Outbreak detection algorithms for seasonal disease data : a case study using Ross River virus disease

Background Detection of outbreaks is an important part of disease surveillance. Although many algorithms have been designed for detecting outbreaks, few have been specifically assessed against diseases that have distinct seasonal incidence patterns, such as those caused by vector-borne pathogens. Methods We applied five previously reported outbreak detection algorithms to Ross River virus (RRV) disease data (1991-2007) for the four local government areas (LGAs) of Brisbane, Emerald, Redland and Townsville in Queensland, Australia. The methods used were the Early Aberration Reporting System (EARS) C1, C2 and C3 methods, negative binomial cusum (NBC), historical limits method (HLM), Poisson outbreak detection (POD) method and the purely temporal SaTScan analysis. Seasonally-adjusted variants of the NBC and SaTScan methods were developed. Some of the algorithms were applied using a range of parameter values, resulting in 17 variants of the five algorithms. Results The 9,188 RRV disease notifications that occurred in the four selected regions over the study period showed marked seasonality, which adversely affected the performance of some of the outbreak detection algorithms. Most of the methods examined were able to detect the same major events. The exception was the seasonally-adjusted NBC methods that detected an excess of short signals. The NBC, POD and temporal SaTScan algorithms were the only methods that consistently had high true positive rates and low false positive and false negative rates across the four study areas. The timeliness of outbreak signals generated by each method was also compared but there was no consistency across outbreaks and LGAs. Conclusions This study has highlighted several issues associated with applying outbreak detection algorithms to seasonal disease data. In lieu of a true gold standard, a quantitative comparison is difficult and caution should be taken when interpreting the true positives, false positives, sensitivity and specificity.

Geographical distribution of human Schistosoma japonicum infection in the Philippines : tools to support disease control and further elimination

S. japonicum infection is believed to be endemic in 28 of the 80 provinces of the Philippines and the most recent data on schistosomiasis prevalence have shown considerable variability between provinces. In order to increase the efficient allocation of parasitic disease control resources in the country, we aimed to describe the small scale spatial variation in S. japonicum prevalence across the Philippines, quantify the role of the physical environment in driving the spatial variation of S. japonicum, and develop a predictive risk map of S. japonicum infection. Data on S. japonicum infection from 35,754 individuals across the country were geo-located at the barangay level and included in the analysis. The analysis was then stratified geographically for Luzon, the Visayas and Mindanao. Zero-inflated binomial Bayesian geostatistical models of S. japonicum prevalence were developed and diagnostic uncertainty was incorporated. Results of the analysis show that in the three regions, males and individuals aged ≥ 20 years had significantly higher prevalence of S. japonicum compared with females and children <5 years. The role of the environmental variables differed between regions of the Philippines. S. japonicum infection was widespread in the Visayas whereas it was much more focal in Luzon and Mindanao. This analysis revealed significant spatial variation in prevalence of S. japonicum infection in the Philippines. This suggests that a spatially targeted approach to schistosomiasis interventions, including mass drug administration, is warranted. When financially possible, additional schistosomiasis surveys should be prioritized to areas identified to be at high risk, but which were underrepresented in our dataset.

Bayesian models for spatio-temporal assessment of disease

This thesis has contributed to the advancement of knowledge in disease modelling by addressing interesting and crucial issues relevant to modelling health data over space and time. The research has led to the increased understanding of spatial scales, temporal scales, and spatial smoothing for modelling diseases, in terms of their methodology and applications. This research is of particular significance to researchers seeking to employ statistical modelling techniques over space and time in various disciplines. A broad class of statistical models are employed to assess what impact of spatial and temporal scales have on simulated and real data.

Integrated chronic disease management in primary-secondary care : a systematic literature review of the evidence

