A weighted configuration model and inhomogeneous epidemics

A random graph model with prescribed degree distribution and degree dependent edge weights is introduced. Each vertex is independently equipped with a random number of half-edges and each half-edge is assigned an integer valued weight according to a distribution that is allowed to depend on the degree of its vertex. Half-edges with the same weight are then paired randomly to create edges. An expression for the threshold for the appearance of a giant component in the resulting graph is derived using results on multi-type branching processes. The same technique also gives an expression for the basic reproduction number for an epidemic on the graph where the probability that a certain edge is used for transmission is a function of the edge weight. It is demonstrated that, if vertices with large degree tend to have large (small) weights on their edges and if the transmission probability increases with the edge weight, then it is easier (harder) for the epidemic to take off compared to a randomized epidemic with the same degree and weight distribution. A recipe for calculating the probability of a large outbreak in the epidemic and the size of such an outbreak is also given. Finally, the model is fitted to three empirical weighted networks of importance for the spread of contagious diseases and it is shown that $R_0$ can be substantially over- or underestimated if the correlation between degree and weight is not taken into account

The effects of user characteristics on query performance in the presence of information request ambiguity

This paper investigates the effects of personality characteristics on individuals' abilities to compose queries from information requests containing various types of ambiguity. In particular, this research examines the effects of user personality characteristics on query performance in the presence of information requests that contained no extraneous, syntactic, or both extraneous and syntactic ambiguities. The results indicate that personality characteristics significantly affect users' abilities to compose accurate queries. Neuroticism, agreeableness, openness to experience, and conscientiousness significantly affected the number of errors made in the query formulations. Conscientiousness affected the length of time taken to compose the queries and neuroticism affected the confidence users had in the accuracy of their queries. Although several personality dimensions affected query performance, no significant interactions between personality dimensions and ambiguity were detected. Furthermore, both query complexity and information request ambiguity exhibited greater impacts on query performance than personality characteristics. Hence, organizations should attempt to train users to deal with query complexity and information request ambiguity before modifying their training programs for personality characteristics

Dose response of the 16p11.2 distal copy number variant on intracranial volume and basal ganglia.

Carriers of large recurrent copy number variants (CNVs) have a higher risk of developing neurodevelopmental disorders. The 16p11.2 distal CNV predisposes carriers to e.g., autism spectrum disorder and schizophrenia. We compared subcortical brain volumes of 12 16p11.2 distal deletion and 12 duplication carriers to 6882 non-carriers from the large-scale brain Magnetic Resonance Imaging collaboration, ENIGMA-CNV. After stringent CNV calling procedures, and standardized FreeSurfer image analysis, we found negative dose-response associations with copy number on intracranial volume and on regional caudate, pallidum and putamen volumes (β = -0.71 to -1.37; P < 0.0005). In an independent sample, consistent results were obtained, with significant effects in the pallidum (β = -0.95, P = 0.0042). The two data sets combined showed significant negative dose-response for the accumbens, caudate, pallidum, putamen and ICV (P = 0.0032, 8.9 × 10-6, 1.7 × 10-9, 3.5 × 10-12 and 1.0 × 10-4, respectively). Full scale IQ was lower in both deletion and duplication carriers compared to non-carriers. This is the first brain MRI study of the impact of the 16p11.2 distal CNV, and we demonstrate a specific effect on subcortical brain structures, suggesting a neuropathological pattern underlying the neurodevelopmental syndromes

The Challenge of Resilience in a Globalised World

Resilience determines the capacity to successfully deal with difficult events and to adapt and overcome adversity. It creates stability in a changing world which in turn promotes job creation, economic growth and environmental sustainability. Resilience is a fundamental prerequisite for Europe as the largest integrated economic area in the world and has an important social dimension which requires the active cooperation of all stakeholders; citizens, the private sector, governments and NGOs included. This report discusses the concept of resilience from different perspectives and the role of science in the continuous process of building a resilient, stable, competitive and prosperous Europe.JRC.G-Institute for the Protection and Security of the Citizen (Ispra

A mechanistic model of infection: why duration and intensity of contacts should be included in models of disease spread

<p>Abstract</p> <p>Background</p> <p>Mathematical models and simulations of disease spread often assume a constant per-contact transmission probability. This assumption ignores the heterogeneity in transmission probabilities, e.g. due to the varying intensity and duration of potentially contagious contacts. Ignoring such heterogeneities might lead to erroneous conclusions from simulation results. In this paper, we show how a mechanistic model of disease transmission differs from this commonly used assumption of a constant per-contact transmission probability.</p> <p>Methods</p> <p>We present an exposure-based, mechanistic model of disease transmission that reflects heterogeneities in contact duration and intensity. Based on empirical contact data, we calculate the expected number of secondary cases induced by an infector (i) for the mechanistic model and (ii) under the classical assumption of a constant per-contact transmission probability. The results of both approaches are compared for different basic reproduction numbers <it>R</it>₀.</p> <p>Results</p> <p>The outcomes of the mechanistic model differ significantly from those of the assumption of a constant per-contact transmission probability. In particular, cases with many different contacts have much lower expected numbers of secondary cases when using the mechanistic model instead of the common assumption. This is due to the fact that the proportion of long, intensive contacts decreases in the contact dataset with an increasing total number of contacts.</p> <p>Conclusion</p> <p>The importance of highly connected individuals, so-called super-spreaders, for disease spread seems to be overestimated when a constant per-contact transmission probability is assumed. This holds particularly for diseases with low basic reproduction numbers. Simulations of disease spread should weight contacts by duration and intensity.</p

