Disease control and management

Globally, the main contributors to morbidity and mortality are chronic conditions, including cardiovascular disease and diabetes. Chronic disease is costly and partially avoidable, with around 60% of deaths and nearly 50% of the global disease burden attributable to these conditions. By 2020, chronic illnesses will likely be the leading cause of disability worldwide. Existing healthcare systems that focus on acute episodic health conditions, both national and international, cannot address the worldwide transition to chronic illness; nor are they appropriate for the ongoing care and management of those already dealing with chronic diseases. As such, chronic disease management requires integrated approaches that incorporate interventions targeted at both individuals and populations, and emphasise the shared risk factors of different conditions. International and Australian strategic planning documents articulate similar elements to manage chronic disease, including the need for aligning sectoral policies for health, forming partnerships, and engaging communities in decision-making. Infectious diseases are also a common and significant contributor to ill health throughout the world. In many countries, this impact has been minimised by the combined efforts of preventative health measures and improved treatment methods. However, in low-income countries, infectious diseases remain the dominant cause of death and disability. The World Health Organization (WHO) estimates that infectious diseases (including respiratory infections) still account for around 23% (or around 14 million) of all deaths each year, and result in over 4.6 billion episodes of diarrhoeal disease and 243 million cases of malaria each year (Lozano et al. 2012, WHO 2009). In addition to the high level of mortality, infectious diseases disable many hundreds of millions of people each year, mainly in developing countries, with the global burden of disease from infectious diseases estimated to be around 300 million DALYs (disability-adjusted life years) (WHO 2012). The aim of this chapter is to outline the impact that infectious diseases and chronic diseases have on the health of the community, describe the public health strategies used to reduce the burden of those diseases, and discuss the historic and emerging disease risks to public health. This chapter examines the comprehensive approaches implemented to prevent both chronic and infectious diseases, and to manage and care for communities with these conditions.

Decision fusion for reliable flood mapping using remote sensing images

Flood extent mapping is a basic tool for flood damage assessment, which can be done by digital classification techniques using satellite imageries, including the data recorded by radar and optical sensors. However, converting the data into the information we need is not a straightforward task. One of the great challenges involved in the data interpretation is to separate the permanent water bodies and flooding regions, including both the fully inundated areas and the wet areas where trees and houses are partly covered with water. This paper adopts the decision fusion technique to combine the mapping results from radar data and the NDVI data derived from optical data. An improved capacity in terms of identifying the permanent or semi-permanent water bodies from flood inundated areas has been achieved. Computer software tools Multispec and Matlab were used.

Women’s Wellness after Cancer Program Study (WWACP)– A multi centre randomised controlled trial examining the benefits and cost effectiveness of an Evidenced Based, e-health intervention

Background Advances in cancer diagnosis and treatment have significantly improved survival rates, through their subsequent health needs are often not adequately addressed by current health services. National Health and Medical Research Council (NHMRC) Partnerships Project awarded a national collaborative project to develop, trial and evaluate clinical benefits and cost effectiveness of an e-health enabled structured health promotion intervention - The Women’s Wellness after Cancer Program (WWACP). The aim of this e-health enabled multimodal intervention is to improve health related quality of life in women previously treated for target cancers. Aim The WWACP is a 12-week web based, interactive, holistic program. Primary outcomes for this project are to promote a positive change in health-related quality of life (HRQoL) and reduction in Body Mass Index (BMI) in the women undertaking WWACP compared to women who receive usual care. Secondary outcomes include managing other side effects of cancer treatment through evidence-based nutrition and exercise practices, dealing with stress, sleep, menopause and sexuality issues. Methods The single-blinded multi-center randomized controlled trial recruited a toatl of 330 women within 24 months of completion of chemotherapy and /or radiotherapy. Women were randomly assigned to either a usual care or intervention group. Women provided with the intervention were provided with an interactive iBook and journal, web interface, and three virtual consultations by experienced cancer nurses. A variety of methods were utilized, to enable positive self- efficacy and lifestyle changes. These include online coaching with a registered nurse trained in the intervention, plus written educational and health promotional information. The program has been delivered through the e-health enabled interfaces, which enables virtual delivery via desktop and mobile computing devices. Importantly this enables accessibility for rural and regional women in Australia who are frequently geographically disadvantaged in terms of health care provision. Results Research focusing on alternative methods of delivering post treatment / or survivorship care in cancer utilizing web based interfaces is limited, but emerging evidence suggests that Internet interventions can increase psychological and physical wellbeing in cancer patients. The WWACP trial aims to establish the effectiveness of delivery of the program in terms of positive patient outcomes and cost effective, flexibility. The trial will be completed in September and results will be presented at the conference. Conclusions Women after acute hematological, breast and gynecological cancer treatments demonstrate good cancer survival rates and face residual health problems which are amenable to behavioral interventions. The conclusion of active treatment is a key 'teachable moment' in which sustainable positive lifestyle change can be achieved if patients receive education and psychological support which targets key treatment related health problems and known chronic disease risk factors.

