically applied and timed accordingly, the framework can allow assessments to be targeted towards appropriate decision making levels and enable better decision-making and more efficient resource allocation for major infrastructure development projects.

Developing an analytical framework to assess the uncertainty and flexibility mismatches across the supply chain

Purpose: The purpose of this paper is to discuss how decisions regarding organisational flexibility can be improved through targeted resource allocation, by focusing on the supply chain's level of uncertainty exposure. Specifically, the issue of where and in what ways flexibility has been incorporated across the organisation's supply chain is addressed. Design/methodology/approach: A two-phase methodology design based on literature review and case study was used. Using 83 journal articles in the areas of uncertainty and flexibility an analytical process for assessing uncertainty-flexibility mismatches was developed. Furthermore, results from ten interviews with senior/middle managers within the Australian manufacturing sector were used to provide preliminary insights on the usefulness and importance of the analytical process and its relationship with organisational practice. Findings: The paper emphasises the importance of having a systematic and encompassing view of uncertainty-flexibility mismatches across the supply chain, as well as the significance of socio-technical engagement. The paper both conceptually and empirically illustrates how, using a structured analytical process, flexibility requirements across the supply, process, control and demand segments of a supply chain might be assessed. A four-step analytical process was accordingly developed and, its application, usefulness and importance discussed using empirical data. Practical implications: The analytical process presented in this paper can assist managers to obtain a comprehensive overview of supply chain flexibility when dealing with situations involving uncertainty. This can facilitate and improve their decision-making with respect to prioritising attention on identified flexibility gaps in order to ensure stability of their performance. Originality/value: The paper presents a supply chain-wide discussion on the difficulties that uncertainty brings to organisations, and how organisational flexibility might serve to moderate those challenges for supply chain management. It discusses how to identify the flexibility gap and proposes an original analytical process for systematic assessment of uncertainty-flexibility mismatches. © Emerald Group Publishing Limited.

A novel approach to priority-setting for HIV prevention among adults in Uganda

 The study used economic and ethical theory, empirical evidence and local stakeholders views to develop a checklist of features of an ideal approach to priority-setting. This was used to determine the ideal approach for priority-setting for HIV prevention in Uganda. The Assessing Cost-Effectiveness (ACE) approach was determined to be the ideal approach using the checklist developed. A pilot study using the approach determined that in Uganda, blood safety and HIV counselling interventions are the most cost-effective, equitable and acceptable interventions. Mass media interventions were the least cost-effective and affordable, had a weak evidence base but were more acceptable. On the other hand interventions targeting Most-at-risk-populations were cost-effective but least acceptable. The study demonstrates the importance of balancing technical rigor and due process to ensure buy-in by stakeholders.

Measuring underreporting and under-ascertainment in infectious disease datasets: a comparison of methods

 Background: Efficient and reliable surveillance and notification systems are vital for monitoring public health and disease outbreaks. However, most surveillance and notification systems are affected by a degree of underestimation (UE) and therefore uncertainty surrounds the 'true' incidence of disease affecting morbidity and mortality rates. Surveillance systems fail to capture cases at two distinct levels of the surveillance pyramid: from the community since not all cases seek healthcare (under-ascertainment), and at the healthcare-level, representing a failure to adequately report symptomatic cases that have sought medical advice (underreporting). There are several methods to estimate the extent of under-ascertainment and underreporting. Methods. Within the context of the ECDC-funded Burden of Communicable Diseases in Europe (BCoDE)-project, an extensive literature review was conducted to identify studies that estimate ascertainment or reporting rates for salmonellosis and campylobacteriosis in European Union Member States (MS) plus European Free Trade Area (EFTA) countries Iceland, Norway and Switzerland and four other OECD countries (USA, Canada, Australia and Japan). Multiplication factors (MFs), a measure of the magnitude of underestimation, were taken directly from the literature or derived (where the proportion of underestimated, under-ascertained, or underreported cases was known) and compared for the two pathogens. Results: MFs varied between and within diseases and countries, representing a need to carefully select the most appropriate MFs and methods for calculating them. The most appropriate MFs are often disease-, country-, age-, and sex-specific. Conclusions: When routine data are used to make decisions on resource allocation or to estimate epidemiological parameters in populations, it becomes important to understand when, where and to what extent these data represent the true picture of disease, and in some instances (such as priority setting) it is necessary to adjust for underestimation. MFs can be used to adjust notification and surveillance data to provide more realistic estimates of incidence. © 2014 Gibbons et al.; licensee BioMed Central Ltd.

Can we beat DDoS attacks in clouds?