Assessing distinct patterns of cognitive aging using tissue-specific brain age prediction based on diffusion tensor imaging and brain morphometry

Multimodal imaging enables sensitive measures of the architecture and integrity of the human brain, but the high-dimensional nature of advanced brain imaging features poses inherent challenges for the analyses and interpretations. Multivariate age prediction reduces the dimensionality to one biologically informative summary measure with potential for assessing deviations from normal lifespan trajectories. A number of studies documented remarkably accurate age prediction, but the differential age trajectories and the cognitive sensitivity of distinct brain tissue classes have yet to be adequately characterized. Exploring differential brain age models driven by tissue-specific classifiers provides a hitherto unexplored opportunity to disentangle independent sources of heterogeneity in brain biology. We trained machine-learning models to estimate brain age using various combinations of FreeSurfer based morphometry and diffusion tensor imaging based indices of white matter microstructure in 612 healthy controls aged 18–87 years. To compare the tissue-specific brain ages and their cognitive sensitivity, we applied each of the 11 models in an independent and cognitively well-characterized sample (n = 265, 20–88 years). Correlations between true and estimated age and mean absolute error (MAE) in our test sample were highest for the most comprehensive brain morphometry (r = 0.83, CI:0.78–0.86, MAE = 6.76 years) and white matter microstructure (r = 0.79, CI:0.74–0.83, MAE = 7.28 years) models, confirming sensitivity and generalizability. The deviance from the chronological age were sensitive to performance on several cognitive tests for various models, including spatial Stroop and symbol coding, indicating poorer performance in individuals with an over-estimated age. Tissue-specific brain age models provide sensitive measures of brain integrity, with implications for the study of a range of brain disorders

Comparability of Results from Pair and Classical Model Formulations for Different Sexually Transmitted Infections

The “classical model” for sexually transmitted infections treats partnerships as instantaneous events summarized by partner change rates, while individual-based and pair models explicitly account for time within partnerships and gaps between partnerships. We compared predictions from the classical and pair models over a range of partnership and gap combinations. While the former predicted similar or marginally higher prevalence at the shortest partnership lengths, the latter predicted self-sustaining transmission for gonorrhoea (GC) and Chlamydia (CT) over much broader partnership and gap combinations. Predictions on the critical level of condom use (Cc) required to prevent transmission also differed substantially when using the same parameters. When calibrated to give the same disease prevalence as the pair model by adjusting the infectious duration for GC and CT, and by adjusting transmission probabilities for HIV, the classical model then predicted much higher Cc values for GC and CT, while Cc predictions for HIV were fairly close. In conclusion, the two approaches give different predictions over potentially important combinations of partnership and gap lengths. Assuming that it is more correct to explicitly model partnerships and gaps, then pair or individual-based models may be needed for GC and CT since model calibration does not resolve the differences

FABP7 expression in normal and stab-injured brain cortex and its role in astrocyte proliferation

Reactive gliosis, in which astrocytes as well as other types of glial cells undergo massive proliferation, is a common hallmark of all brain pathologies. Brain-type fatty acid-binding protein (FABP7) is abundantly expressed in neural stem cells and astrocytes of developing brain, suggesting its role in differentiation and/or proliferation of glial cells through regulation of lipid metabolism and/or signaling. However, the role of FABP7 in proliferation of glial cells during reactive gliosis is unknown. In this study, we examined the expression of FABP7 in mouse cortical stab injury model and also the phenotype of FABP7-KO mice in glial cell proliferation. Western blotting showed that FABP7 expression was increased significantly in the injured cortex compared with the contralateral side. By immunohistochemistry, FABP7 was localized to GFAP+ astrocytes (21% of FABP7+ cells) and NG2+ oligodendrocyte progenitor cells (62%) in the normal cortex. In the injured cortex there was no change in the population of FABP7+/NG2+ cells, while there was a significant increase in FABP7+/GFAP+ cells. In the stab-injured cortex of FABP7-KO mice there was decrease in the total number of reactive astrocytes and in the number of BrdU+ astrocytes compared with wild-type mice. Primary cultured astrocytes from FABP7-KO mice also showed a significant decrease in proliferation and omega-3 fatty acid incorporation compared with wild-type astrocytes. Overall, these data suggest that FABP7 is involved in the proliferation of astrocytes by controlling cellular fatty acid homeostasis