How infectious diseases spread in space within one cycle of an epidemic is an important question that has received considerable theoretical attention. There are, however, few empirical studies to support theoretical approaches, because data is scarce. Weekly reports obtained since 1984 from a network of general practitioners spanning the entire French territory allows the analysis of the spatio–temporal dynamics of influenza over a fine spatial scale. This analysis indicates that diffusion over long distances, possibly due to global transportation systems, is so quick that homogeneous global mixing occurs before the epidemic builds up within infected patches. A simple model in which the total number of cases is given by the empirical time–series and cases are randomly assigned to patches according to the population weight of the patches exhibits the same spatio–temporal properties as real epidemic cycles: homogeneous mixing models constitute appropriate descriptions, except in the vicinity of the epidemic's peak, where geographic heterogeneities play a role.

Current literature suggests a higher risk of pregnancy-related complications in patients with renal fibromuscular dysplasia (FMD). The aim of our study was to assess the nature and prevalence of pregnancy-related complications in patients subsequently diagnosed with FMD. A call for participation was sent to centers contributing to the European/International FMD Registry. Patients with at least 1 pregnancy were included. Data on pregnancy were collected through medical files and FMD characteristics through the European/International FMD Registry. Data from 534 pregnancies were obtained in 237 patients. Despite the fact that, in 96% of cases, FMD was not diagnosed before pregnancy, 40% of women (n=93) experienced pregnancy-related complications, mostly gestational hypertension (25%) and preterm birth (20%), while preeclampsia was reported in only 7.5%. Only 1 patient experienced arterial dissection and another patient an aneurysm rupture. When compared with patients without pregnancy-related complications, patients with complicated pregnancies were younger at FMD diagnosis (43 versus 51 years old; P <0.001) and had a lower prevalence of cerebrovascular FMD (30% versus 52%; P =0.003) but underwent more often renal revascularization (63% versus 40%, P <0.001). In conclusion, the prevalence of pregnancy-related complications such as gestational hypertension and preterm birth was high in patients with FMD, probably related to the severity of renal FMD. However, the prevalence of preeclampsia and arterial complications was low/moderate. These findings emphasize the need to screen hypertensive women for FMD to ensure revascularization before pregnancy if indicated and appropriate follow-up during pregnancy, without discouraging patients with FMD from considering pregnancy.

Fibromuscular dysplasia (FMD), a nonatherosclerotic, noninflammatory disease of medium-sized arteries, is an underdiagnosed disease. We investigated the urinary proteome and developed a classifier for discrimination of FMD from healthy controls and other diseases. We further hypothesized that urinary proteomics biomarkers may be associated with alterations in medium-sized, but not large artery geometry and mechanics. The study included 33 patients with mostly multifocal, renal FMD who underwent in depth arterial exploration using ultra-high frequency ultrasound. The cohort was separated in a training set of 23 patients with FMD from Belgium and an independent test set of 10 patients with FMD from Italy. For each set, controls matched 2:1 were selected from the Human Urinary Proteome Database. The specificity of the classifier was tested in 700 additional controls from general population studies, patients with chronic kidney disease (n=66) and coronary artery disease (n=31). Three hundred thirty-five urinary peptides, mostly related to collagen turnover, were identified in the training cohort and combined into a classifier. When applying in the test cohort, the area under the receiver operating characteristic curve was 1.00, 100% specificity at 100% sensitivity. The classifier maintained a high specificity in additional controls (98.3%), patients with chronic kidney (90.9%) and coronary artery (96.8%) diseases. Furthermore, in patients with FMD, the proteomic score was positively associated with radial wall thickness and wall cross-sectional area. In conclusion, a proteomic score has the potential to discriminate between patients with FMD and controls. If confirmed in a wider and more diverse cohort, these findings may pave the way for a noninvasive diagnostic test of FMD. Download figure Download PowerPoint

Summary Objectives: To summarize excellent current research in the field of Health Information Systems. Method: Creation of a synopsis of the articles selected for the 2014 edition of the IMIA Yearbook. Results: Four papers from international peer reviewed journals were selected and are summarized. Conclusions: Selected articles illustrate current research regarding the impact and the evaluation of health information technology and the latest developments in health information exchange.

Summary Objectives: Summarize excellent current research published in 2015 in the field of Public Health and Epidemiology Informatics. Methods: The complete 2015 literature concerning public health and epidemiology informatics has been searched in PubMed and Web of Science, and the returned references were reviewed by the two section editors to select 14 candidate best papers. These papers were then peer-reviewed by external reviewers to allow the editorial team an enlightened selection of the best papers. Results: Among the 1,272 references retrieved from PubMed and Web of Science, three were finally selected as best papers. The first one presents a language agnostic approach for epidemic event detection in news articles. The second paper describes a system using big health data gathered by a statewide system to forecast emergency department visits. The last paper proposes a rather original approach that uses machine learning to solve the old issue of outbreak detection and prediction. Conclusions: The increasing availability of data, now directly from health systems, will probably lead to a boom in public health surveillance systems and in large-scale epidemiologic studies.