Cloud is becoming a dominant computing platform. Naturally, a question that arises is whether we can beat notorious DDoS attacks in a cloud environment. Researchers have demonstrated that the essential issue of DDoS attack and defense is resource competition between defenders and attackers. A cloud usually possesses profound resources and has full control and dynamic allocation capability of its resources. Therefore, cloud offers us the potential to overcome DDoS attacks. However, individual cloud hosted servers are still vulnerable to DDoS attacks if they still run in the traditional way. In this paper, we propose a dynamic resource allocation strategy to counter DDoS attacks against individual cloud customers. When a DDoS attack occurs, we employ the idle resources of the cloud to clone sufficient intrusion prevention servers for the victim in order to quickly filter out attack packets and guarantee the quality of the service for benign users simultaneously. We establish a mathematical model to approximate the needs of our resource investment based on queueing theory. Through careful system analysis and real-world data set experiments, we conclude that we can defeat DDoS attacks in a cloud environment. © 2013 IEEE.

Identifying race bettor groups by their gambling behaviour

Given the increasing social acceptance of gambling, as well as its ease of accessibility through telephone, Internet and game consoles, it is no wonder that gambling has seen an increase in popularity in the past decade (Pinto & Mansfield, 2011). Gambling is now recognized as the largest entertainment service industry in the world, with its revenue greater than both music sales and movies combined (McGowan, 2008, cited in Pinto & Mansfield, 2011). A vast majority of the gambling research deals with problem and pathological gambling (Jolley et al., 2006; Lam & Mizerski, 2009; Mizerski et al., 2011). This is despite the evidence that only 2% of the gambling population are classified as problem gamblers (Productivity Commission, 2010). This ignores understanding the gambling behaviour of the general gambling population (Lee et al., 2006). Recently, there has been increasing effort to understand the behaviour of the general gambling population (Jolley et al., 2006; Lam & Mizerski, 2009). However, few studies have investigated whether there are different gambling groups based on their behaviours in the population.
Market segmentation is a widely used tool in marketing to identify heterogeneous groups of individuals. Market segmentation can lead to efficient resource allocation, competitive advantages and increase business profitability (Dibb & Simkin, 2009; Dibb et al., 2002). The gambling industry offers a variety of gambling products that has now resulted in increased competition which can draw away existing and potential bettors to other companies. It is now important for gambling service providers to better understand betting behaviour of their customers in order to devise strategies to retain them. Accordingly, the purpose of this research is to investigate whether different gambling cohorts exist based on their gambling behaviour.

Enabling cloud computing in emergency management systems

Emergencies, including both natural and man - made disasters, increasingly pose an immediate threat to life, health, property, and environment. For example, Hurricane Katrina, the deadliest and most destructive Atlantic tropical cyclone of the 2005 Atlantic hurricane season, led to at least 1,883 people's death and an estimated loss of - 108 billion property. To reduce the damage by emergencies, a wide range of cutting-edge technologies on medicine and information are used in all phases of emergency management. This article proposes a cloud-based emergency management system for environmental and structural monitoring that utilizes the powerful computing and storage capability of datacenters to analyze the mass data collected by the wireless intelligent sensor network deployed in civil environment. The system also benefits from smartphone and social network platform to setup the spatial and population models, which enables faster evacuation and better resource allocation.

Framing the socialisation process of the DBA candidate: what can universities offer and what should candidates bring?

In Australia, the Doctorate of Business Administration (DBA) remains a popular program but considerable anguish persists within the university sector over just what it is offering students. In this article, we use the process of postgraduate socialisation to understand how candidates, supervisors and administrators navigate pathways to successful completion and offering of a DBA program. We identify four modes of knowledge applicable to the DBA and suggest that universities and candidates may draw on one another’s cultural capital to determine which mode(s) can be offered. We also illustrate how candidates exercise agency through their cultural and social capital as they move through the program. We present a conceptual framework to help guide future research, and resource allocation on the DBA.

Automated analysis of performance and energy consumption for cloud applications

In cloud environments, IT solutions are delivered to users via shared infrastructure. One consequence of this model is that large cloud data centres consume large amounts of energy and produce significant carbon footprints. A key objective of cloud providers is thus to develop resource provisioning and management solutions at minimum energy consumption while still guaranteeing Service Level Agreements (SLAs). However, a thorough understanding of both system performance and energy consumption patterns in complex cloud systems is imperative to achieve a balance of energy efficiency and acceptable performance. In this paper, we present StressCloud, a performance and energy consumption analysis tool for cloud systems. StressCloud can automatically generate load tests and profile system performance and energy consumption data. Using StressCloud, we have conducted extensive experiments to profile and analyse system performance and energy consumption with different types and mixes of runtime tasks. We collected finegrained energy consumption and performance data with different resource allocation strategies, system configurations and workloads. The experimental results show the correlation coefficients of energy consumption, system resource allocation strategies and workload, as well as the performance of the cloud applications. Our results can be used to guide the design and deployment of cloud applications to balance energy and performance requirements.