A cultural assessment of family dispute resolution: Findings about access, retention and outcomes from the evaluation of a Family Relationship Centre

The cultural appropriateness of human service processes is a major factor in determining the effectiveness of their delivery. Sensitivity to issues of culture is particularly critical in dealing with family disputes, which are generally highly emotive and require difficult decisions to be made regarding children, material assets and ongoing relationships. In this article we draw on findings from an evaluation of the Family Relationship Centre at Broadmeadows (FRCB) to offer some insights into and suggestions about managing cultural matters in the current practice of family dispute resolution (FDR) in Australia. The brief for the original research was to evaluate the cultural appropriateness of FDR services offered to culturally and linguistically diverse (CALD) communities living within the FRCB’s catchment area, specifically members of the Lebanese, Turkish and Iraqi communities. The conclusions of the evaluations were substantially positive. The work of the Centre was found to illustrate many aspects of best practice but also raised questions worthy of future exploration. The current article reports on issues of access, retention and outcomes obtained by CALD clients at various stages of the FRCB service.

Mixed pixel analysis and assessment for flood mapping

The most difficult operation in flood inundation mapping using optical flood images is to map the ‘wet’ areas where trees and houses are partly covered by water. This can be referred to as a typical problem of the presence of mixed pixels in the images. A number of automatic information extracting image classification algorithms have been developed over the years for flood mapping using optical remote sensing images, with most labelling a pixel as a particular class. However, they often fail to generate reliable flood inundation mapping because of the presence of mixed pixels in the images. To solve this problem, spectral unmixing methods have been developed. In this thesis, methods for selecting endmembers and the method to model the primary classes for unmixing, the two most important issues in spectral unmixing, are investigated. We conduct comparative studies of three typical spectral unmixing algorithms, Partial Constrained Linear Spectral unmixing, Multiple Endmember Selection Mixture Analysis and spectral unmixing using the Extended Support Vector Machine method. They are analysed and assessed by error analysis in flood mapping using MODIS, Landsat and World View-2 images. The Conventional Root Mean Square Error Assessment is applied to obtain errors for estimated fractions of each primary class. Moreover, a newly developed Fuzzy Error Matrix is used to obtain a clear picture of error distributions at the pixel level. This thesis shows that the Extended Support Vector Machine method is able to provide a more reliable estimation of fractional abundances and allows the use of a complete set of training samples to model a defined pure class. Furthermore, it can be applied to analysis of both pure and mixed pixels to provide integrated hard-soft classification results. Our research also identifies and explores a serious drawback in relation to endmember selections in current spectral unmixing methods which apply fixed sets of endmember classes or pure classes for mixture analysis of every pixel in an entire image. However, as it is not accurate to assume that every pixel in an image must contain all endmember classes, these methods usually cause an over-estimation of the fractional abundances in a particular pixel. In this thesis, a subset of adaptive endmembers in every pixel is derived using the proposed methods to form an endmember index matrix. The experimental results show that using the pixel-dependent endmembers in unmixing significantly improves performance.