83 research outputs found
Exact solution of bond percolation on small arbitrary graphs
We introduce a set of iterative equations that exactly solves the size
distribution of components on small arbitrary graphs after the random removal
of edges. We also demonstrate how these equations can be used to predict the
distribution of the node partitions (i.e., the constrained distribution of the
size of each component) in undirected graphs. Besides opening the way to the
theoretical prediction of percolation on arbitrary graphs of large but finite
size, we show how our results find application in graph theory, epidemiology,
percolation and fragmentation theory.Comment: 5 pages and 3 figure
Adaptive networks: coevolution of disease and topology
Adaptive networks have been recently introduced in the context of disease
propagation on complex networks. They account for the mutual interaction
between the network topology and the states of the nodes. Until now, existing
models have been analyzed using low-complexity analytic formalisms, revealing
nevertheless some novel dynamical features. However, current methods have
failed to reproduce with accuracy the simultaneous time evolution of the
disease and the underlying network topology. In the framework of the adaptive
SIS model of Gross et al. [Phys. Rev. Lett. 96, 208701 (2006)], we introduce an
improved compartmental formalism able to handle this coevolutionary task
successfully. With this approach, we analyze the interplay and outcomes of both
dynamical elements, process and structure, on adaptive networks featuring
different degree distributions at the initial stage.Comment: 11 pages, 8 figures, 1 appendix. To be published in Physical Review
Pharmacogenomics of blood lipid regulation
Blood lipids are important modifiable risk factors for coronary heart disease and drugs target different lipid fractions. Considerable efforts have been made to identify genetic variants that modulate responses to drugs in the hope of optimizing their use. Pharmacogenomics and new biotechnologies now allow for meaningful integration of human genetic findings and therapeutic development for increased efficiency and precision of lipid-lowering drugs. Polygenic predictors of disease risk are also changing how patient populations can be stratified, enabling targeted therapeutic interventions to patients more likely to derive the highest benefit, marking a shift from single variant to genomic approaches in pharmacogenomics.IRS
Modeling the dynamical interaction between epidemics on overlay networks
Epidemics seldom occur as isolated phenomena. Typically, two or more viral
agents spread within the same host population and may interact dynamically with
each other. We present a general model where two viral agents interact via an
immunity mechanism as they propagate simultaneously on two networks connecting
the same set of nodes. Exploiting a correspondence between the propagation
dynamics and a dynamical process performing progressive network generation, we
develop an analytic approach that accurately captures the dynamical interaction
between epidemics on overlay networks. The formalism allows for overlay
networks with arbitrary joint degree distribution and overlap. To illustrate
the versatility of our approach, we consider a hypothetical delayed
intervention scenario in which an immunizing agent is disseminated in a host
population to hinder the propagation of an undesirable agent (e.g. the spread
of preventive information in the context of an emerging infectious disease).Comment: Accepted for publication in Phys. Rev. E. 15 pages, 7 figure
Propagation dynamics on networks featuring complex topologies
Analytical description of propagation phenomena on random networks has
flourished in recent years, yet more complex systems have mainly been studied
through numerical means. In this paper, a mean-field description is used to
coherently couple the dynamics of the network elements (nodes, vertices,
individuals...) on the one hand and their recurrent topological patterns
(subgraphs, groups...) on the other hand. In a SIS model of epidemic spread on
social networks with community structure, this approach yields a set of ODEs
for the time evolution of the system, as well as analytical solutions for the
epidemic threshold and equilibria. The results obtained are in good agreement
with numerical simulations and reproduce random networks behavior in the
appropriate limits which highlights the influence of topology on the processes.
Finally, it is demonstrated that our model predicts higher epidemic thresholds
for clustered structures than for equivalent random topologies in the case of
networks with zero degree correlation.Comment: 10 pages, 5 figures, 1 Appendix. Published in Phys. Rev. E (mistakes
in the PRE version are corrected here
Propagation on networks: an exact alternative perspective
By generating the specifics of a network structure only when needed
(on-the-fly), we derive a simple stochastic process that exactly models the
time evolution of susceptible-infectious dynamics on finite-size networks. The
small number of dynamical variables of this birth-death Markov process greatly
simplifies analytical calculations. We show how a dual analytical description,
treating large scale epidemics with a Gaussian approximations and small
outbreaks with a branching process, provides an accurate approximation of the
distribution even for rather small networks. The approach also offers important
computational advantages and generalizes to a vast class of systems.Comment: 8 pages, 4 figure
Opioid prescribing practices and training needs of Québec family physicians for chronic noncancer pain
Abstract : AIM: To examine medical practices and training needs of Québec family physicians with respect to pain management and opioid prescription for chronic noncancer pain (CNCP).
METHODOLOGY: An online survey was carried out in 2016.
RESULTS: Of 636 respondents (43.0% men; 54.3% ≥ 50 years old), 15.2% and 70.9% felt very or somewhat confident that they could properly prescribe opioids for CNCP. Concerns related to abuse (72.5% strongly/somewhat agree), dependence (73.2%), and lack of support (75.4%) were the main barriers reported. Only 19.7% always/often screened their patients for risks of abuse and dependence using a screening tool. About two-thirds of participants (65.7%) had recently (last five years) taken part in continuing education programs on opioid use for CNCP and 73.4% on CNCP management. Patient evaluation and differential diagnoses of chronic pain syndromes were rated as a top priority for further training.
CONCLUSIONS: This study provides insights into Québec family physicians' concerns, practices, and needs with respect to the management of CNCP. Physicians' difficulties around the application of strategies to mitigate the problem of opioid abuse and addiction are worrying. The need to better train physicians in the field of pain and addiction cannot be emphasized enough
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