Introduction: Diabetes has traditionally been managed as a single chronic disease state, but it exists with co-morbidities such as depression and metabolic syndrome. Treatment is multifaceted, requiring both primary and secondary care, however, the delivery of diabetes care is often fragmented. Integrated chronic disease management is a growing model of interest, and is underpinned by the chronic care model (CCM), devised as a guide for primary care management of patients with chronic conditions. The model identifies six key elements for effective care, and has shown promise in improving the management of diabetes. Aim: To find empirical evidence of integrated care interventions targeted at co-morbidities including diabetes, across primary/secondary care. Method: A systematic review of peer reviewed literature from PubMed, CINAHL, Embase, Cochrane Library and Joanna Briggs was performed. Studies were reviewed according to inclusion criteria- studies published in English, between 2004-2014, empirical studies, studies with evidence of primary/secondary implementation, and those dealing with chronic co-morbid disease states. Results: 51 studies met the inclusion criteria. Included studies were mostly from the US (38), with five from Australia, UK (2), Canada (2), Netherlands (1), Norway (1), Ireland (1), and one multi-country study. It was found that all interventions adopted at least one (average 3-4) of the chronic care model, with the majority implementing delivery system redesign activities within the primary care practice/s. We found evidence of interventions which significantly reduced emergency department and hospital admissions, improved processes of care, patient health outcomes such as HbA1c, improved patient satisfaction, and reduced costs. Conclusion/Implications for practice: Diabetes exists as a co-morbid disease, requiring both primary and secondary care. We found that integrated care interventions adopting elements of the chronic care model positively impacted on patient outcomes, service utilisation, as well as costs. This review has highlighted that it may not be necessary to adopt all CCM elements to improve clinical outcomes, patient satisfaction and costs.

Intravitreal drug delivery in retinal disease : are we out of our depth?

Introduction With the ever-increasing global burden of retinal disease, there is an urgent need to vastly improve formulation strategies that enhance posterior eye delivery of therapeutics. Despite intravitreal administration having demonstrated notable superiority over other routes in enhancing retinal drug availability, there still exist various significant physical/biochemical barriers preventing optimal drug delivery into the retina. A further complication lies with an inability to reliably translate laboratory-based retinal models into a clinical setting. Several formulation approaches have recently been evaluated to improve intravitreal therapeutic outcomes, and our aim in this review is to highlight strategies that hold the most promise. Areas covered We discuss the complex barriers faced by the intravitreal route and examine how formulation strategies including implants, nanoparticulate carriers, viral vectors and sonotherapy have been utilized to attain both sustained delivery and enhanced penetration through to the retina. We conclude by highlighting the advances and limitations of current in vitro, ex vivo and in vivo retinal models in use by researchers globally. Expert opinion Various nanoparticle compositions have demonstrated the ability to overcome the retinal barriers successfully; however, their utility is limited to the laboratory setting. Optimization of these formulations and the development of more robust experimental retinal models are necessary to translate success in the laboratory into clinically efficacious outcomes.

Emerging methods in using GIS to analyse Barmah Forest virus disease in Queensland, Australia

Barmah Forest virus (BFV) disease is an emerging mosquito-borne disease in Australia. We aimed to outline some recent methods in using GIS for the analysis of BFV disease in Queensland, Australia. A large database of geocoded BFV cases has been established in conjunction with population data. The database has been used in recently published studies conducted by the authors to determine spatio-temporal BFV disease hotspots and spatial patterns using spatial autocorrelation and semi-variogram analysis in conjunction with the development of interpolated BFV disease standardised incidence maps. This paper briefly outlines spatial analysis methodologies using GIS tools used in those studies. This paper summarises methods and results from previous studies by the authors, and presents a GIS methodology to be used in future spatial analytical studies in attempt to enhance the understanding of BFV disease in Queensland. The methodology developed is useful in improving the analysis of BFV disease data and will enhance the understanding of the BFV disease distribution in Queensland, Australia.

Evolution to a chronic disease niche correlates with increased sensitivity to tryptophan availability for the obligate intracellular bacterium Chlamydia pneumoniae

The chlamydiae are obligate intracellular parasites that have evolved specific interactions with their various hosts and host cell types to ensure their successful survival and consequential pathogenesis. The species Chlamydia pneumoniae is ubiquitous, with serological studies showing that most humans are infected at some stage in their lifetime. While most human infections are asymptomatic, C. pneumoniae can cause more-severe respiratory disease and pneumonia and has been linked to chronic diseases such as asthma, atherosclerosis, and even Alzheimer's disease. The widely dispersed animal-adapted C. pneumoniae strains cause an equally wide range of diseases in their hosts. It is emerging that the ability of C. pneumoniae to survive inside its target cells, including evasion of the host's immune attack mechanisms, is linked to the acquisition of key metabolites. Tryptophan and arginine are key checkpoint compounds in this host-parasite battle. Interestingly, the animal strains of C. pneumoniae have a slightly larger genome, enabling them to cope better with metabolite restrictions. It therefore appears that as the evolutionarily more ancient animal strains have evolved to infect humans, they have selectively become more "susceptible" to the levels of key metabolites, such as tryptophan. While this might initially appear to be a weakness, it allows these human C. pneumoniae strains to exquisitely sense host immune attack and respond by rapidly reverting to a persistent phase. During persistence, they reduce their metabolic levels, halting progression of their developmental cycle, waiting until the hostile external conditions have passed before they reemerge.

