Markov Chain Methods For Analyzing Complex Transport Networks

We have developed a steady state theory of complex transport networks used to model the flow of commodity, information, viruses, opinions, or traffic. Our approach is based on the use of the Markov chains defined on the graph representations of transport networks allowing for the effective network design, network performance evaluation, embedding, partitioning, and network fault tolerance analysis. Random walks embed graphs into Euclidean space in which distances and angles acquire a clear statistical interpretation. Being defined on the dual graph representations of transport networks random walks describe the equilibrium configurations of not random commodity flows on primary graphs. This theory unifies many network concepts into one framework and can also be elegantly extended to describe networks represented by directed graphs and multiple interacting networks.Comment: 26 pages, 4 figure

The panorama of future sick-leave diagnoses among young adults initially long-term sickness absent due to neck, shoulder, or back diagnoses. An 11-year prospective cohort study

<p>Abstract</p> <p>Background</p> <p>Little is known about future sick-leave diagnoses among individuals on long-term sickness absence. The aim of this study was to describe the panorama of sick-leave diagnoses over time among young adults initially sick-listed for ≥ 28 days due to back, neck, or shoulder diagnoses</p> <p>Methods</p> <p>An 11-year prospective population-based cohort study including all 213 individuals in a Swedish municipality who, in 1985, were aged 25–34 years and had a new sick-leave spell ≥ 28 days due to neck, shoulder, or back diagnoses.</p> <p>Results</p> <p>Over the 11-year period, the young adults in this cohort had 176,825 sick-leave days in 7,878 sick-leave periods (in 4,610 sick-leave spells) due to disorders in 17 of the 18 ICD-8 diagnostic categories (International Classification of Diseases, Revision 8). Musculoskeletal or mental diagnoses accounted for most of the sick-leave days, whereas most of the sick-leave periods were due to musculoskeletal, respiratory, or infectious disorders, or to unclassified symptoms. Most cohort members had had four to eight different sick-leave diagnoses over the 11 years, although some had had up to 11 diagnoses. Only two individuals (1%) had been sickness absent solely due to musculoskeletal diagnoses.</p> <p>Conclusion</p> <p>Although the young adults initially were sick listed with back, neck, or shoulder diagnoses, their sickness absence during the follow up were due to a wide variety of other medical diagnoses. It might be that the ill-health content of sickness absence due to back pain is greater than usually assumed. More research on prognoses of sick-leave diagnoses among long-term sick listed is warranted.</p

Investigating the effectiveness and feasibility of exercise on microvascular reactivity and quality of life in systemic sclerosis patients: study protocol for a feasibility study

Background: Raynaud’s phenomenon is one of the first clinical manifestations observed in systemic sclerosis (SSc). This microvasculature disorder affects mostly the digits in over 95% of SSc patients, significantly affecting their healthrelated quality of life (HRQoL) and incurring higher hospital admissions and other healthcare costs. Exercise is known to improve both micro- and macrovascular function – aerobic exercise and resistance training, separately or combined, have been demonstrated to lead to significant vasculo-physiological improvements in conditions that present vasculopathy. However, the effects of a combined exercise programme on microcirculation in SSc patients has yet to be investigated. Therefore, the purpose of this study is to assess the effects of high-intensity interval training (HIIT) combined with circuit resistance training on the microvascular function in the digital area of SSc patients. Methods: This will be a randomised controlled, feasibility trial with two arms, wherein 30 patients with SSc in receipt of medical treatment will be randomly assigned to usual care (medical treatment) or to a 12-week supervised exercise programme. Patients in the exercise group will undertake two, 45-min sessions each week consisting of 30 min HIIT (30 s 100% peak power output/30 s passive recovery) on the arm crank ergometer and 15 min of upper body circuit resistance training. Patients will be assessed before as well as at 3 and 6 months following randomisation. Primary outcomes of the study will be recruitment and retention rate, intervention acceptability and adherence to the exercise programme. Secondary outcomes include the digital area cutaneous microvascular function (laser Doppler fluximetry combined with iontophoresis), physical fitness, functional ability, upper back transcutaneous oxygen tension, body composition and quality of life (EQ-5D-5L). Selected interviews with a subsample of patients will be undertaken to explore their experiences of having Raynaud’s phenomenon and the acceptability of the exercise intervention and study procedures. Discussion: Data from this study will be used to identify the feasibility of a combined exercise programme to be implemented in SSc patients, the acceptability of the intervention and the study design, and to determine the effects of exercise on the microvasculature. Overall, this study will provide sufficient data to inform and support a full multicentre clinical trial

Sickness absence due to specific mental diagnoses and all-cause and cause-specific mortality: a cohort study of 4.9 million inhabitants of Sweden.

Despite the magnitude and increase of sickness absence due to mental diagnoses, little is known regarding long-term health outcomes. The aim of this nationwide population-based, prospective cohort study was to investigate the association between sickness absence due to specific mental diagnoses and the risk of all-cause and cause-specific mortality

Is There an Association between Long-Term Sick Leave and Disability Pension and Unemployment beyond the Effect of Health Status? – A Cohort Study

Background: Studies have shown that long-term sick leave is a strong predictor of disability pension. However, few have aimed to disentangle the effect of sick leave and of health status. The objective of this study was to investigate whether there is an association between long-term sick leave and disability pension and unemployment, when taking health status into account. Methods/Principal Findings: The study was based on the Stockholm Public Health Cohort, restricted to 13,027 employed individuals (45.9 % men) aged 18–59 in 2002 and followed until 2007. Hazard ratios (HR) with 95 % Confidence Interval (CI) were estimated by Cox regression models adjusting for socio-demographic factors and five measures of health status. Having been on long-term sick leave increased the risk of disability pension (HR 4.01; 95 % CI 3.19–5.05) and longterm unemployment (HR 1.45; 95 % CI 1.05–2.00), after adjustment for health status. The analyses of long-term sick leave due to specific illness showed that the increased risk for long-term unemployment was confined to the group on sick leave due to musculoskeletal (HR 1.70 95 % CI 1.00–2.89) and mental illness (HR 1.80 95 % CI 1.13–2.88) and further that there was an increased risk for short-term unemployment in the group on sick leave due to mental illness (HR1.57 95%CI 1.09–2.26). Conclusions/Significance: Long-term sick leave increases the risks of both disability pension and unemployment even when taking health status into account. The results support the hypothesis that long-term sick leave may start a process o