Sensing bluetooth mobility data: potentials and applications

Information related to mobility dynamics constitutes an important factor to be considered in traffic management to improve the efficiency of existing systems. We present a proof-of-concept deployment of sensors using the Bluetooth technology to detect traffic flow conditions. Besides traditional method consisting of a network of stationary sensors, we present a novel approach that uses sensors deployed in moving vehicles that allows new type studies and captures new insights of mobility. Both approaches complement the most common methods of traffic sensing while being more cost-effective and easily available. Early experimental results show the variety of information available through both approaches spanning from Origin/Destination matrices and travel times to insights into emerging mobile neighborhoods. These metrics are important to improve traffic management increasing the efficiency of urban mobility networks

A regional Bayesian POT model for flood frequency analysis

Flood frequency analysis is usually based on the fitting of an extreme value distribution to the local streamflow series. However, when the local data series is short, frequency analysis results become unreliable. Regional frequency analysis is a convenient way to reduce the estimation uncertainty. In this work, we propose a regional Bayesian model for short record length sites. This model is less restrictive than the index flood model while preserving the formalism of "homogeneous regions". The performance of the proposed model is assessed on a set of gauging stations in France. The accuracy of quantile estimates as a function of the degree of homogeneity of the pooling group is also analysed. The results indicate that the regional Bayesian model outperforms the index flood model and local estimators. Furthermore, it seems that working with relatively large and homogeneous regions may lead to more accurate results than working with smaller and highly homogeneous regions

Clinical Prediction Rule for Stratifying Risk of Pulmonary Multidrug-Resistant Tuberculosis

Multidrug-resistant tuberculosis (MDR-TB), resistance to at least isoniazid and rifampin, is a worldwide problem.To develop a clinical prediction rule to stratify risk for MDR-TB among patients with pulmonary tuberculosis.Derivation and internal validation of the rule among adult patients prospectively recruited from 37 health centers (Perú), either a) presenting with a positive acid-fast bacillus smear, or b) had failed therapy or had a relapse within the first 12 months.Among 964 patients, 82 had MDR-TB (prevalence, 8.5%). Variables included were MDR-TB contact within the family, previous tuberculosis, cavitary radiologic pattern, and abnormal lung exam. The area under the receiver-operating curve (AUROC) was 0.76. Selecting a cut-off score of one or greater resulted in a sensitivity of 72.6%, specificity of 62.8%, likelihood ratio (LR) positive of 1.95, and LR negative of 0.44. Similarly, selecting a cut-off score of two or greater resulted in a sensitivity of 60.8%, specificity of 87.5%, LR positive of 4.85, and LR negative of 0.45. Finally, selecting a cut-off score of three or greater resulted in a sensitivity of 45.1%, specificity of 95.3%, LR positive of 9.56, and LR negative of 0.58.A simple clinical prediction rule at presentation can stratify risk for MDR-TB. If further validated, the rule could be used for management decisions in resource-limited areas

The use of insulin declines as patients live farther from their source of care: results of a survey of adults with type 2 diabetes

BACKGROUND: Although most diabetic patients do not achieve good physiologic control, patients who live closer to their source of primary care tend to have better glycemic control than those who live farther away. We sought to assess the role of travel burden as a barrier to the use of insulin in adults with diabetes METHODS: 781 adults receiving primary care for type 2 diabetes were recruited from the Vermont Diabetes Information System. They completed postal surveys and were interviewed at home. Travel burden was estimated as the shortest possible driving distance from the patient's home to the site of primary care. Medication use, age, sex, race, marital status, education, health insurance, duration of diabetes, and frequency of care were self-reported. Body mass index was measured by a trained field interviewer. Glycemic control was measured by the glycosolated hemoglobin A1C assay. RESULTS: Driving distance was significantly associated with insulin use, controlling for the covariates and potential confounders. The odds ratio for using insulin associated with each kilometer of driving distance was 0.97 (95% confidence interval 0.95, 0.99; P = 0.01). The odds ratio for using insulin for those living within 10 km (compared to those with greater driving distances) was 2.29 (1.35, 3.88; P = 0.02). DISCUSSION: Adults with type 2 diabetes who live farther from their source of primary care are significantly less likely to use insulin. This association is not due to confounding by age, sex, race, education, income, health insurance, body mass index, duration of diabetes, use of oral agents, glycemic control, or frequency of care, and may be responsible for the poorer physiologic control noted among patients with greater travel burdens

Dual use of Medicare and the Veterans Health Administration: are there adverse health outcomes?

BACKGROUND: Millions of veterans are eligible to use the Veterans Health Administration (VHA) and Medicare because of their military service and age. This article examines whether an indirect measure of dual use based on inpatient services is associated with increased mortality risk. METHODS: Data on 1,566 self-responding men (weighted N = 1,522) from the Survey of Assets and Health Dynamics among the Oldest Old (AHEAD) were linked to Medicare claims and the National Death Index. Dual use was indirectly indicated when the self-reported number of hospital episodes in the 12 months prior to baseline was greater than that observed in the Medicare claims. The independent association of dual use with mortality was estimated using proportional hazards regression. RESULTS: 96 (11%) of the veterans were classified as dual users. 766 men (50.3%) had died by December 31, 2002, including 64.9% of the dual users and 49.3% of all others, for an attributable mortality risk of 15.6% (p < .003). Adjusting for demographics, socioeconomics, comorbidity, hospitalization status, and selection bias at baseline, as well as subsequent hospitalization for ambulatory care sensitive conditions, the independent effect of dual use was a 56.1% increased relative risk of mortality (AHR = 1.561; p = .009). CONCLUSION: An indirect measure of veterans' dual use of the VHA and Medicare systems, based on inpatient services, was associated with an increased risk of death. Further examination of dual use, especially in the outpatient setting, is needed, because dual inpatient and dual outpatient use may be different phenomena

Biomedical informatics and translational medicine

Biomedical informatics involves a core set of methodologies that can provide a foundation for crossing the "translational barriers" associated with translational medicine. To this end, the fundamental aspects of biomedical informatics (e.g., bioinformatics, imaging informatics, clinical informatics, and public health informatics) may be essential in helping improve the ability to bring basic research findings to the bedside, evaluate the efficacy of interventions across communities, and enable the assessment of the eventual impact of translational medicine innovations on health policies. Here, a brief description is provided for a selection of key biomedical informatics topics (Decision Support, Natural Language Processing, Standards, Information Retrieval, and Electronic Health Records) and their relevance to translational medicine. Based on contributions and advancements in each of these topic areas, the article proposes that biomedical informatics practitioners ("biomedical informaticians") can be essential members of translational medicine teams

Modelling Bluetooth Inquiry for SUMO

SUMO provides an interface for the implementation of arbitrary additional vehicle devices. This paper describes how this interface was used to implement Bluetooth devices with a special focus on the inquiry process and how its modelling relates to real world measurements and a simple analytic model