A comparison of treatment options for management of end stage kidney disease in elderly patients : a systematic review

Background Chronic kidney disease is a global public health problem of increasing prevalence. There are five stages of kidney disease, with Stage 5 indicating end stage kidney disease (ESKD) requiring dialysis or death will eventually occur. Over the last two decades there have been increasing numbers of people commencing dialysis. A majority of this increase has occurred in the population of people who are 65 years and over. With the older population it is difficult to determine at times whether dialysis will provide any benefit over non-dialysis management. The poor prognosis for the population over 65 years raises issues around management of ESKD in this population. It is therefore important to review any research that has been undertaken in this area which compares outcomes of the older ESKD population who have commenced dialysis with those who have received non-dialysis management. Objective The primary objective was to assess the effect of dialysis compared with non-dialysis management for the population of 65 years and over with ESKD. Inclusion criteria Types of participants This review considered studies that included participants who were 65 years and older. These participants needed to have been diagnosed with ESKD for greater than three months and also be either receiving renal replacement therapy (RRT) (hemodialysis [HD] or peritoneal dialysis [PD]) or non-dialysis management. The settings for the studies included the home, self-care centre, satellite centre, hospital, hospice or nursing home. Types of intervention(s)/phenomena of interest This review considered studies where the intervention was RRT (HD or PD) for the participants with ESKD. There was no restriction on frequency of RRT or length of time the participant received RRT. The comparator was participants who were not undergoing RRT. Types of studies This review considered both experimental and epidemiological study designs including randomized controlled trials, non-randomized controlled trials, quasi-experimental, before and after studies, prospective and retrospective cohort studies, case control studies and analytical cross sectional studies. This review also considered descriptive epidemiological study designs including case series, individual case reports and descriptive cross sectional studies for inclusion. This review included any of the following primary and secondary outcome measures: •Primary outcome – survival measures •Secondary outcomes – functional performance score (e.g. Karnofsky Performance score) •Symptoms and severity of end stage kidney disease •Hospital admissions •Health related quality of life (e.g. KDQOL, SF36 and HRQOL) •Comorbidities (e.g. Charlson Comorbidity index).

Self-management programs in stage 1-4 chronic kidney disease : a literature review.

Background Chronic kidney disease (CKD) is a complex health problem, which requires individuals to invest considerable time and energy in managing their health and adhering to multifaceted treatment regimens. Objectives To review studies delivering self-management interventions to people with CKD (Stages 1–4) and assess whether these interventions improve patient outcomes. Design: Systematic review. Methods Nine electronic databases (MedLine, CINAHL, EMBASE, ProQuest Health & Medical Complete, ProQuest Nursing & Allied Health, The Cochrane Library, The Joanna Briggs Institute EBP Database, Web of Science and PsycINFO) were searched using relevant terms for papers published between January 2003 and February 2013. Results The search strategy identified 2,051 papers, of which 34 were retrieved in full with only 5 studies involving 274 patients meeting the inclusion criteria. Three studies were randomised controlled trials, a variety of methods were used to measure outcomes, and four studies included a nurse on the self-management intervention team. There was little consistency in the delivery, intensity, duration and format of the self-management programmes. There is some evidence that knowledge- and health-related quality of life improved. Generally, small effects were observed for levels of adherence and progression of CKD according to physiologic measures. Conclusion The effectiveness of self-management programmes in CKD (Stages 1–4) cannot be conclusively ascertained, and further research is required. It is desirable that individuals with CKD are supported to effectively self-manage day-to-day aspects of their health.

Challenges in improving chronic disease survivorship outcomes using tele-health and self-managed online solutions

The advances in modern information and communication (ICT) technology continue to address the challenges and improve` health outcomes for the survivors of chronic disease such as prostate cancer. The management of survivorship is increasingly becoming an important need for the survivors to manage their chronic conditions. The technology interventions such as tele-health as well as self-managed technology applications have shown a potential to improve survivorship outcomes. However, the application of these tools should be supported by strong health economics evidence. This work discusses the challenges of technology led survivorship care models and presents an integrated approach to address these challenges.